changes

Signed-off-by: Felipe Monteiro Jácome <[email protected]>

Author: engFelipeMonteiro

.gitignore

@@ -7,4 +7,5 @@ dist
 .coverage
 .tox
 .*cache
-htmlcov
+htmlcov
+env39/

prometheus_client/exposition.py

@@ -168,7 +168,6 @@ def sample_line(line):
         return f'{line.name}{labelstr} {floatToGoString(line.value)}{timestamp}\n'
 
     output = []
-    output_string = ""
     for metric in registry.collect():
         try:
             mname = metric.name
@@ -187,6 +186,7 @@ def sample_line(line):
                 mtype = 'histogram'
             elif mtype == 'unknown':
                 mtype = 'untyped'
+            # default encoder
             if 'encoder' not in vars(metric) or ('encoder' in vars(metric) and metric.encoder != 'pandas'):
                 # normal calls
                 output.append('# HELP {} {}\n'.format(
@@ -208,15 +208,16 @@ def sample_line(line):
                     output.append(f'# TYPE {metric.name}{suffix} gauge\n')
                     output.extend(lines)
             else:
+                # pandas encoder
                 output.append('# HELP {} {}\n'.format(
                     mname, metric.documentation.replace('\\', r'\\').replace('\n', r'\n')))
                 output.append(f'# TYPE {mname} {mtype}\n')
-                import pdb; pdb.set_trace()
+                output.extend(metric[metric._tag].to_list())
         except Exception as exception:
             exception.args = (exception.args or ('',)) + (metric,)
             raise
-
-        return ''.join(output).encode('utf-8')
+       
+    return ''.join(output).encode('utf-8')
 
 
 def choose_encoder(accept_header):

prometheus_client/metrics.py

@@ -739,13 +739,8 @@ def _raise_if_not_observable(self):
     def _is_parent(self):
         return self._labelnames and not self._labelvalues
 
-    def _get_metric(self):
-        print("get_metric")
-        return Metric(self._name, self._documentation, self._type, self._unit)
-
     def describe(self):
-        print("describe")
-        return [self._get_metric()]
+        return [self._metrics]
 
     def collect(self):
         return [self._metrics]
@@ -758,66 +753,56 @@ def __repr__(self):
         metric_type = type(self)
         return f"{metric_type.__module__}.{metric_type.__name__}({self._name})"
 
-    def generate_pandas_report(self, value='value', tag='report'):
+    def generate_pandas_report(self):
         def make_str(row):
-            return f"{self._name}({[ f'{col}={row[col]}, ' for col in self._metrics.columns  if col not in [value, tag]]})"
- 
-        # generate another column with metric formated
-        # make_str = lambda x: "metric01(a={}, b={})".format(x['a'],x['b'])
-        # a = s.apply(make_str , axis=1)
-        # https://github.com/prometheus/client_python/discussions/772
-
-        self._metrics[value] = self._metrics.apply(make_str, axis=1) 
+            return  f"""{self._name}({','.join([ f'{col}={row[col]} ' for col in self._labelnames  if col not in [self._value, self._tag]])}) {row[self._value]} {chr(10)}"""
+        with self._lock:
+            self._metrics[self._tag] = self._metrics.apply(make_str, axis=1) 
         # self._metrics
 
     def set_metric(self, df: pd.DataFrame):
         with self._lock:
+            df.name = self._name
+            df.type = self._type
+            df.documentation = self._documentation
+            df.encoder = 'pandas'
             self._metrics = df
         self.generate_pandas_report()
-        import pdb; pdb.set_trace()
-
-    #def __init__(self: T,
-    #             name: str,
-    #             documentation: str,
-    #             labelnames: Iterable[str] = (),
-    #             namespace: str = '',
-    #             subsystem: str = '',
-    #             unit: str = '',
-    #             registry: Optional[CollectorRegistry] = REGISTRY,
-    #             _labelvalues: Optional[Sequence[str]] = None,
-    #             ) -> None:
+
     def __init__(
             self: T,
-            df: pd.DataFrame,
+            name: str = '',
+            documentation: str = '',
             namespace: str = '',
             subsystem: str = '',
-            registry: Optional[CollectorRegistry] = REGISTRY
+            unit: str = '',
+            df=None,
+            columns=None,
+            registry: Optional[CollectorRegistry] = REGISTRY,
+            tag='report',
+            value='value'
             ) -> None:
         """
         Esta classe parte do pressuporto que a metrica é trocada com mais eficiencia do que ficar alterando apenas 1 valor
         o calculo pode ser feito em outro lugar e passar apenas a estrutura completo pronto em DataFrame
         """
-        if 'documentation' in vars(df):
-            documentation = df.documentation
-        else:
-            documentation = 'no doc provided'
-        if 'unit' in vars(df):
-            unit = df.unit
-        else:
-            unit = 'no unit provided'
-        if 'name' in vars(df):
-            name = df.name
-        else:
-            name = 'no name provided'
-        df.type = self._type
-        df.encoder = self._encoder
         self._name = _build_full_name(self._type, name, namespace, subsystem, unit)
-        self._labelnames = _validate_labelnames(self, df.columns)
+        if columns:
+            self._labelvalues = columns
+        else:
+            self._labelvalues = df.columns
+        self._labelnames = _validate_labelnames(self, self._labelvalues)
         self._labelvalues = tuple(None or ())
         self._kwargs: Dict[str, Any] = {}
         self._documentation = documentation
         self._unit = unit
-
+        self._tag = tag
+        self._value = value
+        df.name = self._name
+        df.type = self._type
+        df.documentation = documentation
+        df.encoder = self._encoder
+        df._tag = tag
         if not METRIC_NAME_RE.match(self._name):
             raise ValueError('Invalid metric name: ' + self._name)
 
@@ -826,14 +811,15 @@ def __init__(
             self._lock = Lock()
             self._metrics = df
 
+
         if self._is_observable():
             self._metric_init()
 
         if not self._labelvalues:
             # Register the multi-wrapper parent metric, or if a label-less metric, the whole shebang.
             if registry:
                 registry.register(self)
-
+        self.generate_pandas_report()
 
     def remove(self, *labelvalues):
         if not self._labelnames:

requirements.txt

@@ -0,0 +1,2 @@
+pytest
+pandas

tests/test_exposition.py

@@ -194,20 +194,87 @@ def collect(self):
 """, generate_latest(self.registry))
 
     def test_gauge_pandas(self):
-        df = pd.DataFrame({'a': [1.1,2.2,3.3,4.4], 'b':[5.1,6.2,7.3,8.4]})
-        df.name = 'report_pandas'
-        df.documentation = 'metric description'
-        df.unit = ''
-        df2 = pd.DataFrame({'c': [1.1,2.2,3.3,4.4], 'd':[5.1,6.2,7.3,8.4]})
-        df2.name = 'report_panda2s'
-        df2.documentation = 'metric description'
-        df2.unit = ''
-        g = PandasGauge(df, registry=self.registry)
-        g = PandasGauge(df2, registry=self.registry)
-        g.generate_pandas_report()
+        """
+        2 possiveis chamadas
+        usa apenas as colunas expostas
+        PandasGauge('report_pandas', 'metric description', columns=['columnn01', 'column02'], registry=self.registry)
+        ou 
+        usará todos as colunas
+        PandasGauge('report_pandas', 'metric description', df=df, registry=self.registry)
+        ou
+        PandasGauge('report_pandas', 'metric description', df=df, columns=['columnn01', 'column02'], registry=self.registry)
+        """
+        df = pd.DataFrame({'a': [1.1,2.2,3.3,4.4], 'b':[5.1,6.2,7.3,8.4], 'value': [1,2,3,4]})
+        df2 = pd.DataFrame({'c': [1.1,2.2,3.3,4.4], 'd':[5.1,6.2,7.3,8.4], 'value': [5,6,7,8]})
+        PandasGauge('report_pandas', 'metric description', df=df, columns= ['a', 'b', 'value'], registry=self.registry)
+        g2 = PandasGauge('report_panda2s', 'metric description2', df=df2, registry=self.registry)
+        
+        self.assertEqual(
+            b'# HELP report_pandas metric description\n'
+            b'# TYPE report_pandas gauge\n'
+            b'report_pandas(a=1.1 ,b=5.1 ) 1.0 \n'
+            b'report_pandas(a=2.2 ,b=6.2 ) 2.0 \n'
+            b'report_pandas(a=3.3 ,b=7.3 ) 3.0 \n'
+            b'report_pandas(a=4.4 ,b=8.4 ) 4.0 \n'
+            b'# HELP report_panda2s metric description2\n'
+            b'# TYPE report_panda2s gauge\n'
+            b'report_panda2s(c=1.1 ,d=5.1 ) 5.0 \n'
+            b'report_panda2s(c=2.2 ,d=6.2 ) 6.0 \n'
+            b'report_panda2s(c=3.3 ,d=7.3 ) 7.0 \n'
+            b'report_panda2s(c=4.4 ,d=8.4 ) 8.0 \n',
+            generate_latest(self.registry)
+            )
+        
+        g2.set_metric(df2)
+        self.assertEqual(
+            b'# HELP report_pandas metric description\n'
+            b'# TYPE report_pandas gauge\n'
+            b'report_pandas(a=1.1 ,b=5.1 ) 1.0 \n'
+            b'report_pandas(a=2.2 ,b=6.2 ) 2.0 \n'
+            b'report_pandas(a=3.3 ,b=7.3 ) 3.0 \n'
+            b'report_pandas(a=4.4 ,b=8.4 ) 4.0 \n'
+            b'# HELP report_panda2s metric description2\n'
+            b'# TYPE report_panda2s gauge\n'
+            b'report_panda2s(c=1.1 ,d=5.1 ) 5 \n'
+            b'report_panda2s(c=2.2 ,d=6.2 ) 6 \n'
+            b'report_panda2s(c=3.3 ,d=7.3 ) 7 \n'
+            b'report_panda2s(c=4.4 ,d=8.4 ) 8 \n',
+            generate_latest(self.registry)
+            )
+
+    def test_gauge_pandas_columns(self):
+        """
+        2 possiveis chamadas
+        usa apenas as colunas expostas
+        PandasGauge('report_pandas', 'metric description', columns=['columnn01', 'column02'], registry=self.registry)
+        ou 
+        usará todos as colunas
+        PandasGauge('report_pandas', 'metric description', df=df, registry=self.registry)
+        ou
+        PandasGauge('report_pandas', 'metric description', df=df, columns=['columnn01', 'column02'], registry=self.registry)
+        """
+        df = pd.DataFrame({'a': [1.1,2.2,3.3,4.4], 'b':[5.1,6.2,7.3,8.4], 'value': [1,2,3,4]})
+        df2 = pd.DataFrame({'c': [1.1,2.2,3.3,4.4], 'd':[5.1,6.2,7.3,8.4], 'result': [5,6,7,8]})
+        PandasGauge('report_pandas', 'metric description', df=df, columns= ['a', 'value'], registry=self.registry)
+        g2 = PandasGauge('report_panda2s', 'metric description2', df=df2, columns=['d', 'result'],value='result' ,registry=self.registry)
+        
+        
         import pdb; pdb.set_trace()
-        self.assertEqual(b'# HELP gg A gauge\n# TYPE gg gauge\ngg 17.0\n', generate_latest(self.registry))
-
+        self.assertEqual(
+            b'# HELP report_pandas metric description\n'
+            b'# TYPE report_pandas gauge\n'
+            b'report_pandas(a=1.1 ) 1.0 \n'
+            b'report_pandas(a=2.2 ) 2.0 \n'
+            b'report_pandas(a=3.3 ) 3.0 \n'
+            b'report_pandas(a=4.4 ) 4.0 \n'
+            b'# HELP report_panda2s metric description2\n'
+            b'# TYPE report_panda2s gauge\n'
+            b'report_panda2s(d=5.1 ) 5.0 \n'
+            b'report_panda2s(d=6.2 ) 6.0 \n'
+            b'report_panda2s(d=7.3 ) 7.0 \n'
+            b'report_panda2s(d=8.4 ) 8.0 \n',
+            generate_latest(self.registry)
+            )
 
 class TestPushGateway(unittest.TestCase):
     def setUp(self):

tests/test_registry.py

@@ -32,5 +32,4 @@ def test_collector_registry_gauge():
 
     registry2 = CollectorRegistry()
     GP = PandasGauge('raid_status2', '1 if raid array is okay', ['label1'], registry=registry2)
-    assert  type(GP._metrics) == pd.core.frame.DataFrame
-    import pdb; pdb.set_trace()
+    assert  type(GP._metrics) == pd.core.frame.DataFrame