diff --git a/CHANGES.rst b/CHANGES.rst
index 44bd2278bc..1567a76381 100644
--- a/CHANGES.rst
+++ b/CHANGES.rst
@@ -4,6 +4,10 @@
 New Tools and Services
 ----------------------
 
+esa.neocc
+^^^^^^^^^
+
+- New module to provide access too the ESA near-earth objects coordination centre. [#2254]
 
 
 API changes
diff --git a/astroquery/esa/neocc/__init__.py b/astroquery/esa/neocc/__init__.py
new file mode 100755
index 0000000000..1b87669e17
--- /dev/null
+++ b/astroquery/esa/neocc/__init__.py
@@ -0,0 +1,39 @@
+# Licensed under a 3-clause BSD style license - see LICENSE.rst
+"""
+NEOCC Query Tool
+================
+
+Module to query the Near Earth Objects Coordination Centre (NEOCC).
+
+"""
+
+import os
+from astropy import config as _config
+
+
+class Conf(_config.ConfigNamespace):
+    """
+    Configuration parameters for 'ESANEOCC'
+    """
+
+    BASE_URL = 'https://' + os.getenv('NEOCC_PORTAL_IP', default='neo.ssa.esa.int')
+
+    API_URL = _config.ConfigItem(BASE_URL + '/PSDB-portlet/download?file=',
+                                 "Main API URL")
+
+    EPHEM_URL = _config.ConfigItem(BASE_URL + '/PSDB-portlet/ephemerides?des=',
+                                   "Ephermerides URL")
+
+    SUMMARY_URL = _config.ConfigItem(BASE_URL + '/search-for-asteroids?sum=1&des=',
+                                     "Object summary URL")
+
+    TIMEOUT = 60
+
+    SSL_CERT_VERIFICATION = bool(int(os.getenv('SSL_CERT_VERIFICATION', default="1")))
+
+
+conf = Conf()
+
+from .core import neocc, NEOCCClass
+
+__all__ = ['neocc', 'NEOCCClass', 'Conf', 'conf']
diff --git a/astroquery/esa/neocc/core.py b/astroquery/esa/neocc/core.py
new file mode 100755
index 0000000000..e3eda74dfd
--- /dev/null
+++ b/astroquery/esa/neocc/core.py
@@ -0,0 +1,222 @@
+# Licensed under a 3-clause BSD style license - see LICENSE.rst
+"""
+Main module from ESA NEOCC library. This module contains the two main
+methods of the library: *query_list* and *query_object*. The information
+is obtained from ESA Near-Earth Object Coordination Centre's (NEOCC) web
+portal: https://neo.ssa.esa.int/.
+"""
+
+import time
+
+from astroquery.query import BaseQuery
+from astroquery.utils import async_to_sync
+
+from astroquery.esa.neocc import lists, tabs
+
+__all__ = ['neocc', 'NEOCCClass']
+
+
+@async_to_sync
+class NEOCCClass(BaseQuery):
+    """
+    Class to init ESA NEOCC Python interface library
+    """
+
+    def query_list(self, list_name):
+        """Get requested list data from ESA NEOCC.
+
+        Different lists that can be requested are:
+
+        * All NEA list: *nea_list*
+        * Updated NEA list: *updated_nea*
+        * Monthly computation date: *monthly_update*
+        * Risk list (normal): *risk_list*
+        * Risk list (special): *risk_list_special*
+        * Close approaches (upcoming): *close_approaches_upcoming*
+        * Close approaches (recent): *close_approaches_recent*
+        * Priority list (normal): *priority_list*
+        * Priority list (faint): *priority_list_faint*
+        * Close encounter list: *close_encounter*
+        * Impacted objects: *impacted_objects*
+        * Catalogue of NEAs (current date): *neo_catalogue_current*
+        * Catalogue of NEAs (middle arc): *neo_catalogue_middle*
+
+        These lists are referenced in https://neo.ssa.esa.int/computer-access
+
+        Parameters
+        ----------
+        list_name : str
+            Name of the requested list. Valid names are: *nea_list,
+            updated_nea, monthly_update, risk_list, risk_list_special,
+            close_approaches_upcoming, close_approaches_recent, priority_list,
+            priority_list_faint, close_encounter, impacted_objects,
+            neo_catalogue_current and neo_catalogue_middle*.
+
+        Returns
+        -------
+        neocc_lst : `~astropy.table.Table`
+            Astropy Table which contains the data of the requested list.
+
+        Note:
+        If the contents request fails the following message will be printed:
+
+        *Initial attempt to obtain list failed. Reattempting...*
+
+        Then a second request will be automatically sent to the NEOCC portal.
+        """
+
+        # Get URL to obtain the data from NEOCC
+        url = lists.get_list_url(list_name)
+
+        # Request list two times if the first attempt fails
+        try:
+            # Parse decoded data
+            neocc_list = lists.get_list_data(url, list_name)
+
+            return neocc_list
+
+        except ConnectionError:  # pragma: no cover
+            print('Initial attempt to obtain list failed. Reattempting...')
+            # Wait 5 seconds
+            time.sleep(5)
+            # Parse decoded data
+            neocc_list = lists.get_list_data(url, list_name)
+
+            return neocc_list
+
+    def query_object(self, name, tab, *,
+                     orbital_elements=None, orbit_epoch=None,
+                     observatory=None, start=None, stop=None, step=None, step_unit=None):
+        """Get requested object data from ESA NEOCC.
+
+        Parameters
+        ----------
+        name : str
+            Name of the requested object
+        tab : str
+            Name of the request tab. Valid names are: summary,
+            orbit_properties, physical_properties, observations,
+            ephemerides, close_approaches and impacts.
+        orbital_elements : str
+            Additional required argument for "orbit_properties" table.
+            Valid arguments are: keplerian, equinoctial
+        orbit_epoch : str
+            Additional required argument for "orbit_properties" table.
+            Valid arguments are: present, middle
+        observatory : str
+            Additional required argument for "ephemerides" table.
+            Observatory code, e.g. '500', 'J04', etc.
+        start : str
+            Additional required argument for "ephemerides" table.
+            Start date in YYYY-MM-DD HH:MM
+        stop : str
+            Additional required argument for "ephemerides" table.
+            End date in YYYY-MM-DD HH:MM
+        step : str
+            Additional required argument for "ephemerides" table.
+            Time step, e.g. '2', '15', etc.
+        step_unit : str
+            Additional required argument for "ephemerides" table.
+            Unit for time step e.g. 'days', 'minutes', etc.
+
+        Returns
+        -------
+        neocc_obj : list of `~astropy.table.Table`
+            One or more tables containing the requested object data.
+            the tab selected.
+        """
+
+        # Define a list with all possible tabs to be requested
+        tab_list = ['impacts', 'close_approaches', 'observations',
+                    'physical_properties', 'orbit_properties',
+                    'ephemerides', 'summary']
+
+        # Check the input of the method if tab is not in the list
+        # print and error and show the valid names
+        if tab not in tab_list:
+            raise KeyError(("Please introduce a valid table name. "
+                           f"Valid names are: {', '.join(tab_list)}"))
+        # Depending on the tab selected the information will be requested
+        # following different methods. Create "switch" for each case:
+
+        # Impacts, close approaches and observations
+        if tab in ('impacts', 'close_approaches', 'observations',
+                   'physical_properties'):
+            # Get URL to obtain the data from NEOCC
+            url = tabs.get_object_url(name, tab)
+
+            # Request data two times if the first attempt fails
+            try:
+                # Get object data
+                data_obj = tabs.get_object_data(url)
+            except ConnectionError:  # pragma: no cover
+                print('Initial attempt to obtain object data failed. '
+                      'Reattempting...')
+
+                # Wait 5 seconds
+                time.sleep(5)
+
+                # Get object data
+                data_obj = tabs.get_object_data(url)
+
+            resp_str = data_obj.decode('utf-8')
+
+            if tab == 'impacts':
+                neocc_obj = tabs.parse_impacts(resp_str)
+            elif tab == 'close_approaches':
+                neocc_obj = tabs.parse_close_aproach(resp_str)
+            elif tab == 'observations':
+                neocc_obj = tabs.parse_observations(resp_str)
+            elif tab == 'physical_properties':
+                neocc_obj = tabs.parse_physical_properties(resp_str)
+
+        # Orbit properties
+        elif tab == 'orbit_properties':
+
+            # Raise error if  elements or epoch are not provided
+            if not all([orbital_elements, orbit_epoch]):
+                raise KeyError(("orbital_elements and orbit_epoch must be specified"
+                                "for an orbit_properties query."))
+
+            # Get URL to obtain the data from NEOCC
+            url = tabs.get_object_url(name, tab, orbital_elements=orbital_elements, orbit_epoch=orbit_epoch)
+
+            # Request data two times if the first attempt fails
+            try:
+                # Get object data
+                data_obj = tabs.get_object_data(url)
+            except ConnectionError:  # pragma: no cover
+                print('Initial attempt to obtain object data failed. '
+                      'Reattempting...')
+
+                # Wait 5 seconds
+                time.sleep(5)
+
+                # Get object data
+                data_obj = tabs.get_object_data(url)
+
+            resp_str = data_obj.decode('utf-8')
+            neocc_obj = tabs.parse_orbital_properties(resp_str)
+
+        # Ephemerides
+        elif tab == 'ephemerides':
+
+            if not all([observatory, start, stop, step, step_unit]):
+                raise KeyError(("Ephemerides queries require the following arguments:"
+                                "observatory, start, stop, step, and step_unit"))
+
+            resp_str = tabs.get_ephemerides_data(name, observatory=observatory, start=start, stop=stop,
+                                                 step=step, step_unit=step_unit)
+            neocc_obj = tabs.parse_ephemerides(resp_str)
+
+        elif tab == 'summary':
+            resp_str = tabs.get_summary_data(name)
+            neocc_obj = tabs.parse_summary(resp_str)
+
+        if not isinstance(neocc_obj, list):
+            neocc_obj = [neocc_obj]
+
+        return neocc_obj
+
+
+neocc = NEOCCClass()
diff --git a/astroquery/esa/neocc/lists.py b/astroquery/esa/neocc/lists.py
new file mode 100755
index 0000000000..7f8eb06948
--- /dev/null
+++ b/astroquery/esa/neocc/lists.py
@@ -0,0 +1,377 @@
+"""
+This module contains all the methods required to request the list data,
+obtain it from the ESA NEOCC portal and parse it to show it properly.
+"""
+
+import re
+import requests
+
+import numpy as np
+
+from astropy.table import Table, Column
+from astropy.time import Time
+
+from astroquery.esa.neocc import conf
+from astroquery.esa.neocc.utils import convert_time
+
+# Import BASE URL and TIMEOUT
+API_URL = conf.API_URL
+TIMEOUT = conf.TIMEOUT
+VERIFICATION = conf.SSL_CERT_VERIFICATION
+
+
+def get_list_url(list_name):
+    """Get url from requested list name.
+
+    Parameters
+    ----------
+    list_name : str
+        Name of the requested list. Valid names are: *nea_list,
+        risk_list, risk_list_special, close_approaches_upcoming,
+        close_approaches_recent, priority_list, priority_list_faint,
+        close_encounter, impacted_objects, neo_catalogue_current and
+        neo_catalogue_middle*.
+
+    Returns
+    -------
+    url : str
+        Final URL string.
+
+    Raises
+    ------
+    KeyError
+        If the requested list_name is not in the dictionary
+    """
+
+    # Define the parameters of each list
+    lists_dict = {
+        "nea_list": 'allneo.lst',
+        "updated_nea": 'updated_nea.lst',
+        "monthly_update": 'monthly_update.done',
+        "risk_list": 'esa_risk_list',
+        "risk_list_special": 'esa_special_risk_list',
+        "close_approaches_upcoming": 'esa_upcoming_close_app',
+        "close_approaches_recent": 'esa_recent_close_app',
+        "priority_list": 'esa_priority_neo_list',
+        "priority_list_faint": 'esa_faint_neo_list',
+        "close_encounter": 'close_encounter2.txt',
+        "impacted_objects": 'past_impactors_list',
+        "neo_catalogue_current": 'neo_kc.cat',
+        "neo_catalogue_middle": 'neo_km.cat'
+    }
+
+    # Raise error is input is not in dictionary
+    if list_name not in lists_dict:
+        raise KeyError('Valid list names are nea_list, updated_nea, '
+                       'monthly_update, risk_list, risk_list_special, '
+                       'close_approaches_upcoming, close_approaches_recent, '
+                       'priority_list, priority_list_faint, '
+                       'close_encounter, impacted_objects, '
+                       'neo_catalogue_current and neo_catalogue_middle')
+
+    # Get url
+    url = lists_dict[list_name]
+
+    return url
+
+
+def get_list_data(url, list_name):
+    """Get requested parsed list from url.
+
+    Parameters
+    ----------
+    list_name : str
+        Name of the requested list.
+    url : str
+        URL of the requested list.
+
+    Returns
+    -------
+    neocc_lst : `~astropy.table.Table`
+        Astropy Table which contains the data of the requested list.
+    """
+
+    # Get data from URL
+    response = requests.get(API_URL + url, timeout=TIMEOUT, verify=VERIFICATION)
+
+    # Raising error based on HTTP status if necessary
+    response.raise_for_status()
+
+    # Parse decoded data
+    data_string = response.content.decode('utf-8')
+    neocc_list = parse_list(list_name, data_string)
+
+    return neocc_list
+
+
+def parse_list(list_name, data_string):
+    """Switch function to select parse method.
+
+    Parameters
+    ----------
+    list_name : str
+        Name of the requested list.
+    data_string : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    neocc_lst : `~astropy.table.Table`
+        Astropy Table which contains the data of the requested list.
+    """
+
+    # Parse data for each type of list
+    if list_name in ("nea_list", "updated_nea", "monthly_update"):
+        neocc_lst = parse_nea(data_string)
+    elif list_name in ("risk_list", "risk_list_special"):
+        neocc_lst = parse_risk(data_string)
+    elif list_name in ("close_approaches_upcoming",
+                       "close_approaches_recent"):
+        neocc_lst = parse_clo(data_string)
+    elif list_name in ("priority_list", "priority_list_faint"):
+        neocc_lst = parse_pri(data_string)
+    elif list_name == "close_encounter":
+        neocc_lst = parse_encounter(data_string)
+    elif list_name == "impacted_objects":
+        neocc_lst = parse_impacted(data_string)
+    elif list_name in ('neo_catalogue_current',
+                       'neo_catalogue_middle'):
+        neocc_lst = parse_neo_catalogue(data_string)
+    else:
+        raise KeyError('Valid list names are nea_list, updated_nea, '
+                       'monthly_update, risk_list, risk_list_special, '
+                       'close_approaches_upcoming, '
+                       'close_approaches_recent, '
+                       'priority_list, priority_list_faint, '
+                       'close_encounter, impacted_objects, '
+                       'neo_catalogue_current and '
+                       'neo_catalogue_middle')
+
+    return neocc_lst
+
+
+def parse_nea(resp_str):
+    """Parse and arrange NEA list, updated NEA and monthly update.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    neocc_lst : `~astropy.table.Table`
+        Astropy Table with NEA list data parsed.
+    """
+
+    resp_str = resp_str.replace('#', '')
+    resp_str = re.sub(' +', ' ', resp_str)
+    return Table.read(resp_str, data_start=0, format="ascii.csv", names=["NEA"])
+
+
+def parse_risk(resp_str):
+    """Parse and arrange risk lists.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    neocc_lst : `~astropy.table.Table`
+        Astropy Table with risk list data parsed.
+    """
+
+    neocc_lst = Table.read(resp_str, header_start=2, data_start=4, format="ascii.fixed_width")
+
+    neocc_lst.rename_columns(("Num/des.       Name", "m", "Vel km/s"),
+                             ('Object Name', 'Diameter in m', 'Vel in km/s'))
+
+    neocc_lst['Date/Time'] = Time(neocc_lst['Date/Time'], scale="utc")
+    neocc_lst['*=Y'] = neocc_lst['*=Y'].astype("<U1")
+
+    if "Years" in neocc_lst.colnames:
+        first_year, last_year = np.array([x.split("-") for x in neocc_lst["Years"]]).swapaxes(0, 1).astype(int)
+        yr_index = neocc_lst.index_column("Years")
+        neocc_lst.remove_column("Years")
+        neocc_lst.add_column(Column(name="Last Year", data=last_year), index=yr_index)
+        neocc_lst.add_column(Column(name="First Year", data=first_year), index=yr_index)
+
+    neocc_lst.meta = {'Object Name': 'name of the NEA',
+                      'Diamater in m': 'approximate diameter in meters',
+                      '*=Y': 'recording an asterisk if the value has been estimated from the absolute magnitude',
+                      'Date/Time': 'predicted impact date in datetime format',
+                      'IP max': 'Maximum Impact Probability',
+                      'PS max': 'Palermo scale rating',
+                      'Vel in km/s': 'Impact velocity at atmospheric entry in km/s',
+                      'First year': 'first year of possible impacts',
+                      'Last year': 'last year of possible impacts',
+                      'IP cum': 'Cumulative Impact Probability',
+                      'PS cum': 'Cumulative Palermo Scale'}
+
+    return neocc_lst
+
+
+def parse_clo(resp_str):
+    """Parse and arrange close approaches lists.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    neocc_lst : `~astropy.table.Table`
+        Astropy Table with close approaches list data parsed.
+    """
+
+    neocc_lst = Table.read(resp_str, header_start=2, data_start=4, format="ascii.fixed_width",
+                           names=('Object Name', 'Date', 'Miss Distance in km', 'Miss Distance in au',
+                                  'Miss Distance in LD', 'Diameter in m', '*=Yes', 'H', 'Max Bright',
+                                  'Rel. vel in km/s', "CAI index"))
+
+    neocc_lst['Date'] = Time(neocc_lst['Date'], scale="utc")
+    neocc_lst["Diameter in m"] = neocc_lst["Diameter in m"].astype(float)
+
+    neocc_lst['Max Bright'] = [np.nan if val == '-' else val for val in neocc_lst['Max Bright']]
+    neocc_lst['Max Bright'] = neocc_lst['Max Bright'].astype(float)
+
+    neocc_lst.meta = {'Object Name': 'name of the NEA',
+                      'Date': 'close approach date in datetime format',
+                      'Miss distance in km': 'miss distance in kilometers with precision of 1 km',
+                      'Miss distance in au': 'miss distance in astronomical units (1 au  = 149597870.7 km)',
+                      'Miss distance in LD': 'miss distance in Lunar Distance (1 LD = 384399 km)',
+                      'Diamater in m': 'approximate diameter in meters',
+                      '*=Yes': 'recording an asterisk if the value has been estimated from the absolute magnitude',
+                      'H': 'Absolute Magnitude',
+                      'Max Bright': 'Maximum brightness at close approach',
+                      'Rel. vel in km/s': 'relative velocity in km/s',
+                      'CAI Index': 'Close Approach Index, indicating how rare the close approach is'}
+
+    return neocc_lst
+
+
+def parse_pri(resp_str):
+    """Parse and arrange priority lists.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    neocc_lst : `~astropy.table.Table`
+        Astropy Table with priority list data parsed.
+    """
+
+    neocc_lst = Table.read(resp_str, data_start=1, format="ascii.no_header",
+                           names=['Priority', 'Object', 'R.A. in arcsec', 'Decl. in deg',
+                                  'Elong. in deg', 'V in mag', 'Sky uncert.', 'End of Visibility'])
+
+    neocc_lst["Object"] = [x.replace(' ', '') for x in neocc_lst["Object"]]
+    neocc_lst['End of Visibility'] = Time.strptime(neocc_lst['End of Visibility'], '%Y/%m/%d')
+
+    neocc_lst.meta = {'Priority': '0=UR: Urgent, 1=NE: Necessary, 2=US: Useful, 3=LP: Low Priority',
+                      'Object': 'designator of the object',
+                      'R.A. in arcsec': 'current right ascension on the sky, Geocentric equatorial, in arcseconds',
+                      'Decl. in deg': 'current declination on the sky, in sexagesimal degrees',
+                      'Elong. in deg': 'current Solar elongation, in sexagesimal degrees',
+                      'V in mag': 'current observable brightness, V band, in magnitudes',
+                      'Sky uncert.': 'uncertainty in the plane of the sky, in arcseconds',
+                      'End of Visibility': 'expected date of end of visibility'}
+
+    return neocc_lst
+
+
+def parse_encounter(resp_str):
+    """Parse and arrange close encounter lists.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    neocc_lst : `~astropy.table.Table`
+        Astropy Table with close encounter list data parsed.
+    """
+
+    neocc_lst = Table.read(resp_str, header_start=1, data_start=3, format="ascii.fixed_width")
+    neocc_lst['Date'] = convert_time(neocc_lst['Date'], conversion_string='%Y/%m/%d')
+
+    neocc_lst.meta = {'Name/design': 'designator of the NEA',
+                      'Planet': 'planet or massive asteroid is involved in the close approach',
+                      'Date': 'close encounter date in datetime format',
+                      'Time approach': 'close encounter date in MJD2000',
+                      'Time uncert': 'time uncertainty in MJD2000',
+                      'Distance': 'Nominal distance at the close approach in au',
+                      'Minimum distance': 'minimum possible distance at the close approach in au',
+                      'Distance uncertainty': 'distance uncertainty in in au',
+                      'Width': 'width of the strechin in au',
+                      'Stretch': ('stretching. It indicates how much the confidence region at the '
+                                  'epoch has been stretched by the time of the approach. This is a '
+                                  'close cousin of the Lyapounov exponent'),
+                      'Probability': 'close approach probability. A value of 1 indicates a certain close approach',
+                      'Velocity': 'velocity in km/s',
+                      'Max Mag': 'maximum brightness magnitude at close approach'}
+
+    return neocc_lst
+
+
+def parse_impacted(resp_str):
+    """Parse impacted objects list.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    neocc_table : *astropy.table.table.Table*
+        Astropy table with impacted objects list data parsed.
+    """
+
+    neocc_table = Table.read(resp_str, header_start=1, format="ascii.fixed_width", fill_values=['n/a', np.nan])
+    neocc_table['Impact date/time in UTC'] = Time(neocc_table['Impact date/time in UTC'], scale='utc')
+
+    return neocc_table
+
+
+def parse_neo_catalogue(resp_str):
+    """Parse neo catalogues (current or middle arc) lists.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+   neocc_lst : `~astropy.table.Table`
+        Astropy Table  with catalogues of NEAs list data parsed.
+    """
+
+    neocc_lst = Table.read(resp_str, data_start=6, format="ascii.no_header",
+                           names=['Name', 'Epoch (MJD)', 'a', 'e', 'i', 'long. node', 'arg. peric.',
+                                  'mean anomaly', 'absolute magnitude', 'slope param.', 'non-grav param.'])
+
+    neocc_lst.meta = {'Name': 'designator of the NEA',
+                      'Epoch (MJD)': 'epoch of the orbit involved in the close approach',
+                      'Six orbital elements': ('semimajor axis (a), eccentricity (e), inclination (i), '
+                                               'longitude of the ascending node (long. node), argument of '
+                                               'pericenter (arg. peric) and mean anomaly'),
+                      'slope param': 'Slope parameter',
+                      'non-grav param.': 'Number of non-gravitational parameters'}
+
+    regex = re.search(r"(format) += '(.+)'.+\n(rectype) += '(.+)'.+\n(elem) "
+                      r"+= '(.+)'.+\n(refsys) += (\w+ \w+)", resp_str)
+    keyvals = zip(regex.groups()[::2], regex.groups()[1::2])
+    for k, v in keyvals:
+        neocc_lst.meta[k] = v
+
+    return neocc_lst
diff --git a/astroquery/esa/neocc/tabs.py b/astroquery/esa/neocc/tabs.py
new file mode 100755
index 0000000000..fbd8992879
--- /dev/null
+++ b/astroquery/esa/neocc/tabs.py
@@ -0,0 +1,907 @@
+"""
+This module contains all the methods required to request the data from
+a particular object, obtain it from the ESA NEOCC portal and parse it
+to show it properly. The information of the object is shows in the
+ESA NEOCC in different tabs that correspond to the different classes
+within this module.
+"""
+
+import logging
+import time
+import re
+import requests
+from bs4 import BeautifulSoup
+
+import numpy as np
+
+from astropy.table import Table, Column, join, vstack
+from astropy.time import Time
+
+from astroquery.esa.neocc import conf
+from astroquery.esa.neocc.utils import convert_time
+
+# Import URLs and TIMEOUT
+API_URL = conf.API_URL
+EPHEM_URL = conf.EPHEM_URL
+SUMMARY_URL = conf.SUMMARY_URL
+TIMEOUT = conf.TIMEOUT
+VERIFICATION = conf.SSL_CERT_VERIFICATION
+
+
+def get_object_url(name, tab, **kwargs):
+    """Get url from requested object and tab name.
+
+    Parameters
+    ----------
+    name : str
+        Name of the requested object.
+    tab : str
+        Name of the requested table. Valid names are: *summary,
+        orbit_properties, physical_properties, observations,
+        ephemerides, close_approaches and impacts*.
+    **kwargs : str
+        orbit_properties and ephemerides tabs require additional arguments:
+
+        * *orbit_properties*: the required additional arguments are:
+
+            * *orbital_elements* : str (keplerian or equinoctial)
+            * *orbit_epoch* : str (present or middle)
+
+        * *ephemerides*: the required additional arguments are:
+
+            * *observatory* : str (observatory code, e.g. '500', 'J04', etc.)
+            * *start* : str (start date in YYYY-MM-DD HH:MM)
+            * *stop* : str (end date in YYYY-MM-DD HH:MM)
+            * *step* : str (time step, e.g. '2', '15', etc.)
+            * *step_unit* : str (e.g. 'days', 'minutes', etc.)
+
+    Returns
+    -------
+    url : string
+        Final url from which data is requested.
+
+    Raises
+    ------
+    KeyError
+        If the requested tab is not in the dictionary.
+    ValueError
+        If the elements requested are not valid.
+    """
+    # Define the parameters of each list
+    tab_dict = {"impacts": '.risk',
+                "close_approaches": '.clolin',
+                "physical_properties": '.phypro',
+                "observations": '.rwo',
+                "orbit_properties": ['.ke0', '.ke1', '.eq0', '.eq1']}
+
+    # Raise error is input is not in dictionary
+    if tab not in tab_dict:
+        raise KeyError('Valid list names are impacts, close_approaches'
+                       ' observations and orbit_properties')
+
+    # Check if orbital_elements is an input
+    if 'orbital_elements' in kwargs:
+        # Check if the elements are Keplerian or Equinoctial
+        if kwargs['orbital_elements'] == "keplerian":
+            # Check if the epoch is present day or middle obs. arch
+            if kwargs['orbit_epoch'] == "present":
+                url = str(name).replace(' ', '%20') + tab_dict[tab][1]
+            elif kwargs['orbit_epoch'] == "middle":
+                url = str(name).replace(' ', '%20') + tab_dict[tab][0]
+        elif kwargs['orbital_elements'] == "equinoctial":
+            if kwargs['orbit_epoch'] == "present":
+                url = str(name).replace(' ', '%20') + tab_dict[tab][3]
+            elif kwargs['orbit_epoch'] == "middle":
+                url = str(name).replace(' ', '%20') + tab_dict[tab][2]
+        else:
+            raise ValueError('The introduced file type does not exist.'
+                             'Check that orbit elements (keplerian or '
+                             'equinoctial) and orbit epoch (present or '
+                             'middle).')
+    else:
+        url = str(name).replace(' ', '%20') + tab_dict[tab]
+
+    return url
+
+
+def get_object_data(url):
+    """Get object in byte format from requested url.
+
+    Parameters
+    ----------
+    url : str
+        URL of the requested data.
+
+    Returns
+    -------
+    data_obj : object
+        Object in byte format.
+    """
+    # Get data from URL
+    data_obj = requests.get(API_URL + url, timeout=TIMEOUT, verify=VERIFICATION).content
+
+    return data_obj
+
+
+def get_ephemerides_data(name, observatory, start, stop, step, step_unit):
+    """
+    Get ephemerides data object in byte format from given arguments.
+    """
+
+    # Unique base url for asteroid properties
+    url_ephe = EPHEM_URL + str(name).replace(' ', '%20') +\
+        '&oc=' + str(observatory) + '&t0=' +\
+        str(start).replace(' ', 'T') + 'Z&t1=' +\
+        str(stop).replace(' ', 'T') + 'Z&ti=' + str(step) +\
+        '&tiu=' + str(step_unit)
+
+    # Request data two times if the first attempt fails
+    try:
+        # Get object data
+        data_obj = requests.get(url_ephe, timeout=TIMEOUT,
+                                verify=VERIFICATION).content
+
+    except ConnectionError:  # pragma: no cover
+        print('Initial attempt to obtain object data failed. '
+              'Reattempting...')
+        logging.warning('Initial attempt to obtain object data'
+                        'failed.')
+        # Wait 5 seconds
+        time.sleep(5)
+        # Get object data
+        data_obj = requests.get(url_ephe, timeout=TIMEOUT,
+                                verify=VERIFICATION).content
+
+    # Check if file contains errors due to bad URL keys
+    resp_str = data_obj.decode('utf-8')
+    if "[ERROR]" in resp_str:
+        raise KeyError(resp_str)
+
+    return resp_str
+
+
+def get_summary_data(name):
+    """
+    Get the summary info html page for a given object.
+    """
+
+    url = SUMMARY_URL + str(name).replace(' ', '%20')
+
+    contents = requests.get(url, timeout=TIMEOUT, verify=VERIFICATION).content
+
+    return contents.decode('utf-8')
+
+
+def parse_impacts(resp_str):
+    """
+    Parse impact table response string.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    response : list(`astropy.table.Table`)
+        The response table, with all the extra info in the meta dictionary.
+    """
+
+    # Make sure there is actually data for this object
+    if "Required risk file is not available for this object" in resp_str:
+        raise ValueError('Required risk file is not available for this object')
+
+    # Split the response into parts to more easily work with.
+    resp_lst = resp_str.split("\n\n")
+
+    # Build the main data table
+    impact_tble = Table.read(resp_lst[1], format='ascii', data_start=3,
+                             names=["date", "MJD", "sigma", "sigimp", "dist", "+/-", "width",
+                                    "stretch", "p_RE", "Exp. Energy in MT", "PS", "TS"])
+    impact_tble.remove_column("+/-")
+    impact_tble['date'] = convert_time(impact_tble['date'])
+
+    # Add the column info to the meta table
+    impact_tble.meta["Column Info"] = {'Date': 'date for the potential impact in datetime format',
+                                       'MJD': 'Modified Julian Day for the potential impact',
+                                       'sigma': 'approximate location along the Line Of Variation (LOV) in sigma space',
+                                       'sigimp': ('The lateral distance in sigma-space from the LOV to the Earth '
+                                                  'surface. A zero implies that the LOV passes through the Earth'),
+                                       'dist': ('Minimum Distance in Earth radii. The lateral distance from the LOV '
+                                                'to the center of the Earth'),
+                                       'width': ('one-sigma semi-width of the Target Plane confidence region '
+                                                 'in Earth radii'),
+                                       'stretch': ('Stretching factor. It indicates how much the confidence region '
+                                                   'at the epoch has been stretched by the time of the approach. '
+                                                   'This is a close cousin of the Lyapounov exponent. Units are in '
+                                                   'Earth radii divided by sigma (RE/sig)'),
+                                       'p_RE': 'probability of Earth Impact (IP)',
+                                       'Exp. Energy in MT': ('Expected energy. It is the product of the impact energy '
+                                                             'and the impact probability'),
+                                       'PS': 'Palermo Scale',
+                                       'TS': 'Torino Scale'}
+
+    # Adding the rest of the metadata from the remaining resp_lst entries
+    regex = re.search((r"(\d+) optical observations.*(\d+) "
+                       r"are rejected as outliers.*\nfrom (.+) to (.+)\."), resp_lst[2])
+    obs_acc, obs_reg, start, end = regex.groups()
+
+    dates = convert_time([start, end], conversion_string='%Y/%m/%d')
+
+    impact_tble.meta["observation_accepted"] = int(obs_acc)
+    impact_tble.meta["observation_rejected"] = int(obs_reg)
+    impact_tble.meta["arc_start"] = dates[0]
+    impact_tble.meta["arc_end"] = dates[1]
+
+    impact_tble.meta["info"] = "/n/n".join(resp_lst[3:6])
+
+    regex = re.search("computation=(.+)", resp_lst[6])
+    impact_tble.meta["computation"] = regex.groups()[0]
+
+    add_note = resp_lst[7].replace("\n", "")
+    if add_note:
+        impact_tble.meta["additional_note"] = add_note
+
+    return impact_tble
+
+
+def parse_close_aproach(resp_str):
+    """
+    Parse close approach response string.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    response : Table
+        The response table, with all the extra info in the meta dictionary.
+    """
+
+    # If there is nothing there, just return an empty table
+    if not resp_str:
+        return Table(names=['BODY', 'CALENDAR-TIME', 'MJD-TIME', 'TIME-UNCERT.', 'NOM.-DISTANCE',
+                            'MIN.-POSS.-DIST.', 'DIST.-UNCERT.', 'STRETCH', 'WIDTH', 'PROBABILITY'])
+
+    df_close_appr = Table.read(resp_str, format="ascii", header_start=1)
+
+    df_close_appr["CALENDAR-TIME"] = convert_time(df_close_appr["CALENDAR-TIME"], conversion_string='%Y/%m/%d')
+
+    df_close_appr.meta["Column Info"] = {'BODY': 'planet or massive asteroid is involved in the close approach',
+                                         'CALENDAR-TIME': 'date of the close approach in datetime format',
+                                         'MJD-TIME': 'Modified Julian Date of the approach',
+                                         'TIME-UNCERT.': 'time uncertainty in MJD2000',
+                                         'NOM.-DISTANCE': 'Nominal distance at the close approach in au',
+                                         'MIN.-POSS.-DIST.': 'Minimum possible distance at the close approach in au',
+                                         'DIST.-UNCERT.': 'distance uncertainty in au',
+                                         'STRETCH': ('It indicates how much the confidence region at the epoch has '
+                                                     'been stretched by the time of the approach. This is a close '
+                                                     'cousin of the Lyapounov exponent. Units in au'),
+                                         'WIDTH': 'width of the stretching',
+                                         'PROBABITLIY': ('Close approach probability. A value of 1 indicates a '
+                                                         'certain close approach')}
+
+    return df_close_appr
+
+
+def _parse_obs_meta(hdr_str):
+    """
+    Parse the header string for the observation tables.
+    """
+
+    mlst = hdr_str.split('\n')
+    pat = re.compile(r'(\w+)\s+=\s+\'{0,1}([\w\.-]+)\'{0,1}')
+
+    meta_dict = {}
+    for ent in mlst:
+        if not ent:  # Skip empty entries
+            continue
+
+        matches = pat.match(ent).groups()
+        meta_dict[matches[0]] = [matches[1]]
+
+    meta_table = Table(meta_dict)
+    meta_table.meta["Title"] = "Observation metadata"
+    meta_table.meta["Column Info"] = {"version": "File version",
+                                      "errmod": "Error model for the data",
+                                      "rmsast": "Root Mean Square for asteroid observations",
+                                      "rmsmag": "Root Mean Square for magnitude"}
+
+    # Making the columns gave the right data types
+    for col in meta_table.colnames:
+        if col == 'errmod':
+            continue
+        meta_table[col] = meta_table[col].astype(float)
+
+    return meta_table
+
+
+def _parse_opt_obs(optical_str):
+    """
+    Building the optical observations table.
+    """
+
+    obs_table = Table.read(optical_str, format="ascii.fixed_width_no_header",
+                           col_starts=[0, 11, 13, 15, 17, 22, 25, 40, 50, 53, 56, 64, 75, 83, 87,
+                                       94, 103, 106, 110, 117, 128, 136, 140, 147, 156, 161, 164,
+                                       170, 177, 180, 187, 194, 196],
+                           col_ends=[10, 12, 14, 16, 21, 24, 39, 49, 52, 55, 63, 74, 82, 86, 93, 102,
+                                     105, 109, 116, 127, 135, 139, 146, 155, 160, 163, 169, 176, 179,
+                                     186, 193, 195, 197],
+                           names=['Design.', 'K', 'T', 'N', 'Date', 'MM', 'DD.ddd',
+                                  'Date Accuracy', 'RA HH', 'RA MM', 'RA SS.sss', 'RA Accuracy',
+                                  'RA RMS', 'RA F', 'RA Bias', 'RA Resid', 'DEC sDD', 'DEC MM',
+                                  'DEC SS.ss', 'DEC Accuracy', 'DEC RMS', 'DEC F', 'DEC Bias',
+                                  'DEC Resid', 'MAG Val', 'MAG B', 'MAG RMS', 'MAG Resid',
+                                  'Ast Cat', 'Obs Code', 'Chi', 'A', 'M'])
+
+    # Combining the date columns
+    date_array = [f"{x}/{y}/{z}" for x, y, z in obs_table["Date", "MM", "DD.ddd"]]
+    obs_table["Date"] = convert_time(date_array, conversion_string='%Y/%m/%d')
+    obs_table.remove_columns(["MM", "DD.ddd"])
+
+    # Combinging the ra/dec columns
+    ra_array = [f"{x:02d}:{y:02d}:{z:02.3f}" for x, y, z in obs_table['RA HH', 'RA MM', 'RA SS.sss']]
+    obs_table.replace_column('RA HH', Column(data=ra_array))
+    obs_table.rename_column("RA HH", "RA")
+    obs_table.remove_columns(['RA MM', 'RA SS.sss'])
+
+    dec_array = [f"{x:02d}:{y:02d}:{z:02.2f}" for x, y, z in obs_table['DEC sDD', 'DEC MM', 'DEC SS.ss']]
+    obs_table.replace_column('DEC sDD', Column(data=dec_array))
+    obs_table.rename_column("DEC sDD", "DEC")
+    obs_table.remove_columns(['DEC MM', 'DEC SS.ss'])
+
+    # Adding table metadata
+    obs_table.meta["Title"] = "Optical Observations"
+    obs_table.meta["Column Info"] = {'Designation': 'number or the provisional designation of the asteroid.',
+                                     'K, Type': ('observation type and technology provided by the MPC. '
+                                                 'Note that for satellite (s) and roving (v) observations '
+                                                 'there are 2 additional dataframes which contain the '
+                                                 'information given by the MPC.'),
+                                     'Date': 'date in UTC iso format.',
+                                     'Right Ascension': ('The data provided include the observation, the a '
+                                                         'priori accuracy (as supplied by the MPC), the a '
+                                                         'priori RMS used for weighing, a flag indicating a '
+                                                         'forced weight, the bias, and the residuals in arcsec.'),
+                                     'Declination': 'same format as Right Ascension.',
+                                     'Apparent magnitude': ('The columns contain the apparent magnitude as '
+                                                            'reported, the a priori RMS used for weighing, and '
+                                                            'the residual, all in magnitudes.'),
+                                     'Quality': ('observatory code is extracted from the MPC published '
+                                                 'observation, the value of chi from the chi**2 test '
+                                                 '(characterization of the relative quality of the observation). '
+                                                 'The "Used A" column is "Yes" if the observation is used in '
+                                                 'our orbit, and "No" if it has been discarded. The same for '
+                                                 'the photometry in the "Used M" column.')}
+
+    return obs_table
+
+
+def _parse_sat_obs(sat_str):
+    """
+    Building the satellite observations table.
+    """
+
+    sat_table = Table.read(sat_str, format="ascii.fixed_width_no_header",
+                           col_starts=[0, 11, 12, 15, 17, 22, 25, 34, 40, 64, 88, 108],
+                           col_ends=[10, 12, 15, 16, 21, 24, 33, 35, 59, 83, 107, 111],
+                           names=['Design.', 'K', 'T', 'N', 'Date', 'MM', 'DD.dddddd',
+                                  'Parallax info.', 'X', 'Y', 'Z', 'Obs Code'])
+
+    # Combining the date column
+    date_array = [f"{x}/{y}/{z}" for x, y, z in sat_table["Date", "MM", "DD.dddddd"]]
+    sat_table["Date"] = convert_time(date_array, conversion_string='%Y/%m/%d')
+    sat_table.remove_columns(["MM", "DD.dddddd"])
+
+    sat_table.meta["Title"] = "Satellite  Observations"
+
+    return sat_table
+
+
+def _parse_rov_obs(rov_str):
+    """
+    Building the roving observer observations table.
+    """
+
+    rov_table = Table.read(rov_str, format="ascii.fixed_width_no_header",
+                           col_starts=[0, 11, 13, 15, 17, 22, 25, 34, 45, 56, 65],
+                           col_ends=[10, 12, 14, 16, 21, 24, 33, 44, 55, 64, 68],
+                           names=['Design.', 'K', 'T', 'N', 'Date', 'MM', 'DD.dddddd',
+                                  'E longitude', 'Latitude', 'Altitude', 'Obs Code'])
+
+    # Combining the date column
+    date_array = [f"{x}/{y}/{z}" for x, y, z in rov_table["Date", "MM", "DD.dddddd"]]
+    rov_table["Date"] = convert_time(date_array, conversion_string='%Y/%m/%d')
+    rov_table.remove_columns(["MM", "DD.dddddd"])
+
+    rov_table.meta["Title"] = "Roving Observer  Observations"
+
+    return rov_table
+
+
+def _parse_radar_obs(radar_str):
+    """
+    Building the radar observations table.
+    """
+
+    radar_str = radar_str[radar_str.find('\n')+1:]  # First row is header
+    radar_table = Table.read(radar_str, format="ascii.fixed_width_no_header",
+                             col_starts=[0, 11, 13, 15, 17, 22, 25, 28, 37, 54, 64,
+                                         73, 75, 87, 99, 106, 112, 124],
+                             col_ends=[10, 12, 14, 16, 21, 24, 27, 36, 53, 63, 72,
+                                       74, 86, 98, 105, 111, 123, 125],
+                             names=["Design", "K", "T", "N", "Datetime", "MM", "DD",
+                                    "hh:mm:ss", "Measure", "Accuracy", "rms", "F",
+                                    "Bias", "Resid", "TRX", "RCX", "Chi", "S"])
+
+    # Combining the datetime columns
+    date_array = [f"{x}/{y}/{z} {t}" for x, y, z, t in radar_table["Datetime", "MM", "DD", "hh:mm:ss"]]
+    radar_table["Datetime"] = Time.strptime(date_array, '%Y/%m/%d %H:%M:%S')
+    radar_table.remove_columns(["MM", "DD", "hh:mm:ss"])
+
+    # Adding metadata
+    radar_table.meta["Title"] = "Radar Observations"
+    radar_table.meta["Column Info"] = {'Designation': 'number or the provisional designation of the asteroid.',
+                                       'K, Type': ('observation type and technology provided by the MPC. A "c" '
+                                                   'indicates the radar observation is referenced to the '
+                                                   'asteroid center of mass, and an "s" indicates the measurement '
+                                                   'is referenced to the radar bounce point.'),
+                                       'Datetime': 'date in UTC format.',
+                                       'Radar range or range rate': ('refers to columns measure (km or km/day), '
+                                                                     'accuracy (precision ofthe measurement), '
+                                                                     'rms, F, bias and Resid.'),
+                                       'Quality': ('transmit (TRX) and receive (RCX) station are given. When '
+                                                   'these differ, an observation is considered as belonging to '
+                                                   'the receiver station. the value of chi from the chi**2 test '
+                                                   '(characterization of the relative quality of the '
+                                                   'observation).The "S" column is "Yes" if the observation is '
+                                                   'used in our orbit, and "No" if it has been discarded.')}
+
+    return radar_table
+
+
+def parse_observations(resp_str, verbose=False):
+    """
+    Parse the close approach response string into the close approach tables.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the tables.
+
+    Returns
+    -------
+    response : list(Table)
+        List of response tables.
+    """
+
+    output_tables = list()  # Setting up to collect the output tables
+
+    # Split the meta data from the data table(s)
+    header, dat_tabs = resp_str.split("END_OF_HEADER")
+
+    # Make the metadata table
+    output_tables.append(_parse_obs_meta(header))
+
+    # Split apart the data tables (there should be one or two of them)
+    # Each Table starts with two header lines of the form:
+    # ! Object ...
+    # ! Design ...
+    table_list = dat_tabs.split("\n!")
+    optical_tab = table_list[2]  # This table will always exist
+
+    # Pulling satellite/roving observer observations out of the optical table if
+    # there are any (these rows have different column structures)
+    optical_tab_list = np.array(optical_tab.split("\n")[1:])  # First row is headings
+    T_col = np.array([(x[12:15]).strip() for x in optical_tab_list])
+    s_rows = '\n'.join(optical_tab_list[T_col == 's'])  # looking for sattelite observations
+    v_rows = '\n'.join(optical_tab_list[T_col == 'v'])  # looking for roving observer observations
+    optical_str = '\n'.join(optical_tab_list[(T_col != 's') & (T_col != 'v')])
+
+    # Building the optical observation table(s)
+    output_tables.append(_parse_opt_obs(optical_str))
+
+    if s_rows:
+        if verbose:
+            print("Found satellite observations")
+
+        output_tables.append(_parse_sat_obs(s_rows))
+
+    if v_rows:
+        if verbose:
+            print("Found roving observer observations.")
+
+        output_tables.append(_parse_rov_obs(v_rows))
+
+    # Building the radar table if it exists
+    if len(table_list) >= 5:
+        radar_str = table_list[4]  # This table will sometimes exist
+        output_tables.append(_parse_radar_obs(radar_str))
+
+    return output_tables
+
+
+def parse_physical_properties(resp_str):
+    """
+    Parse the physical properties response string.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    response : Table
+        The response table.
+    """
+
+    if resp_str == '':
+        raise ValueError('Object not found: the name of the object is wrong or misspelt')
+
+    # Split apart the table and reference data
+    tbl, refs = resp_str.split("REFERENCES")
+
+    # Some rows have multple values which we will split into different Rows
+    tbl_list = tbl.split("\n")
+
+    repaired_string = ""
+    for elt in tbl_list:
+        row = elt.split(",")
+        if len(row) > 4:
+            for i in range(1, len(row)-2):
+                repaired_string += f"{row[0]},{row[i]},{row[-2]},{row[-1]}\n"
+        else:
+            repaired_string += elt + "\n"
+
+    # Building the physical properties table
+    phys_prop = Table.read(repaired_string, format="ascii.no_header",
+                           names=('Property', 'Value', 'Units', 'Reference'))
+
+    # Building the referenced table
+    ref_list = refs.split("\n")
+    search_pat = re.compile(r"(\[\d+\]),([\w\s]+),(.+)")
+
+    numbers = list()
+    names = list()
+    sources = list()
+
+    for ref in ref_list:
+        if not ref:
+            continue  # some extra empty rows
+
+        num, nm, src = search_pat.search(ref).groups()
+        numbers.append(num)
+        names.append(nm)
+        sources.append(src)
+
+    ref_table = Table(data=[numbers, names, sources],
+                      names=["Reference", "Reference Name", "Reference Additional"])
+
+    # Joining the tables
+    phys_prop = join(phys_prop, ref_table, keys='Reference')
+    phys_prop.remove_column("Reference")
+    phys_prop.sort("Property")
+
+    return phys_prop
+
+
+def _make_prop_table(props, vals, secname):
+    """
+    Given correspondong properties and values, and the section the relate to,
+    build an orbital properties style table.
+    """
+
+    prop_tab = Table(names=("Property", "Value"), data=[props, vals], dtype=[str, str])
+    prop_tab["Section"] = secname
+    prop_tab = prop_tab["Section", "Property", "Value"]
+
+    return prop_tab
+
+
+def _fill_sym_matrix(data, dim):
+    """
+    Fill a symmetrical matrix from a 1D data array, given a dimension.
+    """
+
+    matrix = np.zeros((dim, dim))
+    d1, d2 = np.triu_indices(dim)
+
+    for i, val in enumerate(data):
+        matrix[d1[i], d2[i]] = val
+        matrix[d2[i], d1[i]] = val
+
+    return matrix
+
+
+def parse_orbital_properties(resp_str):
+    """
+    Parse the orbintal properties response string.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    response : list(Table)
+        List of response tables.
+    """
+
+    table_lst = list()
+
+    header, body = resp_str.split("END_OF_HEADER")
+
+    # Parse Header
+    pat = re.compile(r'(\w+)\s+=\s+\'?([^\']+)\'?\s+!')
+    props = list()
+    vals = list()
+
+    for row in header.split("\n"):
+        if not row:  # Skip empty entries
+            continue
+        matches = pat.match(row).groups()
+        props.append(matches[0])
+        vals.append(matches[1].strip())
+
+    table_lst.append(_make_prop_table(props, vals, "HEADER"))
+
+    body_lst = body.split("! ")
+    pat = re.compile("(.+): +")
+
+    # Keplerian or equinoctial elements
+    ek_elts = body_lst[1].split("\n")
+    ek_section = pat.search(ek_elts[0]).groups()[0]
+    ek_names = re.split(", +", pat.sub("", ek_elts[0]))
+
+    prop_list = list()
+    for ek in ek_elts[1:]:
+        eklst = re.split(r"\s+", ek)
+        if len(eklst) < 2:  # skip empty rows
+            continue
+        if eklst[1] in ("KEP", "EQU"):
+            ek_vals = eklst[2:]
+        else:
+            prop_list.append((eklst[1], eklst[2]))
+
+    ek_tbl = _make_prop_table(ek_names, ek_vals, ek_section)
+    for prop in prop_list:
+        ek_tbl.add_row([prop[0], prop[1], prop[0]])
+
+    table_lst.append(ek_tbl)
+
+    # We need this list of properties for a number of tables so pull them out now
+    cols = list(ek_tbl["Property"][ek_tbl["Section"] == ek_section])
+
+    # Non-gravitational parameters
+    lsp_lst = body_lst[2].split("\n")
+
+    section = pat.search(lsp_lst[0]).groups()[0]
+    lsp_names = re.split(", +", pat.sub("", lsp_lst[0]))
+    lsp_vals = re.split(r"\s+", lsp_lst[1], maxsplit=len(lsp_names)+1)[2:]
+
+    lps_tbl = _make_prop_table(lsp_names, lsp_vals, section)
+    table_lst.append(lps_tbl)
+
+    # dynamical parameters
+    kep_n = 3
+    if 'parameters' in body_lst[3]:
+        section = re.search(r"(\w+ parameters)", body_lst[3]).groups()[0]
+
+        ngr_names, ngr_vals = body_lst[4].split("\n")[:2]
+        ngr_names = re.split(r",\s+", ngr_names)
+        ngr_vals = re.split(r"\s+", ngr_vals)[2:]
+
+        ngr_tbl = _make_prop_table(ngr_names, ngr_vals, section)
+        table_lst.append(ngr_tbl)
+
+        for row in ngr_tbl:
+            if float(row["Value"]):
+                cols.append(row["Property"])
+
+        kep_n = 5
+
+    # Equinoctial or Keplarian specific code
+    if "Equinoctial" in ek_section:
+
+        for row in body_lst[-3:]:
+            if "WEA" in row:
+                row, cov = re.split("\n", row, maxsplit=1)
+
+            row_list = re.split(r"\s+", row)
+            table_lst.append(_make_prop_table(cols, row_list[1:len(cols)+1], row_list[0]))
+
+    else:  # Keplarian
+        props = list()
+        vals = list()
+        pat = re.compile(r"(\w+)\s+(.+)\n")
+
+        for row in body_lst[kep_n:-1]:
+            matches = pat.match(row).groups()
+
+            props.append(matches[0])
+            vals.append(matches[1])
+
+        table_lst.append(_make_prop_table(props, vals, props))
+
+        row, cov = re.split("\n", body_lst[-1], maxsplit=1)
+        row_list = re.split(r"\s+", row)
+        table_lst.append(_make_prop_table(cols, row_list[1:len(cols)+1], row_list[0]))
+
+    # Building the main table, adding the section grouping, and putting in the return list
+    main_table = vstack(table_lst)
+    main_table.meta["Title"] = "Orbital Elements"
+    orbital_table_list = [main_table.group_by("Section")]
+
+    # Making the matrix tables (COV/COR/NOR)
+    mat_dict = dict()
+
+    for row in cov.split("\n"):
+        rlst = re.split(r"\s+", row)
+        if len(rlst) < 2:
+            continue
+
+        mat_dict[rlst[1]] = mat_dict.get(rlst[1], []) + rlst[2:]
+
+    dimension = int(lps_tbl["Value"][lps_tbl["Property"] == "dimension"][0])
+
+    for mat_name in mat_dict:
+        mat_arr = _fill_sym_matrix(np.array(mat_dict[mat_name]).astype(float), dimension)
+        mat_table = Table(data=mat_arr, names=cols)
+        mat_table.add_column(Column(name=mat_name, data=cols), index=0)
+
+        mat_table.meta["Title"] = mat_name
+
+        orbital_table_list.append(mat_table)
+
+    return orbital_table_list
+
+
+def parse_ephemerides(resp_str):
+    """
+    Parse the ephemerides response string.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    response : Table
+        The response table.
+    """
+
+    if "No ephemerides file" in resp_str:
+        raise ValueError('No ephemerides file found for this object.')
+
+    # Splitting the string into lines up to the nines which is where the table data starts
+    resp_list = re.split("\n", resp_str, maxsplit=9)
+
+    # Parsing the table info
+    # This row defines the column widthes as == ==== ...
+    col_inds = np.array([[m.start(0), m.end(0)] for m in re.finditer(r'\s+(=+)', resp_list[8])])
+
+    # Want to combine the column names and units
+    colnames = [(' '.join(x)).strip() for x in zip([resp_list[6][x:y].strip() for x, y in col_inds],
+                                                   [resp_list[7][x:y].strip() for x, y in col_inds])]
+
+    ephem_table = Table.read(resp_list[9], format="ascii.fixed_width_no_header",
+                             col_starts=col_inds[:, 0], col_ends=col_inds[:, 1], names=colnames)
+
+    # Combine Date and Hour columns and make into time object
+    ephem_table["Date"] = convert_time(ephem_table["Date"], ephem_table["Hour (UTC)"]/24, conversion_string="%d %b %Y")
+    ephem_table.remove_column("Hour (UTC)")
+
+    # Change error columns in to floats and give column names units
+    ephem_table["Err1"] = [float(x.replace('"', '')) for x in ephem_table["Err1"]]
+    ephem_table.rename_column("Err1", 'Err1 (")')
+
+    ephem_table["Err2"] = [float(x.replace('"', '')) for x in ephem_table["Err2"]]
+    ephem_table.rename_column("Err2", 'Err2 (")')
+
+    # Parse the query meta data and add to the table
+    for meta in resp_list[:5]:
+        elts = meta.split(": ")
+        ephem_table.meta[elts[0]] = elts[1]
+
+    # Adding the column info
+    ephem_table.meta["Column Info"] = ('Ephemerides data frame shows:\n'
+                                       '-The Date and the Hour considered\n'
+                                       '-The Right Ascension (RA) and Declination (DEC) '
+                                       'coordinates\n'
+                                       '-The estimated V magnitude (Mag) of the object\n'
+                                       '-The Altitude (Alt) over the horizon of the '
+                                       'target at the specific time for the specific '
+                                       'location. For negative values the object is '
+                                       'unobservable. For geocentric position and for '
+                                       'space telescopes the value is meaningless\n'
+                                       '-The Airmass for the specific time. The Airmass'
+                                       ' is INF when the object is under the horizon. '
+                                       'For geocentric position and space telescope the'
+                                       ' value is meaningless\n'
+                                       '-The Sun elevation (Sun elev.) of the target, '
+                                       'that means the angle of the Sun above or under '
+                                       'the Horizon\n'
+                                       '-The Solar elongation (SolEl) of the target, '
+                                       'that means the angle Sun-observer-target\n'
+                                       '-The Lunar elongation (LunEl) of the target, '
+                                       'that means the angle Moon-observer-target\n'
+                                       '-The Phase angle, that is the angle '
+                                       'Sun-target-observer\n'
+                                       '-The Galactic Latitude (Glat)\n'
+                                       '-The Galactic Longitude (Glon)\n'
+                                       '-The distance Sun-object (R)\n'
+                                       '-The distance Earth-object (Delta)\n'
+                                       '-The Apparent motion in RA (corrected by '
+                                       'cos(DEC), which means the real motion on sky), '
+                                       'and in DEC, in arcsec/min of the object\n'
+                                       '-The angular velocity (Vel) in arcsec/min\n'
+                                       '-The position Angle (PA) value\n'
+                                       '-The Sky plane error with the long axis (Err1),'
+                                       ' short axis (Err2)\n'
+                                       '-The uncertainty ellipse position angle, given '
+                                       'in degrees. It gives the primary axis '
+                                       'orientation of the major axis of the ellipse in'
+                                       ' degrees measured from North.')
+
+    return ephem_table
+
+
+def parse_summary(resp_str):
+    """
+    Parse the summary data string.
+
+    Parameters
+    ----------
+    resp_str : str
+        String containing the raw data for the table.
+
+    Returns
+    -------
+    response : Table
+        The response table.
+    """
+
+    if "Object not found" in resp_str:
+        raise ValueError('Object not found: the name of the object is wrong or misspelt')
+
+    parsed_html = BeautifulSoup(resp_str, 'lxml')
+
+    # Pull out the properties
+    props = parsed_html.find_all("div", {"class": "simple-list__cell"})
+    prop_list = [str(x.contents[0]).strip() for x in props]
+
+    # Pulling out Discovery data/Observatory if they are present
+    # (These don't follow the name-value-unit format
+    try:
+        obs_ind = prop_list.index("Discovery Date")
+    except ValueError:
+        try:
+            obs_ind = prop_list.index("Observatory")
+        except ValueError:
+            obs_ind = len(prop_list)
+
+    obs_props = prop_list[obs_ind:]
+    prop_list = prop_list[:obs_ind]
+
+    # Building the table
+    summary_tab = Table(names=["Physical Properties", "Value", "Units"],
+                        data=np.array(prop_list).reshape((len(prop_list)//3, 3)))
+
+    # Dealing with the special cases
+    diameter = parsed_html.find_all("span", {"id": re.compile("_NEOSearch_WAR_PSDBportlet_.*diameter-value.*")})
+    diameter = diameter[0].contents[0]
+    summary_tab["Value"][summary_tab["Physical Properties"] == "Diameter"] = diameter
+
+    summary_tab["Physical Properties"][summary_tab["Physical Properties"] == ""] = ("Nominal distance "
+                                                                                    "(from Earth center)")
+
+    # Adding the other properties as metadata
+    for i in range(0, len(obs_props), 2):
+        summary_tab.meta[obs_props[i]] = obs_props[i+1]
+
+    return summary_tab
diff --git a/astroquery/esa/neocc/test/__init__.py b/astroquery/esa/neocc/test/__init__.py
new file mode 100755
index 0000000000..e69de29bb2
diff --git a/astroquery/esa/neocc/test/data/1685.rwo b/astroquery/esa/neocc/test/data/1685.rwo
new file mode 100644
index 0000000000..33078b9797
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/1685.rwo
@@ -0,0 +1,55 @@
+version =   3
+errmod  = 'vfcc17'
+RMSast  =   3.56997E-01
+RMSmag  =   4.17766E-01
+END_OF_HEADER
+! Object   Obser ============= Date ============= ================== Right Ascension =================  ================= Declination ===================== ==== Magnitude ==== Ast Obs  Residual SEL
+! Design   K T N YYYY MM DD.dddddddddd   Accuracy HH MM SS.sss  Accuracy      RMS  F     Bias    Resid sDD MM SS.ss  Accuracy      RMS  F     Bias    Resid Val  B   RMS  Resid Cat Cod       Chi A M
+ 1685      O X   1948 07 17.37721       1.000E-05 21 11 38.550  1.489E-01  999.000 F    0.000  -87.315 +06 56 14.40  1.000E-01  999.000 F    0.000  -29.964                         662      0.09 0 0
+ 1685      O C 2 1999 04 20.458706      1.000E-06 17 25 59.714  1.261E-02    0.500 F    0.000   -0.296 -32 45 54.61  1.000E-02    0.500 F    0.000   -0.062 17.05V  0.50  -0.12   l 689      0.61 1 1
+ 1685      O V   2008 02 14.30053       1.000E-05 05 13 06.230  1.500E-01    1.118 F   -0.107    0.426 -00 34 40.90  1.000E-01    1.118 F    0.073   -0.325 13.8 V  0.70  -0.07   o 247      0.48 1 1
+ 1685      O v   2008 02 14.30053 237.818000  37.819100    470.0 247
+ 1685      O V   2008 02 14.30205       1.000E-05 05 13 06.820  1.500E-01    1.118 F   -0.107    0.617 -00 34 40.00  1.000E-01    1.118 F    0.073   -0.375 14.1 V  0.70   0.23   o 247      0.65 1 1
+ 1685      O v   2008 02 14.30205 237.818000  37.819100    470.0 247
+ 1685      O V   2008 02 14.30382       1.000E-05 05 13 07.350  1.500E-01    1.118 F   -0.107   -1.518 -00 34 39.20  1.000E-01    1.118 F    0.073   -0.681 14.1 V  0.70   0.23   o 247      1.49 1 1
+ 1685      O v   2008 02 14.30382 237.818000  37.819100    470.0 247
+ 1685      O V   2008 02 14.30508       1.000E-05 05 13 07.930  1.500E-01    1.118 F   -0.107    0.002 -00 34 38.20  1.000E-01    1.118 F    0.073   -0.469 14.5 V  0.70   0.63   o 247      0.42 1 1
+ 1685      O v   2008 02 14.30508 237.818000  37.819100    470.0 247
+ 1685      O V   2008 02 14.30660       1.000E-05 05 13 08.470  1.500E-01    1.118 F   -0.107   -0.560 -00 34 37.40  1.000E-01    1.118 F    0.073   -0.619 13.4 V  0.70  -0.47   o 247      0.75 1 1
+ 1685      O v   2008 02 14.30660 237.818000  37.819100    470.0 247
+ 1685      S S   2010 02 11.490128      1.000E-06 15 06 37.600  1.316E-01    1.000 F    0.098    0.107 -28 39 41.90  1.000E-01    1.000 F    0.063   -0.230                       L C51      0.25 1 0
+ 1685      S s   2010 02 11.49012 1      -4336.226400000000      -4288.288000000000      -3256.894200000000 C51
+ 1685      S S   2010 02 11.622433      1.000E-06 15 06 45.590  1.316E-01    1.000 F    0.098    0.105 -28 40 46.20  1.000E-01    1.000 F    0.063   -0.564                       L C51      0.57 1 0
+ 1685      S s   2010 02 11.62243 1      -4330.288300000000      -4305.010400000000      -3242.622600000000 C51
+ 1685      S S   2010 02 11.754736      1.000E-06 15 06 53.530  1.316E-01    1.000 F    0.098   -0.189 -28 41 49.80  1.000E-01    1.000 F    0.063   -0.291                       L C51      0.35 1 0
+ 1685      S s   2010 02 11.75473 1      -4323.588000000000      -4320.723800000000      -3230.463299999999 C51
+ 1685      S S   2010 02 11.887041      1.000E-06 15 07 01.460  1.316E-01    1.000 F    0.098   -0.249 -28 42 53.20  1.000E-01    1.000 F    0.063    0.092                       L C51      0.27 1 0
+ 1685      S s   2010 02 11.88704 1      -4316.748600000000      -4336.489799999999      -3218.295200000000 C51
+ 1685      S S   2010 02 11.953257      1.000E-06 15 07 05.440  1.315E-01    1.000 F    0.098    0.001 -28 43 25.50  1.000E-01    1.000 F    0.063   -0.355                       L C51      0.36 1 0
+ 1685      S s   2010 02 11.95325 1      -4304.301900000000      -4326.899999999999      -3247.927200000000 C51
+ 1685      O C K 2012 07 12.14463       1.000E-05 23 59 03.240  1.426E-01    1.000 F   -0.029   -0.187 +18 07 37.50  1.000E-01    1.000 F    0.046   -0.091 14.7 V  0.70   0.18   u I56      0.21 1 1
+ 1685      O C K 2012 07 12.14681       1.000E-05 23 59 03.910  1.426E-01    1.000 F   -0.029   -0.549 +18 07 47.00  1.000E-01    1.000 F    0.046    0.069 14.8 V  0.70   0.28   u I56      0.55 1 1
+ 1685      O C K 2012 07 12.14899       1.000E-05 23 59 04.590  1.426E-01    1.000 F   -0.029   -0.768 +18 07 56.50  1.000E-01    1.000 F    0.046    0.230 14.7 V  0.70   0.18   u I56      0.80 1 1
+ 1685      S S   2021 05 31.042506      1.000E-06 11 45 18.322  1.468E-02    1.000 F    0.212    0.178 -11 54 29.38  1.000E-02    1.000 F    0.088   -1.625                       L C51      1.64 1 0
+ 1685      S s   2021 05 31.04250 1      -6484.022500000000      -1118.991300000000      -1930.371400000000 C51
+ 1685      S S   2021 05 31.173281      1.000E-06 11 45 23.052  1.468E-02    1.000 F    0.212   -0.147 -11 53 48.91  1.000E-02    1.000 F    0.088    0.429                       L C51      0.45 1 0
+ 1685      S s   2021 05 31.17328 1      -6490.866600000000      -1130.893200000000      -1900.120100000000 C51
+ 1685      S S   2021 05 31.369255      1.000E-06 11 45 30.187  1.468E-02    1.000 F    0.212   -0.698 -11 52 52.32  1.000E-02    1.000 F    0.088   -0.149                       L C51      0.71 1 0
+ 1685      S s   2021 05 31.36925 1      -6463.753400000000      -1158.987800000000      -1974.379100000000 C51
+ 1685      S S   2021 05 31.761455      1.000E-06 11 45 44.686  1.468E-02    1.000 F    0.212   -1.305 -11 50 59.75  1.000E-02    1.000 F    0.088    0.092                       L C51      1.31 1 0
+ 1685      S s   2021 05 31.76145 1      -6459.399200000000      -1201.464200000000      -1963.200300000000 C51
+ 1685      S S   2021 06 01.022880      1.000E-06 11 45 54.650  1.468E-02    1.000 F    0.212    0.687 -11 49 46.85  1.000E-02    1.000 F    0.088   -0.505                       L C51      0.85 1 0
+ 1685      S s   2021 06 01.02288 1      -6447.879800000000      -1231.902500000000      -1982.163400000000 C51
+ 1685      O C   2023 08 15.037233      1.000E-06 15 39 30.002  1.433E-02    0.735 F    0.000    0.291 -17 12 39.28  1.000E-02    0.735 F    0.000    0.355 16.45c  0.50  -0.17   V W68      0.63 1 1
+ 1685      O C   2023 08 15.060168      1.000E-06 15 39 31.159  1.433E-02    0.735 F    0.000    0.044 -17 12 33.62  1.000E-02    0.735 F    0.000    0.073 16.99c  0.50   0.37   V W68      0.12 1 1
+! Object   Obser ====== Date =======  ============ Radar range/range rate (km or km/d) =============  Station  ====  Residual
+! Design   K T N YYYY MM DD hh:mm:ss         Measure  Accuracy       rms F        Bias       Resid    TRX  RCX        Chi   S
+ 1685      V s   1980 07 22 07:00:00   -878240.64531   1.08832   1.08832 F     0.00000     1.28093    -1   -1         1.20  1
+ 1685      V s   1988 07 21 07:30:00   -825097.87226  16.32483  16.32483 F     0.00000    -1.10430    -1   -1         0.07  1
+ 1685      R s   1988 07 22 07:34:00  32723876.63161   2.99792   2.99792 F     0.00000     0.53779    -1   -1         0.22  1
+ 1685      R s   1988 07 23 07:20:00  31976564.33515   2.99792   2.99792 F     0.00000    -0.07246    -1   -1         0.01  1
+ 1685      R s   1988 07 24 07:35:00  31263444.26790   2.99792   2.99792 F     0.00000     0.08916    -1   -1         0.05  1
+ 1685      R s   1988 07 25 07:42:00  30606046.92461   2.99792   2.99792 F     0.00000     0.33692    -1   -1         0.15  1
+ 1685      R c   2012 07 22 08:55:00  46331349.56662   1.19917   1.19917 F     0.00000     0.05516    -1   -1         0.32  1
+ 1685      R c   2016 01 19 04:00:00  23823552.84755   1.49896   1.49896 F     0.00000     0.60426    -14  -14        0.51  1
+ 1685      R c   2016 01 22 01:20:00  23417404.66809   0.74948   0.74948 F     0.00000    -0.20286    -14  -14        0.65  1
diff --git a/astroquery/esa/neocc/test/data/1979XB.risk b/astroquery/esa/neocc/test/data/1979XB.risk
new file mode 100644
index 0000000000..3af3aac8b5
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/1979XB.risk
@@ -0,0 +1,27 @@
+Object: 1979XB
+
+    date             MJD        sigma   sigimp   dist +/- width  stretch     p_RE      exp. en.    PS    TS  
+YYYY/MM/DD.ddd                                       (RE)          (RE)      (RE)        (MT)
+------------------------------------------------------------------------------------------------------------
+ 2056-12-12.902    72344.902    0.255    0.000   0.22 +/- 0.105   2.89E6    2.86E-7    1.15E-2    -3.22   0   
+ 2065-12-16.462    75635.463   -1.110    0.000   1.10 +/- 0.092   3.61E7    2.70E-9    9.03E-5    -5.36   0   
+ 2086-12-16.663    83305.664   -1.101    0.000   1.02 +/- 0.143   4.22E6    7.14E-8    2.39E-3    -4.03   0   
+ 2101-12-14.203    88781.204   -0.384    0.000   0.61 +/- 0.089   1.94E8    3.48E-9    1.31E-4    -5.36   0   
+ 2105-12-12.764    90240.765    1.003    0.000   0.91 +/- 0.062   2.19E7    1.28E-8    5.74E-4    -4.75   0   
+ 2113-12-14.753    93164.753   -0.706    0.000   0.29 +/- 0.027   1.31E6    5.15E-7    1.85E-2    -3.25   0   
+ 2113-12-14.756    93164.756   -0.708    0.000   1.00 +/- 0.045   7.13E7    4.53E-9    1.63E-4    -5.30   0   
+ 2117-12-15.496    94626.496   -1.316    0.000   0.36 +/- 0.000   1.74E8    2.06E-9    6.91E-5    -5.68   0   
+
+Based on    18 optical observations (of which    0 are rejected as outliers)
+from 1979/12/11.511 to 1979/12/15.430.
+
+Coordinates are given on the Target Plane
+
+Unit is one Earth radius, but impact cross section
+has radius between  1.12 and  1.12 Earth radii
+
+Coordinates for LOV = EQU scaled= 1 second= F
+
+AstOD software version= 2.0, Date of computation=20190808 162907.255 CET
+
+
diff --git a/astroquery/esa/neocc/test/data/1979XB.rwo b/astroquery/esa/neocc/test/data/1979XB.rwo
new file mode 100644
index 0000000000..02a8b8ec3b
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/1979XB.rwo
@@ -0,0 +1,24 @@
+version =   3
+errmod  = 'vfcc17'
+RMSast  =   4.49806E-01
+END_OF_HEADER
+! Object   Obser ============= Date ============= ================== Right Ascension =================  ================= Declination ===================== ==== Magnitude ==== Ast Obs  Residual SEL
+! Design   K T N YYYY MM DD.dddddddddd   Accuracy HH MM SS.sss  Accuracy      RMS  F     Bias    Resid sDD MM SS.ss  Accuracy      RMS  F     Bias    Resid Val  B   RMS  Resid Cat Cod       Chi A M
+ 1979XB    O A 0 1979 12 11.51059       1.000E-05 04 26 03.910  1.306E-01    2.500 F    0.000    1.712 -29 29 25.30  1.000E-01    2.500 F    0.000    0.089 16      1.00   0.00     413      0.95 1 1
+ 1979XB    O A 0 1979 12 11.55573       1.000E-05 04 25 24.260  1.304E-01    2.500 F    0.000   -2.105 -29 35 22.40  1.000E-01    2.500 F    0.000   -0.769                         413      1.76 1 0
+ 1979XB    O A 0 1979 12 13.44144       1.000E-05 03 48 05.550  1.232E-01    2.500 F    0.000   -1.568 -34 46 29.80  1.000E-01    2.500 F    0.000   -1.496                         413      1.03 1 0
+ 1979XB    O A 0 1979 12 13.44838       1.000E-05 03 47 53.980  1.232E-01    2.500 F    0.000    3.561 -34 47 51.60  1.000E-01    2.500 F    0.000    2.496                         413      2.03 1 0
+ 1979XB    O A 0 1979 12 14.43661       1.000E-05 03 13 17.520  1.174E-01    2.500 F    0.000   -0.428 -38 28 53.30  1.000E-01    2.500 F    0.000   -0.001                         413      0.20 1 0
+ 1979XB    O A 0 1979 12 14.44355       1.000E-05 03 12 58.780  1.174E-01    2.500 F    0.000   -1.874 -38 30 34.80  1.000E-01    2.500 F    0.000    0.100                         413      0.89 1 0
+ 1979XB    O A 0 1979 12 15.41910       1.000E-05 02 18 42.460  1.107E-01    4.330 F    0.000   -1.736 -42 26 47.40  1.000E-01    4.330 F    0.000   -0.128                         413      0.42 1 0
+ 1979XB    O A 0 1979 12 15.41979       1.000E-05 02 18 39.640  1.107E-01    4.330 F    0.000   -0.354 -42 26 58.20  1.000E-01    4.330 F    0.000   -1.482                         413      0.37 1 0
+ 1979XB    O A 0 1979 12 15.42049       1.000E-05 02 18 36.680  1.107E-01    4.330 F    0.000   -0.037 -42 27 05.00  1.000E-01    4.330 F    0.000    1.296                         413      0.31 1 0
+ 1979XB    O A 0 1979 12 15.42118       1.000E-05 02 18 33.790  1.107E-01    4.330 F    0.000    0.593 -42 27 16.40  1.000E-01    4.330 F    0.000   -0.667                         413      0.21 1 0
+ 1979XB    O A 0 1979 12 15.42187       1.000E-05 02 18 30.730  1.107E-01    4.330 F    0.000   -0.648 -42 27 24.40  1.000E-01    4.330 F    0.000    0.765                         413      0.24 1 0
+ 1979XB    O A 0 1979 12 15.42257       1.000E-05 02 18 27.800  1.107E-01    4.330 F    0.000    0.034 -42 27 35.60  1.000E-01    4.330 F    0.000   -0.870                         413      0.21 1 0
+ 1979XB    O A 0 1979 12 15.42326       1.000E-05 02 18 24.910  1.107E-01    4.330 F    0.000    0.697 -42 27 44.20  1.000E-01    4.330 F    0.000   -0.047                         413      0.17 1 0
+ 1979XB    O A 0 1979 12 15.42396       1.000E-05 02 18 22.140  1.107E-01    4.330 F    0.000    3.173 -42 27 54.00  1.000E-01    4.330 F    0.000   -0.292                         413      0.77 1 0
+ 1979XB    O A 0 1979 12 15.42465       1.000E-05 02 18 18.900  1.106E-01    4.330 F    0.000   -0.015 -42 28 01.60  1.000E-01    4.330 F    0.000    1.523                         413      0.37 1 0
+ 1979XB    O A 0 1979 12 15.42535       1.000E-05 02 18 16.060  1.106E-01    4.330 F    0.000    1.708 -42 28 13.90  1.000E-01    4.330 F    0.000   -1.231                         413      0.51 1 0
+ 1979XB    O A 0 1979 12 15.42604       1.000E-05 02 18 12.890  1.106E-01    4.330 F    0.000   -0.682 -42 28 21.00  1.000E-01    4.330 F    0.000    1.075                         413      0.31 1 0
+ 1979XB    O A 0 1979 12 15.42951       1.000E-05 02 17 58.020  1.106E-01    4.330 F    0.000   -0.677 -42 29 10.60  1.000E-01    4.330 F    0.000   -1.294                         413      0.35 1 0
diff --git a/astroquery/esa/neocc/test/data/1994CJ1.phypro b/astroquery/esa/neocc/test/data/1994CJ1.phypro
new file mode 100644
index 0000000000..10deeec6f2
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/1994CJ1.phypro
@@ -0,0 +1,24 @@
+Rotation Period,30.0,h,[2]
+Quality,1,B,R,-,[2]
+Amplitude,0.8,mag,[2]
+Rotation Direction,-,-,[-]
+Spinvector L,-,deg,[-]
+Spinvector B,-,deg,[-]
+Taxonomy,A,-,[1]
+Taxonomy (all),A,-,[1]
+Absolute Magnitude (H),21.539,mag,[3]
+Slope Parameter (G),0.15**,mag,[4]
+Slope Parameter (G),0.15**,mag,[3]
+Albedo,-,-,[-]
+Diameter,170*,m,[5]
+Color Index Information,-,mag,[-]
+Sightings,Radar R,-,[6]
+
+REFERENCES
+
+[1],EARN,1.) Ieva, S. et al. (2018) Astron. Astrophys. 615, A127. (Photometric survey of 67 near-Earth objects)
+[2],EARN,1.) Warner, B.D. (2015) MPB 42, 41-53. (NEAR-EARTH ASTEROID LIGHTCURVE ANALYSIS AT CS3-PALMER DIVIDE STATION: 2014 JUNE-OCTOBER) (45 NEAs) 2.) <a href="http://echo.jpl.nasa.gov/asteroids/index.html">JPL's NEO Radar Detection Program Webpage</A>
+[3],ESA ODIM,ESA orbit determination and impact monitoring system
+[4],NEODyS,NEO Dynamic Site: https://newton.spacedys.com/neodys2
+[5],Estimation,Estimated from absolute magnitude
+[6],EARN,1.) <a href="http://echo.jpl.nasa.gov/asteroids/index.html">JPL's NEO Radar Detection Program Webpage</A>
diff --git a/astroquery/esa/neocc/test/data/2009BD.eq1 b/astroquery/esa/neocc/test/data/2009BD.eq1
new file mode 100644
index 0000000000..bb93042e17
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/2009BD.eq1
@@ -0,0 +1,41 @@
+format  = 'OEF2.0'       ! file format
+rectype = 'ML'           ! record type (1L/ML)
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+2009BD
+! Equinoctial elements: a, e*sin(LP), e*cos(LP), tan(i/2)*sin(LN), tan(i/2)*cos(LN), mean long.
+ EQU   1.0617101378986786E+00  -0.025818703424772  -0.044587885274639   -0.010590108706158   -0.003183567935651  328.342445924295
+ MJD     59400.000000000 TDT
+ MAG  28.241  0.150
+! Non-gravitational parameters: model used, number of model parameters, dimension, list of solve for parameters to be currently determined
+ LSP   1  2    8    1  2
+! Vector of dynamical parameters
+! Area-to-mass ratio [m^2/t], Yarkovsky parameter [1E-10 au/day^2]
+ NGR   3.92228537753657E-01 -5.47745799289690E-02
+! RMS    9.51104E-08   5.34106E-08   4.47485E-08   1.10381E-08   3.92551E-09   4.53546E-04   3.84023E-02   1.42153E-03
+! EIG   8.12187E-13   9.91506E-11   1.14077E-09   3.23655E-09   1.10120E-08   2.43064E-04   1.12416E-03   3.84141E-02
+! WEA   0.00000  -0.00000  -0.00000   0.00000   0.00000  -0.00861   0.99969   0.02321
+ COV   9.045990514037489E-15 -4.310036457017179E-15 -3.623923200230800E-15
+ COV   7.951277173791751E-16  2.433446550442114E-16 -4.077556067712391E-11
+ COV   1.856604260872520E-09  1.127418762306244E-10  2.852693731431724E-15
+ COV   1.695013101481106E-15 -5.107616571257660E-16 -1.582486235449776E-16
+ COV   2.134253610483744E-11 -8.850408878561094E-10 -3.395061739668442E-11
+ COV   2.002430444954872E-15 -3.168326921269105E-16 -9.416269632401159E-17
+ COV   1.919930885836673E-11 -1.458005542385519E-09 -5.214810877052482E-11
+ COV   1.218404125341872E-16  4.220573281161046E-17 -3.756839821274132E-12
+ COV   1.121700530687301E-10  5.572019776769766E-12  1.540960912636563E-17
+ COV  -1.111870974226557E-12  2.171817388574150E-11  1.460839240186428E-12
+ COV   2.057035958948727E-07 -1.270111586962808E-05 -5.031736877239956E-07
+ COV   1.474738404491826E-03  3.420817295306519E-05  2.020745570284735E-06
+ NOR   1.510392160590388E+24  3.010613756591358E+22 -2.847190405857299E+22
+ NOR  -3.923755200799400E+22  7.119193656338679E+22  3.165996417810469E+20
+ NOR   1.559455452436434E+18 -3.200499908212041E+19  6.121980907326906E+20
+ NOR  -5.623473512675061E+20 -7.986575664669402E+20  1.446144763410462E+21
+ NOR   6.307817607896067E+18  3.107869581052138E+16 -6.382017139330865E+17
+ NOR   5.389508119220778E+20  7.325948110922601E+20 -1.330387237238508E+21
+ NOR  -5.969336651611347E+18 -2.939907570786912E+16  6.032061168235244E+17
+ NOR   1.042952010180453E+21 -1.888457578653545E+21 -8.220830314108549E+18
+ NOR  -4.050470856079116E+16  8.317908634731254E+17  3.420540185237647E+21
+ NOR   1.491642233759076E+19  7.349239747451518E+16 -1.509124137606627E+18
+ NOR   6.636445438213666E+16  3.268852801282463E+14 -6.708641583403737E+15
+ NOR   1.610114931151027E+12 -3.304452850969597E+13  6.781869208569199E+14
diff --git a/astroquery/esa/neocc/test/data/2009BD.ke1 b/astroquery/esa/neocc/test/data/2009BD.ke1
new file mode 100644
index 0000000000..744bf32503
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/2009BD.ke1
@@ -0,0 +1,49 @@
+format  = 'OEF2.0'       ! file format
+rectype = 'ML'           ! record type (1L/ML)
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+2009BD
+! Keplerian elements: a, e, i, long. node, arg. peric., mean anomaly
+ KEP   1.0617247805226826E+00   0.051537228123124    1.266349635713  253.274880478698  316.800386773210  118.202272507656
+ MJD     59400.000000000 TDT
+ MAG  28.211  0.150
+! Non-gravitational parameters: model used, number of model parameters, dimension, list of solve for parameters to be currently determined
+ LSP   1  2    8    1  2
+! Vector of dynamical parameters
+! Area-to-mass ratio [m^2/t], Yarkovsky parameter [1E-10 au/day^2]
+ NGR   2.37035178629626E-01 -1.15784215281726E-02
+! PERIHELION   1.0070064283049109E+00
+! APHELION   1.1164431327404543E+00
+! ANODE   6.2600326949319839E-03
+! DNODE   1.1372972056508317E-01
+! MOID   4.3964231475132533E-03
+! PERIOD   399.5916069065273
+! PHA F
+! VINFTY     0.7154750514529
+! U_PAR 1.9
+! ORB_TYPE Apollo
+! RMS    7.01581E-08   5.31748E-08   1.29894E-06   5.09881E-06   3.74353E-05   4.09042E-04   3.57250E-02   8.21041E-04
+ COV   4.922152548986896E-15  3.484428884555513E-15 -7.634404945886848E-14
+ COV   4.148712009383356E-14  2.019040346257700E-12 -2.764463190818844E-11
+ COV   1.246867581529311E-09  3.843533198353016E-11  2.827561462755755E-15
+ COV  -5.405774536524888E-14  1.462216108485957E-14  1.290437163529423E-12
+ COV  -2.152041694491314E-11  1.355687457023633E-09  2.972665493188818E-11
+ COV   1.687235161726139E-12 -3.605754857704478E-12 -3.358876276638499E-11
+ COV   4.085564999083462E-10 -8.713427953220452E-09 -3.232365291370131E-10
+ COV   2.599781583430189E-11  1.383593807953824E-13 -2.622479867379940E-12
+ COV  -5.914677303229551E-08 -7.212764867149595E-10  1.401399763171649E-09
+ COV  -1.091986245865296E-08  7.512274544947883E-08  3.466647462202165E-09
+ COV   1.673157279294236E-07 -9.921020929085676E-06 -2.337541895298061E-07
+ COV   1.276275593949321E-03  2.340783169302650E-05  6.741076504304530E-07
+ COR   1.000000000000000E+00  9.340025104439406E-01 -8.377411503201720E-01
+ COR   1.159757854182112E-01  7.687523261713063E-01 -9.633073929925071E-01
+ COR   4.974742049257239E-01  6.672498332897613E-01  1.000000000000000E+00
+ COR  -7.826436979118973E-01  5.393083017084759E-02  6.482608808854323E-01
+ COR  -9.894099434912152E-01  7.136435069888891E-01  6.808875401123898E-01
+ COR   1.000000000000000E+00 -5.444273784075008E-01 -6.907568150681833E-01
+ COR   7.689461590507449E-01 -1.877712094825448E-01 -3.030874808446405E-01
+ COR   9.999999999999998E-01  7.248683848196402E-04 -1.257405477103848E-03
+ COR  -3.247060581244433E-01 -1.722934292829369E-01  9.999999999999999E-01
+ COR  -7.131284531778465E-01  5.617178168810760E-02  1.127882948103178E-01
+ COR   1.000000000000000E+00 -6.789155407408433E-01 -6.960274886266391E-01
+ COR   1.000000000000000E+00  7.980393862837573E-01  9.999999999999998E-01
diff --git a/astroquery/esa/neocc/test/data/2010GM23.phypro b/astroquery/esa/neocc/test/data/2010GM23.phypro
new file mode 100644
index 0000000000..600fc659b8
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/2010GM23.phypro
@@ -0,0 +1,21 @@
+Rotation Period,-,h,[-]
+Quality,-,-,[-]
+Amplitude,-,mag,[-]
+Rotation Direction,-,-,[-]
+Spinvector L,-,deg,[-]
+Spinvector B,-,deg,[-]
+Taxonomy,-,-,[-]
+Taxonomy (all),-,-,[-]
+Absolute Magnitude (H),24.663,mag,[1]
+Slope Parameter (G),0.15**,mag,[1]
+Slope Parameter (G),0.15**,mag,[2]
+Albedo,0.01,-,[3]
+Diameter,341,m,[3]
+Color Index Information,-,mag,[-]
+Sightings,-,-,[-]
+
+REFERENCES
+
+[1],ESA ODIM,ESA orbit determination and impact monitoring system
+[2],NEODyS,NEO Dynamic Site: https://newton.spacedys.com/neodys2
+[3],EARN,1.) Mainzer, A. et al. (2014) Astrophys. J. 784, 110. (The Population of Tiny Near-Earth Objects Observed by NEOWISE)
diff --git a/astroquery/esa/neocc/test/data/2016YC8.rwo b/astroquery/esa/neocc/test/data/2016YC8.rwo
new file mode 100644
index 0000000000..802a73980c
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/2016YC8.rwo
@@ -0,0 +1,99 @@
+version =   3
+errmod  = 'vfcc17'
+RMSast  =   4.91024E-01
+RMSmag  =   3.64713E-01
+END_OF_HEADER
+! Object   Obser ============= Date ============= ================== Right Ascension =================  ================= Declination ===================== ==== Magnitude ==== Ast Obs  Residual SEL
+! Design   K T N YYYY MM DD.dddddddddd   Accuracy HH MM SS.sss  Accuracy      RMS  F     Bias    Resid sDD MM SS.ss  Accuracy      RMS  F     Bias    Resid Val  B   RMS  Resid Cat Cod       Chi A M
+ 2016YC8   O C   2016 12 27.35845       1.000E-05 06 37 34.270  9.918E-02    0.661 F    0.043   -0.819 +48 36 30.70  1.000E-01    0.661 F   -0.019    0.396 20.6 V  0.70  -0.01   q G96      1.38 1 1
+ 2016YC8   O C   2016 12 27.36376       1.000E-05 06 37 32.630  9.918E-02    0.661 F    0.043   -0.710 +48 36 30.80  1.000E-01    0.661 F   -0.019    0.214 20.7 V  0.70   0.09   q G96      1.13 1 1
+ 2016YC8   O C   2016 12 27.36822       1.000E-05 06 37 31.260  9.918E-02    0.661 F    0.043   -0.559 +48 36 31.50  1.000E-01    0.661 F   -0.019    0.730 20.6 V  0.70  -0.01   q G96      1.40 1 1
+ 2016YC8   O C   2016 12 27.37256       1.000E-05 06 37 29.860  9.918E-02    0.661 F    0.043   -1.089 +48 36 31.60  1.000E-01    0.661 F   -0.019    0.699 20.6 V  0.70  -0.01   q G96      1.97 1 1
+ 2016YC8   O C   2016 12 27.41822       1.000E-05 06 37 15.870  9.918E-02    1.000 F    0.043   -0.599 +48 36 29.50  1.000E-01    1.000 F   -0.019   -0.107 20.6 V  0.70  -0.00   q I52      0.61 1 1
+ 2016YC8   O C   2016 12 27.41945       1.000E-05 06 37 15.550  9.918E-02    1.000 F    0.043   -0.063 +48 36 29.60  1.000E-01    1.000 F   -0.019    0.092 20.6 V  0.70  -0.00   q I52      0.11 1 1
+ 2016YC8   O C   2016 12 27.42085       1.000E-05 06 37 15.130  9.918E-02    1.000 F    0.043   -0.008 +48 36 29.30  1.000E-01    1.000 F   -0.019   -0.092 20.5 V  0.70  -0.10   q I52      0.09 1 1
+ 2016YC8   O C   2016 12 27.422375      1.000E-06 06 37 14.360  9.918E-02    0.300 F    0.000    0.033 +48 36 24.50  1.000E-01    0.300 F    0.000   -0.004 20.2 G  0.70  -0.12   U H01      0.11 1 1
+ 2016YC8   O C   2016 12 27.42332       1.000E-05 06 37 14.360  9.918E-02    1.000 F    0.043   -0.209 +48 36 29.10  1.000E-01    1.000 F   -0.019   -0.076 20.5 V  0.70  -0.10   q I52      0.22 1 1
+ 2016YC8   O C   2016 12 27.428553      1.000E-06 06 37 12.510  9.918E-02    0.300 F    0.000    0.073 +48 36 23.80  1.000E-01    0.300 F    0.000   -0.034 20.3 G  0.70  -0.02   U H01      0.27 1 1
+ 2016YC8   O C   2016 12 27.43494       1.000E-05 06 37 10.860  9.918E-02    0.661 F    0.043   -0.087 +48 36 27.90  1.000E-01    0.661 F   -0.019   -0.095 20.9 V  0.70   0.30   q G96      0.20 1 1
+ 2016YC8   O C   2016 12 27.436119      1.000E-06 06 37 10.240  9.918E-02    0.300 F    0.000   -0.024 +48 36 22.90  1.000E-01    0.300 F    0.000   -0.017 20.4 G  0.70   0.08   U H01      0.10 1 1
+ 2016YC8   O C   2016 12 27.43727       1.000E-05 06 37 10.150  9.918E-02    0.661 F    0.043   -0.175 +48 36 27.60  1.000E-01    0.661 F   -0.019   -0.127 20.6 V  0.70   0.00   q G96      0.33 1 1
+ 2016YC8   O C   2016 12 27.43948       1.000E-05 06 37 09.480  9.918E-02    0.661 F    0.043   -0.235 +48 36 27.50  1.000E-01    0.661 F   -0.019    0.038 19.9 V  0.70  -0.70   q G96      0.36 1 1
+ 2016YC8   O C   2016 12 27.455114      1.000E-06 06 37 04.630  9.919E-02    0.300 F    0.000    0.075 +48 36 20.10  1.000E-01    0.300 F    0.000   -0.073 20.5 G  0.70   0.18   U H01      0.36 1 1
+ 2016YC8   O C I 2016 12 27.80390       1.000E-05 06 35 44.550  9.917E-02    1.000 F    0.043    0.879 +48 36 42.70  1.000E-01    1.000 F   -0.019   -0.496                       q 587      1.01 1 0
+ 2016YC8   O C K 2016 12 27.80942       1.000E-05 06 35 42.970  9.917E-02    1.000 F    0.043    1.166 +48 36 45.00  1.000E-01    1.000 F   -0.019   -0.470                       q 587      1.26 1 0
+ 2016YC8   O C K 2016 12 27.96778       1.000E-05 06 34 55.040  9.915E-02    1.000 F    0.057   -0.256 +48 37 30.90  1.000E-01    1.000 F   -0.030   -0.526 20.1 V  0.70  -0.44   q I93      0.59 1 1
+ 2016YC8   O C K 2016 12 27.97361       1.000E-05 06 34 53.130  9.915E-02    1.000 F    0.057   -0.673 +48 37 32.70  1.000E-01    1.000 F   -0.030    0.231 20.4 V  0.70  -0.14   q I93      0.71 1 1
+ 2016YC8   O C K 2016 12 27.97985       1.000E-05 06 34 51.200  9.915E-02    1.000 F    0.057    0.047 +48 37 33.30  1.000E-01    1.000 F   -0.030   -0.203 20.3 V  0.70  -0.24   q I93      0.21 1 1
+ 2016YC8   O C K 2016 12 27.997619      1.000E-06 06 34 45.856  9.914E-03    0.400 F    0.000    0.092 +48 37 48.56  1.000E-02    0.400 F    0.000   -0.015 20.8 G  0.70   0.54   U Z84      0.23 1 1
+ 2016YC8   O C K 2016 12 28.007920      1.000E-06 06 34 42.461  9.914E-03    0.400 F    0.000   -0.090 +48 37 49.68  1.000E-02    0.400 F    0.000   -0.176 20.9 G  0.70   0.64   U Z84      0.50 1 1
+ 2016YC8   O C K 2016 12 28.270352      1.000E-06 06 33 27.560  9.913E-02    1.000 F   -0.002   -0.135 +48 38 08.50  1.000E-01    1.000 F   -0.008    0.155 20.4 V  0.70  -0.11   u H21      0.21 1 1
+ 2016YC8   O C K 2016 12 28.273946      1.000E-06 06 33 26.350  9.913E-02    1.000 F   -0.002   -0.239 +48 38 08.60  1.000E-01    1.000 F   -0.008    0.192 20.6 V  0.70   0.09   u H21      0.31 1 1
+ 2016YC8   O C K 2016 12 28.278900      1.000E-06 06 33 24.720  9.913E-02    1.000 F   -0.002   -0.013 +48 38 08.50  1.000E-01    1.000 F   -0.008    0.057 20.8 V  0.70   0.29   u H21      0.06 1 1
+ 2016YC8   O C K 2016 12 28.82595       1.000E-05 06 30 51.530  9.913E-02    1.000 F   -0.023   -0.061 +48 38 04.70  1.000E-01    1.000 F    0.268    0.189 20.0 R  0.70  -0.05   o K88      0.20 1 1
+ 2016YC8   O C K 2016 12 28.83152       1.000E-05 06 30 49.670  9.913E-02    1.000 F   -0.023   -0.134 +48 38 05.80  1.000E-01    1.000 F    0.268   -0.023 19.7 R  0.70  -0.35   o K88      0.14 1 1
+ 2016YC8   O C K 2016 12 28.83711       1.000E-05 06 30 47.830  9.913E-02    1.000 F   -0.023    0.125 +48 38 07.00  1.000E-01    1.000 F    0.268   -0.086 19.9 R  0.70  -0.15   o K88      0.15 1 1
+ 2016YC8   O C K 2016 12 28.84658       1.000E-05 06 30 45.670  9.913E-02    1.000 F   -0.023    0.658 +48 38 07.40  1.000E-01    1.000 F    0.268    0.207 20.1 R  0.70   0.05   o K51      0.69 1 1
+ 2016YC8   O C K 2016 12 28.84866       1.000E-05 06 30 44.960  9.913E-02    1.000 F   -0.023    0.498 +48 38 07.80  1.000E-01    1.000 F    0.268    0.092 20.1 R  0.70   0.05   o K51      0.51 1 1
+ 2016YC8   O C   2016 12 30.86742       1.000E-05 06 19 35.370  9.926E-02    1.225 F    0.047   -0.145 +48 34 06.60  1.000E-01    1.225 F   -0.019    0.546                       q 246      0.46 1 0
+ 2016YC8   O C   2016 12 30.86914       1.000E-05 06 19 34.620  9.926E-02    1.225 F    0.047   -0.644 +48 34 06.80  1.000E-01    1.225 F   -0.019    0.913                       q 246      0.91 1 0
+ 2016YC8   O C   2016 12 30.86964       1.000E-05 06 19 34.400  9.926E-02    1.225 F    0.047   -0.808 +48 34 05.80  1.000E-01    1.225 F   -0.019   -0.037 19.9 R  0.70   0.07   q 246      0.66 1 1
+ 2016YC8   O C   2016 12 30.87013       1.000E-05 06 19 34.280  9.926E-02    1.225 F    0.047   -0.019 +48 34 05.20  1.000E-01    1.225 F   -0.019   -0.588                       q 246      0.48 1 0
+ 2016YC8   O C   2016 12 30.87108       1.000E-05 06 19 33.860  9.926E-02    1.225 F    0.047   -0.348 +48 34 07.00  1.000E-01    1.225 F   -0.019    1.310                       q 246      1.11 1 0
+ 2016YC8   O C   2016 12 30.87129       1.000E-05 06 19 33.780  9.926E-02    1.225 F    0.047   -0.293 +48 34 06.30  1.000E-01    1.225 F   -0.019    0.631                       q 246      0.57 1 0
+ 2016YC8   O C   2017 01 01.79773       1.000E-05 06 06 45.750  9.975E-02    1.803 F    0.000    0.978 +48 19 12.00  1.000E-01    1.803 F    0.000   -0.033 19.9 V  0.70  -0.12   S 033      0.54 1 1
+ 2016YC8   O C   2017 01 01.80003       1.000E-05 06 06 44.680  9.975E-02    1.803 F    0.000    1.106 +48 19 11.10  1.000E-01    1.803 F    0.000   -0.096 19.6 V  0.70  -0.42   S 033      0.62 1 1
+ 2016YC8   O C   2017 01 01.80233       1.000E-05 06 06 43.600  9.975E-02    1.803 F    0.000    1.149 +48 19 10.50  1.000E-01    1.803 F    0.000    0.150 19.6 V  0.70  -0.42   S 033      0.64 1 1
+ 2016YC8   O C   2017 01 01.80463       1.000E-05 06 06 42.490  9.975E-02    1.803 F    0.000    0.909 +48 19 09.50  1.000E-01    1.803 F    0.000    0.006 19.6 V  0.70  -0.42   S 033      0.50 1 1
+ 2016YC8   O C   2017 01 01.80692       1.000E-05 06 06 41.420  9.975E-02    1.803 F    0.000    1.037 +48 19 08.60  1.000E-01    1.803 F    0.000   -0.033 19.3 V  0.70  -0.72   S 033      0.58 1 1
+ 2016YC8   O C   2017 01 01.82021       1.000E-05 06 06 34.940  9.975E-02    1.323 F    0.059   -0.343 +48 19 09.60  1.000E-01    1.323 F    0.016    0.227                       q 246      0.31 1 0
+ 2016YC8   O C   2017 01 01.82046       1.000E-05 06 06 34.860  9.975E-02    1.323 F    0.059    0.056 +48 19 09.80  1.000E-01    1.323 F    0.016    0.528                       q 246      0.40 1 0
+ 2016YC8   O C   2017 01 01.82097       1.000E-05 06 06 34.540  9.975E-02    1.323 F    0.059   -0.692 +48 19 10.90  1.000E-01    1.323 F    0.016    1.835                       q 246      1.48 1 0
+ 2016YC8   O C   2017 01 01.82123       1.000E-05 06 06 34.470  9.975E-02    1.323 F    0.059   -0.144 +48 19 07.40  1.000E-01    1.323 F    0.016   -1.559                       q 246      1.18 1 0
+ 2016YC8   O C   2017 01 01.82194       1.000E-05 06 06 34.120  9.975E-02    1.323 F    0.059   -0.232 +48 19 09.00  1.000E-01    1.323 F    0.016    0.331                       q 246      0.31 1 0
+ 2016YC8   O C   2017 01 01.82306       1.000E-05 06 06 33.670  9.975E-02    1.323 F    0.059    0.650 +48 19 08.50  1.000E-01    1.323 F    0.016    0.290                       q 246      0.54 1 0
+ 2016YC8   O C   2017 01 01.82429       1.000E-05 06 06 32.990  9.975E-02    1.323 F    0.059   -0.230 +48 19 08.00  1.000E-01    1.323 F    0.016    0.297                       q 246      0.28 1 0
+ 2016YC8   O C   2017 01 01.87492       1.000E-05 06 06 08.670  9.976E-02    1.803 F    0.000    1.179 +48 18 38.30  1.000E-01    1.803 F    0.000    0.200 19.3 V  0.70  -0.72   S 033      0.66 1 1
+ 2016YC8   O C   2017 01 01.87722       1.000E-05 06 06 07.540  9.976E-02    1.803 F    0.000    1.137 +48 18 36.80  1.000E-01    1.803 F    0.000   -0.081 20.5 V  0.70   0.48   S 033      0.63 1 1
+ 2016YC8   O C   2017 01 01.87951       1.000E-05 06 06 06.400  9.977E-02    1.803 F    0.000    0.954 +48 18 35.40  1.000E-01    1.803 F    0.000   -0.255 19.6 V  0.70  -0.42   S 033      0.55 1 1
+ 2016YC8   O C   2017 01 01.88256       1.000E-05 06 06 04.910  9.977E-02    1.803 F    0.000    1.008 +48 18 34.00  1.000E-01    1.803 F    0.000   -0.001 20.4 V  0.70   0.38   S 033      0.56 1 1
+ 2016YC8   O C   2017 01 01.92228       1.000E-05 06 05 45.370  9.978E-02    1.803 F    0.000    1.537 +48 18 10.50  1.000E-01    1.803 F    0.000    0.231 20.4 V  0.70   0.39   S 033      0.86 1 1
+ 2016YC8   O C   2017 01 01.92458       1.000E-05 06 05 44.210  9.978E-02    1.803 F    0.000    1.336 +48 18 10.70  1.000E-01    1.803 F    0.000    1.933 20.5 V  0.70   0.49   S 033      1.30 1 1
+ 2016YC8   O C   2017 01 01.92687       1.000E-05 06 05 43.060  9.978E-02    1.803 F    0.000    1.189 +48 18 07.30  1.000E-01    1.803 F    0.000    0.042 20.5 V  0.70   0.49   S 033      0.66 1 1
+ 2016YC8   O C   2017 01 01.92918       1.000E-05 06 05 41.920  9.978E-02    1.803 F    0.000    1.244 +48 18 05.90  1.000E-01    1.803 F    0.000    0.179 20.5 V  0.70   0.49   S 033      0.70 1 1
+ 2016YC8   O C K 2017 01 02.89650       1.000E-05 05 58 14.350  1.002E-01    1.000 F    0.034   -0.383 +48 04 44.80  1.000E-01    1.000 F   -0.024   -0.184 19.5 V  0.70  -0.41   q J69      0.43 1 1
+ 2016YC8   O C K 2017 01 02.90695       1.000E-05 05 58 08.770  1.002E-01    1.000 F    0.034    0.076 +48 04 36.50  1.000E-01    1.000 F   -0.024   -0.129 19.7 V  0.70  -0.21   q J69      0.15 1 1
+ 2016YC8   O C K 2017 01 03.33785       1.000E-05 05 54 25.630  1.004E-01    0.500 F   -0.084   -0.067 +47 57 55.30  1.000E-01    0.500 F    0.269   -0.207 18.7 R  0.70  -0.76   o 291      0.44 1 1
+ 2016YC8   O C K 2017 01 03.33939       1.000E-05 05 54 24.740  1.004E-01    0.500 F   -0.084   -0.058 +47 57 53.50  1.000E-01    0.500 F    0.269    0.045 18.7 R  0.70  -0.76   o 291      0.15 1 1
+ 2016YC8   O C K 2017 01 03.34096       1.000E-05 05 54 23.820  1.004E-01    0.500 F   -0.084   -0.181 +47 57 51.20  1.000E-01    0.500 F    0.269   -0.154 18.8 R  0.70  -0.66   o 291      0.48 1 1
+ 2016YC8   O C K 2017 01 03.81129       1.000E-05 05 50 30.430  1.008E-01    0.600 F    0.000   -0.122 +47 47 50.60  1.000E-01    0.600 F    0.000    0.265                       U 204      0.49 1 0
+ 2016YC8   O C K 2017 01 03.82803       1.000E-05 05 50 20.700  1.008E-01    0.600 F    0.000    0.064 +47 47 34.00  1.000E-01    0.600 F    0.000   -0.218 19.7 G  0.70   0.17   U 204      0.38 1 1
+ 2016YC8   O C K 2017 01 03.84093       1.000E-05 05 50 13.130  1.008E-01    0.600 F    0.000    0.069 +47 47 21.40  1.000E-01    0.600 F    0.000    0.120                       U 204      0.23 1 0
+ 2016YC8   O C   2017 01 04.400450      1.000E-06 05 44 58.156  1.012E-02    0.100 F    0.000    0.024 +47 35 43.23  1.000E-02    0.100 F    0.000   -0.039 19.8 G  0.70   0.33   U T12      0.55 1 1
+ 2016YC8   O C   2017 01 04.401106      1.000E-06 05 44 57.727  1.012E-02    0.100 F    0.000    0.023 +47 35 42.23  1.000E-02    0.100 F    0.000   -0.011 19.8 G  0.70   0.33   U T12      0.30 1 1
+ 2016YC8   O C K 2017 01 04.46619       1.000E-05 05 44 10.230  1.013E-01    0.500 F   -0.137   -0.147 +47 32 27.00  1.000E-01    0.500 F    0.228    0.062 19.6 R  0.70   0.26   o 291      0.32 1 1
+ 2016YC8   O C K 2017 01 04.46774       1.000E-05 05 44 09.320  1.013E-01    0.500 F   -0.137   -0.077 +47 32 23.70  1.000E-01    0.500 F    0.228    0.020 19.5 R  0.70   0.16   o 291      0.16 1 1
+ 2016YC8   O C K 2017 01 04.46930       1.000E-05 05 44 08.370  1.013E-01    0.500 F   -0.137   -0.363 +47 32 21.20  1.000E-01    0.500 F    0.228    0.803 19.5 R  0.70   0.16   o 291      1.77 1 1
+ 2016YC8   O C K 2017 01 07.87096       1.000E-05 05 05 57.490  1.057E-01    1.000 F    0.000    0.978 +45 13 03.00  1.000E-01    1.000 F    0.000   -0.322                       S 595      1.03 1 0
+ 2016YC8   O C K 2017 01 07.89010       1.000E-05 05 05 40.660  1.057E-01    1.000 F    0.000    0.556 +45 11 52.10  1.000E-01    1.000 F    0.000   -0.255 19.7 V  0.70   0.31   S 595      0.61 1 1
+ 2016YC8   O C K 2017 01 08.169035      1.000E-06 05 01 54.610  1.062E-01    1.118 F    0.024    0.416 +44 54 25.20  1.000E-01    1.118 F   -0.014   -0.049 19.8 V  0.70   0.44   u H21      0.38 1 1
+ 2016YC8   O C K 2017 01 08.173125      1.000E-06 05 01 50.890  1.062E-01    1.118 F    0.024    0.431 +44 54 08.70  1.000E-01    1.118 F   -0.014   -0.049 19.0 V  0.70  -0.36   u H21      0.39 1 1
+ 2016YC8   O C K 2017 01 08.177429      1.000E-06 05 01 46.960  1.063E-01    1.118 F    0.024    0.289 +44 53 51.30  1.000E-01    1.118 F   -0.014    0.009 19.9 V  0.70   0.54   u H21      0.26 1 1
+ 2016YC8   O C K 2017 01 08.181735      1.000E-06 05 01 43.040  1.063E-01    1.118 F    0.024    0.274 +44 53 33.60  1.000E-01    1.118 F   -0.014   -0.128 19.5 V  0.70   0.14   u H21      0.27 1 1
+ 2016YC8   O C K 2017 01 08.186920      1.000E-06 05 01 38.320  1.063E-01    1.118 F    0.024    0.256 +44 53 12.50  1.000E-01    1.118 F   -0.014    0.048 19.9 V  0.70   0.54   u H21      0.23 1 1
+ 2016YC8   O C ^ 2017 01 08.33109       1.000E-05 04 59 31.630  1.066E-01    1.000 F   -0.032    0.042 +44 43 27.70  1.000E-01    1.000 F    0.287   -0.120 19.2 R  0.70   0.26   o 695      0.13 1 1
+ 2016YC8   O C ^ 2017 01 08.33193       1.000E-05 04 59 30.870  1.066E-01    1.000 F   -0.032    0.084 +44 43 23.90  1.000E-01    1.000 F    0.287   -0.048 19.2 R  0.70   0.26   o 695      0.10 1 1
+ 2016YC8   O C ^ 2017 01 08.33278       1.000E-05 04 59 30.100  1.066E-01    1.000 F   -0.032    0.114 +44 43 20.00  1.000E-01    1.000 F    0.287   -0.026 19.1 R  0.70   0.16   o 695      0.12 1 1
+ 2016YC8   O C K 2017 01 13.94315       1.000E-05 03 18 39.110  1.283E-01    1.000 F   -0.054    0.563 +31 13 11.60  1.000E-01    1.000 F    0.016    0.121 18.2 R  0.70  -0.41   q 203      0.59 1 1
+ 2016YC8   O C K 2017 01 13.95926       1.000E-05 03 18 16.880  1.284E-01    1.000 F   -0.054   -0.433 +31 08 57.90  1.000E-01    1.000 F    0.016    0.580 18.4 R  0.70  -0.21   q 203      0.74 1 1
+ 2016YC8   S S   2017 01 16.315971      1.000E-06 02 24 23.320  1.420E-01    1.000 F   -0.108   -0.388 +18 51 04.00  1.000E-01    1.000 F    0.165   -0.827                       L C51      0.96 1 0
+ 2016YC8   S s   2017 01 16.31597 1       4872.895700000000       4241.780000000000       2308.541700000000 C51
+ 2016YC8   S S   2017 01 16.381424      1.000E-06 02 22 50.230  1.423E-01    1.000 F   -0.127   -1.451 +18 26 37.50  1.000E-01    1.000 F    0.165   -0.895                       L C51      1.80 1 0
+ 2016YC8   S s   2017 01 16.38142 1       4872.197700000000       4255.811300000000       2284.158900000000 C51
+ 2016YC8   O C K 2017 01 18.84885       1.000E-05 01 24 55.140  1.499E-01    1.000 F    0.064    0.309 +01 38 29.80  1.000E-01    1.000 F    0.044    0.505                       q J95      0.68 1 0
+ 2016YC8   O C K 2017 01 18.85868       1.000E-05 01 24 40.970  1.499E-01    1.000 F    0.064   -0.570 +01 34 23.80  1.000E-01    1.000 F    0.044    0.422                       q J95      0.77 1 0
+ 2016YC8   O C K 2017 01 18.87132       1.000E-05 01 24 23.000  1.499E-01    1.000 F    0.064    1.014 +01 29 07.80  1.000E-01    1.000 F    0.044    0.519 20.0 R  0.70   0.41   q J95      1.31 1 1
+! Object   Obser ====== Date =======  ============ Radar range/range rate (km or km/d) =============  Station  ====  Residual
+! Design   K T N YYYY MM DD hh:mm:ss         Measure  Accuracy       rms F        Bias       Resid    TRX  RCX        Chi   S
+ 2016YC8   V c   2017 01 15 23:07:00   -191302.12026   0.54416   0.54416 F     0.00000     0.05567    -1   -1         0.35  1
+ 2016YC8   R c   2017 01 15 23:16:00   3850008.88881   0.59958   0.59958 F     0.00000     0.00293    -1   -1         0.29  1
diff --git a/astroquery/esa/neocc/test/data/2018TA.phypro b/astroquery/esa/neocc/test/data/2018TA.phypro
new file mode 100644
index 0000000000..fa4298801b
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/2018TA.phypro
@@ -0,0 +1,21 @@
+Rotation Period,-,h,[-]
+Quality,-,-,[-]
+Amplitude,-,mag,[-]
+Rotation Direction,-,-,[-]
+Spinvector L,-,deg,[-]
+Spinvector B,-,deg,[-]
+Taxonomy,-,-,[-]
+Taxonomy (all),-,-,[-]
+Absolute Magnitude (H),24.873,mag,[1]
+Slope Parameter (G),0.15**,mag,[2]
+Slope Parameter (G),0.15**,mag,[1]
+Albedo,-,-,[-]
+Diameter,40*,m,[3]
+Color Index Information,-,mag,[-]
+Sightings,-,-,[-]
+
+REFERENCES
+
+[1],ESA ODIM,ESA orbit determination and impact monitoring system
+[2],NEODyS,NEO Dynamic Site: https://newton.spacedys.com/neodys2
+[3],Estimation,Estimated from absolute magnitude
diff --git a/astroquery/esa/neocc/test/data/2019JF1.eph b/astroquery/esa/neocc/test/data/2019JF1.eph
new file mode 100644
index 0000000000..ef28665afa
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/2019JF1.eph
@@ -0,0 +1,36 @@
+                        Equatorial coordinates                                                                                         App. motion                           Sky plane error     
+    Date      Hour        RA            DEC       Mag   Alt  Airmass   Sun elev.   SolEl  LunEl  Phase Glat  Glon     R     Delta   RA*cosDE     DEC       Vel    PA       Err1     Err2   AngAx 
+             (UTC)     (h  m  s)     (d  '  ")         (deg)             (deg)     (deg)  (deg)  (deg) (deg) (deg)   (au)    (au)   ("/min)   ("/min)    ("/min) (deg)                     (deg) 
+ =========== ======  =============  ============ ===== ===== ======== =========== ====== ====== ====== ===== ===== ======= =======  ========  ========  ======== =====  ========  ======== ======
+ 15 Jul 2021  0.000    7 18 36.633  +21 56 57.48  27.0  65.0    1.103   69.2         4.3   64.1    3.0  15.6 195.9   1.442   2.454    1.7074   -0.2558    1.7265  98.5    3.325"    0.004"  99.0
+ 16 Jul 2021  0.000    7 21 34.407  +21 50 47.10  27.0  64.8    1.105   69.3         4.5   77.0    3.2  16.1 196.3   1.445   2.456    1.7029   -0.2636    1.7232  98.8    3.326"    0.004"  99.3
+ 17 Jul 2021  0.000    7 24 31.581  +21 44 25.47  27.0  64.5    1.107   69.3         4.8   90.2    3.4  16.7 196.6   1.447   2.457    1.6984   -0.2714    1.7200  99.1    3.327"    0.004"  99.6
+ 18 Jul 2021  0.000    7 27 28.154  +21 37 52.73  27.0  64.3    1.109   69.3         5.1  103.6    3.5  17.3 197.0   1.449   2.459    1.6939   -0.2791    1.7168  99.4    3.328"    0.004"  99.8
+ 19 Jul 2021  0.000    7 30 24.127  +21 31  9.01  27.0  64.1    1.112   69.3         5.3  117.1    3.7  17.9 197.4   1.452   2.460    1.6895   -0.2867    1.7136  99.6    3.330"    0.004" 100.1
+ 20 Jul 2021  0.000    7 33 19.501  +21 24 14.46  27.0  63.8    1.114   69.3         5.6  130.8    3.9  18.5 197.8   1.454   2.462    1.6851   -0.2941    1.7105  99.9    3.331"    0.004" 100.3
+ 21 Jul 2021  0.000    7 36 14.278  +21 17  9.21  27.1  63.6    1.116   69.3         5.9  144.5    4.1  19.1 198.2   1.456   2.463    1.6807   -0.3015    1.7075 100.2    3.333"    0.004" 100.6
+ 22 Jul 2021  0.000    7 39  8.459  +21  9 53.38  27.1  63.3    1.119   69.3         6.1  158.2    4.3  19.6 198.6   1.458   2.464    1.6764   -0.3088    1.7046 100.4    3.335"    0.004" 100.9
+ 23 Jul 2021  0.000    7 42  2.050  +21  2 27.12  27.1  63.1    1.121   69.3         6.4  171.3    4.4  20.2 199.0   1.460   2.466    1.6721   -0.3160    1.7017 100.7    3.338"    0.004" 101.1
+ 24 Jul 2021  0.000    7 44 55.052  +20 54 50.55  27.1  62.8    1.124   69.3         6.7 -173.0    4.6  20.8 199.4   1.463   2.467    1.6678   -0.3232    1.6989 101.0    3.340"    0.004" 101.4
+ 25 Jul 2021  0.000    7 47 47.471  +20 47  3.80  27.1  62.5    1.127   69.2         6.9 -160.5    4.8  21.4 199.8   1.465   2.468    1.6637   -0.3302    1.6961 101.2    3.343"    0.004" 101.6
+ 26 Jul 2021  0.000    7 50 39.309  +20 39  6.99  27.1  62.3    1.129   69.2         7.2 -147.7    5.0  21.9 200.2   1.467   2.469    1.6595   -0.3371    1.6934 101.5    3.346"    0.004" 101.9
+ 27 Jul 2021  0.000    7 53 30.571  +20 31  0.25  27.1  62.0    1.132   69.2         7.5 -135.2    5.2  22.5 200.6   1.469   2.470    1.6554   -0.3440    1.6908 101.7    3.349"    0.004" 102.1
+ 28 Jul 2021  0.000    7 56 21.259  +20 22 43.70  27.2  61.7    1.135   69.1         7.8 -123.0    5.3  23.1 201.0   1.471   2.471    1.6514   -0.3508    1.6882 102.0    3.352"    0.004" 102.3
+ 29 Jul 2021  0.000    7 59 11.378  +20 14 17.47  27.2  61.5    1.138   69.1         8.0 -111.2    5.5  23.6 201.4   1.473   2.472    1.6474   -0.3575    1.6857 102.2    3.355"    0.004" 102.6
+ 30 Jul 2021  0.000    8  2  0.929  +20  5 41.68  27.2  61.2    1.141   69.1         8.3  -99.6    5.7  24.2 201.8   1.475   2.472    1.6434   -0.3641    1.6833 102.5    3.359"    0.004" 102.8
+ 31 Jul 2021  0.000    8  4 49.917  +19 56 56.45  27.2  60.9    1.144   69.0         8.6  -88.3    5.9  24.8 202.2   1.477   2.473    1.6395   -0.3706    1.6808 102.7    3.363"    0.004" 103.0
+  1 Aug 2021  0.000    8  7 38.343  +19 48  1.91  27.2  60.6    1.147   68.9         8.9  -77.1    6.1  25.3 202.6   1.479   2.474    1.6356   -0.3770    1.6785 103.0    3.367"    0.004" 103.3
+  2 Aug 2021  0.000    8 10 26.209  +19 38 58.18  27.2  60.3    1.150   68.9         9.2  -66.0    6.2  25.9 203.1   1.481   2.474    1.6317   -0.3833    1.6761 103.2    3.371"    0.004" 103.5
+  3 Aug 2021  0.000    8 13 13.520  +19 29 45.39  27.2  60.0    1.154   68.8         9.4  -54.9    6.4  26.4 203.5   1.483   2.475    1.6279   -0.3896    1.6738 103.5    3.376"    0.004" 103.7
+  4 Aug 2021  0.000    8 16  0.276  +19 20 23.65  27.2  59.7    1.157   68.7         9.7  -43.7    6.6  27.0 203.9   1.485   2.475    1.6241   -0.3957    1.6716 103.7    3.380"    0.004" 103.9
+  5 Aug 2021  0.000    8 18 46.481  +19 10 53.10  27.3  59.4    1.161   68.6        10.0  -32.3    6.8  27.5 204.4   1.487   2.475    1.6203   -0.4018    1.6693 103.9    3.385"    0.004" 104.2
+  6 Aug 2021  0.000    8 21 32.137  +19  1 13.85  27.3  59.1    1.164   68.6        10.3  -20.8    7.0  28.1 204.8   1.489   2.476    1.6165   -0.4078    1.6671 104.2    3.390"    0.004" 104.4
+  7 Aug 2021  0.000    8 24 17.246  +18 51 26.04  27.3  58.8    1.168   68.5        10.6   -9.6    7.2  28.6 205.2   1.490   2.476    1.6128   -0.4137    1.6650 104.4    3.395"    0.004" 104.6
+  8 Aug 2021  0.000    8 27  1.811  +18 41 29.78  27.3  58.5    1.172   68.4        10.9    5.9    7.4  29.2 205.7   1.492   2.476    1.6090   -0.4195    1.6628 104.6    3.401"    0.004" 104.8
+  9 Aug 2021  0.000    8 29 45.833  +18 31 25.20  27.3  58.2    1.176   68.2        11.2   16.9    7.5  29.7 206.1   1.494   2.476    1.6053   -0.4253    1.6607 104.8    3.406"    0.004" 105.0
+ 10 Aug 2021  0.000    8 32 29.316  +18 21 12.43  27.3  57.9    1.180   68.1        11.4   29.3    7.7  30.3 206.6   1.496   2.476    1.6017   -0.4309    1.6586 105.1    3.412"    0.004" 105.2
+ 11 Aug 2021  0.000    8 35 12.261  +18 10 51.60  27.3  57.6    1.184   68.0        11.7   42.2    7.9  30.8 207.0   1.497   2.475    1.5980   -0.4365    1.6565 105.3    3.418"    0.004" 105.4
+ 12 Aug 2021  0.000    8 37 54.672  +18  0 22.82  27.3  57.3    1.188   67.9        12.0   55.3    8.1  31.3 207.5   1.499   2.475    1.5944   -0.4419    1.6545 105.5    3.425"    0.004" 105.6
+ 13 Aug 2021  0.000    8 40 36.553  +17 49 46.22  27.3  56.9    1.192   67.7        12.3   68.6    8.3  31.9 208.0   1.501   2.475    1.5908   -0.4473    1.6525 105.7    3.431"    0.004" 105.8
+ 14 Aug 2021  0.000    8 43 17.905  +17 39  1.94  27.3  56.6    1.197   67.6        12.6   81.9    8.5  32.4 208.4   1.502   2.475    1.5872   -0.4526    1.6505 105.9    3.438"    0.004" 106.0
+ 15 Aug 2021  0.000    8 45 58.735  +17 28 10.08  27.4  56.3    1.201   67.5        12.9   95.4    8.6  32.9 208.9   1.504   2.474    1.5837   -0.4578    1.6485 106.1    3.444"    0.004" 106.2
diff --git a/astroquery/esa/neocc/test/data/2020BX12.rwo b/astroquery/esa/neocc/test/data/2020BX12.rwo
new file mode 100644
index 0000000000..03ceb86051
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/2020BX12.rwo
@@ -0,0 +1,179 @@
+version =   3
+errmod  = 'vfcc17'
+RMSast  =   5.99030E-01
+RMSmag  =   3.71435E-01
+END_OF_HEADER
+! Object   Obser ============= Date ============= ================== Right Ascension =================  ================= Declination ===================== ==== Magnitude ==== Ast Obs  Residual SEL
+! Design   K T N YYYY MM DD.dddddddddd   Accuracy HH MM SS.sss  Accuracy      RMS  F     Bias    Resid sDD MM SS.ss  Accuracy      RMS  F     Bias    Resid Val  B   RMS  Resid Cat Cod       Chi A M
+ 2020BX12  O C   2014 01 05.593690      1.000E-06 13 13 31.138  1.446E-02    0.200 F    0.000   -0.155 -15 25 02.58  1.000E-02    0.200 F    0.000   -0.026 20.7 G  0.70  -0.44   V F51      0.92 1 1
+ 2020BX12  O C   2014 01 05.598606      1.000E-06 13 13 33.851  1.446E-02    0.200 F    0.000   -0.351 -15 24 50.05  1.000E-02    0.200 F    0.000    0.215 19.7 G  0.70  -1.44   V F51      2.17 1 1
+ 2020BX12  O C   2016 01 03.622243      1.000E-06 11 29 57.642  1.344E-02    0.200 F    0.000    0.277 -26 20 57.41  1.000E-02    0.200 F    0.000    0.062 22.2 G  0.70   1.37   V F51      1.55 1 1
+ 2020BX12  O C   2016 01 03.651174      1.000E-06 11 30 09.696  1.344E-02    0.200 F    0.000    0.045 -26 20 31.75  1.000E-02    0.200 F    0.000   -0.040 21.8 G  0.70   0.97   V F51      0.31 1 1
+ 2020BX12  O C   2016 08 06.585652      1.000E-06 00 25 44.045  1.304E-02    0.200 F    0.000   -0.152 -29 36 23.27  1.000E-02    0.200 F    0.000    0.386 22.3 G  0.70  -0.42   V F51      2.12 1 1
+ 2020BX12  O C   2016 08 06.595362      1.000E-06 00 25 43.603  1.304E-02    0.200 F    0.000    0.344 -29 36 45.95  1.000E-02    0.200 F    0.000    0.132 22.6 G  0.70  -0.12   V F51      1.93 1 1
+ 2020BX12  O C   2016 08 06.605056      1.000E-06 00 25 43.064  1.304E-02    0.200 F    0.000   -0.435 -29 37 08.95  1.000E-02    0.200 F    0.000   -0.495 22.2 G  0.70  -0.52   V F51      3.21 0 1
+ 2020BX12  O C   2016 08 06.614762      1.000E-06 00 25 42.615  1.304E-02    0.200 F    0.000   -0.034 -29 37 30.82  1.000E-02    0.200 F    0.000    0.020 22.5 G  0.70  -0.22   V F51      0.21 1 1
+ 2020BX12  O C   2016 08 09.544923      1.000E-06 00 23 15.374  1.279E-02    0.200 F    0.000    0.028 -31 29 44.23  1.000E-02    0.200 F    0.000   -0.320 22.9 G  0.70   0.19   V F51      1.63 1 1
+ 2020BX12  O C   2016 08 09.554586      1.000E-06 00 23 14.792  1.279E-02    0.200 F    0.000   -0.067 -31 30 06.10  1.000E-02    0.200 F    0.000   -0.127 23.5 G  0.70   0.79   V F51      0.74 1 1
+ 2020BX12  O C   2016 08 09.573920      1.000E-06 00 23 13.665  1.279E-02    0.200 F    0.000    0.238 -31 30 49.84  1.000E-02    0.200 F    0.000    0.224 22.8 G  0.70   0.09   V F51      1.69 1 1
+ 2020BX12  O C   2017 12 08.595129      1.000E-06 09 01 57.527  1.306E-02    0.200 F    0.000   -0.074 -29 28 10.10  1.000E-02    0.200 F    0.000   -0.047 22.9 G  0.70   0.61   V F51      0.44 1 1
+ 2020BX12  O C   2017 12 08.605295      1.000E-06 09 01 58.458  1.306E-02    0.200 F    0.000    0.115 -29 28 17.76  1.000E-02    0.200 F    0.000   -0.000 22.8 G  0.70   0.51   V F51      0.58 1 1
+ 2020BX12  S S   2018 01 25.715775      1.000E-06 14 04 23.230  1.416E-02    1.000 F    0.178    0.315 -19 19 22.30  1.000E-02    1.000 F    0.107    0.360                       L C51      0.48 1 0
+ 2020BX12  S s   2018 01 25.71577 1      -3551.344400000000      -4903.629900000001      -3230.672600000000 C51
+ 2020BX12  S S   2018 01 25.715903      1.000E-06 14 04 23.522  1.416E-02    1.000 F    0.178    1.146 -19 19 19.60  1.000E-02    1.000 F    0.107    0.358                       L C51      1.21 1 0
+ 2020BX12  S s   2018 01 25.71590 1      -3538.276100000000      -4864.406000000000      -3303.581300000000 C51
+ 2020BX12  S S   2018 01 25.781227      1.000E-06 14 06 11.054  1.418E-02    1.000 F    0.165    0.517 -19 04 23.02  1.000E-02    1.000 F    0.077    0.053                       L C51      0.52 1 0
+ 2020BX12  S s   2018 01 25.78122 1      -3545.739800000000      -4907.640800000000      -3230.733200000000 C51
+ 2020BX12  O C   2018 08 05.550150      1.000E-06 00 10 54.668  1.319E-02    0.200 F    0.000    0.058 -28 25 01.84  1.000E-02    0.200 F    0.000    0.413 23.7 G  0.70   1.26   V F51      2.11 1 1
+ 2020BX12  O C   2018 08 05.561163      1.000E-06 00 10 53.988  1.319E-02    0.200 F    0.000   -0.276 -28 25 30.36  1.000E-02    0.200 F    0.000   -0.365 23.5 G  0.70   1.06   V F51      2.35 1 1
+ 2020BX12  O C   2018 08 05.572160      1.000E-06 00 10 53.347  1.319E-02    0.200 F    0.000   -0.100 -28 25 58.03  1.000E-02    0.200 F    0.000   -0.357 23.6 G  0.70   1.16   V F51      1.88 1 1
+ 2020BX12  O C   2020 01 27.378454      1.000E-06 07 34 48.390  1.178E-01    0.894 F    0.000   -0.097 -38 14 23.20  1.000E-01    0.894 F    0.000   -0.165 17.58o  0.50  -0.05   V T08      0.21 1 1
+ 2020BX12  O C   2020 01 27.387784      1.000E-06 07 34 42.700  1.178E-01    0.894 F    0.000   -0.065 -38 14 03.90  1.000E-01    0.894 F    0.000   -0.007 17.57o  0.50  -0.06   V T08      0.07 1 1
+ 2020BX12  O C   2020 01 27.391009      1.000E-06 07 34 40.730  1.178E-01    0.894 F    0.000   -0.052 -38 13 57.30  1.000E-01    0.894 F    0.000   -0.076 17.54o  0.50  -0.09   V T08      0.10 1 1
+ 2020BX12  O C   2020 01 27.400993      1.000E-06 07 34 34.620  1.178E-01    0.894 F    0.000   -0.031 -38 13 36.80  1.000E-01    0.894 F    0.000   -0.397 17.57o  0.50  -0.06   V T08      0.45 1 1
+ 2020BX12  O C   2020 01 27.414856      1.000E-06 07 34 26.130  1.178E-01    0.894 F    0.000    0.192 -38 13 07.20  1.000E-01    0.894 F    0.000   -0.141 17.72o  0.50   0.10   V T08      0.27 1 1
+ 2020BX12  O C K 2020 01 27.54883       1.000E-05 07 33 08.420  1.180E-01    1.000 F    0.123   -0.054 -38 07 16.50  1.000E-01    1.000 F   -0.045    0.485 17.6 V  0.70  -0.32   q E23      0.49 1 1
+ 2020BX12  O C K 2020 01 27.55578       1.000E-05 07 33 04.060  1.180E-01    1.000 F    0.123    0.126 -38 07 01.30  1.000E-01    1.000 F   -0.045    0.144 18.3 V  0.70   0.38   q E23      0.19 1 1
+ 2020BX12  O C K 2020 01 27.56272       1.000E-05 07 32 59.660  1.180E-01    1.000 F    0.123   -0.165 -38 06 45.70  1.000E-01    1.000 F   -0.045    0.105 18.1 V  0.70   0.19   q E23      0.20 1 1
+ 2020BX12  O C K 2020 01 28.00406       1.000E-05 07 28 27.570  1.185E-01    0.600 F    0.000   -0.149 -37 48 42.50  1.000E-01    0.600 F    0.000    0.047 17.3 V  0.70  -0.49   U X31      0.26 1 1
+ 2020BX12  O C K 2020 01 28.00684       1.000E-05 07 28 25.600  1.185E-01    0.600 F    0.000   -0.776 -37 48 35.60  1.000E-01    0.600 F    0.000    0.138 17.6 V  0.70  -0.19   U X31      1.32 1 1
+ 2020BX12  O C K 2020 01 28.01519       1.000E-05 07 28 19.900  1.185E-01    0.600 F    0.000    0.101 -37 48 15.30  1.000E-01    0.600 F    0.000   -0.117 17.8 V  0.70   0.02   U X31      0.26 1 1
+ 2020BX12  O C K 2020 01 28.01671       1.000E-05 07 28 18.840  1.185E-01    0.600 F    0.000    0.025 -37 48 11.90  1.000E-01    0.600 F    0.000   -0.477 17.6 V  0.70  -0.18   U X31      0.80 1 1
+ 2020BX12  O C # 2020 01 28.05615       1.000E-05 07 27 52.120  1.186E-01    0.600 F    0.000    0.104 -37 46 25.90  1.000E-01    0.600 F    0.000   -0.035 17.5 G  0.70   0.01   V W88      0.18 1 1
+ 2020BX12  O C # 2020 01 28.06140       1.000E-05 07 27 48.400  1.186E-01    0.600 F    0.000   -0.287 -37 46 12.60  1.000E-01    0.600 F    0.000   -0.077 17.2 G  0.70  -0.29   V W88      0.50 1 1
+ 2020BX12  O C # 2020 01 28.06630       1.000E-05 07 27 44.970  1.186E-01    0.600 F    0.000   -0.062 -37 45 59.80  1.000E-01    0.600 F    0.000    0.208 17.5 G  0.70   0.01   V W88      0.36 1 1
+ 2020BX12  O C   2020 01 28.09217       1.000E-05 07 27 26.740  1.186E-01    0.400 F    0.000   -0.182 -37 44 57.10  1.000E-01    0.400 F    0.000    0.239 17.4 R  0.70   0.04   t W85      0.76 1 1
+ 2020BX12  O C   2020 01 28.09345       1.000E-05 07 27 25.850  1.186E-01    0.400 F    0.000    0.093 -37 44 53.80  1.000E-01    0.400 F    0.000    0.180 17.4 R  0.70   0.04   t W85      0.51 1 1
+ 2020BX12  O C   2020 01 28.09475       1.000E-05 07 27 24.920  1.186E-01    0.400 F    0.000    0.068 -37 44 50.50  1.000E-01    0.400 F    0.000    0.064 17.3 R  0.70  -0.06   t W85      0.23 1 1
+ 2020BX12  O C   2020 01 28.09710       1.000E-05 07 27 23.240  1.186E-01    0.400 F    0.000    0.051 -37 44 44.20  1.000E-01    0.400 F    0.000    0.178 17.3 R  0.70  -0.06   t W85      0.46 1 1
+ 2020BX12  O C   2020 01 29.328936      1.000E-06 07 10 58.300  1.205E-01    0.800 F    0.000    0.023 -36 32 56.70  1.000E-01    0.800 F    0.000   -0.107 17.78c  0.50   0.36   V T05      0.14 1 1
+ 2020BX12  O C   2020 01 29.333626      1.000E-06 07 10 53.670  1.205E-01    0.800 F    0.000    0.287 -36 32 36.00  1.000E-01    0.800 F    0.000   -0.280 17.20c  0.50  -0.22   V T05      0.50 1 1
+ 2020BX12  O C   2020 01 29.344597      1.000E-06 07 10 42.730  1.205E-01    0.800 F    0.000   -0.028 -36 31 46.30  1.000E-01    0.800 F    0.000    0.227 17.37c  0.50  -0.04   V T05      0.29 1 1
+ 2020BX12  O C K 2020 01 29.51159       1.000E-05 07 07 59.530  1.209E-01    1.000 F   -0.023   -0.086 -36 17 08.40  1.000E-01    1.000 F   -0.004    0.261 17.2 V  0.70  -0.11   q E23      0.28 1 1
+ 2020BX12  O C K 2020 01 29.51853       1.000E-05 07 07 52.300  1.209E-01    1.000 F   -0.023   -0.101 -36 16 34.30  1.000E-01    1.000 F   -0.004    0.025 17.9 V  0.70   0.60   q E23      0.10 1 1
+ 2020BX12  O C K 2020 01 29.52547       1.000E-05 07 07 45.050  1.209E-01    1.000 F   -0.023   -0.174 -36 15 59.40  1.000E-01    1.000 F   -0.004    0.378 17.2 V  0.70  -0.10   q E23      0.42 1 1
+ 2020BX12  O C   2020 01 29.60851       1.000E-05 07 06 18.460  1.211E-01    0.600 F    0.000    1.130 -36 08 50.70  1.000E-01    0.600 F    0.000   -0.648 16.8 G  0.70  -0.19   V Q38      2.18 1 1
+ 2020BX12  O C   2020 01 29.61113       1.000E-05 07 06 15.520  1.211E-01    0.600 F    0.000   -0.658 -36 08 36.80  1.000E-01    0.600 F    0.000   -0.686 17.0 G  0.70   0.01   V Q38      1.59 1 1
+ 2020BX12  O C   2020 01 29.61347       1.000E-05 07 06 13.240  1.211E-01    0.600 F    0.000    1.947 -36 08 24.60  1.000E-01    0.600 F    0.000   -0.960 17.5 G  0.70   0.51   V Q38      3.61 0 1
+ 2020BX12  O C K 2020 01 29.92957       1.000E-05 07 00 35.920  1.218E-01    0.600 F    0.000   -0.541 -35 40 54.70  1.000E-01    0.600 F    0.000   -0.226 17.1 G  0.70   0.22   V 587      0.98 1 1
+ 2020BX12  O C K 2020 01 29.93024       1.000E-05 07 00 35.160  1.218E-01    0.600 F    0.000   -0.264 -35 40 51.10  1.000E-01    0.600 F    0.000   -0.663                       V 587      1.19 1 0
+ 2020BX12  O C K 2020 01 29.93192       1.000E-05 07 00 33.220  1.218E-01    0.600 F    0.000    0.021 -35 40 40.20  1.000E-01    0.600 F    0.000    0.104                       V 587      0.18 1 0
+ 2020BX12  O C K 2020 01 30.16591       1.000E-05 06 55 58.520  1.225E-01    1.000 F   -0.021    0.409 -35 13 56.50  1.000E-01    1.000 F   -0.031    0.023 17.0 V  0.70  -0.07   q I47      0.41 1 1
+ 2020BX12  O C K 2020 01 30.16765       1.000E-05 06 55 56.310  1.225E-01    1.000 F   -0.021    0.241 -35 13 44.90  1.000E-01    1.000 F   -0.031   -0.261 16.7 V  0.70  -0.37   q I47      0.36 1 1
+ 2020BX12  O C K 2020 01 30.16929       1.000E-05 06 55 54.210  1.225E-01    1.000 F   -0.021   -0.115 -35 13 34.00  1.000E-01    1.000 F   -0.031   -0.578 16.8 V  0.70  -0.27   q I47      0.59 1 1
+ 2020BX12  O C   2020 01 30.82135       1.000E-05 06 41 17.700  1.247E-01    0.400 F    0.000   -0.065 -33 46 57.90  1.000E-01    0.400 F    0.000   -0.075 16.5 R  0.70   0.09   t K91      0.25 1 1
+ 2020BX12  O C   2020 01 30.82168       1.000E-05 06 41 17.190  1.247E-01    0.400 F    0.000   -0.009 -33 46 54.80  1.000E-01    0.400 F    0.000   -0.041 16.5 R  0.70   0.09   t K91      0.11 1 1
+ 2020BX12  O C   2020 01 30.82200       1.000E-05 06 41 16.690  1.247E-01    0.400 F    0.000   -0.021 -33 46 51.90  1.000E-01    0.400 F    0.000   -0.116 16.4 R  0.70  -0.01   t K91      0.30 1 1
+ 2020BX12  O C   2020 01 30.82264       1.000E-05 06 41 15.700  1.247E-01    0.400 F    0.000    0.080 -33 46 46.00  1.000E-01    0.400 F    0.000   -0.168 16.4 R  0.70  -0.01   t K91      0.47 1 1
+ 2020BX12  O C ' 2020 01 31.15270       1.000E-05 06 32 25.650  1.260E-01    1.732 F    0.017   -0.040 -32 50 07.30  1.000E-01    1.732 F   -0.046   -0.486 16.5 V  0.70  -0.18   q W88      0.28 1 1
+ 2020BX12  O C ' 2020 01 31.15392       1.000E-05 06 32 23.530  1.260E-01    1.732 F    0.017    0.059 -32 49 52.80  1.000E-01    1.732 F   -0.046    0.147 16.1 V  0.70  -0.58   q W88      0.09 1 1
+ 2020BX12  O C ' 2020 01 31.15450       1.000E-05 06 32 22.480  1.260E-01    1.732 F    0.017   -0.423 -32 49 46.00  1.000E-01    1.732 F   -0.046    0.350 16.2 V  0.70  -0.48   q W88      0.32 1 1
+ 2020BX12  O C ' 2020 01 31.15529       1.000E-05 06 32 21.160  1.260E-01    1.732 F    0.017    0.314 -32 49 37.10  1.000E-01    1.732 F   -0.046    0.259 16.1 V  0.70  -0.58   q W88      0.24 1 1
+ 2020BX12  O C ' 2020 01 31.15588       1.000E-05 06 32 20.080  1.260E-01    1.732 F    0.017   -0.320 -32 49 29.90  1.000E-01    1.732 F   -0.046    0.741 16.2 V  0.70  -0.48   q W88      0.47 1 1
+ 2020BX12  O C ' 2020 01 31.15647       1.000E-05 06 32 19.080  1.261E-01    1.732 F    0.017    0.056 -32 49 24.00  1.000E-01    1.732 F   -0.046   -0.080 16.1 V  0.70  -0.58   q W88      0.06 1 1
+ 2020BX12  O C ' 2020 01 31.15704       1.000E-05 06 32 18.070  1.261E-01    1.732 F    0.017   -0.131 -32 49 17.50  1.000E-01    1.732 F   -0.046   -0.077 16.2 V  0.70  -0.48   q W88      0.09 1 1
+ 2020BX12  O C ' 2020 01 31.15767       1.000E-05 06 32 16.960  1.261E-01    1.732 F    0.017   -0.257 -32 49 10.00  1.000E-01    1.732 F   -0.046    0.240 16.3 V  0.70  -0.38   q W88      0.20 1 1
+ 2020BX12  O C ' 2020 01 31.15882       1.000E-05 06 32 14.940  1.261E-01    1.732 F    0.017   -0.402 -32 48 57.20  1.000E-01    1.732 F   -0.046   -0.082 16.2 V  0.70  -0.48   q W88      0.24 1 1
+ 2020BX12  O C ' 2020 01 31.16002       1.000E-05 06 32 12.840  1.261E-01    1.732 F    0.017   -0.446 -32 48 42.90  1.000E-01    1.732 F   -0.046    0.513 16.3 V  0.70  -0.38   q W88      0.39 1 1
+ 2020BX12  O C ' 2020 01 31.16059       1.000E-05 06 32 11.860  1.261E-01    1.732 F    0.017   -0.243 -32 48 37.00  1.000E-01    1.732 F   -0.046   -0.101 16.2 V  0.70  -0.48   q W88      0.15 1 1
+ 2020BX12  O C ' 2020 01 31.16117       1.000E-05 06 32 10.850  1.261E-01    1.732 F    0.017   -0.196 -32 48 29.70  1.000E-01    1.732 F   -0.046    0.567 16.3 V  0.70  -0.38   q W88      0.35 1 1
+ 2020BX12  O C   2020 01 31.351638      1.000E-06 06 26 40.590  1.269E-01    0.800 F    0.000    0.337 -32 12 44.20  1.000E-01    0.800 F    0.000   -0.060 16.45o  0.50   0.18   V T08      0.43 1 1
+ 2020BX12  O C   2020 01 31.355158      1.000E-06 06 26 33.940  1.269E-01    0.800 F    0.000   -0.089 -32 11 59.90  1.000E-01    0.800 F    0.000   -0.095 16.46o  0.50   0.19   V T08      0.16 1 1
+ 2020BX12  O C   2020 01 31.372330      1.000E-06 06 26 01.540  1.270E-01    0.800 F    0.000   -0.259 -32 08 21.70  1.000E-01    0.800 F    0.000   -0.009 16.08o  0.50  -0.18   V T08      0.32 1 1
+ 2020BX12  O C   2020 01 31.406320      1.000E-06 06 24 56.950  1.272E-01    0.800 F    0.000   -0.180 -32 01 01.20  1.000E-01    0.800 F    0.000   -0.248 16.49o  0.50   0.25   V T08      0.38 1 1
+ 2020BX12  O C K 2020 01 31.847753      1.000E-06 06 10 19.490  1.297E-01    0.400 F    0.000    0.166 -30 10 19.00  1.000E-01    0.400 F    0.000   -0.084 16.0 G  0.70  -0.10   V K92      0.47 1 1
+ 2020BX12  O C K 2020 01 31.848892      1.000E-06 06 10 16.940  1.297E-01    0.400 F    0.000    0.094 -30 09 59.70  1.000E-01    0.400 F    0.000    0.036 15.7 G  0.70  -0.40   V K92      0.25 1 1
+ 2020BX12  O C K 2020 01 31.849653      1.000E-06 06 10 15.230  1.297E-01    0.400 F    0.000   -0.028 -30 09 47.00  1.000E-01    0.400 F    0.000   -0.088 16.0 G  0.70  -0.10   V K92      0.23 1 1
+ 2020BX12  O C | 2020 02 01.15625       1.000E-05 05 58 28.260  1.317E-01    1.118 F   -0.013   -0.158 -28 35 17.50  1.000E-01    1.118 F   -0.003   -0.141 16.2 V  0.70  -0.05   u 807      0.19 1 1
+ 2020BX12  O C | 2020 02 01.15697       1.000E-05 05 58 26.500  1.317E-01    1.118 F   -0.013    0.323 -28 35 02.80  1.000E-01    1.118 F   -0.003   -0.202 16.2 V  0.70  -0.05   u 807      0.34 1 1
+ 2020BX12  O C | 2020 02 01.15771       1.000E-05 05 58 24.610  1.317E-01    1.118 F   -0.013   -0.246 -28 34 47.30  1.000E-01    1.118 F   -0.003    0.118 16.3 V  0.70   0.05   u 807      0.24 1 1
+ 2020BX12  O C | 2020 02 01.15848       1.000E-05 05 58 22.700  1.317E-01    1.118 F   -0.013   -0.087 -28 34 31.70  1.000E-01    1.118 F   -0.003   -0.086 16.1 V  0.70  -0.15   u 807      0.11 1 1
+ 2020BX12  O C | 2020 02 01.15929       1.000E-05 05 58 20.700  1.317E-01    1.118 F   -0.013    0.208 -28 34 14.90  1.000E-01    1.118 F   -0.003    0.080 15.8 V  0.70  -0.45   u 807      0.20 1 1
+ 2020BX12  O C K 2020 02 02.053228      1.000E-06 05 15 32.060  1.393E-01    0.447 F    0.000    0.197 -21 48 35.50  1.000E-01    0.447 F    0.000   -0.123 15.3 G  0.70  -0.32   V W85      0.52 1 1
+ 2020BX12  O C K 2020 02 02.054936      1.000E-06 05 15 26.120  1.393E-01    0.447 F    0.000    0.029 -21 47 34.50  1.000E-01    0.447 F    0.000    0.065 15.2 G  0.70  -0.42   V W85      0.16 1 1
+ 2020BX12  O C K 2020 02 02.056652      1.000E-06 05 15 20.180  1.393E-01    0.447 F    0.000    0.298 -21 46 33.30  1.000E-01    0.447 F    0.000    0.095 15.0 G  0.70  -0.62   V W85      0.71 1 1
+ 2020BX12  O C K 2020 02 02.058378      1.000E-06 05 15 14.170  1.393E-01    0.447 F    0.000    0.126 -21 45 31.80  1.000E-01    0.447 F    0.000   -0.007 15.0 G  0.70  -0.62   V W85      0.28 1 1
+ 2020BX12  O C K 2020 02 02.060095      1.000E-06 05 15 08.200  1.393E-01    0.447 F    0.000    0.125 -21 44 30.30  1.000E-01    0.447 F    0.000    0.139 15.1 G  0.70  -0.52   V W85      0.42 1 1
+ 2020BX12  O C | 2020 02 02.07149       1.000E-05 05 14 28.480  1.394E-01    1.118 F   -0.041    0.007 -21 37 41.50  1.000E-01    1.118 F   -0.015   -0.120 15.8 V  0.70  -0.09   u 807      0.11 1 1
+ 2020BX12  O C | 2020 02 02.07239       1.000E-05 05 14 25.330  1.394E-01    1.118 F   -0.041   -0.094 -21 37 09.10  1.000E-01    1.118 F   -0.015   -0.169 15.9 V  0.70   0.01   u 807      0.17 1 1
+ 2020BX12  O C | 2020 02 02.07422       1.000E-05 05 14 18.920  1.395E-01    1.118 F   -0.041   -0.329 -21 36 02.70  1.000E-01    1.118 F   -0.015    0.190 15.9 V  0.70   0.01   u 807      0.34 1 1
+ 2020BX12  O C | 2020 02 02.07514       1.000E-05 05 14 15.720  1.395E-01    1.118 F   -0.041   -0.112 -21 35 29.70  1.000E-01    1.118 F   -0.015   -0.043 15.9 V  0.70   0.01   u 807      0.11 1 1
+ 2020BX12  O C | 2020 02 02.07594       1.000E-05 05 14 12.910  1.395E-01    1.118 F   -0.041   -0.295 -21 35 00.60  1.000E-01    1.118 F   -0.015    0.141 15.8 V  0.70  -0.09   u 807      0.29 1 1
+ 2020BX12  O C   2020 02 02.08450       1.000E-05 05 13 52.500  1.395E-01    0.600 F    0.000   -0.059 -21 33 23.40  1.000E-01    0.600 F    0.000   -0.331 15.7 G  0.70   0.09   V I52      0.56 1 1
+ 2020BX12  O C   2020 02 02.08474       1.000E-05 05 13 51.640  1.395E-01    0.600 F    0.000   -0.356 -21 33 14.60  1.000E-01    0.600 F    0.000   -0.167 15.7 G  0.70   0.09   V I52      0.66 1 1
+ 2020BX12  O C   2020 02 02.08499       1.000E-05 05 13 50.780  1.395E-01    0.600 F    0.000   -0.165 -21 33 05.70  1.000E-01    0.600 F    0.000   -0.265 15.7 G  0.70   0.09   V I52      0.52 1 1
+ 2020BX12  O C   2020 02 02.08524       1.000E-05 05 13 49.920  1.395E-01    0.600 F    0.000    0.028 -21 32 56.80  1.000E-01    0.600 F    0.000   -0.364 15.6 G  0.70  -0.01   V I52      0.61 1 1
+ 2020BX12  O C   2020 02 02.146782      1.000E-06 05 10 13.560  1.401E-01    0.735 F    0.000    0.611 -20 55 13.40  1.000E-01    0.735 F    0.000    0.590 16.45g  0.50   0.30   U I41      1.16 1 1
+ 2020BX12  O C   2020 02 02.147130      1.000E-06 05 10 12.320  1.401E-01    0.735 F    0.000    0.694 -20 55 01.10  1.000E-01    0.735 F    0.000   -0.171 16.45g  0.50   0.30   U I41      0.98 1 1
+ 2020BX12  O C   2020 02 02.256018      1.000E-06 05 03 35.210  1.412E-01    0.735 F    0.000    0.667 -19 44 16.90  1.000E-01    0.735 F    0.000    1.454 15.67R  0.50   0.23   U I41      2.19 1 1
+ 2020BX12  O C   2020 02 02.256366      1.000E-06 05 03 33.850  1.412E-01    0.735 F    0.000   -0.324 -19 44 04.30  1.000E-01    0.735 F    0.000   -0.006 15.67R  0.50   0.23   U I41      0.44 1 1
+ 2020BX12  O C   2020 02 02.256910      1.000E-06 05 03 31.780  1.412E-01    0.735 F    0.000   -1.079 -19 43 40.60  1.000E-01    0.735 F    0.000    1.708 15.71R  0.50   0.27   U I41      2.76 1 1
+ 2020BX12  O C   2020 02 02.257257      1.000E-06 05 03 30.490  1.412E-01    0.735 F    0.000   -1.130 -19 43 26.90  1.000E-01    0.735 F    0.000    1.380 15.71R  0.50   0.27   U I41      2.44 1 1
+ 2020BX12  S S   2020 02 02.565692      1.000E-06 04 43 59.150  1.443E-02    1.000 F   -0.084   -0.180 -15 54 11.02  1.000E-02    1.000 F    0.118   -0.353                       L C51      0.40 1 0
+ 2020BX12  S s   2020 02 02.56569 1       1942.833800000000       6379.887899999999      -1609.032200000000 C51
+ 2020BX12  O C K 2020 02 02.847822      1.000E-06 04 24 16.390  1.468E-01    0.600 F    0.000    0.414 -11 55 04.20  1.000E-01    0.600 F    0.000   -0.372 15.4 G  0.70  -0.05   V J95      0.93 1 1
+ 2020BX12  O C K 2020 02 02.848685      1.000E-06 04 24 12.530  1.468E-01    0.600 F    0.000   -0.055 -11 54 16.50  1.000E-01    0.600 F    0.000   -0.453 15.8 G  0.70   0.35   V J95      0.77 1 1
+ 2020BX12  O C K 2020 02 02.849553      1.000E-06 04 24 08.700  1.468E-01    0.600 F    0.000    0.254 -11 53 28.00  1.000E-01    0.600 F    0.000   -0.032 15.7 G  0.70   0.25   V J95      0.43 1 1
+ 2020BX12  O C K 2020 02 02.850403      1.000E-06 04 24 04.910  1.468E-01    0.600 F    0.000   -0.010 -11 52 40.90  1.000E-01    0.600 F    0.000   -0.033 15.8 G  0.70   0.35   V J95      0.06 1 1
+ 2020BX12  O C   2020 02 03.09091       1.000E-05 04 06 06.710  1.486E-01    0.600 F    0.000    0.031 -07 57 45.30  1.000E-01    0.600 F    0.000   -0.162 15.4 G  0.70  -0.06   V I52      0.28 1 1
+ 2020BX12  O C   2020 02 03.09115       1.000E-05 04 06 05.580  1.486E-01    0.600 F    0.000    0.145 -07 57 30.60  1.000E-01    0.600 F    0.000   -0.151 15.9 G  0.70   0.44   V I52      0.35 1 1
+ 2020BX12  O C   2020 02 03.09140       1.000E-05 04 06 04.420  1.486E-01    0.600 F    0.000    0.518 -07 57 15.70  1.000E-01    0.600 F    0.000   -0.555 15.4 G  0.70  -0.06   V I52      1.27 1 1
+ 2020BX12  O C   2020 02 03.311394      1.000E-06 03 48 29.160  1.496E-01    0.800 F    0.000    0.084 -04 03 27.60  1.000E-01    0.800 F    0.000    0.155 15.62o  0.50   0.17   V T05      0.22 1 1
+ 2020BX12  O C   2020 02 03.317576      1.000E-06 03 47 58.550  1.496E-01    0.800 F    0.000    0.356 -03 56 41.90  1.000E-01    0.800 F    0.000   -0.322 15.24o  0.50  -0.21   V T05      0.60 1 1
+ 2020BX12  O C   2020 02 03.327777      1.000E-06 03 47 07.980  1.497E-01    0.800 F    0.000    0.441 -03 45 30.50  1.000E-01    0.800 F    0.000   -0.537 15.57o  0.50   0.11   V T05      0.87 1 1
+ 2020BX12  O C K 2020 02 03.782635      1.000E-06 03 09 12.670  1.495E-01    0.600 F    0.000   -0.606 +04 50 09.40  1.000E-01    0.600 F    0.000   -0.068 16.2 G  0.70   0.50   V C95      1.03 1 1
+ 2020BX12  O C K 2020 02 03.784630      1.000E-06 03 09 02.260  1.495E-01    0.600 F    0.000   -0.258 +04 52 28.00  1.000E-01    0.600 F    0.000    0.481 15.6 G  0.70  -0.10   V C95      0.92 1 1
+ 2020BX12  O C K 2020 02 03.786647      1.000E-06 03 08 51.720  1.494E-01    0.600 F    0.000   -0.124 +04 54 47.20  1.000E-01    0.600 F    0.000    0.121 16.0 G  0.70   0.30   V C95      0.29 1 1
+ 2020BX12  O C K 2020 02 03.798327      1.000E-06 03 07 52.560  1.494E-01    0.671 F    0.000   -1.075 +05 07 39.60  1.000E-01    0.671 F    0.000    0.583 16.4 G  0.70   0.69   V Z99      1.84 1 1
+ 2020BX12  O C K 2020 02 03.799243      1.000E-06 03 07 47.790  1.494E-01    0.671 F    0.000   -0.935 +05 08 42.90  1.000E-01    0.671 F    0.000    0.540 16.3 G  0.70   0.59   V Z99      1.62 1 1
+ 2020BX12  O C K 2020 02 03.800226      1.000E-06 03 07 42.680  1.494E-01    0.671 F    0.000   -0.649 +05 09 51.10  1.000E-01    0.671 F    0.000    0.767 16.2 G  0.70   0.49   V Z99      1.51 1 1
+ 2020BX12  O C K 2020 02 03.801150      1.000E-06 03 07 37.850  1.494E-01    0.671 F    0.000   -0.777 +05 10 55.00  1.000E-01    0.671 F    0.000    0.777 16.2 G  0.70   0.49   V Z99      1.65 1 1
+ 2020BX12  O C K 2020 02 03.802136      1.000E-06 03 07 32.710  1.494E-01    0.671 F    0.000   -0.702 +05 12 03.40  1.000E-01    0.671 F    0.000    1.004 16.3 G  0.70   0.59   V Z99      1.84 1 1
+ 2020BX12  O C K 2020 02 03.858586      1.000E-06 03 02 37.850  1.491E-01    0.735 F    0.000    0.020 +06 17 06.60  1.000E-01    0.735 F    0.000   -0.409 15.7 G  0.70  -0.05   V J69      0.56 1 1
+ 2020BX12  O C H 2020 02 03.864460      1.000E-06 03 02 04.590  1.491E-01    0.671 F    0.000    0.222 +06 24 07.30  1.000E-01    0.671 F    0.000   -0.462                       V 204      0.77 1 0
+ 2020BX12  O C K 2020 02 03.865177      1.000E-06 03 02 03.440  1.491E-01    0.735 F    0.000    0.248 +06 24 40.80  1.000E-01    0.735 F    0.000    0.240 16.0 G  0.70   0.24   V J69      0.47 1 1
+ 2020BX12  O C K 2020 02 03.866093      1.000E-06 03 01 56.060  1.491E-01    0.671 F    0.000    0.103 +06 26 00.00  1.000E-01    0.671 F    0.000   -0.042                       V 204      0.17 1 0
+ 2020BX12  O C K 2020 02 03.867253      1.000E-06 03 01 52.560  1.491E-01    0.735 F    0.000   -0.323 +06 27 03.10  1.000E-01    0.735 F    0.000   -0.254 15.9 G  0.70   0.14   V J69      0.56 1 1
+ 2020BX12  O C H 2020 02 03.867712      1.000E-06 03 01 47.620  1.490E-01    0.671 F    0.000    0.225 +06 27 51.40  1.000E-01    0.671 F    0.000    0.060                       V 204      0.35 1 0
+ 2020BX12  O C K 2020 02 03.869323      1.000E-06 03 01 39.220  1.490E-01    0.671 F    0.000    0.310 +06 29 42.10  1.000E-01    0.671 F    0.000    0.031 16.1 G  0.70   0.34   V 204      0.47 1 1
+ 2020BX12  O C K 2020 02 03.869334      1.000E-06 03 01 41.710  1.490E-01    0.735 F    0.000   -0.068 +06 29 26.10  1.000E-01    0.735 F    0.000   -0.361 15.9 G  0.70   0.14   V J69      0.50 1 1
+ 2020BX12  O C K 2020 02 03.870942      1.000E-06 03 01 30.770  1.490E-01    0.671 F    0.000    0.261 +06 31 33.20  1.000E-01    0.671 F    0.000   -0.129                       V 204      0.44 1 0
+ 2020BX12  O C K 2020 02 03.871414      1.000E-06 03 01 30.880  1.490E-01    0.735 F    0.000    0.396 +06 31 49.30  1.000E-01    0.735 F    0.000   -0.168 15.8 G  0.70   0.04   V J69      0.59 1 1
+ 2020BX12  O C K 2020 02 03.873495      1.000E-06 03 01 20.010  1.490E-01    0.735 F    0.000    0.329 +06 34 12.40  1.000E-01    0.735 F    0.000   -0.111 15.9 G  0.70   0.14   V J69      0.48 1 1
+ 2020BX12  O C K 2020 02 04.803746      1.000E-06 01 43 11.440  1.388E-01    0.600 F    0.000    0.383 +22 17 34.20  1.000E-01    0.600 F    0.000    0.411 16.0 R  0.70  -0.47   V 160      0.94 1 1
+ 2020BX12  O C K 2020 02 04.804139      1.000E-06 01 43 09.590  1.388E-01    0.600 F    0.000    0.862 +22 17 52.90  1.000E-01    0.600 F    0.000   -0.115 15.7 R  0.70  -0.77   V 160      1.47 1 1
+ 2020BX12  O C K 2020 02 04.804529      1.000E-06 01 43 07.730  1.388E-01    0.600 F    0.000    1.000 +22 18 11.30  1.000E-01    0.600 F    0.000   -0.790 16.1 R  0.70  -0.37   V 160      2.15 1 1
+ 2020BX12  O C K 2020 02 05.742306      1.000E-06 00 37 34.650  1.274E-01    0.600 F    0.000    0.320 +31 53 24.00  1.000E-01    0.600 F    0.000   -0.115 17.0 R  0.70  -0.39   V 160      0.57 1 1
+ 2020BX12  O C K 2020 02 05.743512      1.000E-06 00 37 30.190  1.273E-01    0.600 F    0.000   -0.032 +31 53 54.80  1.000E-01    0.600 F    0.000   -0.023 16.6 R  0.70  -0.79   V 160      0.07 1 1
+ 2020BX12  O C K 2020 02 05.744706      1.000E-06 00 37 25.790  1.273E-01    0.600 F    0.000   -0.212 +31 54 25.30  1.000E-01    0.600 F    0.000    0.106 16.9 R  0.70  -0.49   V 160      0.40 1 1
+ 2020BX12  O C K 2020 02 05.75770       1.000E-05 00 36 39.270  1.272E-01    0.600 F    0.000   -0.244 +31 59 35.80  1.000E-01    0.600 F    0.000    0.066 17.6 G  0.70   0.08   V K87      0.42 1 1
+ 2020BX12  O C K 2020 02 05.76225       1.000E-05 00 36 22.720  1.272E-01    0.600 F    0.000    0.058 +32 01 30.00  1.000E-01    0.600 F    0.000   -0.145 17.5 G  0.70  -0.03   V K87      0.26 1 1
+ 2020BX12  O C K 2020 02 05.76692       1.000E-05 00 36 05.700  1.271E-01    0.600 F    0.000   -0.501 +32 03 27.40  1.000E-01    0.600 F    0.000    0.282 17.7 G  0.70   0.17   V K87      0.96 1 1
+ 2020BX12  O C K 2020 02 05.77154       1.000E-05 00 35 48.960  1.271E-01    0.600 F    0.000   -0.255 +32 05 22.60  1.000E-01    0.600 F    0.000    0.210 17.6 G  0.70   0.07   V K87      0.55 1 1
+ 2020BX12  O C   2020 02 06.08499       1.000E-05 00 18 03.910  1.243E-01    0.600 F    0.000   -0.503 +34 03 56.90  1.000E-01    0.600 F    0.000   -0.046 17.5 G  0.70  -0.30   V I52      0.85 1 1
+ 2020BX12  O C   2020 02 06.08518       1.000E-05 00 18 03.330  1.243E-01    0.600 F    0.000   -0.015 +34 04 00.80  1.000E-01    0.600 F    0.000    0.156 17.6 G  0.70  -0.20   V I52      0.26 1 1
+ 2020BX12  O C   2020 02 06.08536       1.000E-05 00 18 02.710  1.243E-01    0.600 F    0.000   -0.429 +34 04 04.00  1.000E-01    0.600 F    0.000   -0.147 17.7 G  0.70  -0.10   V I52      0.76 1 1
+ 2020BX12  O C   2020 02 06.08558       1.000E-05 00 18 02.020  1.243E-01    0.600 F    0.000   -0.095 +34 04 08.40  1.000E-01    0.600 F    0.000   -0.027 17.4 G  0.70  -0.40   V I52      0.17 1 1
+ 2020BX12  O C K 2020 02 06.75542       1.000E-05 23 46 22.650  1.199E-01    0.600 F    0.000    0.309 +36 57 50.20  1.000E-01    0.600 F    0.000   -0.234 18.5 G  0.70   0.19   V K87      0.65 1 1
+ 2020BX12  O C K 2020 02 06.75617       1.000E-05 23 46 20.760  1.198E-01    0.600 F    0.000    0.358 +36 57 59.00  1.000E-01    0.600 F    0.000   -0.187 18.6 G  0.70   0.29   V K87      0.68 1 1
+ 2020BX12  O C K 2020 02 06.758120      1.000E-06 23 46 17.080  1.198E-01    0.671 F    0.000    0.217 +36 58 29.00  1.000E-01    0.671 F    0.000   -0.132 18.2 G  0.70  -0.11   V J95      0.38 1 1
+ 2020BX12  O C K 2020 02 06.76288       1.000E-05 23 46 03.810  1.198E-01    0.600 F    0.000   -0.076 +36 59 17.20  1.000E-01    0.600 F    0.000   -0.049 18.3 G  0.70  -0.02   V K87      0.15 1 1
+ 2020BX12  O C K 2020 02 06.763663      1.000E-06 23 46 03.070  1.198E-01    0.671 F    0.000    0.249 +36 59 33.60  1.000E-01    0.671 F    0.000   -0.256 18.4 G  0.70   0.08   V J95      0.53 1 1
+ 2020BX12  O C K 2020 02 06.76706       1.000E-05 23 45 53.290  1.198E-01    0.600 F    0.000   -0.229 +37 00 05.50  1.000E-01    0.600 F    0.000   -0.151 18.1 G  0.70  -0.22   V K87      0.46 1 1
+ 2020BX12  O C K 2020 02 06.769301      1.000E-06 23 45 48.880  1.198E-01    0.671 F    0.000    0.535 +37 00 39.20  1.000E-01    0.671 F    0.000   -0.162 18.3 G  0.70  -0.02   V J95      0.84 1 1
+ 2020BX12  O C K 2020 02 06.774491      1.000E-06 23 45 35.800  1.198E-01    0.671 F    0.000    0.169 +37 01 39.40  1.000E-01    0.671 F    0.000    0.025 18.3 G  0.70  -0.03   V J95      0.26 1 1
+ 2020BX12  O C K 2020 02 06.785306      1.000E-06 23 45 08.690  1.197E-01    0.671 F    0.000   -0.136 +37 03 43.50  1.000E-01    0.671 F    0.000   -0.060 18.3 G  0.70  -0.03   V J95      0.22 1 1
+ 2020BX12  O C K 2020 02 07.75674       1.000E-05 23 11 30.850  1.160E-01    0.600 F    0.000    0.131 +39 20 49.00  1.000E-01    0.600 F    0.000    0.244 19.2 G  0.70   0.29   V 204      0.46 1 1
+ 2020BX12  O C K 2020 02 07.76524       1.000E-05 23 11 16.010  1.160E-01    0.600 F    0.000    0.105 +39 21 35.50  1.000E-01    0.600 F    0.000   -0.071                       V 204      0.21 1 0
+ 2020BX12  O C H 2020 02 07.77336       1.000E-05 23 11 01.870  1.160E-01    0.600 F    0.000   -0.230 +39 22 19.70  1.000E-01    0.600 F    0.000   -0.282                       V 204      0.61 1 0
+ 2020BX12  O C   2022 02 03.173006      1.000E-06 04 32 31.120  1.461E-01    0.500 F    0.000    0.014 -13 07 46.60  1.000E-01    0.500 F    0.000   -0.034 19.19G  0.50  -0.07   V G96      0.07 1 1
+ 2020BX12  O C   2022 02 03.178646      1.000E-06 04 32 27.980  1.461E-01    0.500 F    0.000    0.211 -13 06 52.50  1.000E-01    0.500 F    0.000   -0.060 19.37G  0.50   0.11   V G96      0.44 1 1
+ 2020BX12  O C   2022 02 03.184276      1.000E-06 04 32 24.820  1.461E-01    0.500 F    0.000    0.026 -13 05 58.60  1.000E-01    0.500 F    0.000   -0.219 19.33G  0.50   0.07   V G96      0.44 1 1
+ 2020BX12  O C   2022 02 03.189910      1.000E-06 04 32 21.670  1.461E-01    0.500 F    0.000    0.011 -13 05 04.00  1.000E-01    0.500 F    0.000    0.252 19.34G  0.50   0.08   V G96      0.51 1 1
+ 2020BX12  O C K 2022 02 05.80212       1.000E-05 04 07 48.220  1.493E-01    1.000 F    0.000   -0.038 -05 32 42.60  1.000E-01    1.000 F    0.000   -0.269 19.0 V  0.70  -0.53   Z K19      0.27 1 1
+ 2020BX12  O C K 2022 02 05.80679       1.000E-05 04 07 45.470  1.493E-01    1.000 F    0.000    0.616 -05 31 51.20  1.000E-01    1.000 F    0.000   -0.868 19.5 V  0.70  -0.03   Z K19      1.07 1 1
+ 2020BX12  O C K 2022 02 05.81146       1.000E-05 04 07 42.590  1.493E-01    1.000 F    0.000   -0.671 -05 30 58.40  1.000E-01    1.000 F    0.000   -0.081 19.6 V  0.70   0.07   Z K19      0.68 1 1
+! Object   Obser ====== Date =======  ============ Radar range/range rate (km or km/d) =============  Station  ====  Residual
+! Design   K T N YYYY MM DD hh:mm:ss         Measure  Accuracy       rms F        Bias       Resid    TRX  RCX        Chi   S
+ 2020BX12  V c   2020 02 04 20:14:00   1010023.56717   1.63248   1.63248 F     0.00000    -0.59658    -1   -1         0.46  1
+ 2020BX12  R c   2020 02 04 20:31:00   4937248.53246   0.59958   0.59958 F     0.00000    -0.01963    -1   -1         0.18  1
diff --git a/astroquery/esa/neocc/test/data/433 Eros.clolin b/astroquery/esa/neocc/test/data/433 Eros.clolin
new file mode 100644
index 0000000000..29b70bf670
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/433 Eros.clolin	
@@ -0,0 +1,6 @@
+TIME SCALE = 'UTC'
+BODY         CALENDAR-TIME     MJD-TIME        TIME-UNCERT.     NOM.-DISTANCE          MIN.-POSS.-DIST.       DIST.-UNCERT.         STRETCH   WIDTH     PROBABILITY
+       EARTH 1975/01/23.31854  42435.318538495 1.278024877E-05  1.511341503946359E-01  1.511340923610960E-01  1.933594469527795E-08 5.914E-08 1.325E-08 1.00E+00
+       EARTH 2012/01/31.45799  55957.457989172 1.075286529E-05  1.786758145648161E-01  1.786757926699883E-01  7.292275621344764E-09 3.072E-08 7.231E-09 1.00E+00
+       EARTH 2056/01/24.45957  72021.459565604 1.472032788E-05  1.497821834273084E-01  1.497821329214336E-01  1.683724911547139E-08 6.812E-08 1.417E-08 1.00E+00
+       EARTH 2093/01/31.65668  85543.656675743 1.982335737E-05  1.824636629273428E-01  1.824634493328226E-01  7.118081416672325E-08 1.357E-07 1.757E-08 1.00E+00
diff --git a/astroquery/esa/neocc/test/data/433.clolin b/astroquery/esa/neocc/test/data/433.clolin
new file mode 100644
index 0000000000..fbef119bb0
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/433.clolin
@@ -0,0 +1,7 @@
+TIME SCALE = 'UTC'
+BODY         CALENDAR-TIME     MJD-TIME        TIME-UNCERT.     NOM.-DISTANCE          MIN.-POSS.-DIST.       DIST.-UNCERT.         STRETCH   WIDTH     PROBABILITY
+       EARTH 1975/01/23.31907  42435.319066982 1.150736139E-05  1.511341904287645E-01  1.511341809807520E-01  1.674939905386203E-08 4.091E-08 1.314E-08 1.00E+00
+       EARTH 2012/01/31.45876  55957.458759002 1.024989019E-05  1.786758127236205E-01  1.786758122415167E-01  7.269760868750444E-09 2.962E-08 7.215E-09 1.00E+00
+       EARTH 2056/01/24.46038  72021.460378791 1.319171716E-05  1.497821787084139E-01  1.497821666594618E-01  1.661446484140748E-08 5.271E-08 1.315E-08 1.00E+00
+       EARTH 2093/01/31.65750  85543.657499489 1.572619005E-05  1.824638321371326E-01  1.824638180864916E-01  4.954403653193194E-08 9.921E-08 1.612E-08 1.00E+00
+       EARTH 2137/01/25.59156 101607.591564701 1.942815179E-05  1.494623181421245E-01  1.494623052937029E-01  1.763366536083567E-08 1.297E-07 1.380E-08 1.00E+00
diff --git a/astroquery/esa/neocc/test/data/433.eq0 b/astroquery/esa/neocc/test/data/433.eq0
new file mode 100644
index 0000000000..b14b4ef2a8
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/433.eq0
@@ -0,0 +1,28 @@
+format  = 'OEF2.0'       ! file format
+rectype = 'ML'           ! record type (1L/ML)
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+433
+! Equinoctial elements: a, e*sin(LP), e*cos(LP), tan(i/2)*sin(LN), tan(i/2)*cos(LN), mean long.
+ EQU   1.4580835432521406E+00   0.186731548622843  -0.121477866041295   -0.078216343748682    0.053535288884293  356.226834917799
+ MJD     53787.596517922 TDT
+ MAG  10.853  0.460
+! Non-gravitational parameters: model used, number of model parameters, dimension
+ LSP   0  0    6
+! RMS    1.64591E-10   1.26495E-08   1.57424E-08   1.77656E-08   1.76889E-08   1.90187E-06
+! EIG   1.47043E-10   3.80508E-09   9.84494E-09   1.47518E-08   2.05006E-08   1.90194E-06
+! WEA   0.00000   0.00373   0.00796  -0.00030  -0.00143  -0.99996
+ COV   2.709005982472826E-20  2.614798138185264E-19  3.520787248325734E-19
+ COV  -6.180094411929307E-20 -2.297535117968991E-19 -1.714008716787934E-17
+ COV   1.600097204963565E-16  1.011550241884446E-16 -1.040124963263759E-17
+ COV   3.222598305797540E-17 -1.350232049194842E-14  2.478222892849441E-16
+ COV   5.827025090471893E-18 -2.165326192138644E-17 -2.877703814285162E-14
+ COV   3.156165844367133E-16 -1.029089123797051E-16  1.099278338989066E-15
+ COV   3.128963806101751E-16  5.164493021228795E-15  3.617099428099010E-12
+ NOR   4.623444572588979E+19 -1.933598563967977E+17 -8.130608955784714E+17
+ NOR   9.050860691630552E+16  1.463318211508055E+17 -7.207723499009023E+15
+ NOR   1.147920461408069E+16  1.032465026564894E+16 -1.335983804344115E+15
+ NOR  -3.178690732280249E+15  1.290203664130051E+14  8.117372696976077E+16
+ NOR  -6.947887441553072E+15 -9.826295991891956E+15  6.966343582107379E+14
+ NOR   4.199603281113704E+15  2.164116603109211E+15 -6.420068915256057E+13
+ NOR   5.272376687255138E+15 -9.753433145203158E+13  6.425009068483109E+12
diff --git a/astroquery/esa/neocc/test/data/433.ke0 b/astroquery/esa/neocc/test/data/433.ke0
new file mode 100644
index 0000000000..f8187f7659
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/433.ke0
@@ -0,0 +1,36 @@
+format  = 'OEF2.0'       ! file format
+rectype = 'ML'           ! record type (1L/ML)
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+433
+! Keplerian elements: a, e, i, long. node, arg. peric., mean anomaly
+ KEP   1.4580632452014517E+00   0.222785069264007   10.829197423797  304.390234169040  178.657316225135  183.884026368892
+ MJD     53699.537843440 TDT
+ MAG  10.844  0.460
+! Non-gravitational parameters: model used, number of model parameters, dimension
+ LSP   0  0    6
+! PERIHELION   1.1332285241279432E+00
+! APHELION   1.7828979662749602E+00
+! ANODE   7.6714546550187301E-01
+! DNODE   1.4840037593463146E-01
+! MOID   1.4839393420148872E-01
+! PERIOD   6.4307699026020032E+02
+! PHA F
+! VINFTY     1.2545861393840
+! U_PAR 0.0
+! ORB_TYPE Amor  
+! RMS    1.65562E-10   9.70227E-09   2.31164E-06   9.00271E-06   1.01067E-05   2.91054E-06
+ COV   2.741070910217469E-20  1.875377119598089E-20 -8.547711150854404E-18
+ COV  -1.424161869536833E-16  2.069981909594347E-17  1.020861252147022E-16
+ COV   9.413409432515281E-17  3.679442347840267E-15  1.576108071279716E-14
+ COV  -1.550739655716465E-14  4.339298265417407E-15  5.343682955647460E-12
+ COV   2.651892644726515E-12 -2.645732678444339E-12  2.362781905795561E-13
+ COV   8.104875730482198E-11 -8.081646039384975E-11  2.806434537696526E-12
+ COV   1.021449579122188E-10 -1.594231888552837E-11  8.471217706908019E-12
+ COR   1.000000000000000E+00  1.167494930651770E-02 -2.233414651547317E-02
+ COR  -9.554897626880261E-02  1.237080461677989E-02  2.118525340584048E-01
+ COR   1.000000000000000E+00  1.640545147426220E-01  1.804427090214044E-01
+ COR  -1.581455411525347E-01  1.536643442357149E-01  1.000000000000000E+00
+ COR   1.274272811732347E-01 -1.132445089573899E-01  3.511804841287464E-02
+ COR   1.000000000000000E+00 -8.882151533922009E-01  1.071047704381259E-01
+ COR   1.000000000000000E+00 -5.419635806199125E-01  1.000000000000000E+00
diff --git a/astroquery/esa/neocc/test/data/433.phypro b/astroquery/esa/neocc/test/data/433.phypro
new file mode 100644
index 0000000000..7d91b5a4a9
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/433.phypro
@@ -0,0 +1,38 @@
+Rotation Period,5.27,h,[4]
+Quality,4,-,[4]
+Amplitude,0.04-1.49,mag,[4]
+Rotation Direction,PRO,-,[1]
+Spinvector L,16,deg,[1]
+Spinvector B,9,deg,[1]
+Taxonomy,Sq,-,[2]
+Taxonomy (all),S,-,[3]
+Absolute Magnitude (H),10.851,mag,[5]
+Absolute Magnitude (H),10.31,mag,[6]
+Slope Parameter (G),0.46**,mag,[5]
+Slope Parameter (G),0.46**,mag,[7]
+Slope Parameter (G),0.2,mag,[8]
+Albedo,0.24,-,[9]
+Diameter,23300,m,[10]
+Color Index Information,0.85,B-V,[11]
+Color Index Information,0.52,U-B,[12]
+Color Index Information,0.39,R-I,[11]
+Color Index Information,0.48,V-R,[11]
+Sightings,Visual S,-,[13]
+Sightings,Radar R,-,[14]
+
+REFERENCES
+
+[1],EARN,1.) Kaasalainen, M. et al. (2001) Icarus 153, 37-51. (Optimization Methods for Asteroid Lightcurve Inversion)
+[2],EARN,1.) Thomas, C.A. et al. (2014) Icarus 228, 217-246. (Physical characterization of Warm Spitzer-observed near-Earth objects)
+[3],EARN,1.) Tholen, D.J. (1989) in "Asteroids II" (Eds. R.P.Binzel et al.), Univ.Ariz.Press, Tucson, USA, pp. 1139-1150. 2.) Bus, S.J. & Binzel, R.P. (2002) Icarus 158,106-145. (Phase II of the Small Main-Belt Asteroid Spectrographic Survey: A Feature-Based Taxonomy.) 3.) Binzel, R.P. et al. (2004) Icarus 170, 259-294. (Observed spectral properties of near-Earth objects: results for population distribution, source regions, and space weathering processes.)
+[4],EARN,1.) Campa, M. (1938) Mem. Soc. Astron. Ital. 11, 285-301. (rotation period of 433 Eros) 2.) Bailey, S.J. (1913) Ann. Harvard Coll. Obs. 72, 165-189. (433 Eros ..) 3.) Roach, F.E. &  L.G. Stoddard (1938) Astrophys. J. 88, 305-312. (433 Eros) 4.) Beyer, M. (1953) Astron. Nachr. 281, 121-130. (433 Eros...) 5.) Chen, D.-h. et al. (1975) Acta Astron. Sin. 16, 131-137. (433 Eros..) 6.) Chen, D-h. et al. (1976) Acta Astron. Sin. 17, 176-184.  (433 Eros..) 7.) Cristescu, C. (1976) Icarus 28, 39-42. (Photoelectric Lightcurves of Asteroid 433 Eros) 8.) Dunlap, J.L. (1974) Astron. J. 79, 324-332. (Minor planets and related objects. XV. Asteroid (1620) Geographos) 9.) Millis, R.L. et al. (1976) Icarus 28, 53-67. (UBV photometry of asteroid 433 Eros) 10.) Miner, E. & J. Young (1976) Icarus 28, 43-51. (Five-color photoelectric photometry of asteroid 433 Eros) 11.) Pop, V. & D. Chis (1976) Icarus 28, 37-38. (Photoelectric lightcurves of asteroid 433 Eros) 12.) Scaltriti, F. & V. Zappala (1976) Icarus 28, 29-35. (Photometric lightcurves and pole determination of 433 Eros) 13.) Tedesco, E.F. (1976) Icarus 28, 21-28. (UBV lightcurves of asteroid 433 Eros) 14.) Taylor, R.C. (1985) Icarus 61, 490-496. (The pole orientation of asteroid 433 Eros determined by photometric astrometry) 15.) Harris, A.W. et al. (1992) Icarus 95,  115-147. (Asteroid lightcurve observations from 1981) 16.) Harris, A.W. et al. (1995) LPSC 27, 553-554. (Photoelectric Lightcurves of 433 Eros) 17.) Harris, A.W. (DLR) (1998) Icarus 131, 291-301. (A Thermal Model for Near-Earth Asteroids) 18.) Harris(JPL), A.W. et al. (1999) Icarus 142,173-201. (Asteroid lightcurve observations from 1981-1983) 19.) Hicks, M. et al. (1999) Icarus 141, 411-414. (NOTE: The Lightcurve and Geometric Albedo of 433 Eros during the 1998 Apparition) 20.) Krugly, Y.N. & V.G. Shevchenko (1999) LPSC 30, 1595-1596. (Magnitude Phase Dependence of Asteroid 433 Eros) 21.) Clark, B.E. et al. (2000) Icarus 145, 641-644. (NEAR Lightcurves of Asteroid 433 Eros) 22.) Erikson, A. et al. (2000) Icarus 147, 487-497. (The Near-Earth Objects Follow-Up Program III: 32 Lightcurves for 12 Objects from 1992 to 1995) (433,1917,2368,3753,4769,4953,6491, 1995 EK1, 1995 FJ; 5738,7467,1995 LH) 23.) Kaasalainen, M. et al. (2001) Icarus 153, 37-51. (Optimization Methods for Asteroid Lightcurve Inversion) 24.) Li, J. et al. (2004) Icarus 172, 415-431. (Photometric analysis of Eros from NEAR data) 25.) Durech, J. (2005) Astron. Astrophys. 431, 381-383. (433 Eros - comparison of lightcurve extreme from 1901-1931 with the presen rotation state) 26.) Koehn, B.W. et al. (2014) MPB 41, 286-300. (LOWELL OBSERVATORY NEAR-EARTH ASTEROID PHOTOMETRIC SURVEY (NEAPS) - 2009 JANUARY THROUGH 2009 JUNE) (433,1943,3554,5011,5604,5620,5693,8566,14402,16834,22753,35107,52768,68350,85867,138883,141052,143651,154244,161989,162385,163758,175706,194386,203217,207945,208023,212546,256412,2001FE90,2004LV3,2005BC,2005SG19,2008QT3,2008WL60,2009DE47,2009DO111,2009EP2,2009FD,2009JM2) 27.) Warner, B.D. (2017) MPB 44, 22-36. (NEAR-EARTH ASTEROID LIGHTCURVE ANALYSIS AT CS3-PALMER DIVIDE STATION: 2016 JULY-SEPTEMBER) (46 NEAs)
+[5],ESA ODIM,ESA orbit determination and impact monitoring system
+[6],EARN,1.) Erikson, A. et al. (2000) Icarus 147, 487-497. (The Near-Earth Objects Follow-Up Program III: 32 Lightcurves for 12 Objects from 1992 to 1995) (433,1917,2368,3753,4769,4953,6491, 1995 EK1, 1995 FJ; 5738,7467,1995 LH)
+[7],NEODyS,NEO Dynamic Site: https://newton.spacedys.com/neodys2
+[8],EARN,1.) Magnusson, P. & Lagerkvist, C.-I. (1990) Astron. & Astrophys. Suppl. Ser. 86, 45-51. (Analysis of asteroid lightcurves. I - Data base and basic reduction)
+[9],EARN,1.) Mueller, M. et al. (2011) Astron. J. 141, 109. (ExploreNEOs. III. PHYSICAL CHARACTERIZATION OF 65 POTENTIAL SPACECRAFT TARGET ASTEROIDS) 2.) Wolters, S.D. et al. (2008) Icarus 193, 535-552. (Thermal infrared and optical observations of four near-Earth asteroid) (433,66063,137032,138258) 3.) Harris, A.W. (DLR), & J.K. Davies (1999) Icarus 142, 464-475 (Physical characteristics of near-Earth asteroids from thermal infrared spectroscopy.) 4.) Morrison, D. (1976) Icarus 28, 125-132. (The diameter and thermal inertia of 433 Eros) 5.) Trilling, D.E. et al. (2010) Astron. J. 140, 770-784. (EXPLORENEOs. I. DESCRIPTION AND FIRST RESULTS FROM THE WARM SPITZER NEAR-EARTH OBJECT SURVEY) (diameters & albedos for 101 NEOs) 6.) Usui, F. et al. (2011) Pub. Astron. Soc.  Japan 63, 1117-1138. (Asteroid Catalog Using AKARI: AKARI/IRC Mid-Infrared Asteroid Survey) 7.) Harris(DLR), A.W. et al. (2011) Astron. J. 141, 75. (ExploreNEOs. II. THE ACCURACY OF THE WARM SPITZER NEAR-EARTH OBJECT SURVEY)
+[10],EARN,1.) Wolters, S.D. et al. (2008) Icarus 193, 535-552. (Thermal infrared and optical observations of four near-Earth asteroid) (433,66063,137032,138258) 2.) Harris, A.W. (DLR), & J.K. Davies (1999) Icarus 142, 464-475 (Physical characteristics of near-Earth asteroids from thermal infrared spectroscopy.) 3.) Morrison, D. (1976) Icarus 28, 125-132. (The diameter and thermal inertia of 433 Eros) 4.) Trilling, D.E. et al. (2010) Astron. J. 140, 770-784. (EXPLORENEOs. I. DESCRIPTION AND FIRST RESULTS FROM THE WARM SPITZER NEAR-EARTH OBJECT SURVEY) (diameters & albedos for 101 NEOs) 5.) Mueller, M. et al. (2011) Astron. J. 141, 109. (ExploreNEOs. III. PHYSICAL CHARACTERIZATION OF 65 POTENTIAL SPACECRAFT TARGET ASTEROIDS) 6.) Usui, F. et al. (2011) Pub. Astron. Soc.  Japan 63, 1117-1138. (Asteroid Catalog Using AKARI: AKARI/IRC Mid-Infrared Asteroid Survey) 7.) Harris(DLR), A.W. et al. (2011) Astron. J. 141, 75. (ExploreNEOs. II. THE ACCURACY OF THE WARM SPITZER NEAR-EARTH OBJECT SURVEY)
+[11],EARN,1.) Velichko, F.P. & A. Rikhteghar (2011) Astronomy 47, 41-43. (Lightcurves, colours and magnitude phase dependences of the asteroids 433 Eros and 1627 Ivar) (in Russian)
+[12],EARN,1.) Tedesco, E.F. (1989) in "Asteroids II" (Eds. R.P.Binzel et al.), Univ.Ariz.Press, Tucson, USA, pp. 1090-1138.
+[13],EARN,1.) Bus, S.J. & Binzel, R.P. (2002) Icarus 158,106-145. (Phase II of the Small Main-Belt Asteroid Spectrographic Survey: A Feature-Based Taxonomy.) 2.) Harris, A.W. (DLR), & J.K. Davies (1999) Icarus 142, 464-475 (Physical characteristics of near-Earth asteroids from thermal infrared spectroscopy.) 3.) Binzel, R.P. et al. (2004) Icarus 170, 259-294. (Observed spectral properties of near-Earth objects: results for population distribution, source regions, and space weathering processes.) 4.) Fevig. R.A. and U. Fink (2007) Icarus 188, 175-188. (Spectral observations of 19 weathered and 23 fresh NEAs and their correlations with orbital parameters)(433,1036,1627,1685,1862,1866,1943,1980,3103,3122,3199,3671,4183,4341,4954,5587,5751,5836,6037,7358,7482,7753,7822,7977,8201,10563,11066,13651,13651,19356,20236,20255,35107,85490,J97GD32,J97UH9,J97US9,J98HE3,J98HT31,J98ME3,J98MS2,K04LC2) 5.) deLeon, J. et al. (2010) Astron. Astrophys 517, A23. (Observations, compositional, and physical characterization of near-Earth and Mars-crosser asteroids from a spectroscopic survey) 6.) Thomas, C.A. et al. (2014) Icarus 228, 217-246. (Physical characterization of Warm Spitzer-observed near-Earth objects) 7.) Wigton, N. et al. (2015) DPS47-106.05. (astract) (3-um spectroscopy of Near-Earth Asteroids: Searching for OH/H2O on small planetary bodies)
+[14],EARN,1.) Mitchell, D.L. et al. (1996) B.A.A.S 28, 1106. (Shape of Asteroid 433 Eros from Inversion of Goldstone Radar Doppler Spectra) 2.) Mitchell, D.L. et al. (1998) Icarus 131, 4-14. (Shape of Asteroid 433 Eros from Inversion of Goldstone Radar Doppler Spectra) 3.) Ostro, S.J. et al. (1990) Icarus  84, 334-351. (The shape of Eros) 4.) Ostro, S.J. et al. (1991) Astron. J. 102, 1490-1502. (Asteroid radar astrometry) 5.) Campbell, D. B. et al., (1976) Icarus 28, 17-20. (70-cm radar observations of 433 Eros.) 6.) Jurgens, R. F., & R. M. Goldstein (1976) Icarus  28, 1-15. (Radar observations at 3.5 and 12.6 cm wavelength of asteroid 433 Eros.) 7.) Magri, C. et al., (2001) Meteoritics Planet. Sci. 36, 1697-1709. (Radar constraints on asteroid regolith compositions using 433 Eros as ground truth.)
diff --git a/astroquery/esa/neocc/test/data/433.risk b/astroquery/esa/neocc/test/data/433.risk
new file mode 100644
index 0000000000..e6b098d127
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/433.risk
@@ -0,0 +1,6 @@
+<HTML>
+<BODY>
+<p>Required risk file is not available for this object</p>
+<HR>
+<I>Error accessing /o/PSDB-portlet/download</I>
+</BODY></HTML>
diff --git a/astroquery/esa/neocc/test/data/433.rwo b/astroquery/esa/neocc/test/data/433.rwo
new file mode 100644
index 0000000000..e7a1f2a4c0
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/433.rwo
@@ -0,0 +1,41 @@
+version =   3
+errmod  = 'vfcc17'
+RMSast  =   3.32005E-01
+RMSmag  =   4.77458E-01
+END_OF_HEADER
+! Object   Obser ============= Date ============= ================== Right Ascension =================  ================= Declination ===================== ==== Magnitude ==== Ast Obs  Residual SEL
+! Design   K T N YYYY MM DD.dddddddddd   Accuracy HH MM SS.sss  Accuracy      RMS  F     Bias    Resid sDD MM SS.ss  Accuracy      RMS  F     Bias    Resid Val  B   RMS  Resid Cat Cod       Chi A M
+ 433       O A   1893 10 29.4132        1.000E-04 06 08 59.320  8.890E-02    5.000 F    0.000   -0.378 +53 39 04.20  1.000E-01    5.000 F    0.000    0.962                         802      0.21 1 0
+ 433       O A   1893 10 31.3458        1.000E-04 06 14 47.820  8.800E-02    5.000 F    0.000    5.507 +54 04 39.40  1.000E-01    5.000 F    0.000    4.498                         802      1.42 1 0
+ 433       O A   1893 11 01.3896        1.000E-04 06 17 54.060  8.754E-02    5.000 F    0.000    1.437 +54 17 52.80  1.000E-01    5.000 F    0.000   -2.147                         802      0.52 1 0
+ 433       O A   1893 11 27.3514        1.000E-04 07 28 02.600  8.042E-02    5.000 F    0.000   -0.406 +57 34 47.90  1.000E-01    5.000 F    0.000   -0.108                         802      0.08 1 0
+ 433       O A   1931 02 09.95119       1.000E-05 10 10 18.000  8.740E+01   87.396 F    0.000 -188.779 -13 48 60.00  6.000E+01   60.000 F    0.000  -13.898 8       1.00  -1.02     024      2.17 1 1
+ 433       S S   2014 09 24.24805       1.000E-05 18 20 14.560  1.388E-01    1.000 F   -0.070   -0.023 -22 14 57.00  1.000E-01    1.000 F    0.132   -0.170 16   R  1.00   2.58   L C51      0.17 1 1
+ 433       S s   2014 09 24.24805 1       1140.043900000000      -6277.170100000000      -2592.299000000000 C51
+ 433       S S   2014 09 24.64267       1.000E-05 18 20 48.510  1.389E-01    1.000 F   -0.070    0.224 -22 12 49.10  1.000E-01    1.000 F    0.132   -0.064                       L C51      0.23 1 0
+ 433       S s   2014 09 24.64267 1       1182.754200000000      -6271.747500000000      -2586.552000000000 C51
+ 433       S S   2014 09 25.10299       1.000E-05 18 21 28.290  1.389E-01    1.000 F   -0.070   -0.153 -22 10 20.10  1.000E-01    1.000 F    0.132   -0.022                       L C51      0.15 1 0
+ 433       S s   2014 09 25.10299 1       1235.200300000000      -6248.741200000000      -2617.603900000000 C51
+ 433       S S   2014 09 25.49761       1.000E-05 18 22 02.620  1.389E-01    1.000 F   -0.048   -0.005 -22 08 12.80  1.000E-01    1.000 F    0.170   -0.306                       L C51      0.31 1 0
+ 433       S s   2014 09 25.49761 1       1277.663000000000      -6243.050400000000      -2610.786200000000 C51
+ 433       S S   2014 09 25.62915       1.000E-05 18 22 14.100  1.390E-01    1.000 F   -0.048    0.018 -22 07 30.30  1.000E-01    1.000 F    0.170   -0.302                       L C51      0.30 1 0
+ 433       S s   2014 09 25.62915 1       1291.996100000000      -6239.895100000001      -2611.276900000000 C51
+ 433       O C K 2010 01 02.76290       1.000E-05 23 26 24.000  1.480E-01    1.118 F    0.019   -0.522 +09 16 56.90  1.000E-01    1.118 F    0.006   -0.220                       u 160      0.51 1 0
+ 433       O C K 2010 01 02.76339       1.000E-05 23 26 24.080  1.480E-01    1.118 F    0.019   -0.382 +09 16 57.40  1.000E-01    1.118 F    0.006   -0.026                       u 160      0.34 1 0
+ 433       O C K 2010 01 02.76389       1.000E-05 23 26 24.150  1.480E-01    1.118 F    0.019   -0.412 +09 16 57.60  1.000E-01    1.118 F    0.006   -0.139 13.1 C  0.70   0.36   u 160      0.39 1 1
+ 433       O C K 2010 01 02.76438       1.000E-05 23 26 24.220  1.480E-01    1.118 F    0.019   -0.420 +09 16 57.80  1.000E-01    1.118 F    0.006   -0.245                       u 160      0.43 1 0
+ 433       O C K 2010 01 02.76486       1.000E-05 23 26 24.280  1.480E-01    1.118 F    0.019   -0.555 +09 16 58.00  1.000E-01    1.118 F    0.006   -0.345 13.0 C  0.70   0.26   u 160      0.58 1 1
+ 433       O C   2023 08 14.91552       1.000E-05 21 15 37.900  1.484E-01    0.600 F    0.000   -0.041 -08 27 19.10  1.000E-01    0.600 F    0.000    0.038 11.4 G  0.70  -0.07   X G02      0.09 1 1
+ 433       O C   2023 08 14.91813       1.000E-05 21 15 37.600  1.484E-01    0.600 F    0.000   -0.043 -08 27 18.80  1.000E-01    0.600 F    0.000    0.164 11.4 G  0.70  -0.07   X G02      0.28 1 1
+ 433       O C   2023 08 14.92206       1.000E-05 21 15 37.160  1.484E-01    0.600 F    0.000    0.129 -08 27 18.90  1.000E-01    0.600 F    0.000   -0.199 11.4 G  0.70  -0.07   X G02      0.40 1 1
+ 433       O C 1 2023 08 18.01055       1.000E-05 21 09 54.240  1.484E-01    0.600 F    0.000    0.127 -08 24 10.20  1.000E-01    0.600 F    0.000    0.113 11.5 G  0.70  -0.02   V C40      0.28 1 1
+ 433       O C 1 2023 08 18.01488       1.000E-05 21 09 53.760  1.484E-01    0.600 F    0.000    0.198 -08 24 09.90  1.000E-01    0.600 F    0.000    0.152 11.5 G  0.70  -0.02   V C40      0.42 1 1
+ 433       O C 1 2023 08 18.01916       1.000E-05 21 09 53.280  1.484E-01    0.600 F    0.000    0.181 -08 24 09.60  1.000E-01    0.600 F    0.000    0.194 11.5 G  0.70  -0.02   V C40      0.44 1 1
+! Object   Obser ====== Date =======  ============ Radar range/range rate (km or km/d) =============  Station  ====  Residual
+! Design   K T N YYYY MM DD hh:mm:ss         Measure  Accuracy       rms F        Bias       Resid    TRX  RCX        Chi   S
+ 433       V s   1975 01 23 04:25:00        39.15429  90.35605  90.35605 F     0.00000   -83.25813    -1   -1         0.92  1
+ 433       V s   1988 12 02 23:30:00    217060.42127  54.41611  54.41611 F     0.00000    -3.39915    -1   -1         0.06  1
+ 433       R c   2012 01 27 06:30:00  26884915.59373   3.74741   3.74741 F     0.00000    -0.40938    -14  -14        0.12  1
+ 433       R c   2012 01 28 06:10:00  26819370.71250   1.64886   1.64886 F     0.00000    -0.53757    -14  -14        0.44  1
+ 433       R c   2012 01 30 08:10:00  26736333.48848   1.64886   1.64886 F     0.00000    -0.79843    -14  -14        0.65  1
+ 433       R c   2019 01 08 10:50:00  31524992.30696   2.99792   2.99792 F     0.00000    -3.42497    -14  -14        2.21  1
diff --git a/astroquery/esa/neocc/test/data/516976%202012HM1.eph b/astroquery/esa/neocc/test/data/516976%202012HM1.eph
new file mode 100644
index 0000000000..47c8eadc75
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/516976%202012HM1.eph
@@ -0,0 +1,15 @@
+Ephemerides generation for: 516976 2012HM1
+Observatory: J75 - OAM Observatory, La Sagra
+Initial Date: 2020/09/01 00:00 UTC
+Final Date: 2020/09/02 00:00 UTC
+Time step: 5 hours
+                                     Equatorial coordinates                                                                                         App. motion                           Sky plane error     
+    Date      Hour      MJD            RA            DEC       Mag    Alt  Airmass   Sun elev.   SolEl  LunEl  Phase Glat  Glon     R     Delta   RA*cosDE     DEC       Vel    PA       Err1     Err2   AngAx 
+             (UTC)     (UTC)        (h  m  s)     (d  '  ")          (deg)             (deg)     (deg)  (deg)  (deg) (deg) (deg)   (au)    (au)   ("/min)   ("/min)    ("/min) (deg)                     (deg) 
+ =========== ====== ============  =============  ============ ====== ===== ======== =========== ====== ====== ====== ===== ===== ======= =======  ========  ========  ======== =====  ========  ======== ======
+  1 Sep 2020  0.000 59093.000000    9 42 59.688  + 8  9 39.70  26.64 -42.6    INF    -43.8        14.5  169.8    5.6  41.6 226.9   2.603   3.568    0.9632   -0.3270    1.0172 108.7    0.014"    0.008" 113.3
+  1 Sep 2020  5.000 59093.208333    9 43 19.087  + 8  8  1.71  26.65   2.7   15.337   -8.5        14.6 -170.0    5.6  41.7 227.0   2.602   3.566    0.9555   -0.3265    1.0098 108.9    0.014"    0.008" 113.3
+  1 Sep 2020 10.000 59093.416666    9 43 38.293  + 8  6 23.59  26.65  56.0    1.205   48.1        14.7 -169.2    5.6  41.7 227.1   2.601   3.565    0.9472   -0.3278    1.0023 109.1    0.014"    0.008" 113.3
+  1 Sep 2020 15.000 59093.625000    9 43 57.442  + 8  4 44.95  26.65  30.4    1.969   41.4        14.8 -167.2    5.7  41.8 227.2   2.601   3.563    0.9509   -0.3297    1.0064 109.1    0.014"    0.008" 113.3
+  1 Sep 2020 20.000 59093.833333    9 44 16.758  + 8  3  5.95  26.65 -26.3    INF    -16.0        14.9 -165.4    5.7  41.9 227.3   2.600   3.562    0.9614   -0.3300    1.0164 108.9    0.014"    0.008" 113.4
+
diff --git a/astroquery/esa/neocc/test/data/594938%202021GE13.clolin b/astroquery/esa/neocc/test/data/594938%202021GE13.clolin
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/astroquery/esa/neocc/test/data/594938%202021GE13.eq1 b/astroquery/esa/neocc/test/data/594938%202021GE13.eq1
new file mode 100644
index 0000000000..f4fd5246c0
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/594938%202021GE13.eq1
@@ -0,0 +1,28 @@
+format  = 'OEF2.0'       ! file format
+rectype = 'ML'           ! record type (1L/ML)
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+594938
+! Equinoctial elements: a, e*sin(LP), e*cos(LP), tan(i/2)*sin(LN), tan(i/2)*cos(LN), mean long.
+ EQU   2.1862529035694496E+00  -0.471373155350099   0.012255889979474    0.239306790837725   -0.113152710184792  290.676321465681
+ MJD     59400.000000000 TDT
+ MAG  18.247  0.150
+! Non-gravitational parameters: model used, number of model parameters, dimension
+ LSP   0  0    6
+! RMS    2.98765E-08   1.00023E-07   1.06041E-07   9.33318E-08   8.15569E-08   1.06268E-05
+! EIG   1.58152E-08   5.60847E-08   7.91052E-08   8.35728E-08   9.48634E-08   1.06274E-05
+! WEA   0.00210  -0.00513  -0.00821  -0.00052   0.00258  -0.99995
+ COV   8.926032596025369E-16 -2.116580579490103E-15 -1.938181671883124E-15
+ COV  -4.597730803125709E-16  2.974833931766122E-16 -2.365972276087561E-13
+ COV   1.000464880124173E-14  4.150592709094470E-15  9.404736109881860E-16
+ COV  -1.584185284406097E-15  5.797980227829348E-13  1.124476071432883E-14
+ COV   2.264867193405029E-16 -1.343213449631762E-15  9.272230533345568E-13
+ COV   8.710824053725137E-15 -2.936696827984569E-16  5.917339650233994E-14
+ COV   6.651523512290038E-15 -2.911570724179466E-13  1.129293886865285E-10
+ NOR   3.916717371140058E+15  4.967409587823874E+14  2.566309576386154E+13
+ NOR   1.193251429791149E+14  2.132532070744408E+14  5.932104519808896E+12
+ NOR   2.082779181547438E+14  2.762370598028001E+13  5.167038049986563E+12
+ NOR   2.468178063103415E+13 -1.944967993490093E+11  2.950016456726281E+14
+ NOR   6.962051713585639E+12 -5.041753521321828E+13 -2.643847390917052E+12
+ NOR   1.197856857440219E+14  8.026550471269813E+12  1.242337884113100E+11
+ NOR   1.902755905108481E+14  1.220391769945428E+12  4.707099732740131E+10
diff --git a/astroquery/esa/neocc/test/data/594938%202021GE13.ke1 b/astroquery/esa/neocc/test/data/594938%202021GE13.ke1
new file mode 100644
index 0000000000..30786e3c67
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/594938%202021GE13.ke1
@@ -0,0 +1,36 @@
+format  = 'OEF2.0'       ! file format
+rectype = 'ML'           ! record type (1L/ML)
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+594938
+! Keplerian elements: a, e, i, long. node, arg. peric., mean anomaly
+ KEP   2.1859956926871762E+00   0.471266513586621   29.647280093062  115.304765589582  156.127269779942  263.277036549725
+ MJD     60200.000000000 TDT
+ MAG  18.247  0.150
+! Non-gravitational parameters: model used, number of model parameters, dimension
+ LSP   0  0    6
+! PERIHELION   1.1558091238791210E+00
+! APHELION   3.2161822614952311E+00
+! ANODE   2.0034031121544715E+00
+! DNODE   1.7179110025928596E-01
+! MOID   1.6582040268236059E-01
+! PERIOD   1.1805173647320241E+03
+! PHA F
+! VINFTY    15.6449154331046
+! U_PAR 0.1
+! ORB_TYPE Amor  
+! RMS    2.96492E-08   9.89986E-08   9.90580E-06   1.78551E-05   2.06919E-05   8.74418E-06
+ COV   8.790769573219951E-16  2.059480756201647E-15 -5.688688942104450E-14
+ COV  -1.492444369027067E-14 -2.231103623729184E-13 -1.426576734993612E-13
+ COV   9.800720358198681E-15 -1.616397252764929E-13 -2.171823343585886E-13
+ COV  -2.837746019356366E-13 -4.010280123756560E-13  9.812489592786124E-11
+ COV  -1.411569255393129E-11  2.477984928756512E-11  1.792445025723872E-11
+ COV   3.188046161402691E-10 -2.887208423745855E-10  2.401131977859697E-11
+ COV   4.281563263543018E-10 -3.896337030348700E-11  7.646072675472740E-11
+ COR   1.000000000000000E+00  7.016415369799237E-01 -1.936908631133016E-01
+ COR  -2.819177385686001E-02 -3.636680188811893E-01 -5.502530749338627E-01
+ COR   1.000000000000000E+00 -1.648274349604935E-01 -1.228664180364294E-01
+ COR  -1.385298428468551E-01 -4.632618104343304E-01  1.000000000000000E+00
+ COR  -7.980870897816615E-02  1.208948702111515E-01  2.069364666111885E-01
+ COR   1.000000000000000E+00 -7.814742149119931E-01  1.537922746051652E-01
+ COR   1.000000000000000E+00 -2.153456594399636E-01  1.000000000000000E+00
diff --git a/astroquery/esa/neocc/test/data/99942%20modif.eq1 b/astroquery/esa/neocc/test/data/99942%20modif.eq1
new file mode 100644
index 0000000000..2190e6124d
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/99942%20modif.eq1
@@ -0,0 +1,37 @@
+format  = 'OEF2.0'       ! file format
+rectype = 'ML'           ! record type (1L/ML)
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+99942
+! Equinoctial elements: a, e*sin(LP), e*cos(LP), tan(i/2)*sin(LN), tan(i/2)*cos(LN), mean long.
+ EQU   9.2269886736945861E-01  -0.094103271182575   0.166706101213236   -0.011838547993563   -0.026632739873978  303.802464147110
+ MJD     59400.000000000 TDT
+ MAG  18.937  0.150
+! Non-gravitational parameters: model used, number of model parameters, dimension, list of solve for parameters to be currently determined
+ LSP   1  2    7    2
+! Vector of dynamical parameters
+! Area-to-mass ratio [m^2/t], Yarkovsky parameter [1E-10 au/day^2]
+ NGR   -2.90058798774592E-04 0.00000000000000E+00
+! RMS    8.56356E-11   2.21962E-09   2.75210E-09   3.12732E-09   2.86935E-09   3.80494E-07   2.35576E-06
+! EIG   1.37295E-12   7.11566E-11   4.33176E-10   1.03595E-09   2.45426E-09   3.46755E-07   2.36097E-06
+! WEA   0.00003  -0.00070  -0.00080  -0.00072   0.00073   0.06709   0.99775
+ COV   7.333454159870582E-21 -1.430518484330030E-19 -2.039563818903334E-19
+ COV  -3.113017211144542E-20  5.375862875480088E-20 -2.053004405199749E-18
+ COV   1.597275681844029E-16  4.926698413567482E-18  5.740286393645988E-18
+ COV   4.271352667122275E-18 -4.594913504072475E-18 -4.472180769915471E-16
+ COV  -3.874443567424468E-15  7.574047815870473E-18  3.291875056941473E-18
+ COV  -3.803341554265734E-18 -2.749179586767622E-16 -4.432741010457999E-15
+ COV   9.780145636066158E-18 -8.803880830027464E-18 -1.124690148114898E-15
+ COV  -3.965436364575741E-15  8.233161784253548E-18  1.021614851189196E-15
+ COV   4.019571373629789E-15  1.447755566503557E-13  3.650738081562956E-13
+ COV   5.549616302269251E-12
+ NOR   5.300622209741479E+23 -2.290711161909014E+21  9.835548513140526E+21
+ NOR  -5.004324032792368E+21 -1.040631488603072E+22  7.957817262570576E+19
+ NOR  -1.027271939437066E+19  8.702458079894510E+19 -8.435995468610375E+19
+ NOR   6.934792805283755E+19  1.152480782675332E+20 -3.145636874337803E+17
+ NOR   4.607554623635341E+16  2.055868586315818E+20 -1.182917694090721E+20
+ NOR  -2.303667476832532E+20  1.458526187349774E+18 -1.913853825851189E+17
+ NOR   8.063490248071409E+19  1.457592239415370E+20 -7.308524987979255E+17
+ NOR   9.808505855283288E+16  2.747456151627550E+20 -1.547055040491858E+18
+ NOR   2.028915058610565E+17  1.205524768491713E+16 -1.539750505396746E+15
+ NOR   1.995683028222035E+14
diff --git a/astroquery/esa/neocc/test/data/99942%20modif.ke1 b/astroquery/esa/neocc/test/data/99942%20modif.ke1
new file mode 100644
index 0000000000..e57a056763
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/99942%20modif.ke1
@@ -0,0 +1,45 @@
+format  = 'OEF2.0'       ! file format
+rectype = 'ML'           ! record type (1L/ML)
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+99942
+! Keplerian elements: a, e, i, long. node, arg. peric., mean anomaly
+ KEP   9.2272184133465496E-01   0.191441141930856    3.339295820378  203.956557646087  126.604103652331  142.857142136292
+ MJD     60200.000000000 TDT
+ MAG  18.945  0.150
+! Non-gravitational parameters: model used, number of model parameters, dimension, list of solve for parameters to be currently determined
+ LSP   1  2    7    2
+! Vector of dynamical parameters
+! Area-to-mass ratio [m^2/t], Yarkovsky parameter [1E-10 au/day^2]
+ NGR   0.00000000000000E+00 -2.88918364689752E-04
+! PERIHELION   7.4607491834500639E-01
+! APHELION   1.0993687643243035E+00
+! ANODE  -8.6707715058413322E-04
+! DNODE  -1.9894296321957006E-01
+! MOID   2.5667311901019960E-04
+! PERIOD   3.2374616153917481E+02
+! PHA T
+! VINFTY     5.4772184467655
+! U_PAR 0.0
+! ORB_TYPE Aten  
+! RMS    1.06829E-10   1.41330E-09   1.59296E-07   7.83456E-06   8.41367E-06   1.08691E-06   2.35078E-06
+ COV   1.141244683709316E-20 -1.277705137668703E-19 -7.185961844756049E-18
+ COV   2.344803252588428E-16 -3.207964820382642E-16  7.470345028716321E-17
+ COV   2.213105466251172E-16  1.997414057656414E-18  7.361967132408794E-17
+ COV  -2.191039348475340E-15  3.405892537385540E-15 -1.064532510674101E-15
+ COV  -1.932412856554877E-15  2.537512917683352E-14 -1.186184458027285E-12
+ COV   1.294935291142860E-12 -1.544086403906037E-13 -2.342661899246152E-13
+ COV   6.138037945640663E-11 -6.561899666200993E-11  6.793585852442817E-12
+ COV   1.024458904371662E-11  7.078989443582840E-11 -7.770406835423008E-12
+ COV  -1.189364539054358E-11  1.181375567936030E-12  1.734265358158205E-12
+ COV   5.526179799653360E-12
+ COR   1.000000000000000E+00 -8.462666109472383E-01 -4.222711318080247E-01
+ COR   2.801574911989598E-01 -3.569066015090954E-01  6.433647831790731E-01
+ COR   8.812522150882851E-01  1.000000000000000E+00  3.270059781450055E-01
+ COR  -1.978797447736855E-01  2.864252214938928E-01 -6.929962519495177E-01
+ COR  -5.816387891860086E-01  1.000000000000000E+00 -9.504588393945979E-01
+ COR   9.661805793028864E-01 -8.918123362063010E-01 -6.255945806562317E-01
+ COR   9.999999999999998E-01 -9.954722745788747E-01  7.977931280884524E-01
+ COR   5.562464491297012E-01  1.000000000000000E+00 -8.496970939783123E-01
+ COR  -6.013355065201714E-01  1.000000000000000E+00  6.787487631354118E-01
+ COR   1.000000000000000E+00
diff --git a/astroquery/esa/neocc/test/data/99942.clolin b/astroquery/esa/neocc/test/data/99942.clolin
new file mode 100644
index 0000000000..4ce871db68
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/99942.clolin
@@ -0,0 +1,28 @@
+TIME SCALE = 'UTC'
+BODY         CALENDAR-TIME     MJD-TIME        TIME-UNCERT.     NOM.-DISTANCE          MIN.-POSS.-DIST.       DIST.-UNCERT.         STRETCH   WIDTH     PROBABILITY
+       EARTH 1957/04/01.13904  35929.139039623 1.337901856E-02  7.539565890398714E-02  7.530990821708286E-02  2.856879293837980E-05 2.873E-05 5.556E-09 1.00E+00
+       EARTH 1964/10/24.90648  38692.906479751 2.142966200E-02  1.876924053780912E-01  1.876509682625918E-01  1.381160956811332E-05 1.720E-05 5.051E-09 1.00E+00
+       EARTH 1965/02/11.51116  38802.511156831 1.475938672E-02  1.258367847472429E-01  1.258344833533570E-01  7.671551502579362E-07 4.733E-06 1.280E-09 1.00E+00
+       EARTH 1972/12/24.49470  41675.494697571 4.521177247E-03  7.923789245024694E-02  7.920056098848807E-02  1.244155168249903E-05 1.584E-05 4.645E-09 1.00E+00
+       EARTH 1980/12/18.07785  44591.077845398 3.286077623E-04  7.212694885576630E-02  7.210237871377251E-02  8.189094531240250E-06 1.136E-05 5.460E-09 1.00E+00
+       EARTH 1982/04/11.51157  45070.511568776 2.467468757E-04  1.795310258259036E-01  1.795031362134027E-01  9.296349233567831E-06 9.296E-06 6.788E-09 1.00E+00
+       EARTH 1990/04/14.86422  47995.864216132 8.082908194E-07  3.292925808981145E-02  3.291450135973848E-02  4.918097460158311E-06 4.919E-06 6.649E-09 1.00E+00
+       EARTH 1998/04/14.82364  50917.823643655 6.985206812E-06  2.438710473453476E-02  2.438481533984125E-02  7.631295916547399E-07 7.633E-07 6.622E-09 1.00E+00
+       EARTH 2004/12/21.39225  53360.392245463 1.231084733E-05  9.638385209156018E-02  9.638269128909421E-02  3.869864676096947E-07 4.604E-07 4.957E-09 1.00E+00
+       EARTH 2013/01/09.48800  56301.488003461 3.716933439E-05  9.666111971943500E-02  9.666098814240516E-02  4.385905093918600E-08 5.149E-08 2.639E-09 1.00E+00
+       EARTH 2021/03/06.05177  59279.051765863 1.071494418E-05  1.126513860557694E-01  1.126513642046631E-01  7.312559389618642E-09 9.405E-09 2.512E-09 1.00E+00
+       EARTH 2029/04/13.90709  62239.907090887 9.247429824E-06  2.541041971280253E-04  2.532817260414157E-04  2.737929974531578E-07 2.775E-07 5.097E-09 1.00E+00
+       EARTH 2044/08/23.69854  67850.698536928 9.656628377E+00  8.122789879220867E-02  2.256247438979676E-02  1.632686342093018E-02 1.678E-02 1.470E-06 1.00E+00
+       EARTH 2051/04/19.85100  70280.851000431 3.897953448E+00  4.036559177886249E-02  1.710305945803160E-04  1.996213102717462E-02 1.997E-02 1.081E-07 1.00E+00
+       EARTH 2066/09/16.33284  75909.332842615 4.222365475E+00  7.371688629778606E-02  2.277188769063767E-02  7.872852763628245E-02 8.257E-02 1.139E-06 7.59E-01
+       EARTH 2073/07/28.99945  78416.999445476 4.134085496E+01  1.111470366103266E-01  5.003166947385704E-04  2.256191830393957E-02 2.299E-02 1.738E-06 1.00E+00
+       EARTH 2080/05/09.86555  80893.865553408 1.510375304E+01  8.774532653495520E-02  3.493371274421791E-04  1.867984695424074E-02 1.877E-02 6.089E-07 1.00E+00
+       EARTH 2087/04/07.41753  83417.417534460 1.281273021E+00  9.700408503312648E-02  3.679937980725016E-04  1.703669775347181E-02 1.704E-02 2.208E-08 1.00E+00
+       EARTH 2102/09/11.38548  89052.385483667 9.035828417E+00  2.504853278527303E-02  2.258010787654003E-02  3.752172278286164E-02 8.510E-02 1.194E-06 7.79E-01
+       EARTH 2109/03/16.92116  91430.921161248 3.929708006E+02  1.859036567263480E-01  8.783217764661589E-04  3.721212974856785E-01 3.756E-01 1.259E-06 1.76E-01
+       EARTH 2109/06/12.89673  91518.896729589 3.568796140E+02  1.219770789077581E-01  8.785890137851331E-04  9.428109723075997E-02 1.071E-01 1.170E-06 5.96E-01
+       EARTH 2116/04/08.82352  94010.823518922 5.092949159E+01  7.329363885687520E-02  9.454623383366076E-04  8.561662450268580E-01 8.562E-01 9.528E-08 7.79E-02
+       EARTH 2124/09/21.39888  97098.398881126 1.800815656E+01  1.519300298088186E-01  2.235834685675346E-02  3.240889706417077E-01 3.276E-01 1.157E-06 2.02E-01
+       EARTH 2131/07/29.04172  99600.041719017 1.207843948E+02  1.134629762852619E-01  1.147734261896822E-03  7.045272883453099E-02 7.171E-02 1.700E-06 7.03E-01
+       EARTH 2138/04/15.97238 102052.972375796 7.392663714E+01  1.085824441995005E-02  1.103191027950315E-03  6.514489696600129E-01 6.546E-01 3.041E-08 1.02E-01
+       EARTH 2145/04/27.20137 104621.201370571 7.440129704E+03  6.274213916785724E-02  9.585526187721039E-04  1.910632513797471E+01 1.912E+01 2.458E-07 3.49E-03
diff --git a/astroquery/esa/neocc/test/data/99942.eph b/astroquery/esa/neocc/test/data/99942.eph
new file mode 100755
index 0000000000..07895c6547
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/99942.eph
@@ -0,0 +1,25 @@
+Ephemerides generation for: 99942 Apophis
+Observatory: 500 - Geocentric
+Initial Date: 2019/05/08 01:30 UTC
+Final Date: 2019/05/23 00:00 UTC
+Time step: 1 days
+                                     Equatorial coordinates                                                                                         App. motion                           Sky plane error     
+    Date      Hour      MJD            RA            DEC       Mag    Alt  Airmass   Sun elev.   SolEl  LunEl  Phase Glat  Glon     R     Delta   RA*cosDE     DEC       Vel    PA       Err1     Err2   AngAx 
+             (UTC)     (UTC)        (h  m  s)     (d  '  ")          (deg)             (deg)     (deg)  (deg)  (deg) (deg) (deg)   (au)    (au)   ("/min)   ("/min)    ("/min) (deg)                     (deg) 
+ =========== ====== ============  =============  ============ ====== ===== ======== =========== ====== ====== ====== ===== ===== ======= =======  ========  ========  ======== =====  ========  ======== ======
+  8 May 2019  1.500 58611.062500    6 43 40.509  +20 47  1.20  21.58   0.0    INF      0.0       -53.3  -14.8   47.4   7.7 193.5   1.098   1.346    2.1406   -0.0992    2.1429  92.7    0.001"    0.000" 115.9
+  9 May 2019  1.500 58612.062500    6 47 20.055  +20 44 29.55  21.58   0.0    INF      0.0       -53.2   -2.4   47.3   8.4 193.9   1.098   1.349    2.1359   -0.1114    2.1389  93.0    0.001"    0.000" 117.5
+ 10 May 2019  1.500 58613.062500    6 50 59.059  +20 41 40.35  21.58   0.0    INF      0.0       -53.1   11.3   47.3   9.2 194.3   1.099   1.352    2.1313   -0.1235    2.1349  93.3    0.001"    0.000" 119.1
+ 11 May 2019  1.500 58614.062500    6 54 37.517  +20 38 33.74  21.58   0.0    INF      0.0       -53.0   24.4   47.2   9.9 194.7   1.099   1.355    2.1267   -0.1356    2.1310  93.6    0.001"    0.000" 120.9
+ 12 May 2019  1.500 58615.062500    6 58 15.428  +20 35  9.86  21.59   0.0    INF      0.0       -52.9   37.6   47.1  10.7 195.1   1.099   1.358    2.1221   -0.1475    2.1273  94.0    0.001"    0.000" 122.9
+ 13 May 2019  1.500 58616.062500    7  1 52.788  +20 31 28.87  21.59   0.0    INF      0.0       -52.7   51.0   47.0  11.4 195.6   1.099   1.361    2.1176   -0.1594    2.1236  94.3    0.001"    0.000" 125.2
+ 14 May 2019  1.500 58617.062500    7  5 29.596  +20 27 30.91  21.59   0.0    INF      0.0       -52.6   64.4   46.9  12.2 196.0   1.099   1.363    2.1131   -0.1711    2.1201  94.6    0.001"    0.000" 127.6
+ 15 May 2019  1.500 58618.062500    7  9  5.851  +20 23 16.13  21.59   0.0    INF      0.0       -52.5   77.8   46.9  12.9 196.4   1.098   1.366    2.1087   -0.1827    2.1166  95.0    0.001"    0.000" 130.4
+ 16 May 2019  1.500 58619.062500    7 12 41.554  +20 18 44.67  21.60   0.0    INF      0.0       -52.4   91.1   46.8  13.6 196.8   1.098   1.369    2.1044   -0.1942    2.1133  95.3    0.001"    0.000" 133.4
+ 17 May 2019  1.500 58620.062500    7 16 16.707  +20 13 56.69  21.60   0.0    INF      0.0       -52.3  104.4   46.7  14.4 197.3   1.098   1.372    2.1001   -0.2057    2.1101  95.6    0.001"    0.000" 136.7
+ 18 May 2019  1.500 58621.062500    7 19 51.312  +20  8 52.34  21.60   0.0    INF      0.0       -52.1  117.5   46.6  15.1 197.7   1.098   1.374    2.0959   -0.2170    2.1071  95.9    0.001"    0.000" 140.2
+ 19 May 2019  1.500 58622.062500    7 23 25.375  +20  3 31.76  21.60   0.0    INF      0.0       -52.0  130.3   46.6  15.8 198.1   1.098   1.377    2.0918   -0.2282    2.1042  96.2    0.001"    0.000" 143.9
+ 20 May 2019  1.500 58623.062500    7 26 58.899  +19 57 55.11  21.60   0.0    INF      0.0       -51.9  142.9   46.5  16.6 198.6   1.097   1.379    2.0878   -0.2393    2.1015  96.5    0.001"    0.000" 147.7
+ 21 May 2019  1.500 58624.062500    7 30 31.891  +19 52  2.53  21.60   0.0    INF      0.0       -51.8  155.1   46.4  17.3 199.0   1.097   1.382    2.0839   -0.2503    2.0989  96.8    0.001"    0.000" 151.5
+ 22 May 2019  1.500 58625.062500    7 34  4.356  +19 45 54.16  21.60   0.0    INF      0.0       -51.7  166.9   46.4  18.0 199.5   1.096   1.384    2.0801   -0.2612    2.0965  97.2    0.001"    0.001" 155.2
+
diff --git a/astroquery/esa/neocc/test/data/99942.eq1 b/astroquery/esa/neocc/test/data/99942.eq1
new file mode 100644
index 0000000000..c872afff57
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/99942.eq1
@@ -0,0 +1,37 @@
+format  = 'OEF2.0'       ! file format
+rectype = 'ML'           ! record type (1L/ML)
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+99942
+! Equinoctial elements: a, e*sin(LP), e*cos(LP), tan(i/2)*sin(LN), tan(i/2)*cos(LN), mean long.
+ EQU   9.2269886736945861E-01  -0.094103271182575   0.166706101213236   -0.011838547993563   -0.026632739873978  303.802464147110
+ MJD     59400.000000000 TDT
+ MAG  18.937  0.150
+! Non-gravitational parameters: model used, number of model parameters, dimension, list of solve for parameters to be currently determined
+ LSP   1  2    7    2
+! Vector of dynamical parameters
+! Area-to-mass ratio [m^2/t], Yarkovsky parameter [1E-10 au/day^2]
+ NGR   0.00000000000000E+00 -2.90058798774592E-04
+! RMS    8.56356E-11   2.21962E-09   2.75210E-09   3.12732E-09   2.86935E-09   3.80494E-07   2.35576E-06
+! EIG   1.37295E-12   7.11566E-11   4.33176E-10   1.03595E-09   2.45426E-09   3.46755E-07   2.36097E-06
+! WEA   0.00003  -0.00070  -0.00080  -0.00072   0.00073   0.06709   0.99775
+ COV   7.333454159870582E-21 -1.430518484330030E-19 -2.039563818903334E-19
+ COV  -3.113017211144542E-20  5.375862875480088E-20 -2.053004405199749E-18
+ COV   1.597275681844029E-16  4.926698413567482E-18  5.740286393645988E-18
+ COV   4.271352667122275E-18 -4.594913504072475E-18 -4.472180769915471E-16
+ COV  -3.874443567424468E-15  7.574047815870473E-18  3.291875056941473E-18
+ COV  -3.803341554265734E-18 -2.749179586767622E-16 -4.432741010457999E-15
+ COV   9.780145636066158E-18 -8.803880830027464E-18 -1.124690148114898E-15
+ COV  -3.965436364575741E-15  8.233161784253548E-18  1.021614851189196E-15
+ COV   4.019571373629789E-15  1.447755566503557E-13  3.650738081562956E-13
+ COV   5.549616302269251E-12
+ NOR   5.300622209741479E+23 -2.290711161909014E+21  9.835548513140526E+21
+ NOR  -5.004324032792368E+21 -1.040631488603072E+22  7.957817262570576E+19
+ NOR  -1.027271939437066E+19  8.702458079894510E+19 -8.435995468610375E+19
+ NOR   6.934792805283755E+19  1.152480782675332E+20 -3.145636874337803E+17
+ NOR   4.607554623635341E+16  2.055868586315818E+20 -1.182917694090721E+20
+ NOR  -2.303667476832532E+20  1.458526187349774E+18 -1.913853825851189E+17
+ NOR   8.063490248071409E+19  1.457592239415370E+20 -7.308524987979255E+17
+ NOR   9.808505855283288E+16  2.747456151627550E+20 -1.547055040491858E+18
+ NOR   2.028915058610565E+17  1.205524768491713E+16 -1.539750505396746E+15
+ NOR   1.995683028222035E+14
diff --git a/astroquery/esa/neocc/test/data/99942.ke1 b/astroquery/esa/neocc/test/data/99942.ke1
new file mode 100644
index 0000000000..75c13ccd46
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/99942.ke1
@@ -0,0 +1,45 @@
+format  = 'OEF2.0'       ! file format
+rectype = 'ML'           ! record type (1L/ML)
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+99942
+! Keplerian elements: a, e, i, long. node, arg. peric., mean anomaly
+ KEP   9.2269886736945861E-01   0.191432363588237    3.338871063790  203.965677120949  126.590200404569  333.246586621592
+ MJD     59400.000000000 TDT
+ MAG  18.937  0.150
+! Non-gravitational parameters: model used, number of model parameters, dimension, list of solve for parameters to be currently determined
+ LSP   1  2    7    2
+! Vector of dynamical parameters
+! Area-to-mass ratio [m^2/t], Yarkovsky parameter [1E-10 au/day^2]
+ NGR   0.00000000000000E+00 -2.90058798774592E-04
+! PERIHELION   7.4606444230873448E-01
+! APHELION   1.0993332924301829E+00
+! ANODE   1.7332557402763152E-04
+! DNODE  -1.9943018007442770E-01
+! MOID   5.0131935660823443E-05
+! PERIOD   3.2373407064637291E+02
+! PHA T
+! VINFTY     5.4765991101528
+! U_PAR 0.0
+! ORB_TYPE Aten  
+! RMS    8.56356E-11   1.42117E-09   1.60002E-07   7.87827E-06   8.45885E-06   1.18224E-06   2.35576E-06
+ COV   7.333454159870579E-21 -1.072918182236659E-19 -4.176671692841386E-18
+ COV   9.884855072605854E-17 -1.661415694105944E-16  6.524001427933614E-17
+ COV   1.597275681844029E-16  2.019717867999143E-18  7.453443457573882E-17
+ COV  -2.218919293658890E-15  3.445852238191066E-15 -1.246500258007324E-15
+ COV  -1.955610591737736E-15  2.560049020716497E-14 -1.198456511546948E-12
+ COV   1.308002126865156E-12 -1.641254199121557E-13 -2.361241193577065E-13
+ COV   6.206715888043304E-11 -6.634024155022408E-11  7.109226523616469E-12
+ COV   1.033311074616798E-11  7.155222227180351E-11 -8.205136372599239E-12
+ COV  -1.199513342097129E-11  1.397697202827495E-12  2.027096482959609E-12
+ COV   5.549616302269252E-12
+ COR   1.000000000000000E+00 -8.815906196369117E-01 -3.048259299337061E-01
+ COR   1.465160097316719E-01 -2.293572403303417E-01  6.443965529496013E-01
+ COR   7.917610081315467E-01  1.000000000000000E+00  3.277837856645864E-01
+ COR  -1.981824621243634E-01  2.866419392720229E-01 -7.418916291588850E-01
+ COR  -5.841246695483345E-01  1.000000000000000E+00 -9.507519080434512E-01
+ COR   9.664352144192019E-01 -8.676511795146528E-01 -6.264475742171590E-01
+ COR   9.999999999999998E-01 -9.954846142168732E-01  7.632817375542019E-01
+ COR   5.567608284147103E-01  9.999999999999999E-01 -8.204794201852713E-01
+ COR  -6.019522484657190E-01  1.000000000000000E+00  7.278407944027667E-01
+ COR   1.000000000000000E+00
diff --git a/astroquery/esa/neocc/test/data/99942.phypro b/astroquery/esa/neocc/test/data/99942.phypro
new file mode 100644
index 0000000000..d35274c837
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/99942.phypro
@@ -0,0 +1,35 @@
+Rotation Period,30.56,h,[4]
+Quality,3,-,[4]
+Amplitude,1.0,mag,[4]
+Rotation Direction,RETRO,-,[1]
+Spinvector L,250,deg,[1]
+Spinvector B,-7.50E1,deg,[1]
+Taxonomy,S/Sq,-,[2]
+Taxonomy (all),Sq,Scomp,-,[3]
+Absolute Magnitude (H),18.937,mag,[5]
+Absolute Magnitude (H),19.09,mag,[6]
+Slope Parameter (G),0.15**,mag,[7]
+Slope Parameter (G),0.24,mag,[1]
+Slope Parameter (G),0.15**,mag,[5]
+Albedo,0.285,-,[8]
+Diameter,375,m,[9]
+Color Index Information,0.846,B-V,[10]
+Color Index Information,0.451,V-R,[10]
+Color Index Information,0.362,R-I,[10]
+Sightings,Radar R,-,[11]
+Sightings,Visual S,-,[12]
+
+REFERENCES
+
+[1],EARN,1.) Pravec, P. et al (2014) Icarus 233,48-60. (The tumbling spin state of (99942) Apophis)
+[2],EARN,1.) Perna, D. et al. (2016) Astron. J. 151, 11(14p). (GRASPING THE NATURE OF POTENTIALLY HAZARDOUS ASTEROIDS) (spectra of 14 PHAs)
+[3],EARN,1.) Binzel, R.P. et al. (2009) Icarus 200, 480-485. (Spectral properties and composition of potentially hazardous Asteroid (99942) Apophis) 2.) DeMeo, F.E. et al. (2014) Icarus 227, 112-122. (Mars encounters cause fresh surfaces on some near-Earth asteroids) (contains taxonomic classification of 249 NEAs) 3.) Perna, D. et al. (2016) Astron. J. 151, 11(14p). (GRASPING THE NATURE OF POTENTIALLY HAZARDOUS ASTEROIDS) (spectra of 14 PHAs)
+[4],EARN,1.) Pravec, P. et al (2014) Icarus 233,48-60. (The tumbling spin state of (99942) Apophis) 2.) <a href="http://obswww.unige.ch/~behrend/page_cou.html"> R. Behrend Courbes des lumiere, Observatoire de Geneve website</A> 3.) Oey, J. (2014) MPB 41, 276-280. (LIGHTCURVE ANALYSIS OF ASTEROIDS FROM BLUE MOUNTAINS OBSERVATORY IN 2013) (99942,163364,285263)
+[5],ESA ODIM,ESA orbit determination and impact monitoring system
+[6],EARN,1.) Pravec, P. et al (2014) Icarus 233,48-60. (The tumbling spin state of (99942) Apophis) 2.) Delbo, M. et al. (2007) Icarus 188,266-269. (Albedo and size determination of potentially hazardous asteroids: (99942) Apophis)
+[7],NEODyS,NEO Dynamic Site: https://newton.spacedys.com/neodys2
+[8],EARN,1.) Licandro, J. et al. (2016) Astron. Astrophys. 585, A10. (GTC/CanariCam observations of (99942) Apophis) 2.) Mueller, T.G. et al. (2014) Astron. Astrophys. 566, A22. (Thermal Infrared Observations of Asteroid (99942) Apophis with Herschel) 3.) Mueller, T. et al. (2013) <a href="http://www.esa.int/Our_Activities/Space_Science/Herschel_intercepts_asteroid_Apophis"> New Size and Albedo for Apophis from IR Data obtained with Herschel Space Telescope</A> 4.) Delbo, M. et al. (2007) Icarus 188,266-269. (Albedo and size determination of potentially hazardous asteroids: (99942) Apophis) 5.) Licandro, J. et al. (2016) Astron. Astrophys. 585, A10. (GTC/CanariCam observations of (99942) Apophis)
+[9],EARN,1.) Licandro, J. et al. (2016) Astron. Astrophys. 585, A10. (GTC/CanariCam observations of (99942) Apophis) 2.) Mueller, T.G. et al. (2014) Astron. Astrophys. 566, A22. (Thermal Infrared Observations of Asteroid (99942) Apophis with Herschel) 3.) Mueller, T. et al. (2013) <a href="http://www.esa.int/Our_Activities/Space_Science/Herschel_intercepts_asteroid_Apophis"> New Size and Albedo for Apophis from IR Data obtained with Herschel Space Telescope</A> 4.) Delbo, M. et al. (2007) Icarus 188,266-269. (Albedo and size determination of potentially hazardous asteroids: (99942) Apophis)
+[10],EARN,1.) Lin, C-H. et al. (2018) P&SS 152, 116-135. (Photometric survey and taxonomic identifications of 92 near-Earth asteroids)
+[11],EARN,1.) <a href="http://echo.jpl.nasa.gov/asteroids/index.html">JPL's NEO Radar Detection Program Webpage</A> 2.) Ostro, S.J. et al. (2005) I.A.U. Circ. <A HREF="http://www.cbat.eps.harvard.edu/iauc/08400/08477.html"><B> 8477.</B></A> (2004 MN_4) Radar observations) 3.) Giorgini, J.D. et al. (2005) I.A.U. Circ. <A HREF="http://www.cbat.eps.harvard.edu/iauc/08500/08593.html"><B> 8593.</B></A> (99942 Apophis) (radar observations and orbital improvement) 4.) Benner, L.A.M. et al. (2006) I.A.U. Circ.  <A HREF="http://www.cbat.eps.harvard.edu/iauc/08700/08711.html"><B> 8711.</B></A> ((99942) APOPHIS) (radar observations and orbital improvement)
+[12],EARN,1.) Binzel, R.P. et al. (2004) Meteorit. Planet. Sci. 39, 351-366. (Dynamical and compositional assessment of near-Earth object mission targets) (new spectra and taxonomy of 22 NEOs) 2.) Binzel, R.P. et al. (2006) LPSC 37, 1491. (The MIT-Hawaii-IRTF joint campaign for NEO spectral reconnaissance.) 3.) Binzel, R.P. et al. <a href="http://smass.mit.edu/minus.html"> Webpage</A> 4.) Binzel, R.P. et al. (2009) Icarus 200, 480-485. (Spectral properties and composition of potentially hazardous Asteroid (99942) Apophis) 5.) Perna, D. et al. (2016) Astron. J. 151, 11(14p). (GRASPING THE NATURE OF POTENTIALLY HAZARDOUS ASTEROIDS) (spectra of 14 PHAs)
diff --git a/astroquery/esa/neocc/test/data/FOO.rwo b/astroquery/esa/neocc/test/data/FOO.rwo
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/astroquery/esa/neocc/test/data/allnea.csv b/astroquery/esa/neocc/test/data/allnea.csv
new file mode 100755
index 0000000000..b998ed3b1c
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/allnea.csv
@@ -0,0 +1,32339 @@
+NEA
+433 Eros
+719 Albert
+887 Alinda
+1036 Ganymed
+1221 Amor
+1566 Icarus
+1580 Betulia
+1620 Geographos
+1627 Ivar
+1685 Toro
+1862 Apollo
+1863 Antinous
+1864 Daedalus
+1865 Cerberus
+1866 Sisyphus
+1915 Quetzalcoatl
+1916 Boreas
+1917 Cuyo
+1943 Anteros
+1980 Tezcatlipoca
+1981 Midas
+2059 Baboquivari
+2061 Anza
+2062 Aten
+2063 Bacchus
+2100 Ra-Shalom
+2101 Adonis
+2102 Tantalus
+2135 Aristaeus
+2201 Oljato
+2202 Pele
+2212 Hephaistos
+2329 Orthos
+2340 Hathor
+2368 Beltrovata
+2608 Seneca
+3102 Krok
+3103 Eger
+3122 Florence
+3199 Nefertiti
+3200 Phaethon
+3271 Ul
+3288 Seleucus
+3352 McAuliffe
+3360 Syrinx
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+3551 Verenia
+3552 Don Quixote
+3553 Mera
+3554 Amun
+3671 Dionysus
+3691 Bede
+3752 Camillo
+3753 Cruithne
+3757 Anagolay
+3838 Epona
+3908 Nyx
+3988 Huma
+4015 Wilson-Harrington
+4034 Vishnu
+4055 Magellan
+4179 Toutatis
+4183 Cuno
+4197 Morpheus
+4257 Ubasti
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+4596 1981QB
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diff --git a/astroquery/esa/neocc/test/data/allneo.lst b/astroquery/esa/neocc/test/data/allneo.lst
new file mode 100644
index 0000000000..753dada200
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/allneo.lst
@@ -0,0 +1,12 @@
+433       Eros                
+719       Albert              
+887       Alinda              
+1036      Ganymed             
+1221      Amor                
+1566      Icarus
+          2021TL              
+          2021TM              
+          2021TN              
+          2021TO              
+          2021TQ              
+          6344P-L             
diff --git a/astroquery/esa/neocc/test/data/close_encounter2.txt b/astroquery/esa/neocc/test/data/close_encounter2.txt
new file mode 100644
index 0000000000..e968a8c17a
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/close_encounter2.txt
@@ -0,0 +1,6 @@
+Thu Aug 03 13:31:22 UTC 2023
+ Name/desig | Planet | Date             | Time approach   | Time uncert     | Distance              | Minimum distance      | Distance uncertainty  | Width     | Stretch   | Probability | Velocity     | Max Mag
+ DDDDDDDDDD | AAAAA  | YYYY/MM/DD.DDDDD | DDDDD.DDDDDDDDD | E.EEEEEEEEEEEEE | E.EEEEEEEEEEEEEEEEEEE | E.EEEEEEEEEEEEEEEEEEE | E.EEEEEEEEEEEEEEEEEEE | E.EEEEEEE | E.EEEEEEE | E.EEEEEE    | DDD.DDDDDDDD | DDD.DDD
+        433 | EARTH  | 1975/01/23.31853 | 42435.318532550 | 1.260737144E-05 | 1.511341538552550E-01 | 1.511340949471563E-01 | 1.962635286041312E-08 | 1.322E-08 | 6.103E-08 | 1.00E+00    |   5.82530834 |   7.445
+     2002MX | EARTH  | 2002/06/12.08369 | 52437.083685526 | 2.355862863E-04 | 4.148563561205888E-02 | 4.128486992493158E-02 | 6.692189692154938E-05 | 2.634E-07 | 6.692E-05 | 1.00E+00    |  25.57598245 |  17.590
+    2000AA6 | EARTH  | 2054/01/11.31202 | 71278.312017212 | 4.189937108E-05 | 3.820285368375039E-02 | 3.820063181644156E-02 | 7.406233699359970E-07 | 3.635E-08 | 7.571E-07 | 1.00E+00    |  17.16618231 |  18.213
\ No newline at end of file
diff --git a/astroquery/esa/neocc/test/data/esa_faint_neo_list b/astroquery/esa/neocc/test/data/esa_faint_neo_list
new file mode 100644
index 0000000000..ba123dcacc
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/esa_faint_neo_list
@@ -0,0 +1,4 @@
+"2021/10/03"
+0  "2012 BD77"   13800.0  -36.0 120 24.7  1251  "2021/12/26"
+1  "2021 SX3"    83340.0   -6.3 155 22.2     1  "2021/12/12"
+0  "2019 UO10"   84960.0  -37.9 135 24.9  9185  "2021/10/13"
diff --git a/astroquery/esa/neocc/test/data/esa_priority_neo_list b/astroquery/esa/neocc/test/data/esa_priority_neo_list
new file mode 100644
index 0000000000..1c1a280eea
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/esa_priority_neo_list
@@ -0,0 +1,177 @@
+"2021/10/03"
+0  "2013 GM8"     5880.0   35.7 146 21.3 62144  "2021/11/16"
+0  "2013 SU19"   12360.0   -7.2 137 21.3     0  "2021/10/05"
+0  "2014 TM"     81420.0   10.7 149 17.7 99999  "2021/10/10"
+0  "2014 WB363"   8760.0   38.6 138 21.9  1281  "2022/02/12"
+0  "2014 WG498"   2820.0  -20.1 156 21.3  1253  "2022/01/10"
+0  "2017 FL101"   1860.0  -15.2 160 20.9 99999  "2021/10/09"
+0  "2017 VV1"    73020.0  -61.0  98 19.8  7179  "2021/11/16"
+0  "2018 CE1"    85380.0  -14.7 157 21.9  1620  "2021/10/23"
+0  "2018 DC"     12780.0   13.9 136 21.8  3965  "2021/10/30"
+0  "2018 HG2"    85980.0   28.3 154 21.9  2817  "2021/11/02"
+0  "2018 HR3"     5760.0   -8.4 161 21.5 11204  "2021/12/13"
+0  "2019 UY3"    76800.0   32.7 126 20.5 99999  "2021/11/11"
+0  "2021 QJ2"    79080.0  -39.0 123 21.7    12  "2021/10/09"
+0  "2021 RF2"    68400.0   -7.7  95 20.4     0  "2021/10/06"
+0  "2021 RX3"    85020.0   24.6 155 22.0     6  "2021/10/07"
+0  "2021 RE4"      660.0   -2.1 171 21.6    76  "2021/10/12"
+0  "2021 RG4"    86160.0  -12.6 160 21.4   282  "2021/11/05"
+0  "2021 RF5"     2700.0  -44.2 132 20.2     4  "2021/10/16"
+0  "2021 RE10"   81960.0   39.7 136 19.9     6  "2021/10/25"
+0  "2021 RV10"   77160.0  -24.0 125 21.9     1  "2021/10/05"
+0  "2021 RP12"   71820.0  -12.5 108 18.4     1  "2021/10/07"
+0  "2021 RN12"    4200.0  -20.6 154 22.0    56  "2021/10/08"
+0  "2021 RS16"    3000.0  -23.5 152 21.2    28  "2021/12/22"
+0  "2021 RT16"    3600.0  -11.3 164 21.6   373  "2021/11/24"
+0  "2021 RE19"    6480.0  -16.4 153 21.6   102  "2021/11/20"
+0  "2021 RE20"   85440.0   13.7 163 21.8   211  "2021/10/08"
+0  "2021 SJ"     85560.0   36.9 145 21.7    15  "2021/10/09"
+0  "2021 ST"      5760.0   13.9 163 18.4     0  "2021/10/10"
+0  "2021 SF1"     6420.0   20.1 157 20.2     1  "2021/10/18"
+0  "2021 SH1"    80100.0    4.2 144 21.7     6  "2021/10/08"
+0  "2021 SM1"     2280.0   17.4 167 19.9     1  "2021/10/19"
+0  "2021 SL1"    83820.0   29.6 148 21.0     5  "2021/10/20"
+0  "2021 SN1"    84480.0   17.5 158 19.8     2  "2021/10/28"
+0  "2021 SV1"    73440.0  -48.0 104 20.4    28  "2021/10/05"
+0  "2021 SY1"    82800.0   -4.8 154 20.2     9  "2021/10/27"
+0  "2021 SB2"     3780.0   -2.1 171 21.3     6  "2021/10/08"
+0  "2021 SC2"     1560.0   -1.4 174 20.2    16  "2021/10/14"
+0  "2021 SD2"    79920.0   23.6 140 20.1     5  "2021/10/09"
+0  "2021 SP2"    12780.0   23.7 134 21.2     5  "2021/10/11"
+0  "2021 SW2"     1380.0   -3.9 171 21.9     1  "2021/10/05"
+0  "2021 SF3"     5460.0   -9.8 161 20.6     8  "2021/11/02"
+0  "2021 SE3"    86220.0   15.8 165 21.6   111  "2021/10/18"
+0  "2021 SD3"    84180.0   -7.2 158 21.3     5  "2021/10/11"
+0  "2021 SC3"    81600.0    7.9 150 21.6     3  "2021/10/09"
+0  "2021 SM3"    11280.0  -14.1 139 19.7     3  "2021/10/19"
+0  "2021 SY3"    83220.0   19.1 153 20.7     1  "2021/10/08"
+1  "2019 GY19"   15180.0   26.3 124 21.6   214  "2022/02/11"
+1  "2019 RU3"    15300.0  -12.7 124 18.6     0  "2021/10/30"
+1  "2020 BS8"     9960.0  -34.4 131 21.8   109  "2021/11/05"
+1  "2021 OC2"     5940.0   54.2 129 21.4   125  "2021/11/11"
+1  "2021 PG10"   24240.0   45.2  92 21.3     4  "2021/10/12"
+1  "2021 PF20"     120.0  -57.9 117 21.7    18  "2021/10/07"
+1  "2021 PJ23"    6960.0  -34.0 138 21.8     1  "2021/10/09"
+1  "2021 RE"      2220.0  -59.2 117 21.5     1  "2021/10/07"
+1  "2021 RY"       660.0   33.6 150 21.3     4  "2021/11/06"
+1  "2021 RB2"    21180.0  -10.4 100 20.4     2  "2021/10/09"
+1  "2021 RM5"    10500.0  -27.9 134 20.6     1  "2021/10/11"
+1  "2021 RX5"    69180.0   74.4  96 21.3     0  "2021/10/08"
+1  "2021 RU9"    62760.0   29.5  76 21.0     1  "2021/10/12"
+1  "2021 RD10"   84300.0  -42.4 130 21.8     1  "2021/10/06"
+1  "2021 RA10"    3480.0   40.4 144 21.6    21  "2021/10/11"
+1  "2021 RK10"    4560.0   -5.8 166 21.7     1  "2021/10/08"
+1  "2021 RQ12"     120.0    3.8 171 21.1     3  "2021/11/01"
+1  "2021 RH14"    4500.0  -23.0 151 21.2     7  "2021/11/22"
+1  "2021 RU14"    9480.0   15.2 149 20.4     1  "2021/10/17"
+1  "2021 RM16"   86040.0   20.5 160 21.3     2  "2021/10/12"
+1  "2021 RV16"   11340.0   -1.7 142 21.3     6  "2021/11/14"
+1  "2021 RH19"   84600.0   12.9 161 20.9     2  "2021/10/19"
+1  "2021 SF"      2220.0  -37.8 138 21.4     1  "2021/10/08"
+1  "2021 SM"      2100.0   16.3 168 20.6     1  "2021/10/18"
+1  "2021 SO"     74940.0   -8.5 121 21.1     0  "2021/10/08"
+1  "2021 RN23"    2820.0  -15.2 160 21.8    13  "2021/10/31"
+1  "2021 SV"     65220.0  -56.5  82 21.2     1  "2021/10/05"
+1  "2021 SU"      2280.0    7.1 177 20.8     1  "2021/10/13"
+1  "2021 SB1"    79380.0   19.8 139 21.4     0  "2021/10/10"
+1  "2021 SE1"    81420.0   17.6 147 19.5     2  "2021/10/25"
+1  "2021 SG1"    82860.0  -36.6 133 21.2     1  "2021/10/10"
+1  "2021 SC1"    10860.0   -8.8 142 21.3     1  "2021/10/30"
+1  "2021 SU1"    77820.0   -5.2 134 21.6     0  "2021/10/06"
+1  "2021 SS1"    80640.0   14.3 145 21.9     4  "2021/10/13"
+1  "2021 SE2"    77520.0    1.0 133 21.4     5  "2021/10/15"
+1  "2021 SG2"    83880.0   -6.8 157 21.4     5  "2021/11/01"
+1  "2021 SH2"      900.0   19.1 164 21.5     3  "2021/11/05"
+1  "2021 SL2"      960.0    9.1 173 21.3     3  "2021/10/15"
+1  "2021 SN2"     5880.0   14.2 162 21.9     2  "2021/11/04"
+1  "2021 SO2"    67920.0   57.1  95 20.6     3  "2021/11/01"
+1  "2021 SR2"    85380.0   38.8 143 20.4     0  "2021/10/11"
+1  "2021 SY2"    10560.0    6.0 146 20.1     3  "2021/10/22"
+1  "2021 SX2"      300.0    7.8 171 20.8     5  "2021/11/11"
+1  "2021 SV2"    86280.0   33.8 149 21.0     2  "2021/11/26"
+1  "2021 SZ2"    11160.0    6.5 143 20.8     1  "2021/10/19"
+1  "2021 SG3"     4080.0   -5.3 168 21.1     3  "2021/10/29"
+1  "2021 SH3"     4320.0  -12.1 162 20.6     2  "2021/10/16"
+1  "2021 SP3"     1260.0   13.4 170 21.2     0  "2021/11/10"
+1  "2021 TC"     78900.0   26.5 135 20.8     1  "2021/10/08"
+1  "2021 TB"     13500.0  -28.0 125 20.1     1  "2021/10/16"
+1  "2021 TD"      6360.0   12.7 161 20.3     1  "2021/10/10"
+1  "2021 TE"     86340.0   32.4 150 20.2     4  "2021/10/27"
+1  "2021 SW3"    84960.0  -10.7 158 21.7     2  "2021/10/07"
+1  "2021 TF"       780.0   -2.2 171 20.7     1  "2021/10/10"
+2  "2014 SH142"   2040.0   -8.0 168 22.0     0  "2021/10/05"
+2  "2014 TX32"   13140.0   39.2 126 19.9    22  "2021/12/30"
+2  "2017 ET22"    7560.0  -18.5 149 21.7     1  "2021/10/12"
+2  "2018 GY1"    84180.0  -43.8 129 21.3     0  "2021/10/17"
+2  "2018 PG22"   70080.0   45.4 102 20.2     0  "2021/10/19"
+2  "2019 DK"     75780.0  -28.3 119 21.8     0  "2021/10/08"
+2  "2021 EO4"    28080.0  -20.3  72 19.5    22  "2022/01/07"
+2  "2021 NU1"    24180.0   14.2  90 20.9     1  "2022/01/02"
+2  "2021 NU5"    11400.0    5.3 142 21.9     0  "2021/10/16"
+2  "2021 PV2"    18060.0   -0.5 114 20.6     2  "2022/01/15"
+2  "2021 PH4"    60180.0  -71.2  77 20.0     1  "2021/10/14"
+2  "2021 PC10"   85740.0  -42.5 132 20.4     1  "2021/11/23"
+2  "2021 QG1"     5460.0   45.4 137 21.5     1  "2021/11/04"
+2  "2021 RD"     83280.0   46.0 134 21.7     1  "2021/10/14"
+2  "2021 RL2"     1620.0   21.8 162 21.9     0  "2021/10/09"
+2  "2021 RM2"    13440.0  -17.8 129 20.9     1  "2021/11/26"
+2  "2021 RT3"    85380.0  -16.1 155 21.6     0  "2021/10/20"
+2  "2021 RF4"     4080.0   -4.3 169 21.4     0  "2021/10/31"
+2  "2021 RP4"    83940.0    2.3 160 21.7     0  "2021/10/08"
+2  "2021 RC10"    3120.0   18.4 166 20.9     0  "2021/10/20"
+2  "2021 RU12"   80100.0   10.1 144 20.4     0  "2021/11/05"
+2  "2021 RK14"    3480.0  -30.9 145 20.6     0  "2021/10/20"
+2  "2021 RR14"    4140.0   -2.0 170 21.1     0  "2021/10/17"
+2  "2021 RD15"   11580.0   29.1 136 20.2     1  "2022/04/22"
+2  "2021 RE15"   77220.0  -15.6 129 21.8     0  "2021/10/10"
+2  "2021 RU19"   77100.0  -29.6 123 21.8     0  "2021/10/11"
+2  "2021 RD20"   85560.0  -29.7 144 20.1     0  "2021/10/23"
+2  "2021 RH26"   82980.0    4.5 156 20.7     1  "2021/11/13"
+2  "2021 SQ2"    17520.0  -35.0 109 20.9     2  "2021/12/25"
+2  "2021 SQ3"     4140.0   13.8 168 21.9     0  "2021/10/23"
+2  "2021 ST3"    83520.0   11.5 157 21.4     2  "2021/11/08"
+2  "2021 SR3"     5100.0    6.8 168 21.8     1  "2022/02/06"
+2  "2021 SS3"     3720.0  -21.4 154 20.6     1  "2021/11/14"
+3  "2012 TJ146"  19260.0   20.7 110 21.3     0  "2021/11/10"
+3  "2016 JG12"    3000.0   30.3 154 20.7     0  "2021/11/20"
+3  "2017 EQ13"   71160.0   25.5 107 20.2     0  "2021/11/10"
+3  "2017 UD45"   67020.0   14.2  91 21.4     0  "2021/11/10"
+3  "2018 PQ23"   64500.0  -34.4  79 20.9     0  "2021/10/31"
+3  "2019 SF6"    83700.0    3.7 159 21.2     0  "2021/10/09"
+3  "2019 UD4"    17700.0   49.1 110 21.1     0  "2021/12/04"
+3  "2020 KW2"    38460.0   66.4  74 20.1     2  "2021/10/21"
+3  "2021 JT5"    11040.0  -33.0 129 21.1     0  "2021/11/06"
+3  "2021 JG7"    76800.0   -3.5 130 21.3     0  "2021/10/18"
+3  "2021 KK"      1200.0    9.6 173 21.0     0  "2021/10/18"
+3  "2021 NY1"    16920.0  -12.5 117 18.0     0  "2021/12/12"
+3  "2021 ND2"    17280.0   16.8 118 20.6     0  "2021/12/19"
+3  "2021 NT3"     3000.0  -27.7 148 20.6     0  "2021/11/05"
+3  "2021 LQ24"    6480.0   39.0 142 17.4     0  "2022/01/30"
+3  "2021 PB"     12420.0  -25.3 130 21.5     0  "2021/10/30"
+3  "2021 PA2"    18780.0   30.8 111 18.2     0  "2022/04/11"
+3  "2021 PF2"    10920.0   30.7 137 20.1     0  "2021/11/27"
+3  "2021 PR2"     6300.0  -14.8 155 18.7     0  "2021/12/01"
+3  "2021 OC5"    30780.0   25.0  66 20.2     4  "2021/10/29"
+3  "2021 PE10"   77040.0    1.2 131 19.3     0  "2021/12/18"
+3  "2021 PA24"   63840.0   22.2  79 21.1     0  "2022/02/19"
+3  "2021 QP1"    11400.0   27.8 137 21.4     0  "2021/11/30"
+3  "2021 QR1"    83940.0  -48.4 125 19.8     0  "2021/11/20"
+3  "2021 QB3"     8640.0  -20.4 144 20.8     0  "2021/10/25"
+3  "2021 QN3"     3600.0  -40.3 135 19.7     0  "2021/12/20"
+3  "2021 QF5"    84540.0   22.8 155 18.6     0  "2021/11/08"
+3  "2021 RL"      5940.0   47.4 135 19.9     0  "2022/02/09"
+3  "2021 RT"      9300.0  -17.6 144 21.4     0  "2021/10/18"
+3  "2021 RR"      4860.0   17.1 163 21.2     0  "2021/10/29"
+3  "2021 QJ6"    16680.0  -13.2 118 19.9     0  "2022/01/03"
+3  "2021 RZ"      1740.0   42.0 142 20.1     0  "2021/11/07"
+3  "2021 RE1"     4260.0   20.0 162 19.8     0  "2021/12/03"
+3  "2021 RJ2"    80280.0   15.4 144 21.2     0  "2021/10/25"
+3  "2021 RE5"     5820.0   32.6 149 20.6     0  "2022/02/04"
+3  "2021 RV5"    83640.0  -34.3 137 20.4     1  "2021/10/30"
+3  "2021 RO9"    74940.0   18.8 122 20.6     0  "2022/03/09"
+3  "2021 RP14"   76020.0   -2.6 127 21.6     0  "2021/10/19"
+3  "2021 RB15"    9660.0   33.6 139 21.0     1  "2021/11/26"
+3  "2021 RL22"   12300.0  -30.8 127 21.0     1  "2022/04/18"
+3  "2021 QO42"    3360.0   12.3 171 21.0     0  "2021/10/25"
+3  "2021 SJ1"    78720.0   19.5 136 21.5     1  "2022/01/02"
+3  "2021 NN50"   71880.0  -11.8 108 21.2     0  "2021/11/20"
diff --git a/astroquery/esa/neocc/test/data/esa_recent_close_app b/astroquery/esa/neocc/test/data/esa_recent_close_app
new file mode 100644
index 0000000000..abe95cd0fa
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/esa_recent_close_app
@@ -0,0 +1,64 @@
+Last Update: 2023-08-03 13:44 UTC
+            Object         |            |   Miss Distance             |     Diameter     |  H   | Max bright | Rel. vel | CAI index  |
+ Num/des.       Name       | Date       |    km   |    au    |   LD   |   m    |  *=Yes  | mag  |   mag      | km/s     |            |
+AAAAAAAAA AAAAAAAAAAAAAAAA | YYYY-MM-DD | DDDDDDD | D.DDDDDD | DD.DDD | NNNN   |   A     | DD.D |   DDD.D    | DD.D     | DDD.DDD    |
+2023OY4                    | 2023-08-02 | 1219027 | 0.008149 |  3.171 |   30   |   *     | 25.4 |    18.1    | 17.6     |   1.794    |
+2023OF1                    | 2023-08-02 | 6799453 | 0.045452 | 17.689 |   40   |   *     | 24.9 |    20.2    | 10.7     |   2.759    |
+2023OS3                    | 2023-08-01 |  962092 | 0.006431 |  2.503 |   10   |   *     | 27.8 |    19.2    |  4.8     |   2.490    |
+2023OD5                    | 2023-08-01 | 5306579 | 0.035472 | 13.805 |   50   |   *     | 24.2 |    18.7    | 18.2     |   2.259    |
+2023OQ3                    | 2023-08-01 | 1506226 | 0.010068 |  3.918 |   30   |   *     | 25.0 |    16.8    |  9.8     |   1.539    |
+2016AW65                   | 2023-07-31 | 6394033 | 0.042741 | 16.634 |   50   |   *     | 24.4 |    19.8    |  5.7     |   2.003    |
+2023OQ2                    | 2023-07-30 | 1569469 | 0.010491 |  4.083 |   12   |   *     | 27.3 |    18.0    |  3.8     |   2.422    |
+2021BD3                    | 2023-07-30 | 5303064 | 0.035449 | 13.796 |   25   |   *     | 25.7 |    22.6    |  8.5     |   2.996    |
+2020PP1                    | 2023-07-29 | 6526534 | 0.043627 | 16.979 |   16   |   *     | 26.8 |    22.2    |  4.1     |   3.348    |
+2023OY3                    | 2023-07-29 | 5535971 | 0.037006 | 14.402 |   24   |   *     | 25.8 |    20.3    | 10.6     |   3.201    |
+2018BG5                    | 2023-07-27 | 4124499 | 0.027571 | 10.730 |   60   |   *     | 24.0 |    19.6    |  8.4     |   1.631    |
+2023OR1                    | 2023-07-27 | 1196243 | 0.007996 |  3.112 |   18   |   *     | 26.4 |    19.1    | 11.4     |   2.311    |
+2015MA54                   | 2023-07-26 | 6303693 | 0.042138 | 16.399 |   30   |   *     | 25.3 |    32.6    |  9.2     |   2.922    |
+2023OZ1                    | 2023-07-23 | 6529160 | 0.043645 | 16.985 |  300   |   *     | 20.2 |    17.7    | 22.1     |   1.034    |
+2023OU                     | 2023-07-22 |  672066 | 0.004492 |  1.748 |   21   |   *     | 26.1 |    16.2    |  6.1     |   1.242    |
+2023MM3                    | 2023-07-22 | 7316738 | 0.048909 | 19.034 |   40   |   *     | 24.6 |    19.6    |  6.4     |   2.338    |
+2023NR1                    | 2023-07-22 | 1119351 | 0.007482 |  2.912 |   80   |   *     | 23.3 |    14.8    | 15.2     |   0.414    |
+2023MX5                    | 2023-07-21 | 4561913 | 0.030495 | 11.868 |   60   |   *     | 23.9 |    21.7    | 11.8     |   1.798    |
+2023NM1                    | 2023-07-21 | 5094578 | 0.034055 | 13.253 |   40   |   *     | 25.0 |    19.1    |  8.9     |   2.531    |
+2023OV1                    | 2023-07-21 |  550644 | 0.003681 |  1.432 |   30   |   *     | 25.4 |    16.2    | 13.4     |   1.017    |
+2023OS                     | 2023-07-21 | 1949171 | 0.013029 |  5.071 |   50   |   *     | 24.3 |    17.6    | 10.8     |   1.300    |
+2020OM                     | 2023-07-20 | 3193078 | 0.021344 |  8.307 |   15   |   *     | 26.9 |    19.1    |  9.5     |   3.387    |
+2023NL                     | 2023-07-20 | 7320118 | 0.048932 | 19.043 |   40   |   *     | 24.6 |    19.9    |  5.5     |   2.237    |
+2022GX2                    | 2023-07-20 | 4580796 | 0.030621 | 11.917 |    5   |   *     | 29.3 |    24.9    |  9.4     |   5.118    |
+2023NE1                    | 2023-07-19 | 4880117 | 0.032622 | 12.695 |   60   |   *     | 23.9 |    18.4    |  5.7     |   1.484    |
+2023OA                     | 2023-07-19 | 2361921 | 0.015788 |  6.144 |   18   |   *     | 26.4 |    19.1    |  7.5     |   2.683    |
+2012YJ7                    | 2023-07-19 | 2686889 | 0.017961 |  6.990 |  110   |   *     | 22.5 |    16.2    | 19.3     |   0.923    |
+2023OU3                    | 2023-07-19 |  689408 | 0.004608 |  1.793 |   23   |   *     | 25.9 |    14.7    |  8.3     |   1.343    |
+2020UQ3                    | 2023-07-18 | 1215951 | 0.008128 |  3.163 |   50   |   *     | 24.1 |    17.1    |  9.3     |   0.676    |
+2018AC4                    | 2023-07-18 | 6972657 | 0.046609 | 18.139 |   30   |   *     | 25.4 |    22.0    | 17.1     |   3.305    |
+2023OJ1                    | 2023-07-18 |  535048 | 0.003577 |  1.392 |   21   |   *     | 26.1 |    14.7    |  6.3     |   1.094    |
+2023OD1                    | 2023-07-18 | 3297583 | 0.022043 |  8.579 |   40   |   *     | 24.9 |    19.5    |  8.6     |   2.031    |
+2023OE1                    | 2023-07-17 |  965363 | 0.006453 |  2.511 |   13   |   *     | 27.1 |    19.2    |  6.4     |   2.266    |
+2023MG6                    | 2023-07-16 | 3636775 | 0.024310 |  9.461 |  300   |   *     | 20.3 |    13.9    | 12.4     |   0.412    |
+2023NW                     | 2023-07-16 | 6013710 | 0.040199 | 15.644 |   30   |   *     | 25.2 |    20.9    | 17.1     |   3.031    |
+2023NU1                    | 2023-07-15 | 5095818 | 0.034063 | 13.257 |  120   |   *     | 22.4 |    17.2    | 16.2     |   1.389    |
+2023NY                     | 2023-07-15 | 4426541 | 0.029590 | 11.515 |   13   |   *     | 27.1 |    20.7    |  2.1     |   2.744    |
+2023OY                     | 2023-07-15 | 1622526 | 0.010846 |  4.221 |   12   |   *     | 27.4 |    19.2    | 11.0     |   3.156    |
+2023OX                     | 2023-07-14 | 2935145 | 0.019620 |  7.636 |   29   |   *     | 25.4 |    18.0    |  6.9     |   2.165    |
+2023NP                     | 2023-07-14 | 5006022 | 0.033463 | 13.023 |   21   |   *     | 26.2 |    20.3    |  8.2     |   3.228    |
+2023OZ                     | 2023-07-13 | 2868022 | 0.019172 |  7.461 |   19   |   *     | 26.3 |    19.0    |  5.9     |   2.633    |
+2023NT1                    | 2023-07-13 |  100889 | 0.000674 |  0.262 |   40   |   *     | 25.0 |    10.9    | 11.3     |  -0.736    |
+2023NU                     | 2023-07-12 | 3233474 | 0.021614 |  8.412 |   60   |   *     | 23.8 |    17.9    | 15.7     |   1.566    |
+2018UY                     | 2023-07-12 | 2849115 | 0.019045 |  7.412 |  250   |   *     | 20.8 |    14.7    | 16.4     |   0.408    |
+2023OM                     | 2023-07-12 | 2931936 | 0.019599 |  7.627 |   27   |   *     | 25.6 |    19.2    | 10.7     |   2.503    |
+2023MQ1                    | 2023-07-11 | 4119805 | 0.027539 | 10.718 |   40   |   *     | 25.0 |    17.8    |  6.0     |   2.064    |
+2023NE                     | 2023-07-11 | 4333123 | 0.028965 | 11.272 |   40   |   *     | 24.7 |    18.1    | 12.0     |   2.253    |
+2023MD2                    | 2023-07-11 | 2141329 | 0.014314 |  5.571 |   50   |   *     | 24.4 |    16.6    |  8.4     |   1.289    |
+2023LN1                    | 2023-07-10 | 6854249 | 0.045818 | 17.831 |   60   |   *     | 23.8 |    18.6    |  5.8     |   1.742    |
+2023NN1                    | 2023-07-09 | 2416905 | 0.016156 |  6.287 |   13   |   *     | 27.2 |    18.4    |  4.9     |   2.884    |
+2018NW                     | 2023-07-09 | 3799687 | 0.025399 |  9.885 |   10   |   *     | 27.9 |    23.1    | 21.5     |   4.406    |
+2019LH5                    | 2023-07-07 | 5714136 | 0.038197 | 14.865 |  280   |   *     | 20.5 |    16.4    | 21.6     |   1.012    |
+2023NQ1                    | 2023-07-06 | 7125591 | 0.047632 | 18.537 |   80   |   *     | 23.1 |    18.6    | 22.4     |   2.025    |
+2023LH2                    | 2023-07-06 | 7198099 | 0.048116 | 18.726 |   40   |   *     | 24.7 |    20.8    |  7.9     |   2.514    |
+2023ME4                    | 2023-07-06 | 1134961 | 0.007587 |  2.953 |   30   |   *     | 25.3 |    16.5    | 10.7     |   1.529    |
+2023NK                     | 2023-07-06 | 1484777 | 0.009925 |  3.863 |   13   |   *     | 27.2 |    19.0    |  3.2     |   2.159    |
+2023NO                     | 2023-07-05 |  381473 | 0.002550 |  0.992 |    7   |   *     | 28.7 |    17.9    |  8.0     |   2.545    |
+2023HO6                    | 2023-07-05 | 2045834 | 0.013676 |  5.322 |  220   |   *     | 21.0 |    13.6    |  7.8     |  -0.122    |
+2023MT1                    | 2023-07-03 | 1101987 | 0.007366 |  2.867 |   15   |   *     | 26.9 |    18.1    |  5.2     |   2.055    |
+2023NG1                    | 2023-07-03 |  705381 | 0.004715 |  1.835 |   20   |   *     | 26.3 |    17.6    |  3.8     |   1.071    |
diff --git a/astroquery/esa/neocc/test/data/esa_risk_list b/astroquery/esa/neocc/test/data/esa_risk_list
new file mode 100644
index 0000000000..0d018afe8f
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/esa_risk_list
@@ -0,0 +1,8 @@
+Last Update: 2021-10-04 05:49 UTC
+            Object         |    Diameter    |             VI Max                                   |          VIs                  |
+ Num/des.       Name       |   m  |   *=Y   |      Date/Time   |  IP max  | PS max |TS  | Vel km/s | Years     | IP cum   | PS cum |
+AAAAAAAAA AAAAAAAAAAAAAAAA | NNNN |    A    | YYYY-MM-DD HH:MM | EEEEEEEE | NNN.NN | NN |  NNN.NN  | YYYY-YYYY | EEEEEEEE | NNN.NN |
+2021QM1                    |   50 |    *    | 2052-04-02 01:36 |  2.98E-4 |  -2.72 |  0 |   23.72  | 2050-2054 |  2.98E-4 |  -2.72 |
+2021KQ2                    |    4 |    *    | 2097-05-21 03:05 | 1.26E-11 | -13.71 |  0 |   11.42  | 2097-2097 | 1.26E-11 | -13.71 |
+2013BR15                   |   30 |    *    | 2100-01-02 18:03 |  1.21E-7 |  -7.15 |  0 |   17.98  | 2100-2100 |  1.60E-7 |  -7.03 |
+2019AS5                    |  1.2 |    *    | 2085-01-07 18:20 |  1.19E-9 | -12.65 |  0 |   15.12  | 2085-2111 |  2.80E-9 | -12.32 |
\ No newline at end of file
diff --git a/astroquery/esa/neocc/test/data/esa_special_risk_list b/astroquery/esa/neocc/test/data/esa_special_risk_list
new file mode 100644
index 0000000000..b1b6fa4799
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/esa_special_risk_list
@@ -0,0 +1,6 @@
+Last Update: 2022-08-19 08:03 UTC
+            Object         |    Diameter    |             VI Max                                   |
+ Num/des.       Name       |   m  |   *=Y   |      Date/Time   |  IP max  | PS max |TS  | Vel km/s |
+AAAAAAAAA AAAAAAAAAAAAAAAA | NNNN |    A    | YYYY-MM-DD HH:MM | EEEEEEEE | NNN.NN | NN |  NNN.NN  |
+101955               Bennu |  484 |         | 2182-09-24 20:24 |  3.70E-4 |  -1.59 |    |   12.68  |
+29075               1950DA | 1300 |         | 2880-03-16 23:48 |  1.96E-5 |  -2.13 |    |   17.99  |
diff --git a/astroquery/esa/neocc/test/data/esa_upcoming_close_app b/astroquery/esa/neocc/test/data/esa_upcoming_close_app
new file mode 100644
index 0000000000..2f9a1b397d
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/esa_upcoming_close_app
@@ -0,0 +1,178 @@
+Last Update: 2023-08-03 13:44 UTC
+            Object         |            |   Miss Distance             |     Diameter     |  H   | Max bright | Rel. vel | CAI index  |
+ Num/des.       Name       | Date       |    km   |    au    |   LD   |   m    |  *=Yes  | mag  |   mag      | km/s     |            |
+AAAAAAAAA AAAAAAAAAAAAAAAA | YYYY-MM-DD | DDDDDDD | D.DDDDDD | DD.DDD | NNNN   |   A     | DD.D |   DDD.D    | DD.D     | DDD.DDD    |
+2023OW4                    | 2023-08-03 |  565277 | 0.003779 |  1.471 |   10   |   *     | 27.8 |    18.1    |  9.7     |   2.464    |
+2020PN1                    | 2023-08-03 | 4152623 | 0.027759 | 10.803 |   29   |   *     | 25.5 |    20.0    |  4.8     |   2.244    |
+620082           2014QL433 | 2023-08-04 | 5348781 | 0.035754 | 13.915 |  400   |   *     | 19.9 |    15.8    | 20.6     |   0.767    |
+2023OR5                    | 2023-08-04 | 2849437 | 0.019047 |  7.413 |   30   |   *     | 25.4 |    18.2    |  7.5     |   2.156    |
+2023OQ                     | 2023-08-06 | 3799973 | 0.025401 |  9.885 |  140   |   *     | 22.0 |    16.9    | 21.3     |   1.070    |
+2022BS2                    | 2023-08-11 | 6679311 | 0.044648 | 17.376 |   30   |   *     | 25.4 |    23.6    |  8.2     |   2.954    |
+2023OE5                    | 2023-08-14 | 1544396 | 0.010324 |  4.018 |   18   |   *     | 26.5 |    19.6    |  3.9     |   1.878    |
+2004BH11                   | 2023-08-15 | 2690868 | 0.017987 |  7.000 |   50   |   *     | 24.2 |    18.1    |  8.9     |   1.399    |
+2022CP1                    | 2023-08-17 | 5307971 | 0.035482 | 13.808 |   12   |   *     | 27.4 |    23.5    |  9.8     |   4.117    |
+2011QJ21                   | 2023-08-19 | 5024564 | 0.033587 | 13.071 |   50   |   *     | 24.5 |    19.0    | 15.0     |   2.329    |
+2016RS1                    | 2023-08-20 | 2431843 | 0.016256 |  6.326 |    5   |   *     | 29.1 |    30.3    |  6.4     |   4.243    |
+2009QR                     | 2023-08-21 | 1029005 | 0.006878 |  2.677 |   12   |   *     | 27.3 |    18.3    |  5.2     |   2.310    |
+6037                1988EG | 2023-08-23 | 6081496 | 0.040652 | 15.821 |  400   |         | 18.8 |    15.2    | 14.3     |   0.370    |
+2022CR5                    | 2023-08-29 | 3732229 | 0.024948 |  9.709 |   30   |   *     | 25.2 |    19.6    | 15.2     |   2.612    |
+2012PZ17                   | 2023-08-30 | 6434275 | 0.043010 | 16.739 |   16   |   *     | 26.7 |    22.6    |  3.6     |   3.220    |
+2017BY32                   | 2023-09-03 | 6616102 | 0.044226 | 17.212 |   19   |   *     | 26.4 |    23.1    |  3.4     |   2.992    |
+2007RR17                   | 2023-09-03 | 2340322 | 0.015644 |  6.088 |   70   |   *     | 23.5 |    15.7    |  7.0     |   0.748    |
+2021JA5                    | 2023-09-07 | 5070725 | 0.033896 | 13.191 |   19   |   *     | 26.4 |    22.0    | 11.0     |   3.496    |
+2020GE                     | 2023-09-08 | 5724348 | 0.038265 | 14.892 |    8   |   *     | 28.2 |    25.8    |  1.4     |   3.308    |
+2020RS1                    | 2023-09-10 | 6153200 | 0.041132 | 16.007 |   13   |   *     | 27.1 |    22.8    |  9.1     |   4.071    |
+2020RT2                    | 2023-09-12 | 4197105 | 0.028056 | 10.919 |    8   |   *     | 28.2 |    23.3    | 10.0     |   4.496    |
+2016LY48                   | 2023-09-16 | 1926156 | 0.012876 |  5.011 |  100   |   *     | 22.8 |    16.9    | 10.8     |   0.526    |
+2010TE                     | 2023-09-16 | 2643366 | 0.017670 |  6.877 |   22   |   *     | 26.0 |    19.3    |  5.9     |   2.356    |
+2014HD198                  | 2023-09-19 | 4711742 | 0.031496 | 12.257 |    4   |   *     | 29.6 |    25.8    | 16.0     |   5.499    |
+2004SW26                   | 2023-09-19 | 7282143 | 0.048678 | 18.944 |   26   |   *     | 25.7 |    20.7    | 11.2     |   3.373    |
+2019SF6                    | 2023-09-26 | 6402302 | 0.042797 | 16.655 |   20   |   *     | 26.2 |    21.0    |  8.6     |   3.492    |
+2013TG6                    | 2023-09-28 | 1365997 | 0.009131 |  3.554 |   18   |   *     | 26.5 |    18.8    |  4.1     |   1.865    |
+2009UG                     | 2023-09-30 | 2349186 | 0.015703 |  6.111 |   80   |   *     | 23.3 |    15.8    |  9.0     |   0.832    |
+2019US                     | 2023-10-02 | 7279377 | 0.048660 | 18.937 |   17   |   *     | 26.6 |    24.1    |  5.9     |   3.630    |
+349507              2008QY | 2023-10-03 | 6324897 | 0.042279 | 16.454 |  700   |   *     | 18.5 |    15.8    | 21.0     |   0.409    |
+2009VT1                    | 2023-10-04 | 2934786 | 0.019618 |  7.635 |    4   |   *     | 29.6 |    22.6    |  7.7     |   4.730    |
+2022TD                     | 2023-10-07 | 3396240 | 0.022702 |  8.835 |   10   |   *     | 27.8 |    22.2    |  9.4     |   3.982    |
+2018ER1                    | 2023-10-08 | 4797938 | 0.032072 | 12.482 |   25   |   *     | 25.7 |    22.0    |  5.3     |   2.612    |
+2022UX1                    | 2023-10-11 | 1155740 | 0.007726 |  3.007 |    9   |   *     | 28.0 |    20.2    |  8.6     |   3.156    |
+2015KW120                  | 2023-10-12 | 6969216 | 0.046586 | 18.130 |   22   |   *     | 26.0 |    22.2    | 13.0     |   3.628    |
+2015XM169                  | 2023-10-12 | 5127112 | 0.034273 | 13.338 |   23   |   *     | 25.9 |    20.8    |  6.7     |   2.949    |
+2021NT14                   | 2023-10-13 | 7126369 | 0.047637 | 18.539 |  250   |   *     | 20.8 |    18.6    |  8.6     |   0.950    |
+2011GA                     | 2023-10-15 | 2607793 | 0.017432 |  6.784 |  230   |   *     | 20.9 |    15.0    | 16.6     |   0.388    |
+2007SQ6                    | 2023-10-15 | 7414727 | 0.049564 | 19.289 |  140   |   *     | 22.0 |    17.5    |  6.5     |   1.141    |
+2019UZ3                    | 2023-10-16 | 3832824 | 0.025621 |  9.971 |   14   |   *     | 27.0 |    21.9    |  8.3     |   3.519    |
+1998HH49                   | 2023-10-17 | 1173409 | 0.007844 |  3.053 |  190   |   *     | 21.3 |    13.0    | 14.8     |  -0.232    |
+2016WM7                    | 2023-10-18 | 6737897 | 0.045040 | 17.528 |   22   |   *     | 26.0 |    22.0    |  4.6     |   3.000    |
+2022UO10                   | 2023-10-19 | 2964278 | 0.019815 |  7.711 |   16   |   *     | 26.8 |    19.7    |  9.8     |   3.230    |
+2020UR                     | 2023-10-20 | 2129300 | 0.014233 |  5.539 |    9   |   *     | 27.9 |    20.8    | 12.9     |   3.776    |
+2013UR1                    | 2023-10-22 | 1598987 | 0.010689 |  4.160 |   10   |   *     | 27.8 |    20.3    | 21.9     |   3.610    |
+2020FM6                    | 2023-10-23 | 5873851 | 0.039264 | 15.281 |  150   |   *     | 21.9 |    18.2    | 15.9     |   1.355    |
+2019HH4                    | 2023-10-24 | 5079887 | 0.033957 | 13.215 |  400   |   *     | 19.9 |    17.8    | 20.0     |   0.718    |
+2014HB192                  | 2023-10-25 | 3085498 | 0.020625 |  8.027 |   20   |   *     | 26.2 |    20.1    | 20.7     |   3.170    |
+2021SZ4                    | 2023-10-26 | 5349193 | 0.035757 | 13.916 |  290   |   *     | 20.4 |    15.3    | 30.0     |   0.976    |
+302169            2001TD45 | 2023-10-26 | 4874503 | 0.032584 | 12.681 |  400   |   *     | 19.8 |    15.0    | 25.7     |   0.673    |
+2019UW6                    | 2023-10-29 | 5061397 | 0.033833 | 13.167 |   17   |   *     | 26.6 |    21.4    | 10.8     |   3.670    |
+525229             2004UU1 | 2023-10-30 | 4076984 | 0.027253 | 10.606 |  210   |   *     | 21.2 |    14.0    | 17.4     |   0.849    |
+2013UV3                    | 2023-11-01 | 5617667 | 0.037552 | 14.614 |   15   |   *     | 26.8 |    22.6    | 15.4     |   4.016    |
+2004VZ14                   | 2023-11-02 |  571112 | 0.003818 |  1.486 |   30   |   *     | 25.3 |    15.5    | 15.2     |   1.013    |
+2016WY                     | 2023-11-02 | 3567700 | 0.023849 |  9.281 |    5   |   *     | 29.2 |    25.9    |  4.0     |   4.268    |
+363505            2003UC20 | 2023-11-02 | 5252527 | 0.035111 | 13.664 | 1900   |         | 18.4 |    14.8    |  8.0     |  -0.189    |
+2022JF                     | 2023-11-03 | 6070249 | 0.040577 | 15.792 |   40   |   *     | 24.8 |    20.5    | 17.1     |   2.748    |
+2016VW2                    | 2023-11-03 | 3728671 | 0.024925 |  9.700 |   19   |   *     | 26.3 |    19.6    |  8.0     |   3.042    |
+2019UH7                    | 2023-11-04 | 3808100 | 0.025456 |  9.907 |   11   |   *     | 27.5 |    21.1    |  5.9     |   3.630    |
+2015VD106                  | 2023-11-07 | 2881675 | 0.019263 |  7.497 |   15   |   *     | 26.9 |    19.8    |  8.2     |   3.180    |
+2018VN7                    | 2023-11-07 | 3959274 | 0.026466 | 10.300 |   30   |   *     | 25.4 |    20.1    | 12.9     |   2.726    |
+2010FD6                    | 2023-11-09 | 6957753 | 0.046510 | 18.100 |    8   |         | 26.8 |    24.2    |  9.4     |   3.993    |
+2014BA3                    | 2023-11-13 | 6017100 | 0.040222 | 15.653 |    8   |   *     | 28.2 |    24.4    |  2.7     |   3.914    |
+2021TN3                    | 2023-11-15 | 6526590 | 0.043628 | 16.979 |   30   |   *     | 25.3 |    21.3    |  6.3     |   2.744    |
+2019VL5                    | 2023-11-16 | 3269984 | 0.021858 |  8.507 |   24   |   *     | 25.8 |    20.9    |  8.2     |   2.613    |
+2017WM16                   | 2023-11-18 | 6208437 | 0.041501 | 16.151 |   16   |   *     | 26.8 |    20.5    |  6.0     |   3.588    |
+2019LB1                    | 2023-11-18 | 6032225 | 0.040323 | 15.693 |   14   |   *     | 27.1 |    25.9    |  4.2     |   3.486    |
+2016DK1                    | 2023-11-19 | 1994335 | 0.013331 |  5.188 |   12   |   *     | 27.4 |    21.4    |  6.8     |   3.089    |
+2022VR1                    | 2023-11-19 | 3106186 | 0.020764 |  8.081 |   40   |   *     | 24.8 |    20.4    |  6.1     |   1.742    |
+2021WB2                    | 2023-11-19 | 3852429 | 0.025752 | 10.022 |   40   |   *     | 24.5 |    18.8    | 16.5     |   2.153    |
+2019UT6                    | 2023-11-24 | 3462470 | 0.023145 |  9.007 |  140   |   *     | 22.1 |    16.9    | 13.2     |   0.880    |
+2019CZ2                    | 2023-11-26 | 1194344 | 0.007984 |  3.107 |   40   |   *     | 24.6 |    18.5    |  5.8     |   0.707    |
+2009EY                     | 2023-11-26 | 5980302 | 0.039976 | 15.558 |   18   |   *     | 26.5 |    24.2    |  9.7     |   3.673    |
+2013UB3                    | 2023-11-27 | 7090437 | 0.047397 | 18.446 |   25   |   *     | 25.7 |    21.7    |  5.4     |   2.978    |
+2012XN134                  | 2023-12-02 | 4181857 | 0.027954 | 10.879 |   10   |   *     | 27.8 |    22.4    |  7.0     |   4.012    |
+1998WB2                    | 2023-12-03 | 4211416 | 0.028152 | 10.956 |  150   |         | 22.1 |    16.6    | 14.2     |   0.984    |
+2013VX4                    | 2023-12-04 | 1957557 | 0.013085 |  5.093 |   60   |   *     | 23.9 |    19.8    |  6.6     |   0.768    |
+139622           2001QQ142 | 2023-12-06 | 5526890 | 0.036945 | 14.378 |  700   |   *     | 18.4 |    14.2    |  6.7     |  -0.234    |
+2020XC3                    | 2023-12-09 | 6881983 | 0.046003 | 17.903 |  110   |   *     | 22.5 |    17.4    | 14.5     |   1.663    |
+2020HX3                    | 2023-12-10 | 3573941 | 0.023890 |  9.297 |   13   |   *     | 27.2 |    21.8    | 15.7     |   3.860    |
+2010XF3                    | 2023-12-11 | 7377915 | 0.049318 | 19.193 |   50   |   *     | 24.3 |    19.1    |  4.0     |   1.828    |
+2017YL1                    | 2023-12-18 | 4981770 | 0.033301 | 12.960 |   40   |   *     | 24.8 |    20.5    | 14.0     |   2.549    |
+2016XD2                    | 2023-12-19 | 7129621 | 0.047659 | 18.547 |   60   |   *     | 23.9 |    18.7    |  6.9     |   1.931    |
+341843             2008EV5 | 2023-12-20 | 6320816 | 0.042252 | 16.443 |  370   |         | 20.0 |    15.9    |  5.3     |   0.318    |
+2018YJ2                    | 2023-12-21 | 7027907 | 0.046979 | 18.283 |  160   |   *     | 21.8 |    18.9    | 13.1     |   1.398    |
+2022YG                     | 2023-12-22 | 4189250 | 0.028003 | 10.898 |   17   |   *     | 26.6 |    21.8    |  5.1     |   3.039    |
+2020YO3                    | 2023-12-23 |  347782 | 0.002325 |  0.905 |   40   |   *     | 24.7 |    13.4    | 16.5     |   0.195    |
+2010UE51                   | 2023-12-24 | 3428332 | 0.022917 |  8.919 |    8   |   *     | 28.3 |    22.4    |  1.3     |   2.904    |
+2020KT4                    | 2023-12-25 | 4635942 | 0.030989 | 12.060 |   80   |   *     | 23.3 |    18.4    |  7.5     |   1.304    |
+2020YR2                    | 2023-12-25 | 5204753 | 0.034792 | 13.540 |    8   |   *     | 28.3 |    23.6    |  8.0     |   4.606    |
+2021AM6                    | 2023-12-31 | 7019738 | 0.046924 | 18.262 |   17   |   *     | 26.6 |    24.3    |  6.6     |   3.643    |
+2019KK5                    | 2024-01-02 | 3893613 | 0.026027 | 10.129 |   90   |   *     | 23.0 |    17.6    | 20.8     |   1.433    |
+2019PJ                     | 2024-01-07 | 2532076 | 0.016926 |  6.587 |   60   |   *     | 23.9 |    17.3    | 14.1     |   1.360    |
+2002AY1                    | 2024-01-08 | 5802186 | 0.038785 | 15.094 |  260   |   *     | 20.6 |    16.1    | 17.3     |   1.011    |
+2020AC1                    | 2024-01-11 | 7467878 | 0.049920 | 19.427 |    7   |   *     | 28.4 |    23.8    |  5.3     |   4.725    |
+2015BW512                  | 2024-01-12 | 4051984 | 0.027086 | 10.541 |   30   |   *     | 25.2 |    24.7    |  8.7     |   2.427    |
+2021CZ2                    | 2024-01-16 | 3393813 | 0.022686 |  8.829 |  110   |   *     | 22.5 |    16.5    | 14.3     |   1.026    |
+2015AK1                    | 2024-01-19 | 2071235 | 0.013845 |  5.388 |   50   |   *     | 24.2 |    17.6    | 12.1     |   1.307    |
+2019BU1                    | 2024-01-21 | 1142214 | 0.007635 |  2.971 |   20   |   *     | 26.2 |    18.3    | 14.2     |   2.191    |
+2019AX14                   | 2024-01-22 | 5767672 | 0.038555 | 15.004 |   16   |   *     | 26.7 |    22.8    | 15.3     |   3.951    |
+2021BL3                    | 2024-01-23 | 6730056 | 0.044988 | 17.508 |   40   |   *     | 24.7 |    21.0    | 23.4     |   2.860    |
+2016WW2                    | 2024-01-24 | 3209984 | 0.021457 |  8.351 |    6   |   *     | 29.0 |    23.0    | 10.1     |   4.699    |
+2017BG92                   | 2024-01-25 | 4489976 | 0.030014 | 11.681 |    6   |   *     | 28.8 |    23.6    |  6.3     |   4.587    |
+2011CQ1                    | 2024-01-26 | 4335561 | 0.028981 | 11.279 |  1.4   |   *     | 32.0 |    26.4    |  4.6     |   5.943    |
+2007EG                     | 2024-01-30 | 5999876 | 0.040107 | 15.608 |   40   |   *     | 24.6 |    21.6    |  8.6     |   2.363    |
+2008OS7                    | 2024-02-02 | 2854055 | 0.019078 |  7.425 |  290   |   *     | 20.5 |    14.6    | 18.2     |   0.354    |
+2019CC5                    | 2024-02-04 | 7162319 | 0.047877 | 18.633 |  140   |   *     | 22.0 |    19.2    | 15.0     |   1.538    |
+2002CA26                   | 2024-02-08 |  626624 | 0.004189 |  1.630 |   22   |   *     | 26.1 |    16.3    | 15.5     |   1.631    |
+2020DK                     | 2024-02-12 | 3476695 | 0.023240 |  9.044 |   22   |   *     | 26.1 |    18.4    |  9.9     |   2.924    |
+2022EM1                    | 2024-02-24 | 4723183 | 0.031573 | 12.287 |   11   |   *     | 27.6 |    22.2    |  9.4     |   4.176    |
+2006DM63                   | 2024-02-27 | 2824983 | 0.018884 |  7.349 |   16   |   *     | 26.7 |    18.8    |  9.9     |   3.174    |
+2019DA1                    | 2024-03-03 | 6539327 | 0.043713 | 17.012 |   23   |   *     | 25.9 |    22.0    | 13.6     |   3.530    |
+2015FM34                   | 2024-03-12 | 7423875 | 0.049626 | 19.313 |  110   |   *     | 22.5 |    20.4    | 11.1     |   1.610    |
+2020FU                     | 2024-03-15 | 6655703 | 0.044491 | 17.315 |   19   |   *     | 26.4 |    21.4    | 15.4     |   3.867    |
+2020FD                     | 2024-03-18 | 1993021 | 0.013323 |  5.185 |   10   |   *     | 27.7 |    20.6    | 15.0     |   3.639    |
+2019CJ                     | 2024-03-24 | 4746403 | 0.031728 | 12.348 |   30   |   *     | 25.4 |    21.4    |  4.4     |   2.248    |
+2021CF6                    | 2024-03-25 | 5561744 | 0.037178 | 14.469 |   60   |   *     | 23.8 |    20.3    |  8.3     |   1.750    |
+2015MB54                   | 2024-03-30 | 4464971 | 0.029846 | 11.615 |   60   |   *     | 24.0 |    19.5    |  3.8     |   1.133    |
+2012DU60                   | 2024-04-03 | 6548825 | 0.043776 | 17.037 |   29   |   *     | 25.4 |    24.0    |  6.9     |   2.848    |
+2023GC2                    | 2024-04-04 | 3342893 | 0.022346 |  8.696 |   12   |   *     | 27.3 |    21.6    |  5.7     |   3.374    |
+2015FF36                   | 2024-04-04 | 3201420 | 0.021400 |  8.328 |   18   |   *     | 26.5 |    26.4    |  8.2     |   3.043    |
+2005FG                     | 2024-04-08 | 7051953 | 0.047139 | 18.345 |   60   |   *     | 23.9 |    20.4    |  5.5     |   1.794    |
+2020BP13                   | 2024-04-09 | 5813614 | 0.038862 | 15.124 |  200   |   *     | 21.2 |    16.6    |  6.8     |   0.763    |
+2021GQ5                    | 2024-04-13 | 3464647 | 0.023160 |  9.013 |    7   |   *     | 28.5 |    24.9    |  7.5     |   4.340    |
+2021FD1                    | 2024-04-13 | 3142007 | 0.021003 |  8.174 |   17   |   *     | 26.7 |    27.2    |  8.2     |   3.128    |
+2023FN13                   | 2024-04-14 | 1272825 | 0.008508 |  3.311 |   13   |   *     | 27.2 |    20.1    |  4.9     |   2.380    |
+2022UO1                    | 2024-04-14 | 6370278 | 0.042583 | 16.572 |   30   |   *     | 25.2 |    23.2    | 14.0     |   3.033    |
+517681           2015DE198 | 2024-04-15 | 7029306 | 0.046988 | 18.286 |  600   |   *     | 19.0 |    18.0    | 14.2     |   0.568    |
+439437             2013NK4 | 2024-04-15 | 3256689 | 0.021770 |  8.472 |  600   |   *     | 18.9 |    12.5    | 16.5     |  -0.065    |
+2021GZ9                    | 2024-04-16 | 7068938 | 0.047253 | 18.390 |   18   |   *     | 26.4 |    22.0    |  3.2     |   3.033    |
+2023HU3                    | 2024-04-18 | 6054869 | 0.040474 | 15.752 |   30   |   *     | 25.0 |    20.0    | 19.1     |   2.983    |
+2021JW2                    | 2024-04-19 |  656452 | 0.004388 |  1.708 |   11   |   *     | 27.6 |    19.5    |  5.1     |   2.107    |
+2017SA20                   | 2024-04-19 | 1602793 | 0.010714 |  4.170 |    8   |   *     | 28.4 |    21.4    |  6.2     |   3.465    |
+2021HY9                    | 2024-04-19 | 2769351 | 0.018512 |  7.204 |    8   |   *     | 28.1 |    21.3    | 10.4     |   4.071    |
+1993HP1                    | 2024-04-22 | 1544937 | 0.010327 |  4.019 |   14   |   *     | 27.1 |    19.5    |  9.0     |   2.820    |
+2021VH2                    | 2024-04-25 | 3564834 | 0.023829 |  9.274 |    6   |   *     | 28.8 |    23.7    |  2.7     |   3.782    |
+2020JM                     | 2024-04-28 | 3779212 | 0.025262 |  9.831 |   21   |   *     | 26.2 |    20.7    |  8.0     |   2.949    |
+2021GD3                    | 2024-04-30 | 4385660 | 0.029316 | 11.409 |   14   |   *     | 27.0 |    20.7    |  3.5     |   3.050    |
+2022TN1                    | 2024-04-30 | 7117961 | 0.047581 | 18.517 |  290   |   *     | 20.5 |    15.2    | 17.7     |   1.143    |
+2022AA5                    | 2024-05-02 | 4358374 | 0.029134 | 11.338 |   70   |   *     | 23.6 |    18.2    |  8.9     |   1.508    |
+2021JG9                    | 2024-05-10 | 5477174 | 0.036613 | 14.249 |   30   |   *     | 25.2 |    20.4    | 16.1     |   2.958    |
+2015KJ19                   | 2024-05-14 | 6042541 | 0.040392 | 15.719 |  110   |   *     | 22.5 |    18.7    | 23.1     |   1.640    |
+2014WF6                    | 2024-05-14 | 2739898 | 0.018315 |  7.128 |   50   |   *     | 24.4 |    17.7    | 18.9     |   1.831    |
+2021JN10                   | 2024-05-14 | 7126473 | 0.047638 | 18.539 |   30   |   *     | 25.2 |    20.5    | 13.1     |   3.103    |
+2021JJ                     | 2024-05-15 | 6536491 | 0.043694 | 17.004 |   27   |   *     | 25.6 |    20.2    |  5.8     |   2.840    |
+2022WR11                   | 2024-05-16 | 3589864 | 0.023997 |  9.339 |   10   |   *     | 27.7 |    22.3    | 18.5     |   4.229    |
+2022WN2                    | 2024-05-17 | 5245986 | 0.035067 | 13.647 |    6   |   *     | 28.9 |    23.9    |  5.5     |   4.714    |
+2015WO1                    | 2024-05-19 | 5068966 | 0.033884 | 13.187 |   90   |   *     | 23.1 |    19.1    | 16.0     |   1.633    |
+2019VB5                    | 2024-05-21 | 2901001 | 0.019392 |  7.547 |  1.6   |   *     | 31.7 |    26.5    |  6.3     |   5.655    |
+2011LZ2                    | 2024-05-26 | 3736232 | 0.024975 |  9.720 |   30   |   *     | 25.3 |    22.1    |  6.1     |   2.236    |
+2008LD                     | 2024-05-28 | 2957544 | 0.019770 |  7.694 |    6   |   *     | 28.9 |    23.9    |  4.5     |   4.032    |
+2021LV                     | 2024-05-29 | 4610626 | 0.030820 | 11.994 |    9   |   *     | 27.9 |    23.1    | 15.5     |   4.548    |
+1998KY26                   | 2024-06-01 | 4589326 | 0.030678 | 11.939 |   27   |  **     | 25.6 |    20.5    |  5.3     |   2.060    |
+2008YN2                    | 2024-06-05 | 4508353 | 0.030136 | 11.728 |   20   |   *     | 26.3 |    22.2    |  7.8     |   3.164    |
+2021LW3                    | 2024-06-06 | 3672404 | 0.024549 |  9.554 |   90   |   *     | 23.1 |    18.5    |  9.8     |   1.153    |
+2021EF1                    | 2024-06-12 | 3154320 | 0.021085 |  8.206 |    4   |   *     | 29.7 |    24.5    | 12.2     |   5.081    |
+2022XC1                    | 2024-06-12 | 6320620 | 0.042251 | 16.443 |   21   |   *     | 26.2 |    22.3    |  6.5     |   3.286    |
+2019LH6                    | 2024-06-13 | 1805741 | 0.012071 |  4.698 |   50   |   *     | 24.1 |    16.5    | 14.3     |   1.172    |
+2004LB2                    | 2024-06-17 | 3178442 | 0.021247 |  8.269 |  130   |   *     | 22.1 |    16.0    | 17.6     |   0.910    |
+2009KV21                   | 2024-06-17 | 6503193 | 0.043471 | 16.918 |   40   |   *     | 24.6 |    19.6    | 10.4     |   2.531    |
+415029            2011UL21 | 2024-06-27 | 6641164 | 0.044393 | 17.277 | 2200   |   *     | 16.0 |    11.8    | 25.9     |  -0.612    |
+2022MM1                    | 2024-06-28 | 2975304 | 0.019889 |  7.740 |   40   |   *     | 24.9 |    19.6    | 10.9     |   2.044    |
+2010XN                     | 2024-06-28 | 5413660 | 0.036188 | 14.083 |   50   |   *     | 24.2 |    20.2    | 11.3     |   2.104    |
+2016CK248                  | 2024-06-28 | 5570079 | 0.037234 | 14.490 |   16   |   *     | 26.7 |    23.1    |  9.0     |   3.722    |
+2022HD1                    | 2024-06-29 | 6562107 | 0.043865 | 17.071 |   60   |   *     | 23.7 |    19.7    |  7.2     |   1.776    |
+2017MB3                    | 2024-06-30 | 1929612 | 0.012899 |  5.020 |   30   |   *     | 25.3 |    18.3    |  6.5     |   1.695    |
+2022BY39                   | 2024-07-02 | 5069868 | 0.033890 | 13.189 |    4   |   *     | 29.9 |    27.0    |  3.0     |   4.706    |
+2022YS5                    | 2024-07-11 | 4207309 | 0.028124 | 10.945 |   40   |   *     | 24.8 |    24.5    |  5.8     |   1.956    |
+2010VV98                   | 2024-07-13 | 5014572 | 0.033520 | 13.045 |   50   |   *     | 24.5 |    20.8    | 13.3     |   2.298    |
+2013JU22                   | 2024-07-15 | 4253116 | 0.028430 | 11.064 |   40   |   *     | 24.9 |    19.5    |  7.2     |   2.195    |
+2011MW1                    | 2024-07-25 | 3858918 | 0.025795 | 10.039 |  120   |   *     | 22.4 |    17.2    |  8.0     |   0.834    |
+2011AM24                   | 2024-07-26 | 6449244 | 0.043111 | 16.777 |  290   |   *     | 20.5 |    16.2    |  6.2     |   0.573    |
+523664             2012OD1 | 2024-07-28 | 5717317 | 0.038218 | 14.873 |  700   |   *     | 18.6 |    18.4    | 23.7     |   0.370    |
+2020PN1                    | 2024-08-02 | 6893507 | 0.046080 | 17.933 |   29   |   *     | 25.5 |    21.6    |  5.5     |   2.775    |
diff --git a/astroquery/esa/neocc/test/data/foo.eph b/astroquery/esa/neocc/test/data/foo.eph
new file mode 100644
index 0000000000..9a79c9a9fa
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/foo.eph
@@ -0,0 +1 @@
+'No ephemerides file'
diff --git a/astroquery/esa/neocc/test/data/foo.eq0 b/astroquery/esa/neocc/test/data/foo.eq0
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/astroquery/esa/neocc/test/data/foo.ke0 b/astroquery/esa/neocc/test/data/foo.ke0
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/astroquery/esa/neocc/test/data/frfre.phypro b/astroquery/esa/neocc/test/data/frfre.phypro
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/astroquery/esa/neocc/test/data/impactedObjectsList.txt b/astroquery/esa/neocc/test/data/impactedObjectsList.txt
new file mode 100644
index 0000000000..ed636c65b1
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/impactedObjectsList.txt
@@ -0,0 +1,4 @@
+2008TC3 2008-10-07
+2018LA 2018-06-02
+2014AA 2014-01-02
+2019MO 2019-06-22
diff --git a/astroquery/esa/neocc/test/data/monthly_update.done b/astroquery/esa/neocc/test/data/monthly_update.done
new file mode 100644
index 0000000000..d264c8a306
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/monthly_update.done
@@ -0,0 +1 @@
+Tue Aug 24 06:21:13 UTC 2021
diff --git a/astroquery/esa/neocc/test/data/neo_kc.cat b/astroquery/esa/neocc/test/data/neo_kc.cat
new file mode 100644
index 0000000000..ebcbb87247
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/neo_kc.cat
@@ -0,0 +1,9 @@
+format  = 'OEF2.0'       ! file format
+rectype = '1L'           ! record type (1L/ML)
+elem    = 'KEP'          ! type of orbital elements
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+! Name, Epoch(MJD), a, e, i, long. node, arg. peric., mean anomaly, absolute magnitude, slope param, non-grav param
+433           59600.000000    1.4582731004919933E+00   2.2272733518842894E-01   1.0828461192253641E+01   3.0429635501527531E+02   1.7889716943295548E+02   2.4690411844800099E+02  10.85  0.46  0
+6344P-L       59400.000000    2.8202277078203988E+00   6.6155999676965871E-01   4.6786111836540556E+00   1.8282300248385891E+02   2.3494660190063559E+02   3.2386152408344321E+02  20.40  0.15  0
+2015GZ        59400.000000    2.8059248663363574E+00   7.1777101854979719E-01   1.3504485380561094E+01   1.9799756552626015E+01   1.1456930451775614E+02   1.2828981992766344E+02  26.06  0.15  0
\ No newline at end of file
diff --git a/astroquery/esa/neocc/test/data/neo_km.cat b/astroquery/esa/neocc/test/data/neo_km.cat
new file mode 100644
index 0000000000..7a502b06dd
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/neo_km.cat
@@ -0,0 +1,9 @@
+format  = 'OEF2.0'       ! file format
+rectype = '1L'           ! record type (1L/ML)
+elem    = 'KEP'          ! type of orbital elements
+refsys  = ECLM J2000     ! default reference system
+END_OF_HEADER
+! Name, Epoch(MJD), a, e, i, long. node, arg. peric., mean anomaly, absolute magnitude, slope param, non-grav param
+433           53791.241721    1.4580850879518152E+00   2.2276648293317824E-01   1.0828968240269813E+01   3.0438968431527178E+02   1.7865613778884747E+02   2.3522149848735475E+02  10.85  0.46  0
+6344P-L       54279.370204    2.8039034258491382E+00   6.6690026321858520E-01   4.7309101708797527E+00   1.8367880827375714E+02   2.3404960119006245E+02   3.3009070787043146E+02  20.40  0.15  0
+2015GZ        57124.262212    2.7971447612145970E+00   7.2012628827801706E-01   1.3510774623902163E+01   2.0375151891132017E+01   1.1383106956423489E+02   9.3612090170941080E+00  26.06  0.15  0
\ No newline at end of file
diff --git a/astroquery/esa/neocc/test/data/null.phypro b/astroquery/esa/neocc/test/data/null.phypro
new file mode 100644
index 0000000000..084bec152b
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/null.phypro
@@ -0,0 +1,18 @@
+Rotation Period,-,h,[-]
+Quality,-,-,[-]
+Amplitude,-,mag,[-]
+Rotation Direction,-,-,[-]
+Spinvector L,-,deg,[-]
+Spinvector B,-,deg,[-]
+Taxonomy,-,-,[-]
+Taxonomy (all),-,-,[-]
+Absolute Magnitude (H),-,mag,[-]
+Slope Parameter (G),-,mag,[-]
+Albedo,-,-,[-]
+Diameter,-,m,[1]
+Color Index Information,-,mag,[-]
+Sightings,-,-,[-]
+
+REFERENCES
+
+[1],Estimation,Estimated from absolute magnitude
diff --git a/astroquery/esa/neocc/test/data/past_impactors_list b/astroquery/esa/neocc/test/data/past_impactors_list
new file mode 100644
index 0000000000..2a09731f3c
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/past_impactors_list
@@ -0,0 +1,7 @@
+Last Update: 2022-04-04 10:00 UTC
+  Object designator  |  Diameter in m  |  Impact date/time in UTC  |  Impact Velocity in km/s  |  Estimated energy in Mt  |  Measured energy in Mt  |
+       2022EB5       |      1.9*       |    2022-03-11 21:22:00    |           18.53           |         2.96E-4          |        4.00E-3          |
+       2019MO        |       5*        |    2019-06-22 21:30:00    |           16.34           |         3.82E-3          |        6.00E-3          |
+       2018LA        |      2.8*       |    2018-06-02 16:44:00    |           16.98           |         8.90E-4          |        9.80E-4          |
+       2014AA        |      2.3*       |    2014-01-02 02:30:00    |           11.97           |         2.44E-4          |           n/a           |
+       2008TC3       |       3*        |    2008-10-07 02:45:00    |           11.77           |         6.77E-4          |        1.00E-3          |
diff --git a/astroquery/esa/neocc/test/data/updated_nea.lst b/astroquery/esa/neocc/test/data/updated_nea.lst
new file mode 100644
index 0000000000..f0349de886
--- /dev/null
+++ b/astroquery/esa/neocc/test/data/updated_nea.lst
@@ -0,0 +1,17 @@
+# Mon Oct 04 06:30:08 UTC 2021
+          2021SF4             
+          2021SK4             
+          2021SL4             
+          2021TK              
+          2021TL              
+          2021TM              
+          2021TN              
+          2021TO              
+          2021TQ              
+# Sun Oct 03 15:00:09 UTC 2021
+          2021TF              
+# Sun Oct 03 14:30:09 UTC 2021
+          2017TJ1             
+          2021SY3             
+          2021SZ3
+          2019UE2
\ No newline at end of file
diff --git a/astroquery/esa/neocc/test/setup_package.py b/astroquery/esa/neocc/test/setup_package.py
new file mode 100644
index 0000000000..8dfac113f0
--- /dev/null
+++ b/astroquery/esa/neocc/test/setup_package.py
@@ -0,0 +1,25 @@
+"""
+This file only needs the get_package_data() function, which will tell
+setup.py to include the relevant files when installing.
+"""
+
+import os
+
+
+def get_package_data():
+    paths_test = [os.path.join('data', '*.lst'),
+                  os.path.join('data', '*.eph'),
+                  os.path.join('data', '*.done'),
+                  os.path.join('data', 'esa_*'),
+                  os.path.join('data', '*.txt'),
+                  os.path.join('data', 'past_impactors_list'),
+                  os.path.join('data', '*.cat'),
+                  os.path.join('data', '*.risk'),
+                  os.path.join('data', '*.clolin'),
+                  os.path.join('data', '*.phypro'),
+                  os.path.join('data', '*.rwo'),
+                  os.path.join('data', '*.ke*'),
+                  os.path.join('data', '*.eq*'),
+                  os.path.join('data', '*.csv*')]
+
+    return {'astroquery.esa.neocc.test': paths_test}
diff --git a/astroquery/esa/neocc/test/test_neocc.py b/astroquery/esa/neocc/test/test_neocc.py
new file mode 100755
index 0000000000..b09d6380d8
--- /dev/null
+++ b/astroquery/esa/neocc/test/test_neocc.py
@@ -0,0 +1,1046 @@
+# -*- coding: utf-8 -*-
+"""
+This module contains all the monkeypatch tests. The data for these
+tests is gathered in data folder and contains the information
+of different lists and object information from ESA NEOCC portal.
+"""
+
+import os
+import re
+import pytest
+import warnings
+
+import numpy as np
+import requests
+
+from astropy.table import Table
+from astropy.time import Time, TimeDelta
+
+from astroquery.utils.mocks import MockResponse
+
+from astroquery.esa import neocc
+
+# Import BASE URL and TIMEOUT
+API_URL = neocc.conf.API_URL
+DATA_DIR = os.path.join(os.path.dirname(__file__), 'data')
+TIMEOUT = neocc.conf.TIMEOUT
+VERIFICATION = neocc.conf.SSL_CERT_VERIFICATION
+
+
+def data_path(filename):
+    """Look for the data directory local to the test_module.py file.
+    """
+    data_dir = os.path.join(os.path.dirname(__file__), 'data')
+    return os.path.join(data_dir, filename)
+
+
+@pytest.fixture
+def patch_get(request):
+    """This function, when called, changes the requests.Session’s
+    request method to call the get_mockreturn function, defined below.
+    """
+    try:
+        monkey_p = request.getfixturevalue("monkeypatch")
+    except AttributeError:  # pytest < 3
+        monkey_p = request.getfuncargvalue("monkeypatch")
+    monkey_p.setattr(requests, 'get', get_mockreturn)
+    return monkey_p
+
+
+def get_mockreturn(name, timeout=TIMEOUT, verify=VERIFICATION):
+    """Define a function to return the appropriate data stored in the
+    data/ directory as a readable object within the MockResponse class.
+    """
+
+    # Split name (the requested url) to obtain the name of the file location stored in \data
+
+    fileloc = name.split(r'=')[1]
+
+    # Exception for ephemerides
+    if '&oc' in fileloc:
+        fileloc = fileloc.split(r'&')[0] + '.eph'
+
+    filename = data_path(fileloc)
+    with open(filename, 'rb') as FLE:
+        content = FLE.read()
+        content = content.replace(b"\r", b"")  # For windows tests
+
+    return MockResponse(content)
+
+
+def test_bad_list_names():
+    """
+    Check errors from invalid names
+    """
+
+    # Invalid inputs
+    bad_names = ["ASedfe", "%&$", "ÁftR+", 154]
+    foo_data = []
+
+    # Assert for invalid names
+    for elements in bad_names:
+        with pytest.raises(KeyError):
+            neocc.lists.get_list_url(elements)
+        with pytest.raises(KeyError):
+            neocc.lists.parse_list(elements, foo_data)
+
+
+def check_table_structure(data_table, table_len, table_cols, float_cols=[], int_cols=[], str_cols=[], time_cols=[]):
+    """
+    Given a data table, checks:
+    - Table length matches given table_len
+    - Table column names match the given table_cols list
+    - All the columns with indices given in float_cols are of float type
+    - Equivalent checks for int_cols, and string_cols
+    - Checks that columns with indices given in time_cols are `~astropy.time.Time` objects
+    """
+
+    table_cols = np.array(table_cols)
+
+    assert len(data_table) == table_len
+    assert len(data_table.columns) == len(table_cols)
+
+    assert all([x == y for x, y in zip(data_table.colnames, table_cols)])
+
+    # Ignore the FutureWarning that only comes up with the oldest dependencies
+    warnings.filterwarnings("ignore", category=FutureWarning,
+                            message="Conversion of the second argument of issubdtype*")
+    assert all([np.issubdtype(data_table[x].dtype, float) for x in table_cols[float_cols]])
+    assert all([np.issubdtype(data_table[x].dtype, int) for x in table_cols[int_cols]])
+    assert all([np.issubdtype(data_table[x].dtype, str) for x in table_cols[str_cols]])
+
+    assert all([isinstance(data_table[x], Time) for x in table_cols[time_cols]])
+
+
+def check_table_values(data_table, true_value_dict):
+    """
+    Checks data_table rows against true values given in true_value_dict.
+    The format of true_value_dict is {<row number>: [true row data], ...}
+    """
+
+    for row, values in true_value_dict.items():
+
+        assert all([x == y if not isinstance(x, np.ma.core.MaskedConstant) else y == "masked"
+                    for x, y in zip(data_table[row].values(), values)])
+
+
+def test_parse_nea(patch_get):
+    """
+    Check data: nea_list, updated_nea and monthly_update
+    """
+
+    # NEA list, Updated NEA list and monthly update
+    nea_list = neocc.neocc.query_list('nea_list')
+    updated_nea = neocc.neocc.query_list('updated_nea')
+    monthly_update = neocc.neocc.query_list('monthly_update')
+
+    # Assert is a pandas Series
+    assert isinstance(nea_list, Table)
+    assert isinstance(updated_nea, Table)
+    assert isinstance(monthly_update, Table)
+
+    # Assert is not empty
+    assert len(nea_list)
+    assert len(updated_nea)
+    assert len(monthly_update)
+
+    # Check size of the files
+    assert len(nea_list) == 12
+    assert len(updated_nea) == 17
+    assert len(monthly_update) == 1
+
+    # Check some elements of the lists NEA list
+    first_neas = Table(names=["NEA"],
+                       data=[['433 Eros', '719 Albert', '887 Alinda',
+                              '1036 Ganymed', '1221 Amor', '1566 Icarus']])
+
+    assert (nea_list[:6]["NEA"] == first_neas["NEA"]).all()
+    assert nea_list["NEA"][-1] == '6344P-L'
+
+    # Updated NEA
+    first_update = Table(names=["NEA"],
+                         data=[['Mon Oct 04 06:30:08 UTC 2021',
+                                '2021SF4', '2021SK4', '2021SL4',
+                                '2021TK', '2021TL', '2021TM', '2021TN',
+                                '2021TO', '2021TQ']])
+
+    assert (updated_nea[:10]["NEA"] == first_update["NEA"]).all()
+    assert updated_nea["NEA"][-1] == '2019UE2'
+
+    # Monthly update
+    assert monthly_update["NEA"][0] == 'Tue Aug 24 06:21:13 UTC 2021'
+    # Check date format DDD MMM DD HH:MM:SS UTC YYYY
+    assert re.match(r'\w{3} \w{3} \d{2} \d{2}:\d{2}:\d{2} \w{3} \d{4}', monthly_update["NEA"][0])
+
+
+@pytest.mark.filterwarnings('ignore:ERFA function *:erfa.core.ErfaWarning')
+def test_parse_risk(patch_get):
+    """Check data: risk_list, risk_list_special
+
+    Ignore ERFA 'dubious year' warnings because they are expected.
+    """
+    # Risk and risk special lists
+    risk_list = neocc.neocc.query_list("risk_list")
+    risk_list_special = neocc.neocc.query_list("risk_list_special")
+
+    # Assert is aastropy Table
+    assert isinstance(risk_list, Table)
+    assert isinstance(risk_list_special, Table)
+
+    risk_columns = ['Object Name', 'Diameter in m', '*=Y', 'Date/Time', 'IP max', 'PS max', 'TS',
+                    'Vel in km/s', 'First Year', 'Last Year', 'IP cum', 'PS cum']
+    risk_special_columns = risk_columns[0:8]
+
+    check_table_structure(risk_list, 4, risk_columns, float_cols=[1, 4, 5, 7, -2, -1],
+                          int_cols=[6, 8, 9], str_cols=[0, 2], time_cols=[3])
+    check_table_structure(risk_list_special, 2, risk_special_columns, float_cols=[4, 5, 7],
+                          int_cols=[1, 6], str_cols=[0, 2], time_cols=[3])
+
+    # Check first, last and random mid element
+    risk_dict = {}
+    risk_dict[0] = ['2021QM1', 50.0, '*', Time('2052-04-02 01:36:00'),
+                    0.000298, -2.72, 0, 23.72, 2050, 2054, 0.000298, -2.72]
+    risk_dict[1] = ['2021KQ2', 4.0, '*', Time('2097-05-21 03:05:00'), 1.26e-11,
+                    -13.71, 0, 11.42, 2097, 2097, 1.26e-11, -13.71]
+    risk_dict[2] = ['2013BR15', 30.0, '*', Time('2100-01-02 18:03:00'), 1.21e-07,
+                    -7.15, 0, 17.98, 2100, 2100, 1.6e-07, -7.03]
+    check_table_values(risk_list, risk_dict)
+
+
+def test_parse_clo(patch_get):
+    """Check data: close_approaches_upcoming, close_approaches_recent
+    """
+
+    # Close approaches upcoming and recent lists
+    close_appr_upcoming = neocc.neocc.query_list("close_approaches_upcoming")
+    close_appr_recent = neocc.neocc.query_list("close_approaches_recent")
+
+    # Assert is an astropy Table
+    assert isinstance(close_appr_upcoming, Table)
+    assert isinstance(close_appr_recent, Table)
+
+    close_columns = ['Object Name', 'Date', 'Miss Distance in km', 'Miss Distance in au',
+                     'Miss Distance in LD', 'Diameter in m', '*=Yes', 'H', 'Max Bright',
+                     'Rel. vel in km/s', 'CAI index']
+    check_table_structure(close_appr_upcoming, 174, close_columns, float_cols=[3, 4, 5, 7, 8, 9, 10],
+                          int_cols=[2], str_cols=[0, 6], time_cols=[1])
+    check_table_structure(close_appr_recent, 60, close_columns, float_cols=[3, 4, 5, 7, 8, 9, 10],
+                          int_cols=[2], str_cols=[0, 6], time_cols=[1])
+
+    # Check first, last and random mid element
+    # Close approaches upcoming
+    closeup_dict = {}
+    closeup_dict[0] = ['2023OW4', Time('2023-08-03 00:00:00.000'), 565277,
+                       0.003779, 1.471, 10.0, '*', 27.8, 18.1, 9.7, 2.464]
+    closeup_dict[-1] = ['2020PN1', Time('2024-08-02 00:00:00.000'), 6893507,
+                        0.04608, 17.933, 29.0, '*', 25.5, 21.6, 5.5, 2.775]
+    closeup_dict[80] = ['2010XF3', Time('2023-12-11 00:00:00.000'), 7377915,
+                        0.049318, 19.193, 50.0, '*', 24.3, 19.1, 4.0, 1.828]
+    check_table_values(close_appr_upcoming, closeup_dict)
+
+    # Close approaches recent
+    closere_dict = {}
+    closere_dict[0] = ['2023OY4', Time('2023-08-02 00:00:00.000'), 1219027,
+                       0.008149, 3.171, 30.0, '*', 25.4, 18.1, 17.6, 1.794]
+    closere_dict[-1] = ['2023NG1', Time('2023-07-03 00:00:00.000'), 705381,
+                        0.004715, 1.835, 20.0, '*', 26.3, 17.6, 3.8, 1.071]
+    closere_dict[40] = ['2023OZ', Time('2023-07-13 00:00:00.000'), 2868022,
+                        0.019172, 7.461, 19.0, '*', 26.3, 19.0, 5.9, 2.633]
+    check_table_values(close_appr_recent, closere_dict)
+
+
+def test_parse_pri(patch_get):
+    """Check data: priority_list, priority_list_faint
+    """
+
+    # Priority list and priority faint list
+    priority_list = neocc.neocc.query_list("priority_list")
+    faint_list = neocc.neocc.query_list("priority_list_faint")
+
+    # Assert is an astropy Table
+    assert isinstance(priority_list, Table)
+    assert isinstance(faint_list, Table)
+
+    priority_columns = ['Priority', 'Object', 'R.A. in arcsec', 'Decl. in deg',
+                        'Elong. in deg', 'V in mag', 'Sky uncert.', 'End of Visibility']
+    check_table_structure(priority_list, 176, priority_columns,
+                          float_cols=[2, 3, 5], int_cols=[0, 4, 6], str_cols=[1], time_cols=[-1])
+    check_table_structure(faint_list, 3, priority_columns,
+                          float_cols=[2, 3, 5], int_cols=[0, 4, 6], str_cols=[1], time_cols=[-1])
+
+    # Assert tables are not empty and have the right dimension
+    assert len(priority_list) == 176
+    assert len(priority_list.columns) == 8
+
+    assert len(faint_list) == 3
+    assert len(faint_list.columns) == 8
+
+    # Check first, last and random mid element
+    # Priority list
+    priority_dict = {}
+    priority_dict[0] = [0, '2013GM8', 5880.0, 35.7, 146, 21.3, 62144, Time('2021-11-16 00:00:00')]
+    priority_dict[-1] = [3, '2021NN50', 71880.0, -11.8, 108, 21.2, 0, Time('2021-11-20 00:00:00')]
+    priority_dict[87] = [1, '2021SY2', 10560.0, 6.0, 146, 20.1, 3, Time('2021-10-22 00:00:00')]
+    check_table_values(priority_list, priority_dict)
+
+    # Priority faint list
+    faint_dict = {}
+    faint_dict[0] = [0, '2012BD77', 13800.0, -36.0, 120, 24.7, 1251, Time('2021-12-26 00:00:00')]
+    faint_dict[1] = [1, '2021SX3', 83340.0, -6.3, 155, 22.2, 1, Time('2021-12-12 00:00:00')]
+    faint_dict[2] = [0, '2019UO10', 84960.0, -37.9, 135, 24.9, 9185, Time('2021-10-13 00:00:00')]
+    check_table_values(faint_list, faint_dict)
+
+
+@pytest.mark.filterwarnings('ignore:ERFA function *:erfa.core.ErfaWarning')
+def test_parse_encounter(patch_get):
+    """Check data: encounter_list
+
+    Ignore ERFA 'dubious year' warnings because they are expected.
+    """
+
+    encounter_list = neocc.neocc.query_list("close_encounter")
+
+    # Assert is an astropy Table
+    assert isinstance(encounter_list, Table)
+
+    encounter_columns = ['Name/desig', 'Planet', 'Date', 'Time approach', 'Time uncert',
+                         'Distance', 'Minimum distance', 'Distance uncertainty', 'Width',
+                         'Stretch', 'Probability', 'Velocity', 'Max Mag']
+    check_table_structure(encounter_list, 3, encounter_columns,
+                          float_cols=slice(3, None), str_cols=[0, 1], time_cols=[2])
+
+    encounter_dict = {}
+    encounter_dict[0] = ['433', 'EARTH', Time('1975-01-23T07:38:40.992'), 42435.31853255,
+                         1.260737144e-05, 0.151134153855255, 0.1511340949471563, 1.962635286041312e-08,
+                         1.322e-08, 6.103e-08, 1.0, 5.82530834, 7.445]
+    encounter_dict[1] = ['2002MX', 'EARTH', Time('2002-06-12T02:00:30.816'), 52437.083685526,
+                         0.0002355862863, 0.04148563561205888, 0.04128486992493158, 6.692189692154938e-05,
+                         2.634e-07, 6.692e-05, 1.0, 25.57598245, 17.59]
+    mid_time = Time.strptime("2054/01/11", '%Y/%m/%d') + TimeDelta(.31202, format="jd")
+    encounter_dict[2] = ['2000AA6', 'EARTH', mid_time, 71278.312017212,
+                         4.189937108e-05, 0.03820285368375039, 0.03820063181644156, 7.40623369935997e-07,
+                         3.635e-08, 7.571e-07, 1.0, 17.16618231, 18.213]
+
+    check_table_values(encounter_list, encounter_dict)
+
+
+def test_parse_impacts(patch_get):
+    """Check data: impacted objects list
+    """
+
+    impact_list = neocc.neocc.query_list("impacted_objects")
+
+    # Assert is a astropy.table.Table
+    assert isinstance(impact_list, Table)
+
+    column_names = ['Object designator', 'Diameter in m', 'Impact date/time in UTC',
+                    'Impact Velocity in km/s', 'Estimated energy in Mt', 'Measured energy in Mt']
+    check_table_structure(impact_list, 5, column_names,
+                          float_cols=slice(3, None), str_cols=[0, 1], time_cols=[2])
+
+    impact_dict = {}
+    impact_dict[0] = ['2022EB5', '1.9*', Time('2022-03-11 21:22:00'), 18.53, 2.96E-4, 4.00E-3]
+    impact_dict[1] = ['2019MO', '5*', Time('2019-06-22 21:30:00'), 16.34, 3.82E-3, 6.00E-3]
+    impact_dict[2] = ['2018LA', '2.8*', Time('2018-06-02 16:44:00'), 16.98, 8.90E-4, 9.80E-4]
+    impact_dict[4] = ['2008TC3', '3*', Time('2008-10-07 02:45:00'), 11.77, 6.77E-4, 1.00E-3]
+    check_table_values(impact_list, impact_dict)
+
+
+def test_parse_catalogues(patch_get):
+    """Check data: encounter_list
+    """
+
+    cat_current = neocc.neocc.query_list("neo_catalogue_current")
+    cat_middle = neocc.neocc.query_list("neo_catalogue_middle")
+
+    assert isinstance(cat_current, Table)
+    assert isinstance(cat_middle, Table)
+
+    cat_columns = ['Name', 'Epoch (MJD)', 'a', 'e', 'i', 'long. node', 'arg. peric.', 'mean anomaly',
+                   'absolute magnitude', 'slope param.', 'non-grav param.']
+
+    check_table_structure(cat_current, 3, cat_columns, float_cols=slice(1, 10), str_cols=[0], int_cols=[-1])
+    check_table_structure(cat_middle, 3, cat_columns, float_cols=slice(1, 10), str_cols=[0], int_cols=[-1])
+
+    # Check first, last and random mid element
+    cat_dict = {}
+    cat_dict[0] = ['433', 59600.000000, 1.4582731004919933E+00, 2.2272733518842894E-01, 1.0828461192253641E+01,
+                   3.0429635501527531E+02, 1.7889716943295548E+02, 2.4690411844800099E+02, 10.85, 0.46, 0]
+    cat_dict[1] = ['6344P-L', 59400.000000, 2.8202277078203988E+00, 6.6155999676965871E-01, 4.6786111836540556E+00,
+                   1.8282300248385891E+02, 2.3494660190063559E+02, 3.2386152408344321E+02, 20.40, 0.15, 0]
+    cat_dict[2] = ['2015GZ', 59400.000000, 2.8059248663363574E+00, 7.1777101854979719E-01, 1.3504485380561094E+01,
+                   1.9799756552626015E+01, 1.1456930451775614E+02, 1.2828981992766344E+02, 26.06, 0.15, 0]
+    check_table_values(cat_current, cat_dict)
+
+
+def check_tab_result_basic(results, num_tabs):
+    assert isinstance(results, list)
+    assert len(results) == num_tabs
+
+
+@pytest.mark.filterwarnings('ignore:ERFA function *:erfa.core.ErfaWarning')
+def test_tabs_impacts(patch_get):
+    """Check data: asteroid impacts tab
+
+    Ignore ERFA 'dubious year' warnings because they are expected.
+    """
+
+    # 433 Eros has no tab "impacts"
+    with pytest.raises(ValueError):
+        neocc.neocc.query_object(name="433", tab='impacts')
+
+    meta_keys = ['Column Info', 'observation_accepted', 'observation_rejected', 'arc_start',
+                 'arc_end', 'info', 'computation', 'additional_note']
+    impact_columns = ['date', 'MJD', 'sigma', 'sigimp', 'dist', 'width', 'stretch', 'p_RE',
+                      'Exp. Energy in MT', 'PS', 'TS']
+
+    # Asteroid 1979XB
+    impact_tab_list = neocc.neocc.query_object(name='1979XB', tab='impacts')
+    check_tab_result_basic(impact_tab_list, 1)
+
+    impact_table = impact_tab_list[0]
+
+    for key in meta_keys[:-1]:
+        assert key in impact_table.meta.keys()
+
+    arc_tmes = [Time.strptime("1979/12/11", '%Y/%m/%d') + TimeDelta(.511, format="jd"),
+                Time.strptime("1979/12/15", '%Y/%m/%d') + TimeDelta(.430, format="jd")]
+    impact_meta = {'observation_accepted': 18,
+                   'observation_rejected': 0,
+                   'arc_start': arc_tmes[0],
+                   'arc_end': arc_tmes[1],
+                   'computation': '20190808 162907.255 CET'}
+
+    for key, value in impact_meta.items():
+        assert impact_table.meta[key] == value
+
+    check_table_structure(impact_table, 8, impact_columns, float_cols=slice(1, 10), int_cols=[-1], time_cols=[0])
+    impact_dict = {}
+    row_time = Time.strptime("2101-12-14", '%Y-%m-%d') + TimeDelta(.203, format="jd")
+    impact_dict[3] = [row_time, 88781.204, -0.384, 0.0, 0.61,
+                      0.089, 194000000.0, 3.48e-09, 0.000131, -5.36, 0]
+    check_table_values(impact_table, impact_dict)
+
+
+@pytest.mark.filterwarnings('ignore:ERFA function *:erfa.core.ErfaWarning')
+def test_tabs_close_approach(patch_get):
+    """Check data: asteroid close approaches tab
+
+    Ignore ERFA 'dubious year' warnings because they are expected.
+    """
+
+    # Check opbject with no close approaches
+    result_lst = neocc.neocc.query_object(name='594938 2021GE13', tab='close_approaches')
+    check_tab_result_basic(result_lst, 1)
+
+    close_tab = result_lst[0]
+    assert isinstance(close_tab, Table)
+    assert len(close_tab) == 0
+
+    close_columns = ['BODY', 'CALENDAR-TIME', 'MJD-TIME', 'TIME-UNCERT.', 'NOM.-DISTANCE',
+                     'MIN.-POSS.-DIST.', 'DIST.-UNCERT.', 'STRETCH', 'WIDTH', 'PROBABILITY']
+
+    # 433
+    result_lst = neocc.neocc.query_object(name="433", tab='close_approaches')
+    check_tab_result_basic(result_lst, 1)
+
+    close_tab = result_lst[0]
+    check_table_structure(close_tab, 5, close_columns, float_cols=slice(2, None), str_cols=[0], time_cols=[1])
+
+    close_dict = {}
+    row_time = Time.strptime("2093/01/31", '%Y/%m/%d') + TimeDelta(.65750, format="jd")
+    close_dict[3] = ['EARTH', row_time, 85543.657499489, 1.572619005e-05, 0.1824638321371326,
+                     0.1824638180864916, 4.954403653193194e-08, 9.921e-08, 1.612e-08, 1.0]
+    check_table_values(close_tab, close_dict)
+
+    # 99942
+    result_lst = neocc.neocc.query_object(name="99942", tab='close_approaches')
+    check_tab_result_basic(result_lst, 1)
+
+    close_tab = result_lst[0]
+    check_table_structure(close_tab, 26, close_columns, float_cols=slice(2, None), str_cols=[0], time_cols=[1])
+
+    close_dict = {}
+    row_time = Time.strptime("1972/12/24", '%Y/%m/%d') + TimeDelta(.49470, format="jd")
+    close_dict[3] = ['EARTH', row_time, 41675.494697571, 0.004521177247, 0.07923789245024694,
+                     0.07920056098848807, 1.244155168249903e-05, 1.584e-05, 4.645e-09, 1.0]
+    check_table_values(close_tab, close_dict)
+
+
+def test_tabs_physical_properties(patch_get):
+    """Check data: physical properties tab
+    """
+
+    # Check value error if empty
+    with pytest.raises(ValueError):
+        neocc.neocc.query_object(name='frfre', tab='physical_properties')
+
+    props_cols = ['Property', 'Value', 'Units', 'Reference Name', 'Reference Additional']
+
+    # 99942
+    result_lst = neocc.neocc.query_object(name='99942', tab='physical_properties')
+    check_tab_result_basic(result_lst, 1)
+
+    phys_props = result_lst[0]
+    check_table_structure(phys_props, 21, props_cols, str_cols=[0, 1, 2, 3, 4])
+
+    phys_dict = {}
+    phys_dict[1] = ['Absolute Magnitude (H)', '18.937', 'mag', 'ESA ODIM',
+                    'ESA orbit determination and impact monitoring system']
+    phys_dict[5] = ['Color Index Information', '0.362', 'R-I', 'EARN',
+                    ('1.) Lin, C-H. et al. (2018) P&SS 152, 116-135. (Photometric survey and taxonomic '
+                     'identifications of 92 near-Earth asteroids)')]
+    phys_dict[14] = ['Slope Parameter (G)', '0.15**', 'mag', 'ESA ODIM',
+                     'ESA orbit determination and impact monitoring system']
+    check_table_values(phys_props, phys_dict)
+
+    # 1994CJ1
+    result_lst = neocc.neocc.query_object(name='1994CJ1', tab='physical_properties')
+    check_tab_result_basic(result_lst, 1)
+
+    phys_props = result_lst[0]
+    check_table_structure(phys_props, 12, props_cols, str_cols=[0, 1, 2, 3, 4])
+
+    phys_dict = {}
+    phys_dict[0] = ['Absolute Magnitude (H)', '21.539', 'mag', 'ESA ODIM',
+                    'ESA orbit determination and impact monitoring system']
+    phys_dict[2] = ['Diameter', '170*', 'm', 'Estimation', 'Estimated from absolute magnitude']
+    phys_dict[8] = ['Slope Parameter (G)', '0.15**', 'mag', 'ESA ODIM',
+                    'ESA orbit determination and impact monitoring system']
+    check_table_values(phys_props, phys_dict)
+
+
+@pytest.mark.filterwarnings('ignore:ERFA function *:erfa.core.ErfaWarning')
+def test_tabs_observations(patch_get):
+    """Check data: asteroid observations tab
+
+    Ignore ERFA 'dubious year' warnings because they are expected.
+    """
+
+    with pytest.raises(ValueError):
+        neocc.neocc.query_object(name='FOO', tab='observations')
+
+    meta_cols = ['version', 'errmod', 'RMSast', 'RMSmag']
+    opt_obs_cols = ['Design.', 'K', 'T', 'N', 'Date', 'Date Accuracy', 'RA', 'RA Accuracy', 'RA RMS', 'RA F',
+                    'RA Bias', 'RA Resid', 'DEC', 'DEC Accuracy', 'DEC RMS', 'DEC F', 'DEC Bias', 'DEC Resid',
+                    'MAG Val', 'MAG B', 'MAG RMS', 'MAG Resid', 'Ast Cat', 'Obs Code', 'Chi', 'A', 'M']
+    sat_obs_cols = ['Design.', 'K', 'T', 'N', 'Date', 'Parallax info.', 'X', 'Y', 'Z', 'Obs Code']
+    rov_obs_cols = ['Design.', 'K', 'T', 'N', 'Date', 'E longitude', 'Latitude', 'Altitude', 'Obs Code']
+    radar_obs_cols = ['Design', 'K', 'T', 'N', 'Datetime', 'Measure', 'Accuracy', 'rms', 'F', 'Bias', 'Resid',
+                      'TRX', 'RCX', 'Chi', 'S']
+
+    # 433
+    result_lst = neocc.neocc.query_object(name='433', tab='observations')
+    check_tab_result_basic(result_lst, 4)
+
+    meta_tab, opt_obs, sat_obs, rad_obs = result_lst
+
+    assert list(meta_tab.meta.keys()) == ['Title', 'Column Info']
+    assert meta_tab.meta["Title"] == 'Observation metadata'
+    check_table_structure(meta_tab, 1, meta_cols, float_cols=[0, 2, 3], str_cols=[1])
+    meta_dict = {0: [3.0, 'vfcc17', 0.332005, 0.477458]}
+    check_table_values(meta_tab, meta_dict)
+
+    assert list(opt_obs.meta.keys()) == ['Title', 'Column Info']
+    assert opt_obs.meta["Title"] == 'Optical Observations'
+    check_table_structure(opt_obs, 21, opt_obs_cols, float_cols=[5, 7, 8, 11, 10, 13, 14, 16, 17, 18, 20, 21, 24],
+                          int_cols=[0, 25, 26], str_cols=[1, 2, 3, 6, 9, 12, 15, 19, 22, 23], time_cols=[4])
+
+    assert list(sat_obs.meta.keys()) == ['Title']
+    assert sat_obs.meta["Title"] == 'Satellite  Observations'
+    check_table_structure(sat_obs, 5, sat_obs_cols, float_cols=[6, 7, 8], int_cols=[0, 3, 5], str_cols=[1, 2, 9],
+                          time_cols=[4])
+
+    assert list(rad_obs.meta.keys()) == ['Title', 'Column Info']
+    assert rad_obs.meta["Title"] == 'Radar Observations'
+    check_table_structure(rad_obs, 6, radar_obs_cols, float_cols=[5, 6, 7, 9, 10, 13], int_cols=[0, 3, 11, 12, 14],
+                          str_cols=[1, 2, 8], time_cols=[4])
+
+    # 1685
+    result_lst = neocc.neocc.query_object(name='1685', tab='observations')
+    check_tab_result_basic(result_lst, 5)
+
+    meta_tab, opt_obs, sat_obs, rov_obs, rad_obs = result_lst
+
+    assert list(meta_tab.meta.keys()) == ['Title', 'Column Info']
+    assert meta_tab.meta["Title"] == 'Observation metadata'
+    check_table_structure(meta_tab, 1, meta_cols, float_cols=[0, 2, 3], str_cols=[1])
+    meta_dict = {0: [3.0, 'vfcc17', 0.356997, 0.417766]}
+    check_table_values(meta_tab, meta_dict)
+
+    assert list(opt_obs.meta.keys()) == ['Title', 'Column Info']
+    assert opt_obs.meta["Title"] == 'Optical Observations'
+
+    check_table_structure(opt_obs, 22, opt_obs_cols, float_cols=[5, 7, 8, 10, 11, 13, 14, 16, 17, 18, 20, 21, 24],
+                          int_cols=[0, 25, 26], str_cols=[1, 2, 3, 6, 9, 12, 15, 19, 22, 23], time_cols=[4])
+    row_time = Time.strptime("1999/04/20", '%Y/%m/%d') + TimeDelta(.458706, format="jd")
+    opt_dict = {1: [1685, 'O', 'C', '2', row_time, 1e-06, '17:25:59.714', 0.01261, 0.5, 'F', 0.000, -0.296,
+                    '-32:45:54.61', 0.01, 0.5, 'F', 0.0, -0.062, 17.05, 'V', 0.5, -0.12, 'l', '689', 0.61, 1, 1]}
+    check_table_values(opt_obs, opt_dict)
+
+    assert list(sat_obs.meta.keys()) == ['Title']
+    assert sat_obs.meta["Title"] == 'Satellite  Observations'
+    check_table_structure(sat_obs, 10, sat_obs_cols, float_cols=[6, 7, 8], int_cols=[0, 3, 5], str_cols=[1, 2, 9],
+                          time_cols=[4])
+    row_time = Time.strptime("2010/02/11", '%Y/%m/%d') + TimeDelta(.95325, format="jd")
+    sat_dict = {4: [1685, 'S', 's', 'masked', row_time, 1, -4304.3019, -4326.899999999999, -3247.9272, 'C51']}
+    check_table_values(sat_obs, sat_dict)
+
+    assert list(rov_obs.meta.keys()) == ['Title']
+    assert rov_obs.meta["Title"] == 'Roving Observer  Observations'
+    check_table_structure(rov_obs, 5, rov_obs_cols, float_cols=[5, 6, 7], int_cols=[0, 8], str_cols=[1, 2],
+                          time_cols=[4])
+    row_time = Time.strptime("2008/02/14", '%Y/%m/%d') + TimeDelta(.30053, format="jd")
+    rov_dict = {0: [1685, 'O', 'v', 'masked', row_time, 237.818, 37.8191, 470.0, 247]}
+    check_table_values(rov_obs, rov_dict)
+
+    assert list(rad_obs.meta.keys()) == ['Title', 'Column Info']
+    assert rad_obs.meta["Title"] == 'Radar Observations'
+    check_table_structure(rad_obs, 9, radar_obs_cols, float_cols=[5, 6, 7, 9, 10, 13], int_cols=[0, 3, 11, 12, 14],
+                          str_cols=[1, 2, 8], time_cols=[4])
+    rad_dict = {4: [1685, 'R', 's', 'masked', Time('1988-07-24T07:35:00.000'), 31263444.2679, 2.99792,
+                    2.99792, 'F', 0.0, 0.08916, -1, -1, 0.05, 1]}
+    check_table_values(rad_obs, rad_dict)
+
+    # 2016YC8
+    result_lst = neocc.neocc.query_object(name='2016YC8', tab='observations')
+    check_tab_result_basic(result_lst, 4)
+
+    meta_tab, opt_obs, sat_obs, rad_obs = result_lst
+
+    assert list(meta_tab.meta.keys()) == ['Title', 'Column Info']
+    assert meta_tab.meta["Title"] == 'Observation metadata'
+    check_table_structure(meta_tab, 1, meta_cols, float_cols=[0, 2, 3], str_cols=[1])
+    meta_dict = {0: [3.0, 'vfcc17', 0.491024, 0.364713]}
+    check_table_values(meta_tab, meta_dict)
+
+    assert list(opt_obs.meta.keys()) == ['Title', 'Column Info']
+    assert opt_obs.meta["Title"] == 'Optical Observations'
+    check_table_structure(opt_obs, 86, opt_obs_cols, float_cols=[5, 7, 8, 10, 11, 13, 14, 16, 17, 18, 20, 21, 24],
+                          int_cols=[25, 26], str_cols=[0, 1, 2, 3, 6, 9, 12, 15, 19, 22, 23], time_cols=[4])
+
+    assert list(sat_obs.meta.keys()) == ['Title']
+    assert sat_obs.meta["Title"] == 'Satellite  Observations'
+    check_table_structure(sat_obs, 2, sat_obs_cols, float_cols=[6, 7, 8], int_cols=[3, 5], str_cols=[0, 1, 2, 9],
+                          time_cols=[4])
+
+    assert list(rad_obs.meta.keys()) == ['Title', 'Column Info']
+    assert rad_obs.meta["Title"] == 'Radar Observations'
+    check_table_structure(rad_obs, 2, radar_obs_cols, float_cols=[5, 6, 7, 9, 10, 13], int_cols=[3, 11, 12, 14],
+                          str_cols=[0, 1, 2, 8], time_cols=[4])
+
+    # 2020BX12
+    result_lst = neocc.neocc.query_object(name='2020BX12', tab='observations')
+    check_tab_result_basic(result_lst, 4)
+
+    meta_tab, opt_obs, sat_obs, rad_obs = result_lst
+
+    assert list(meta_tab.meta.keys()) == ['Title', 'Column Info']
+    assert meta_tab.meta["Title"] == 'Observation metadata'
+    check_table_structure(meta_tab, 1, meta_cols, float_cols=[0, 2, 3], str_cols=[1])
+    meta_dict = {0: [3.0, 'vfcc17', 0.59903, 0.371435]}
+    check_table_values(meta_tab, meta_dict)
+
+    assert list(opt_obs.meta.keys()) == ['Title', 'Column Info']
+    assert opt_obs.meta["Title"] == 'Optical Observations'
+    check_table_structure(opt_obs, 164, opt_obs_cols, float_cols=[5, 7, 8, 10, 11, 13, 14, 16, 17, 18, 20, 21, 24],
+                          int_cols=[25, 26], str_cols=[0, 1, 2, 3, 6, 9, 12, 15, 19, 22, 23], time_cols=[4])
+
+    assert list(sat_obs.meta.keys()) == ['Title']
+    assert sat_obs.meta["Title"] == 'Satellite  Observations'
+    check_table_structure(sat_obs, 4, sat_obs_cols, float_cols=[6, 7, 8], int_cols=[3, 5], str_cols=[0, 1, 2, 9],
+                          time_cols=[4])
+
+    assert list(rad_obs.meta.keys()) == ['Title', 'Column Info']
+    assert rad_obs.meta["Title"] == 'Radar Observations'
+    check_table_structure(rad_obs, 2, radar_obs_cols, float_cols=[5, 6, 7, 9, 10, 13], int_cols=[3, 11, 12, 14],
+                          str_cols=[0, 1, 2, 8], time_cols=[4])
+
+    # 1979XB
+    result_lst = neocc.neocc.query_object(name='1979XB', tab='observations')
+    check_tab_result_basic(result_lst, 2)
+
+    meta_tab, opt_obs = result_lst
+
+    assert list(meta_tab.meta.keys()) == ['Title', 'Column Info']
+    assert meta_tab.meta["Title"] == 'Observation metadata'
+    check_table_structure(meta_tab, 1, meta_cols[:-1], float_cols=[0, 2], str_cols=[1])
+    meta_dict = {0: [3.0, 'vfcc17', 0.449806]}
+    check_table_values(meta_tab, meta_dict)
+
+    assert list(opt_obs.meta.keys()) == ['Title', 'Column Info']
+    assert opt_obs.meta["Title"] == 'Optical Observations'
+    check_table_structure(opt_obs, 18, opt_obs_cols, float_cols=[5, 7, 8, 10, 11, 13, 14, 16, 17, 20, 21, 24],
+                          int_cols=[25, 26], str_cols=[0, 1, 2, 6, 9, 12, 15], time_cols=[4])
+
+
+def check_keplarian_elements(elt_tab):
+
+    secs = ['Keplerian elements', "RMS"]
+    props = ['PERIHELION', 'APHELION', 'ANODE', 'DNODE', 'MOID', 'PERIOD', 'PHA', 'VINFTY', 'U_PAR', 'ORB_TYPE']
+
+    assert all([x in elt_tab['Section'] for x in secs])
+    assert all([x in elt_tab['Property'] for x in props])
+
+
+def test_tabs_kep_orbit_properties(patch_get):
+    """Check data: asteroid orbit properties tab
+    """
+
+    # Assert blank file
+    with pytest.raises(ValueError):
+        neocc.neocc.query_object(name='foo', tab='orbit_properties',
+                                 orbital_elements='keplerian', orbit_epoch='middle')
+
+    # Assert KeyError in case some kwargs is missing
+    with pytest.raises(KeyError):
+        neocc.neocc.query_object(name='99942', tab='orbit_properties', orbital_elements='keplerian')
+
+    elt_cols = ['Section', 'Property', 'Value']
+    mat_cols = ['a', 'e', 'i', 'long. node', 'arg. peric.', 'mean anomaly']
+    amr = ["Area-to-mass ratio [m^2/t]"]
+    yp = ["Yarkovsky parameter [1E-10 au/day^2]"]
+
+    # 433
+    result_lst = neocc.neocc.query_object(name='433', tab='orbit_properties',
+                                          orbital_elements="keplerian", orbit_epoch="middle")
+    check_tab_result_basic(result_lst, 3)
+
+    elements, cov, cor = result_lst
+    assert elements.meta["Title"] == 'Orbital Elements'
+    check_table_structure(elements, 30, elt_cols, str_cols=[0, 1, 2])
+    check_keplarian_elements(elements)
+
+    check_table_structure(cov, 6, ["COV"]+mat_cols, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cov["COV"], mat_cols)])
+
+    check_table_structure(cor, 6, ["COR"]+mat_cols, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cor["COR"], mat_cols)])
+
+    # 99942
+    result_lst = neocc.neocc.query_object(name='99942', tab='orbit_properties',
+                                          orbital_elements="keplerian", orbit_epoch="present")
+    check_tab_result_basic(result_lst, 3)
+
+    elements, cov, cor = result_lst
+    assert elements.meta["Title"] == 'Orbital Elements'
+    check_table_structure(elements, 34, elt_cols, str_cols=[0, 1, 2])
+    check_keplarian_elements(elements)
+
+    elt_dict = {}
+    elt_dict[1] = ['APHELION', 'APHELION', '1.0993332924301829E+00']
+    elt_dict[5] = ['HEADER', 'refsys', 'ECLM J2000']
+    elt_dict[8] = ['Keplerian elements', 'i', '3.338871063790']
+    elt_dict[13] = ['MJD', '59400.000000000', 'MJD']
+    elt_dict[15] = ['Non-gravitational parameters', 'model used', '1']
+    elt_dict[23] = ['RMS', 'a', '8.56356E-11']
+    elt_dict[-1] = ['dynamical parameters', 'Yarkovsky parameter [1E-10 au/day^2]', '-2.90058798774592E-04']
+    check_table_values(elements, elt_dict)
+
+    check_table_structure(cov, 7, ["COV"]+mat_cols+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cov["COV"], mat_cols+yp)])
+
+    cov_arr = np.array([[7.33345e-21, -1.07291e-19, -4.17667e-18, 9.88485e-17,
+                         -1.66141e-16, 6.52400e-17, 1.59727e-16],
+                        [-1.07291e-19, 2.01971e-18, 7.45344e-17, -2.21891e-15,
+                         3.44585e-15, -1.24650e-15, -1.95561e-15],
+                        [-4.17667e-18, 7.45344e-17, 2.56004e-14, -1.19845e-12,
+                         1.30800e-12, -1.64125e-13, -2.36124e-13],
+                        [9.88485e-17, -2.21891e-15, -1.19845e-12, 6.20671e-11,
+                         -6.63402e-11, 7.10922e-12, 1.03331e-11],
+                        [-1.66141e-16, 3.44585e-15, 1.30800e-12, -6.63402e-11,
+                         7.15522e-11, -8.20513e-12, -1.19951e-11],
+                        [6.52400e-17, -1.24650e-15, -1.64125e-13, 7.10922e-12,
+                         -8.20513e-12, 1.39769e-12, 2.02709e-12],
+                        [1.59727e-16, -1.95561e-15, -2.36124e-13, 1.03331e-11,
+                         -1.19951e-11, 2.02709e-12, 5.54961e-12]])
+    assert np.isclose(np.array(cov[mat_cols+yp].as_array().tolist()), cov_arr, atol=0, rtol=1e-5).all()
+
+    check_table_structure(cor, 7, ["COR"]+mat_cols+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cor["COR"], mat_cols+yp)])
+
+    cor_arr = np.array([[1.000000, -0.881591, -0.304826, 0.146516, -0.229357, 0.644397, 0.791761],
+                        [-0.881591, 1.000000, 0.327784, -0.198182, 0.286642, -0.741892, -0.584125],
+                        [-0.304826, 0.327784, 1.000000, -0.950752, 0.966435, -0.867651, -0.626448],
+                        [0.146516, -0.198182, -0.950752, 1.000000, -0.995485, 0.763282, 0.556761],
+                        [-0.229357, 0.286642, 0.966435, -0.995485, 1.000000, -0.820479, -0.601952],
+                        [0.644397, -0.741892, -0.867651, 0.763282, -0.820479, 1.000000, 0.727841],
+                        [0.791761, -0.584125, -0.626448, 0.556761, -0.601952, 0.727841, 1.000000]])
+    assert np.isclose(np.array(cor[mat_cols+yp].as_array().tolist()), cor_arr, atol=0, rtol=1e-5).all()
+
+    # 99942 modif
+    result_lst = neocc.neocc.query_object(name='99942 modif', tab='orbit_properties',
+                                          orbital_elements="keplerian", orbit_epoch="present")
+    check_tab_result_basic(result_lst, 3)
+
+    elements, cov, cor = result_lst
+    assert elements.meta["Title"] == 'Orbital Elements'
+    check_table_structure(elements, 34, elt_cols, str_cols=[0, 1, 2])
+    check_keplarian_elements(elements)
+
+    check_table_structure(cov, 7, ["COV"]+mat_cols+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cov["COV"], mat_cols+yp)])
+
+    check_table_structure(cor, 7, ["COR"]+mat_cols+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cor["COR"], mat_cols+yp)])
+
+    # 2009BD
+    result_lst = neocc.neocc.query_object(name='2009BD', tab='orbit_properties',
+                                          orbital_elements="keplerian", orbit_epoch="present")
+    check_tab_result_basic(result_lst, 3)
+
+    elements, cov, cor = result_lst
+    assert elements.meta["Title"] == 'Orbital Elements'
+    check_table_structure(elements, 35, elt_cols, str_cols=[0, 1, 2])
+    check_keplarian_elements(elements)
+
+    check_table_structure(cov, 8, ["COV"]+mat_cols+amr+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cov["COV"], mat_cols+amr+yp)])
+
+    check_table_structure(cor, 8, ["COR"]+mat_cols+amr+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cor["COR"], mat_cols+amr+yp)])
+
+    # 594938 2021GE13
+    result_lst = neocc.neocc.query_object(name='594938 2021GE13', tab='orbit_properties',
+                                          orbital_elements="keplerian", orbit_epoch="present")
+    check_tab_result_basic(result_lst, 3)
+
+    elements, cov, cor = result_lst
+    assert elements.meta["Title"] == 'Orbital Elements'
+    check_table_structure(elements, 30, elt_cols, str_cols=[0, 1, 2])
+    check_keplarian_elements(elements)
+
+    check_table_structure(cov, 6, ["COV"]+mat_cols, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cov["COV"], mat_cols)])
+
+    check_table_structure(cor, 6, ["COR"]+mat_cols, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cor["COR"], mat_cols)])
+
+
+def check_equinoctial_elements(elt_tab):
+    secs = ["Equinoctial elements", "RMS", "EIG", "WEA"]
+    assert all([x in elt_tab['Section'] for x in secs])
+
+
+def test_tabs_equi_orbit_properties(patch_get):
+    """Check data: asteroid orbit properties tab
+    """
+
+    # Assert blank file
+    with pytest.raises(ValueError):
+        neocc.neocc.query_object(name='foo', tab='orbit_properties',
+                                 orbital_elements='equinoctial', orbit_epoch='middle')
+    # Assert KeyError in case some kwargs is missing
+    with pytest.raises(KeyError):
+        neocc.neocc.query_object(name='99942', tab='orbit_properties')
+    with pytest.raises(KeyError):
+        neocc.neocc.query_object(name='99942', tab='orbit_properties', orbit_epoch='middle')
+
+    elt_cols = ['Section', 'Property', 'Value']
+    mat_cols = ['a', 'e*sin(LP)', 'e*cos(LP)', 'tan(i/2)*sin(LN)', 'tan(i/2)*cos(LN)', 'mean long.']
+    amr = ["Area-to-mass ratio [m^2/t]"]
+    yp = ["Yarkovsky parameter [1E-10 au/day^2]"]
+
+    # 433
+    result_lst = neocc.neocc.query_object(name='433', tab='orbit_properties',
+                                          orbital_elements="equinoctial", orbit_epoch="middle")
+    check_tab_result_basic(result_lst, 3)
+
+    elements, cov, nor = result_lst
+    assert elements.meta["Title"] == 'Orbital Elements'
+    check_table_structure(elements, 32, elt_cols, str_cols=[0, 1, 2])
+    check_equinoctial_elements(elements)
+
+    check_table_structure(cov, 6, ["COV"]+mat_cols, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cov["COV"], mat_cols)])
+
+    check_table_structure(nor, 6, ["NOR"]+mat_cols, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(nor["NOR"], mat_cols)])
+
+    # 99942
+    result_lst = neocc.neocc.query_object(name='99942', tab='orbit_properties',
+                                          orbital_elements="equinoctial", orbit_epoch="present")
+    check_tab_result_basic(result_lst, 3)
+
+    elements, cov, nor = result_lst
+    assert elements.meta["Title"] == 'Orbital Elements'
+    check_table_structure(elements, 38, elt_cols, str_cols=[0, 1, 2])
+    check_equinoctial_elements(elements)
+
+    check_table_structure(cov, 7, ["COV"]+mat_cols+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cov["COV"], mat_cols+yp)])
+
+    check_table_structure(nor, 7, ["NOR"]+mat_cols+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(nor["NOR"], mat_cols+yp)])
+
+    # 99942 modif
+    result_lst = neocc.neocc.query_object(name='99942 modif', tab='orbit_properties',
+                                          orbital_elements="equinoctial", orbit_epoch="present")
+    check_tab_result_basic(result_lst, 3)
+
+    elements, cov, nor = result_lst
+    assert elements.meta["Title"] == 'Orbital Elements'
+    check_table_structure(elements, 38, elt_cols, str_cols=[0, 1, 2])
+    check_equinoctial_elements(elements)
+
+    check_table_structure(cov, 7, ["COV"]+mat_cols+amr, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cov["COV"], mat_cols+amr)])
+
+    check_table_structure(nor, 7, ["NOR"]+mat_cols+amr, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(nor["NOR"], mat_cols+amr)])
+
+    # 2009BD
+    result_lst = neocc.neocc.query_object(name='2009BD', tab='orbit_properties',
+                                          orbital_elements="equinoctial", orbit_epoch="present")
+    check_tab_result_basic(result_lst, 3)
+
+    elements, cov, nor = result_lst
+    assert elements.meta["Title"] == 'Orbital Elements'
+    check_table_structure(elements, 41, elt_cols, str_cols=[0, 1, 2])
+    check_equinoctial_elements(elements)
+
+    elt_dict = {}
+    elt_dict[0] = ['EIG', 'a', '8.12187E-13']
+    elt_dict[8] = ['Equinoctial elements', 'a', '1.0617101378986786E+00']
+    elt_dict[14] = ['HEADER', 'format', 'OEF2.0']
+    elt_dict[20] = ['Non-gravitational parameters', 'number of model parameters', '2']
+    elt_dict[28] = ['RMS', 'mean long.', '4.53546E-04']
+    elt_dict[31] = ['WEA', 'a', '0.00000']
+    elt_dict[39] = ['dynamical parameters', 'Area-to-mass ratio [m^2/t]', '3.92228537753657E-01']
+    check_table_values(elements, elt_dict)
+
+    check_table_structure(cov, 8, ["COV"]+mat_cols+amr+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cov["COV"], mat_cols+amr+yp)])
+
+    cov_arr = np.array([[9.04599e-15, -4.31003e-15, -3.62392e-15, 7.95127e-16,
+                         2.43344e-16, -4.07755e-11, 1.85660e-09, 1.12741e-10],
+                        [-4.31003e-15, 2.85269e-15, 1.69501e-15, -5.10761e-16,
+                         -1.58248e-16, 2.13425e-11, -8.85040e-10, -3.39506e-11],
+                        [-3.62392e-15, 1.69501e-15, 2.00243e-15, -3.16832e-16,
+                         -9.41627e-17, 1.91993e-11, -1.45800e-09, -5.21481e-11],
+                        [7.95127e-16, -5.10761e-16, -3.16832e-16, 1.21840e-16,
+                         4.22057e-17, -3.75684e-12, 1.12170e-10, 5.57202e-12],
+                        [2.43344e-16, -1.58248e-16, -9.41627e-17, 4.22057e-17,
+                         1.54096e-17, -1.11187e-12, 2.17181e-11, 1.46083e-12],
+                        [-4.07755e-11, 2.13425e-11, 1.91993e-11, -3.75684e-12,
+                         -1.11187e-12, 2.05703e-07, -1.27011e-05, -5.03173e-07],
+                        [1.85660e-09, -8.85040e-10, -1.45800e-09, 1.12170e-10,
+                         2.17181e-11, -1.27011e-05, 1.47473e-03, 3.42081e-05],
+                        [1.12741e-10, -3.39506e-11, -5.21481e-11, 5.57202e-12,
+                         1.46083e-12, -5.03173e-07, 3.42081e-05, 2.02074e-06]])
+    assert np.isclose(np.array(cov[mat_cols+amr+yp].as_array().tolist()), cov_arr, atol=0, rtol=1e-5).all()
+
+    check_table_structure(nor, 8, ["NOR"]+mat_cols+amr+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(nor["NOR"], mat_cols+amr+yp)])
+
+    nor_arr = np.array([[1.510392e+24, 3.010614e+22, -2.847190e+22, -3.923755e+22,
+                         7.119194e+22, 3.165996e+20, 1.559455e+18, -3.200500e+19],
+                        [3.010614e+22, 6.121981e+20, -5.623474e+20, -7.986576e+20,
+                         1.446145e+21, 6.307818e+18, 3.107870e+16, -6.382017e+17],
+                        [-2.847190e+22, -5.623474e+20, 5.389508e+20, 7.325948e+20,
+                         -1.330387e+21, -5.969337e+18, -2.939908e+16, 6.032061e+17],
+                        [-3.923755e+22, -7.986576e+20, 7.325948e+20, 1.042952e+21,
+                         -1.888458e+21, -8.220830e+18, -4.050471e+16, 8.317909e+17],
+                        [7.119194e+22, 1.446145e+21, -1.330387e+21, -1.888458e+21,
+                         3.420540e+21, 1.491642e+19, 7.349240e+16, -1.509124e+18],
+                        [3.165996e+20, 6.307818e+18, -5.969337e+18, -8.220830e+18,
+                         1.491642e+19, 6.636445e+16, 3.268853e+14, -6.708642e+15],
+                        [1.559455e+18, 3.107870e+16, -2.939908e+16, -4.050471e+16,
+                         7.349240e+16, 3.268853e+14, 1.610115e+12, -3.304453e+13],
+                        [-3.200500e+19, -6.382017e+17, 6.032061e+17, 8.317909e+17,
+                         -1.509124e+18, -6.708642e+15, -3.304453e+13, 6.781869e+14]])
+    assert np.isclose(np.array(nor[mat_cols+amr+yp].as_array().tolist()), nor_arr, atol=0, rtol=1e-5).all()
+
+    # 594938 2021GE13
+    result_lst = neocc.neocc.query_object(name='99942', tab='orbit_properties',
+                                          orbital_elements="equinoctial", orbit_epoch="present")
+    check_tab_result_basic(result_lst, 3)
+
+    elements, cov, nor = result_lst
+    assert elements.meta["Title"] == 'Orbital Elements'
+    check_table_structure(elements, 38, elt_cols, str_cols=[0, 1, 2])
+    check_equinoctial_elements(elements)
+
+    check_table_structure(cov, 7, ["COV"]+mat_cols+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(cov["COV"], mat_cols+yp)])
+
+    check_table_structure(nor, 7, ["NOR"]+mat_cols+yp, str_cols=[0], float_cols=slice(1, None))
+    all([x == y for x, y in zip(nor["NOR"], mat_cols+yp)])
+
+
+def test_tabs_ephemerides(patch_get):
+    """Check data: asteroid ephemerides tab
+    """
+
+    # Assert blank file
+    with pytest.raises(ValueError):
+        neocc.neocc.query_object(name='foo', tab='ephemerides', observatory='500', start='2021-10-01 00:00',
+                                 stop='2021-10-01 00:00', step='1', step_unit='days')
+    # Assert KeyError in case some kwargs is missing
+    with pytest.raises(KeyError):
+        neocc.neocc.query_object(name='99942', tab='ephemerides')
+    with pytest.raises(KeyError):
+        neocc.neocc.query_object(name='99942', tab='ephemerides',
+                                 observatory='500', stop='2021-10-01 00:00',
+                                 step='1', step_unit='days')
+    with pytest.raises(KeyError):
+        neocc.neocc.query_object(name='99942', tab='ephemerides',
+                                 observatory='500', start='2021-10-01 00:00',
+                                 step='1', step_unit='days')
+    with pytest.raises(KeyError):
+        neocc.neocc.query_object(name='99942', tab='ephemerides',
+                                 observatory='500', start='2021-10-01 00:00',
+                                 stop='2021-10-02 00:00', step_unit='days')
+    with pytest.raises(KeyError):
+        neocc.neocc.query_object(name='516976 2012HM1', tab='ephemerides',
+                                 observatory='500', start='2021-10-01 00:00',
+                                 stop='2021-10-02 00:00', step='2')
+
+    ephem_columns = ['Date', 'MJD (UTC)', 'RA (h  m  s)', 'DEC (d  \'  ")', 'Mag', 'Alt (deg)', 'Airmass',
+                     'Sun elev. (deg)', 'SolEl (deg)', 'LunEl (deg)', 'Phase (deg)', 'Glat (deg)',
+                     'Glon (deg)', 'R (au)', 'Delta (au)', 'RA*cosDE ("/min)', 'DEC ("/min)',
+                     'Vel ("/min)', 'PA (deg)', 'Err1 (")', 'Err2 (")', 'AngAx (deg)']
+
+    # 99942
+    eph_lst = neocc.neocc.query_object(name='99942', tab='ephemerides', observatory='500',
+                                       start='2019-05-08 01:30', stop='2019-05-23 00:00',
+                                       step='1', step_unit='days')
+    assert len(eph_lst) == 1
+
+    eph = eph_lst[0]
+
+    # Checking the metadata
+    assert eph.meta['Observatory'] == '500 - Geocentric'
+    assert eph.meta['Initial Date'] == '2019/05/08 01:30 UTC'
+    assert eph.meta['Final Date'] == '2019/05/23 00:00 UTC'
+    assert eph.meta['Time step'] == '1 days'
+
+    # Checking the table
+    check_table_structure(eph, 15, ephem_columns, str_cols=[2, 3], time_cols=[0],
+                          float_cols=[1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21])
+    eph_dict = {4: [Time('2019-05-12T01:30:00.000'), 58615.0625, '6 58 15.428', '+20 35  9.86', 21.59, 0.0,
+                    np.inf, 0.0, -52.9, 37.6, 47.1, 10.7, 195.1, 1.099, 1.358, 2.1221, -0.1475, 2.1273, 94.0,
+                    0.001, 0.0, 122.9]}
+    check_table_values(eph, eph_dict)
+
+    # 516976 2012HM1
+    eph_lst = neocc.neocc.query_object(name='516976 2012HM1', tab='ephemerides', observatory='J75',
+                                       start='2020-09-01 00:00', stop='2020-09-02 00:00',
+                                       step='5', step_unit='hours')
+    assert len(eph_lst) == 1
+
+    eph = eph_lst[0]
+
+    # Checking the metadata
+    assert eph.meta['Observatory'] == 'J75 - OAM Observatory, La Sagra'
+    assert eph.meta['Initial Date'] == '2020/09/01 00:00 UTC'
+    assert eph.meta['Final Date'] == '2020/09/02 00:00 UTC'
+    assert eph.meta['Time step'] == '5 hours'
+
+    # Checking the table
+    check_table_structure(eph, 5, ephem_columns, str_cols=[2, 3], time_cols=[0],
+                          float_cols=[1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21])
+    eph_dict = {0: [Time('2020-09-01T00:00:00.000'), 59093.0, '9 42 59.688', '+ 8  9 39.70', 26.64, -42.6,
+                    np.inf, -43.8, 14.5, 169.8, 5.6, 41.6, 226.9, 2.603, 3.568, 0.9632, -0.327, 1.0172, 108.7,
+                    0.014, 0.008, 113.3]}
+    check_table_values(eph, eph_dict)
diff --git a/astroquery/esa/neocc/test/test_neocc_remote.py b/astroquery/esa/neocc/test/test_neocc_remote.py
new file mode 100644
index 0000000000..76de3c103d
--- /dev/null
+++ b/astroquery/esa/neocc/test/test_neocc_remote.py
@@ -0,0 +1,543 @@
+# -*- coding: utf-8 -*-
+"""
+This module contains all the remote tests. The data for these
+tests is requested to ESA NEOCC portal.
+
+* Project: NEOCC portal Python interface
+* Property: European Space Agency (ESA)
+* Developed by: Elecnor Deimos
+* Author: C. Álvaro Arroyo Parejo
+* Date: 21-08-2022
+"""
+
+import os
+import re
+import random
+import pytest
+import requests
+import warnings
+
+import numpy as np
+
+from astropy.table import Table
+from astropy.time import Time
+
+from astroquery.esa import neocc
+
+# Import BASE URL and TIMEOUT
+API_URL = neocc.conf.API_URL
+DATA_DIR = os.path.join(os.path.dirname(__file__), 'data')
+TIMEOUT = neocc.conf.TIMEOUT
+VERIFICATION = neocc.conf.SSL_CERT_VERIFICATION
+
+
+@pytest.mark.filterwarnings('ignore:ERFA function *:erfa.core.ErfaWarning')
+@pytest.mark.remote_data
+class TestLists:
+    """Class which contains the unitary tests for lists module.
+
+    Ignore ERFA 'dubious year' warnings because they are expected.
+    """
+    # Dictionary for lists
+    lists_dict = {
+        "nea_list": 'allneo.lst',
+        "updated_nea": 'updated_nea.lst',
+        "monthly_update": 'monthly_update.done',
+        "risk_list": 'esa_risk_list',
+        "risk_list_special": 'esa_special_risk_list',
+        "close_approaches_upcoming": 'esa_upcoming_close_app',
+        "close_approaches_recent": 'esa_recent_close_app',
+        "priority_list": 'esa_priority_neo_list',
+        "priority_list_faint": 'esa_faint_neo_list',
+        "close_encounter": 'close_encounter2.txt',
+        "impacted_objects": 'past_impactors_list',
+        "neo_catalogue_current": 'neo_kc.cat',
+        "neo_catalogue_middle": 'neo_km.cat'
+    }
+
+    # Ignore the FutureWarning that only comes up with the oldest dependencies
+    warnings.filterwarnings("ignore", category=FutureWarning,
+                            message="Conversion of the second argument of issubdtype*")
+
+    def test_get_list_url(self):
+        """Test for checking the URL termination for requested lists.
+        Check invalid list name raise KeyError.
+        """
+        # Valid inputs
+        valid_names = ["nea_list", "updated_nea", "monthly_update",
+                       "risk_list", "risk_list_special",
+                       "close_approaches_upcoming",
+                       "close_approaches_recent",
+                       "priority_list", "priority_list_faint",
+                       "close_encounter", "impacted_objects"]
+        # Invalid inputs
+        bad_names = ["ASedfe", "%&$", "ÁftR+", 154]
+        # Assert for valid names
+        for element in valid_names:
+            assert neocc.lists.get_list_url(element) == self.lists_dict[element]
+        # Assert for invalid names
+        for elements in bad_names:
+            with pytest.raises(KeyError):
+                neocc.lists.get_list_url(elements)
+
+    def test_get_list_data(self):
+        """Check data obtained is an astropy Table
+        """
+        # Check pd.Series output
+        list_names = ["nea_list", "updated_nea", "monthly_update", "risk_list", "risk_list_special",
+                      "close_approaches_upcoming", "close_approaches_recent", "priority_list",
+                      "close_encounter", "priority_list_faint", "impacted_objects"]
+        for series in list_names:
+            assert isinstance(neocc.lists.get_list_data(self.lists_dict[series], series), Table)
+
+    def test_parse_list(self):
+        """Check data obtained is an astropy Table
+        """
+        # Check pd.Series output
+        url_list = ["nea_list", "updated_nea", "monthly_update", "risk_list", "risk_list_special",
+                    "close_approaches_upcoming", "close_approaches_recent", "priority_list",
+                    "close_encounter", "priority_list_faint", "impacted_objects"]
+
+        for url in url_list:
+            # Get data from URL
+            data_list = requests.get(API_URL + self.lists_dict[url],
+                                     timeout=TIMEOUT,
+                                     verify=VERIFICATION).content
+            # Decode the data using UTF-8
+            data_list_d = data_list.decode('utf-8')
+
+            assert isinstance(neocc.lists.parse_list(url, data_list_d), Table)
+
+        # Invalid inputs
+        bad_names = ["ASedfe", "%&$", "ÁftR+", 154]
+        # Assert for invalid names
+        for elements in bad_names:
+            with pytest.raises(KeyError):
+                neocc.lists.parse_list(elements, data_list_d)
+
+    def test_parse_nea(self):
+        """Check data: nea list, updated nea list and monthly update
+        """
+        url_series = ["nea_list", "updated_nea", "monthly_update"]
+        for url in url_series:
+            # Get data from URL
+            data_list = requests.get(API_URL + self.lists_dict[url],
+                                     timeout=TIMEOUT,
+                                     verify=VERIFICATION).content
+            # Decode the data using UTF-8
+            data_list_d = data_list.decode('utf-8')
+            # Parse using parse_nea
+            new_list = neocc.lists.parse_nea(data_list_d)
+            # Assert is a pandas Series
+            assert isinstance(new_list, Table)
+            # Assert is not empty
+            assert len(new_list)
+
+            # List of all NEAs
+            if url == "nea_list":
+
+                # Check size of the result
+                assert len(new_list) > 20000
+
+                filename = os.path.join(DATA_DIR, "allnea.csv")
+                nea_list = Table.read(filename, format="ascii.csv")
+
+                # Check 74 first elements are equal from reference data
+                # (since provisional designator may change)
+                assert (new_list[:74] == nea_list[:74]).all()
+            else:
+                # Check date format DDD MMM DD HH:MM:SS UTC YYYY
+                assert re.match(r'\w{3} \w{3} \d{2} \d{2}:\d{2}:\d{2} \w{3} \d{4}', new_list["NEA"][0])
+
+    def test_parse_risk(self):
+        """Check data: risk_list, risk_list_special
+        """
+        url_risks = ['risk_list', 'risk_list_special']
+        # Columns of risk lists
+        risk_columns = ['Object Name', 'Diameter in m', '*=Y',
+                        'Date/Time', 'IP max', 'PS max', 'TS',
+                        'Vel in km/s', 'First Year', 'Last Year',
+                        'IP cum', 'PS cum']
+        risk_special_columns = risk_columns[0:8]
+
+        for url in url_risks:
+            # Get data from URL
+            data_list = requests.get(API_URL + self.lists_dict[url],
+                                     timeout=TIMEOUT,
+                                     verify=VERIFICATION).content
+            # Decode te data using UTF-8
+            data_list_d = data_list.decode('utf-8')
+
+            # Parse using parse_risk
+            new_list = neocc.lists.parse_risk(data_list_d)
+            assert isinstance(new_list, Table)
+
+            if url == 'risk_list':
+
+                # Assert dataframe is not empty, columns names, length
+                assert len(new_list)
+                assert all([x == y for x, y in zip(new_list.colnames, risk_columns)])
+                assert len(new_list) > 1000
+
+                # Assert columns data types
+                # Floats
+                float_cols = ['Diameter in m', 'IP max', 'PS max', 'Vel in km/s', 'IP cum', 'PS cum']
+                assert all([np.issubdtype(new_list[x].dtype, float) for x in float_cols])
+
+                # int64
+                int_cols = ['TS', 'First Year', 'Last Year']
+                assert all([np.issubdtype(new_list[x].dtype, int) for x in int_cols])
+
+                # String
+                str_cols = ['Object Name', '*=Y']
+                assert all([np.issubdtype(new_list[x].dtype, str) for x in str_cols])
+
+                # Datetime
+                assert isinstance(new_list['Date/Time'], Time)
+
+            else:
+                # Assert dataframe is not empty, columns names
+                assert len(new_list)
+                assert all([x == y for x, y in zip(new_list.colnames, risk_special_columns)])
+
+                # Assert columns data types
+                # Floats
+                float_cols = ['IP max', 'PS max', 'Vel in km/s']
+                assert all([np.issubdtype(new_list[x].dtype, float) for x in float_cols])
+
+                # ints
+                int_cols = ['TS', 'Diameter in m']
+                assert all([np.issubdtype(new_list[x].dtype, int) for x in int_cols])
+
+                # String
+                str_cols = ['Object Name', '*=Y']
+                assert all([np.issubdtype(new_list[x].dtype, str) for x in str_cols])
+
+    def test_parse_clo(self):
+        """Check data: close_approaches_upcoming,
+        close_approaches_recent
+        """
+        url_close = ['close_approaches_upcoming', 'close_approaches_recent']
+
+        # Columns of close approaches lists
+        close_columns = ['Object Name', 'Date',
+                         'Miss Distance in km', 'Miss Distance in au',
+                         'Miss Distance in LD', 'Diameter in m',
+                         '*=Yes', 'H', 'Max Bright',
+                         'Rel. vel in km/s']
+
+        for url in url_close:
+            # Get data from URL
+            data_list = requests.get(API_URL + self.lists_dict[url],
+                                     timeout=TIMEOUT,
+                                     verify=VERIFICATION).content
+
+            # Decode the data using UTF-8
+            data_list_d = data_list.decode('utf-8')
+
+            # Parse using parse_clo
+            new_list = neocc.lists.parse_clo(data_list_d)
+            assert isinstance(new_list, Table)
+
+            # Assert dataframe is not empty, columns names and length
+            assert len(new_list)
+            assert all([x == y for x, y in zip(new_list.colnames, close_columns)])
+            assert len(new_list) > 10
+
+            # Assert columns data types
+            # Floats
+            float_cols = ['Miss Distance in au', 'Miss Distance in LD', 'Diameter in m',
+                          'H', 'Max Bright', 'Rel. vel in km/s']
+            assert all([np.issubdtype(new_list[x].dtype, float) for x in float_cols])
+
+            # int64
+            assert np.issubdtype(new_list['Miss Distance in km'].dtype, int)
+
+            # Object
+            str_cols = ['Object Name', '*=Yes']
+            assert all([np.issubdtype(new_list[x].dtype, str) for x in str_cols])
+
+            # Datetime
+            assert isinstance(new_list['Date'], Time)
+
+    def test_parse_pri(self):
+        """Check data: priority_list, priority_list_faint
+        """
+        url_priority = ['priority_list', 'priority_list_faint']
+        # Columns of priority lists
+        priority_columns = ['Priority', 'Object',
+                            'R.A. in arcsec', 'Decl. in deg',
+                            'Elong. in deg', 'V in mag', 'Sky uncert.',
+                            'End of Visibility']
+
+        for url in url_priority:
+            # Get data from URL
+            data_list = requests.get(API_URL + self.lists_dict[url],
+                                     timeout=TIMEOUT,
+                                     verify=VERIFICATION).content
+            # Decode the data using UTF-8
+            data_list_d = data_list.decode('utf-8')
+            # Parse using parse_pri
+            new_list = neocc.lists.parse_pri(data_list_d)
+
+            # Assert is an astropy table
+            assert isinstance(new_list, Table)
+
+            # Assert table is not empty, columns names and length
+            assert len(new_list)
+            assert all([x == y for x, y in zip(new_list.colnames, priority_columns)])
+            assert len(new_list) > 100
+
+            # Assert columns data types
+            # Floats
+            float_cols = ['R.A. in arcsec', 'Decl. in deg', 'V in mag']
+            assert all([np.issubdtype(new_list[x].dtype, float) for x in float_cols])
+
+            # int64
+            int_cols = ['Priority', 'Elong. in deg', 'Sky uncert.']
+            assert all([np.issubdtype(new_list[x].dtype, int) for x in int_cols])
+
+            # Object
+            assert np.issubdtype(new_list["Object"].dtype, str)
+
+            # Datetime
+            assert isinstance(new_list['End of Visibility'], Time)
+
+    def test_parse_encounter(self):
+        """Check data: close_encounter
+        """
+        url = 'close_encounter'
+        # Columns of close approaches lists
+        encounter_columns = ['Name/desig', 'Planet', 'Date',
+                             'Time approach', 'Time uncert',
+                             'Distance', 'Minimum distance',
+                             'Distance uncertainty', 'Width',
+                             'Stretch', 'Probability', 'Velocity',
+                             'Max Mag']
+
+        # Get data from URL
+        data_list = requests.get(API_URL + self.lists_dict[url],
+                                 timeout=TIMEOUT,
+                                 verify=VERIFICATION).content
+        # Decode the data using UTF-8
+        data_list_d = data_list.decode('utf-8')
+        # Parse using parse_encounter
+        new_list = neocc.lists.parse_encounter(data_list_d)
+
+        # Assert is a pandas DataFrame
+        assert isinstance(new_list, Table)
+
+        # Assert dataframe is not empty, columns names and length
+        assert len(new_list)
+        assert all([x == y for x, y in zip(new_list.colnames, encounter_columns)])
+        assert len(new_list) > 100000
+
+        # Assert columns data types
+        # Floats
+        float_cols = encounter_columns[3:]
+        assert all([np.issubdtype(new_list[x].dtype, float) for x in float_cols])
+
+        # Str
+        str_cols = ['Name/desig', 'Planet']
+        assert all([np.issubdtype(new_list[x].dtype, str) for x in str_cols])
+
+        # Datetime
+        assert isinstance(new_list['Date'], Time)
+
+    def test_parse_impacted(self):
+        """Check data: impacted_objects
+        """
+        url = 'impacted_objects'
+        # Get data from URL
+        data_list = requests.get(API_URL + self.lists_dict[url],
+                                 timeout=TIMEOUT,
+                                 verify=VERIFICATION).content
+
+        # Decode the data using UTF-8
+        data_list_d = data_list.decode('utf-8')
+
+        # Parse using parse_impacted
+        new_list = neocc.lists.parse_impacted(data_list_d)
+
+        # Assert is an astropy Table
+        assert isinstance(new_list, Table)
+
+        # Assert Table is not empty and length
+        # Assert Table is not empty, columns names and length
+        assert len(new_list) != 0
+        assert len(new_list) < 100
+
+    def test_parse_neo_catalogue(self):
+        """Check data: close_encounter
+        """
+        url_cat = ['neo_catalogue_current',
+                   'neo_catalogue_middle']
+
+        # Columns of close approaches lists
+        cat_columns = ['Name', 'Epoch (MJD)', 'a', 'e', 'i',
+                       'long. node', 'arg. peric.', 'mean anomaly',
+                       'absolute magnitude', 'slope param.',
+                       'non-grav param.']
+
+        for url in url_cat:
+            # Get data from URL
+            data_list = requests.get(API_URL + self.lists_dict[url],
+                                     timeout=TIMEOUT,
+                                     verify=VERIFICATION).content
+
+            # Decode the data using UTF-8
+            data_list_d = data_list.decode('utf-8')
+
+            # Parse using parse_neo_catalogue
+            new_list = neocc.lists.parse_neo_catalogue(data_list_d)
+
+            # Assert is an astropy Table
+            assert isinstance(new_list, Table)
+
+            # Assert dataframe is not empty, columns names and length
+            assert len(new_list)
+            assert all([x == y for x, y in zip(new_list.colnames, cat_columns)])
+            assert len(new_list) > 10000
+
+            # Assert columns data types
+            # Floats
+            float_cols = ['Epoch (MJD)', 'a', 'e', 'i',
+                          'long. node', 'arg. peric.', 'mean anomaly',
+                          'absolute magnitude', 'slope param.']
+            assert all([np.issubdtype(new_list[x].dtype, float) for x in float_cols])
+
+            # Object
+            assert np.issubdtype(new_list['Name'].dtype, str)
+
+            # Int
+            assert np.issubdtype(new_list['non-grav param.'].dtype, int)
+
+
+@pytest.mark.filterwarnings('ignore:ERFA function *:erfa.core.ErfaWarning')
+@pytest.mark.remote_data
+class TestTabs:
+    """Class which contains the unitary tests for tabs module.
+    """
+    path_nea = os.path.join(DATA_DIR, 'allnea.csv')
+    nea_list = Table.read(path_nea, format="ascii.csv")
+
+    # Ignore the FutureWarning that only comes up with the oldest dependencies
+    warnings.filterwarnings("ignore", category=FutureWarning,
+                            message="Conversion of the second argument of issubdtype*")
+
+    def test_get_object_url(self):
+        """Test for checking the URL termination for requested object tab.
+        Check invalid list name raise KeyError.
+        """
+        # Dictionary for tabs
+        tab_dict = {
+            "impacts": '.risk',
+            "close_approaches": '.clolin',
+            "observations": '.rwo',
+            "physical_properties": '.phypro',
+            "orbit_properties": ['.ke0', '.ke1', '.eq0', '.eq1']
+        }
+
+        # Choose a random object from stored nea list
+        rnd_object = random.choice(self.nea_list["NEA"])
+
+        # Tabs to test
+        object_tabs = ['impacts', 'close_approaches',
+                       'observations', 'orbit_properties', '&cefrgfe',
+                       4851]
+
+        # Possible additional argument
+        orbital_element = ['keplerian', 'equinoctial']
+        orbit_epoch = ['present', 'middle']
+
+        # Iterate to obtain all possible urls
+        for tab in object_tabs:
+            if tab == 'orbit_properties':
+                for element in orbital_element:
+                    for epoch in orbit_epoch:
+                        with pytest.raises(ValueError):
+                            neocc.tabs.get_object_url(rnd_object, tab,
+                                                      orbital_elements=None,
+                                                      orbit_epoch=epoch)
+            elif tab in ['&cefrgfe', 4851]:
+                with pytest.raises(KeyError):
+                    neocc.tabs.get_object_url(rnd_object, tab)
+            else:
+                assert neocc.tabs.get_object_url(rnd_object, tab) ==\
+                    str(rnd_object).replace(' ', '%20') +\
+                    tab_dict[tab]
+
+    def test_get_object_data(self):
+        """Test for obtaining the content of a URL.
+        """
+        # Choose a random object from stored nea list
+        rnd_object = random.choice(self.nea_list["NEA"])
+
+        # Tabs used in url function
+        object_tabs = ['impacts', 'close_approaches',
+                       'observations', 'orbit_properties',
+                       'physical_properties']
+
+        # Possible additional argument
+        orbital_element = ['keplerian', 'equinoctial']
+        orbit_epoch = ['present', 'middle']
+
+        # Iterate to obtain all possible urls
+        for tab in object_tabs:
+            if tab == 'orbit_properties':
+                for element in orbital_element:
+                    for epoch in orbit_epoch:
+                        url = neocc.tabs.get_object_url(rnd_object, tab,
+                                                        orbital_elements=element,
+                                                        orbit_epoch=epoch)
+                        assert isinstance(neocc.tabs.get_object_data(url), bytes)
+            else:
+                url = neocc.tabs.get_object_url(rnd_object, tab)
+                assert isinstance(neocc.tabs.get_object_data(url), bytes)
+
+    @classmethod
+    def test_tabs_names(cls):
+        """Test is a invalid name
+        """
+        # Invalid inputs
+        bad_names = ["ASedfe", "%&$", "ÁftR+", 154]
+        for element in bad_names:
+            with pytest.raises(KeyError):
+                neocc.neocc.query_object(name='433', tab=element)
+
+    def test_tabs_summary(self):
+        """Check data: summary tab
+        """
+        # Check value error if empty
+        with pytest.raises(ValueError):
+            neocc.neocc.query_object(name='foo', tab='summary')
+
+        # Choose a random object from stored nea list
+        rnd_object = random.choice(self.nea_list["NEA"])
+
+        # Request summary and check types
+        result_list = neocc.neocc.query_object(name=rnd_object, tab='summary')
+        assert isinstance(result_list, list)
+        summary = result_list[0]
+        assert isinstance(summary, Table)
+        assert 'Discovery Date' in summary.meta.keys()
+        assert 'Observatory' in summary.meta.keys()
+
+        # Assert size of physical properties file
+        assert len(summary)
+        summary_cols = ['Physical Properties', 'Value', 'Units']
+        assert all([x == y for x, y in zip(summary.colnames, summary_cols)])
+
+        # Assert dtype
+        assert all([np.issubdtype(summary[x].dtype, str) for x in summary_cols])
+
+        # Check specific asteroids that will remain inmutable
+        ast_summ1 = neocc.neocc.query_object(name='433', tab='summary')[0]
+        assert ast_summ1.meta["Observatory"] == 'Berlin (1835-1913)'
+        assert ast_summ1.meta["Discovery Date"] == '1898-08-13'
+
+        # Check asteroid with no observatory nor discovery date
+        # This object may change
+        ast_summ2 = neocc.neocc.query_object(name='2006BV4', tab='summary')[0]
+        assert "Observatory" not in ast_summ2.meta
+        assert "Discovery Date" not in ast_summ2.meta
diff --git a/astroquery/esa/neocc/utils.py b/astroquery/esa/neocc/utils.py
new file mode 100644
index 0000000000..6cc464f743
--- /dev/null
+++ b/astroquery/esa/neocc/utils.py
@@ -0,0 +1,41 @@
+# Useful general purpose functions for NEOCC
+import numpy as np
+
+from astropy.time import Time, TimeDelta
+
+
+def convert_time(date_col, time_col=None, conversion_string=None):
+    """
+    Converte date/time column(s) and turn them into an astropy Time object.
+
+    Parameters
+    ----------
+    date_col : `astropy.table.Column`
+        The column with dates (or datetime) strings in it.
+    time_col : `astropy.table.Column`
+        Optional. Column with only time strings.
+    conversion_string : str
+        Optional. If the date(time) string are in a non-standard format
+        the conversion string will be used with `astropy.time.Time.strptime`
+        to create the Time object.
+
+    Returns
+    -------
+    response : `astropy.time.Time`
+        The converted time column as an astropy Time object.
+    """
+
+    if time_col is None:
+        day, tme = np.array([x.split(".") for x in date_col]).swapaxes(0, 1)
+        time_delta = TimeDelta([float("." + x) for x in tme], format='jd')
+
+    else:
+        day = np.array(date_col)
+        time_delta = TimeDelta(time_col, format="jd")
+
+    if conversion_string:
+        time_obj = Time.strptime(day, conversion_string)
+    else:
+        time_obj = Time(day)
+
+    return time_obj + time_delta
diff --git a/astroquery/solarsystem/neocc/__init__.py b/astroquery/solarsystem/neocc/__init__.py
new file mode 100644
index 0000000000..bc7e3da36e
--- /dev/null
+++ b/astroquery/solarsystem/neocc/__init__.py
@@ -0,0 +1,12 @@
+# Licensed under a 3-clause BSD style license - see LICENSE.rst
+
+"""
+astroquery.solarsystem.neocc
+--------------------------
+
+a collection of data services provided by NEOCC
+"""
+
+from astroquery.esa.neocc import neocc, NEOCCClass
+
+__all__ = ["neocc", "NEOCCClass"]
diff --git a/docs/esa/neocc/neocc.rst b/docs/esa/neocc/neocc.rst
new file mode 100644
index 0000000000..ee050d1868
--- /dev/null
+++ b/docs/esa/neocc/neocc.rst
@@ -0,0 +1,358 @@
+
+.. _astroquery.esa.neocc:
+
+***********************************************************************************************
+ESA NEOCC Portal Python Interface Library (`astroquery.esa.neocc`/astroquery.solarsystem.neocc)
+***********************************************************************************************
+
+The ESA NEO Coordination Centre (NEOCC) is the operational centre of ESA’s Planetary Defence Office
+PDO) within the Space Safety Programme (S2P). Its aim is to coordinate and contribute to the
+observation of small Solar System bodies in order to evaluate and monitor the threat coming from 
+near-Earth objects (NEOs).
+
+ESA NEOCC Portal Python interface library makes the data that `ESA NEOCC <https://neo.ssa.esa.int/>`_
+provides easily accessible through a Python program.
+
+The main functionality of this library is to allow a programmer to easily retrieve:
+
+* All the NEAs
+* Other data that the NEOCC provides (risk list, close approach list, etc.)
+* All basic and advanced information regarding a NEA
+* An ephemeris service for NEAs
+
+============================
+Getting ESA NEOCC's products
+============================
+
+--------------------------------
+1. Direct download of list files
+--------------------------------
+
+This function allows the user to download the requested list data from ESA NEOCC.
+Different lists that can be requested are:
+
+* All NEA list: ``nea_list``
+* Catalogue of NEAs (current date): ``neo_catalogue_current``
+* Catalogue of NEAs (middle arc): ``neo_catalogue_middle``
+* Updated NEA list: ``updated_nea``
+* Monthly computation date: ``monthly_update``
+* Risk list (normal): ``risk_list``
+* Risk list (special): ``risk_list_special``
+* Close approaches (upcoming): ``close_approaches_upcoming``
+* Close approaches (recent): ``close_approaches_recent``
+* Priority list (normal): ``priority_list``
+* Priority list (faint): ``priority_list_faint``
+* Close encounter list: ``close_encounter``
+* Impacted objects: ``impacted_objects``
+ 
+These lists are referenced in `<https://neo.ssa.esa.int/computer-access>`_.
+
+--------
+Examples
+--------
+
+NEA list
+^^^^^^^^
+
+The output of this list is a `~astropy.table.Table` which contains the list of all NEAs
+currently considered in the NEOCC system.
+
+.. doctest-remote-data::
+
+    >>> from astroquery.esa.neocc import neocc
+    >>> list_data = neocc.query_list(list_name='nea_list')
+    >>> print(list_data)  # doctest: +IGNORE_OUTPUT
+        NEA     
+    ------------
+        433 Eros
+      719 Albert
+      887 Alinda
+    1036 Ganymed
+       1221 Amor
+             ...
+          2023RJ
+          2023RK
+          2023RL
+          2023RM
+          6344P-L
+    Length = 32564 rows
+
+
+Each asteroid can be accessed using its index. This information can
+be used as input for :meth:`~astroquery.esa.neocc.NEOCCClass.query_object` method.
+
+.. doctest-remote-data::
+
+    >>> print(list_data["NEA"][4])
+    1221 Amor
+
+Close approaches
+^^^^^^^^^^^^^^^^
+
+The output of this list is a `~astropy.table.Table` which
+contains information about asteroid close approaches.
+
+.. doctest-remote-data::
+
+    >>> from astroquery.esa.neocc import neocc
+    >>> list_data = neocc.query_list(list_name='close_approaches_upcoming')
+    >>> print(list_data)  # doctest: +IGNORE_OUTPUT
+    Object Name           Date          ... Rel. vel in km/s CAI index
+    ----------- ----------------------- ... ---------------- ---------
+        2021JA5 2023-09-07 00:00:00.000 ...             11.0     3.496
+        2023QC5 2023-09-08 00:00:00.000 ...              7.6     2.662
+         2020GE 2023-09-08 00:00:00.000 ...              1.4     3.308
+         2023RH 2023-09-08 00:00:00.000 ...             19.1     2.114
+         2023RG 2023-09-08 00:00:00.000 ...             12.5     3.242
+            ...                     ... ...              ...       ...
+       2012SX49 2024-08-29 00:00:00.000 ...              4.3     2.665
+       2016RJ20 2024-08-30 00:00:00.000 ...             14.8     2.118
+         2021JT 2024-09-02 00:00:00.000 ...              8.3     4.216
+       2021RB16 2024-09-02 00:00:00.000 ...              8.5     3.685
+        2007RX8 2024-09-02 00:00:00.000 ...              7.0     2.322
+    Length = 182 rows
+
+
+**Note:** If the contents request fails the following message will be printed:
+
+*Initial attempt to obtain list failed. Reattempting...*
+
+Then a second request will be automatically sent to the NEOCC portal.
+
+---------------------------------------
+2. Direct download of data on an object
+---------------------------------------
+
+This function allows the user to download the requested data tabe for a designated object.
+The list of data properties that can be requested is:
+
+* Asteroid orbit properties: ``orbit_properties``
+* Asteroid physical properties: ``physical_properties``
+* Asteroid observation records: ``observations``
+* Generation of observational ephemerides for an object: ``ephemerides``
+* Asteroid close approach report: ``close_approaches``
+* Possible impacts: ``impacts``
+
+These properties are referenced in `<https://neo.ssa.esa.int/computer-access>`_.
+
+--------
+Examples
+--------
+
+Impacts, Physical Properties and Observations
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+This example tries to summarize how to access the data of this tabs and how to
+use it. Note that this classes only require as inputs the name of
+the object and the requested tab.
+
+The information can be obtained introducing directly the name of
+the object, but it can be also added from the output of a
+:meth:`~astroquery.esa.neocc.NEOCCClass.query_list` search:
+
+.. doctest-remote-data::
+
+    >>> from astroquery.esa.neocc import neocc
+    >>> ast_impacts = neocc.query_object(name='1979XB', tab='impacts')
+
+or
+
+.. doctest-remote-data::
+
+    >>> nea_list = neocc.query_list(list_name='nea_list')
+    >>> print(nea_list["NEA"][3163])
+    1979XB
+    >>> ast_impacts = neocc.query_object(name=nea_list["NEA"][3163], tab='impacts')
+
+or
+
+.. doctest-remote-data::
+
+    >>> risk_list = neocc.query_list(list_name='risk_list')
+    >>> print(risk_list['Object Name'][1])
+    1979XB
+    >>> ast_impacts = neocc.query_object(name=risk_list['Object Name'][1], tab='impacts')
+
+This query returns a list containing a single table:
+
+.. doctest-remote-data::
+
+    >>> print(ast_impacts[0])  # doctest: +IGNORE_OUTPUT
+              date             MJD    sigma  sigimp ... Exp. Energy in MT   PS   TS
+    ----------------------- --------- ------ ------ ... ----------------- ----- ---
+    2056-12-12 21:38:52.800 72344.902  0.255    0.0 ...             0.013 -2.86   0
+    2065-12-16 11:06:43.200 75635.463  -1.11    0.0 ...           3.3e-05 -5.42   0
+    2101-12-14 04:53:45.600 88781.204 -0.384    0.0 ...           8.6e-05 -5.32   0
+    2113-12-14 18:04:19.200 93164.753 -0.706    0.0 ...           0.00879 -3.35   0
+
+
+**Note:** Most of the tables returned by this tye of query contain additional information
+in the ``meta`` property, including information about the table columns.
+
+.. doctest-remote-data::
+   
+   >>> print(ast_impacts[0].meta.keys())
+   odict_keys(['Column Info', 'observation_accepted', 'observation_rejected', 'arc_start', 'arc_end', 'info', 'computation'])
+
+
+Physical Properties
+^^^^^^^^^^^^^^^^^^^
+
+This example shows how to obtain the physical properties table.
+
+.. doctest-remote-data::
+
+    >>> from astroquery.esa.neocc import neocc
+    >>> properties = neocc.query_object(name='433', tab='physical_properties')
+
+ Again, the output is a list containing a single table.
+
+.. doctest-remote-data::
+
+    >>> print(properties[0])  # doctest: +IGNORE_OUTPUT
+            Property        ...
+    ----------------------- ...
+     Absolute Magnitude (H) ...
+     Absolute Magnitude (H) ...
+                     Albedo ...
+                  Amplitude ...
+    Color Index Information ...
+    Color Index Information ...
+    Color Index Information ...
+    Color Index Information ...
+                   Diameter ...
+                    Quality ...
+         Rotation Direction ...
+            Rotation Period ...
+                  Sightings ...
+                  Sightings ...
+        Slope Parameter (G) ...
+               Spinvector B ...
+               Spinvector L ...
+                   Taxonomy ...
+             Taxonomy (all) ...
+
+
+Observations
+^^^^^^^^^^^^
+
+In this example we query for Observations tables, a query that
+returns a list containing 3-5 `~astropy.table.Table` objects depending if there are
+"Roving observer" or satellite observations.
+
+
+.. doctest-remote-data::
+
+    >>> ast_observations = neocc.query_object(name='99942', tab='observations')
+    >>> for tab in ast_observations:
+    ...     print(tab.meta["Title"])
+    Observation metadata
+    Optical Observations
+    Satellite  Observations
+    Radar Observations
+    >>> sat_obs = ast_observations[2]
+    >>> print(sat_obs)  # doctest: +IGNORE_OUTPUT
+    Design.  K   T   N  ...     X              Y                 Z          Obs Code
+    ------- --- --- --- ... ---------- ----------------- ------------------ --------
+      99942   S   s  -- ... -5634.1734        -2466.2657         -3038.3924      C51
+      99942   S   s  -- ... -5654.1816        -2501.9465         -2971.1902      C51
+      99942   S   s  -- ... -5645.7831        -2512.1036         -2978.6411      C51
+      99942   S   s  -- ... -5617.3465        -2486.4031         -3053.2209      C51
+      99942   S   s  -- ... -5620.3829        -2542.3521         -3001.1135      C51
+        ... ... ... ... ...        ...               ...                ...      ...
+      99942   S   s  -- ... -4105.3228 5345.915299999999          1235.1318      C51
+      99942   S   s  -- ... -4117.8192         5343.1834          1205.2107      C51
+      99942   S   s  -- ... -4137.4411         5329.7318          1197.3972      C51
+      99942   S   s  -- ... -4144.5939 5319.084499999999          1219.4675      C51
+    Length = 1357 rows
+
+Close Approaches
+^^^^^^^^^^^^^^^^
+
+This example queris for close approaches, another query
+which results in a single data table.
+
+.. doctest-remote-data::
+
+    >>> close_appr = neocc.query_object(name='99942', tab='close_approaches')
+    >>> print(close_appr[0])  # doctest: +IGNORE_OUTPUT
+    BODY      CALENDAR-TIME          MJD-TIME    ...  STRETCH    WIDTH   PROBABILITY
+    ----- ----------------------- --------------- ... --------- --------- -----------
+    EARTH 1957-04-01T03:19:44.544 35929.138710654 ... 2.871e-05 5.533e-09         1.0
+    EARTH 1964-10-24T21:44:40.127 38692.906017295 ...  1.72e-05 5.033e-09         1.0
+    EARTH 1965-02-11T12:15:30.527 38802.510774301 ... 4.732e-06 1.272e-09         1.0
+    EARTH 1972-12-24T11:51:41.472 41675.494228687 ... 1.584e-05 4.627e-09         1.0
+    EARTH 1980-12-18T01:51:14.400 44591.077250448 ... 1.136e-05 5.436e-09         1.0
+      ...                     ...             ... ...       ...       ...         ...
+    EARTH 2087-04-07T09:10:54.912 83417.382583343 ...   0.01214 3.978e-08         1.0
+    EARTH 2102-09-11T03:12:44.640 89052.133849042 ...   0.08822 1.191e-06       0.751
+    EARTH 2109-03-22T13:19:55.200 91436.555501683 ...    0.3509 1.066e-06       0.189
+    EARTH 2109-06-08T14:21:12.384 91514.598061046 ...    0.1121 1.149e-06       0.577
+    EARTH 2116-04-07T12:48:42.912  94009.53382919 ...    0.7074 9.723e-08      0.0943
+    [18 rows x 10 columns]
+
+Orbit Properties
+^^^^^^^^^^^^^^^^
+
+In order to access the orbital properties
+information, it is necessary to provide two additional inputs to
+:meth:`~astroquery.esa.neocc.NEOCCClass.query_object` method: ``orbital_elements`` and ``orbit_epoch``.
+
+This query returns a list of three tables, the orbital properties, and the covariance
+and corotation matrices.
+
+.. doctest-remote-data::
+
+    >>> ast_orbit_prop = neocc.query_object(name='99942', tab='orbit_properties',
+    ...                                     orbital_elements='keplerian', orbit_epoch='present')
+    >>> for tab in ast_orbit_prop:
+    ...     print(tab.meta["Title"])
+    Orbital Elements
+    COV
+    COR
+    >>> print(ast_orbit_prop[0][:5])  # doctest: +IGNORE_OUTPUT
+    Section  Property          Value
+    -------- -------- -----------------------
+       ANODE    ANODE -8.6707715058413322E-04
+    APHELION APHELION  1.0993687643243035E+00
+       DNODE    DNODE -1.9894296321957006E-01
+      HEADER   format                  OEF2.0
+      HEADER  rectype                      ML
+
+
+Ephemerides
+^^^^^^^^^^^
+In order to access ephemerides information, it
+is necessary to provide five additional inputs to :meth:`~astroquery.esa.neocc.NEOCCClass.query_object`
+method: ``observatory``, ``start``, ``stop``, ``step`` and ``step_unit``.
+
+.. doctest-remote-data::
+
+    >>> ast_ephemerides = neocc.query_object(name='99942', tab='ephemerides', observatory='500',
+    ...                                      start='2019-05-08 01:30', stop='2019-05-23 01:30',
+    ...                                      step='1', step_unit='days')
+    >>> ast_ephemerides = ast_ephemerides[0]
+    >>> print(ast_ephemerides.meta.keys())
+    odict_keys(['Ephemerides generation for', 'Observatory', 'Initial Date', 'Final Date', 'Time step', 'Column Info'])
+    >>> print(ast_ephemerides)  # doctest: +IGNORE_OUTPUT +REMOTE_DATA
+               Date          MJD (UTC)  RA (h  m  s) ... Err1 (") Err2 (") AngAx (deg)
+    ----------------------- ---------- ------------ ... -------- -------- -----------
+    2019-05-08T01:30:00.000 58611.0625  6 43 40.510 ...    0.001      0.0       115.8
+    2019-05-09T01:30:00.000 58612.0625  6 47 20.055 ...    0.001      0.0       117.3
+    2019-05-10T01:30:00.000 58613.0625  6 50 59.059 ...    0.001      0.0       119.0
+    2019-05-11T01:30:00.000 58614.0625  6 54 37.518 ...    0.001      0.0       120.8
+    2019-05-12T01:30:00.000 58615.0625  6 58 15.428 ...    0.001      0.0       122.8
+                        ...        ...          ... ...      ...      ...         ...
+    2019-05-19T01:30:00.000 58622.0625  7 23 25.375 ...    0.001      0.0       143.8
+    2019-05-20T01:30:00.000 58623.0625  7 26 58.899 ...    0.001      0.0       147.6
+    2019-05-21T01:30:00.000 58624.0625  7 30 31.891 ...    0.001      0.0       151.5
+    2019-05-22T01:30:00.000 58625.0625  7 34  4.357 ...    0.001    0.001       155.2
+    2019-05-23T01:30:00.000 58626.0625  7 37 36.303 ...    0.001    0.001       158.7
+
+
+
+Reference/API
+=============
+
+.. automodapi:: astroquery.esa.neocc
+    :no-inheritance-diagram:
diff --git a/docs/index.rst b/docs/index.rst
index 1f6f5e7850..1a4690d992 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -263,6 +263,7 @@ The following modules have been completed using a common API:
   esa/iso/iso.rst
   esa/jwst/jwst.rst
   esa/xmm_newton/xmm_newton.rst
+  esa/neocc/neocc.rst
   esasky/esasky.rst
   eso/eso.rst
   image_cutouts/first/first.rst