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2 changes: 2 additions & 0 deletions .gitignore
Original file line number Diff line number Diff line change
Expand Up @@ -114,3 +114,5 @@ dask-worker-space/

# VCS versioning
src/coffea/_version.py

.DS_Store
2 changes: 1 addition & 1 deletion .readthedocs.yaml
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Expand Up @@ -20,7 +20,7 @@ build:
- echo "setuptools!=78.0.1" >> ruciospark_constraints.txt
- PIP_CONSTRAINT="$(pwd)/ruciospark_constraints.txt" python -m pip install '.[dev]' rucio-clients
pre_build:
- cd docs && sphinx-autogen source/reference.rst -t source/_templates -o source/modules && cd ../
- cd docs && sphinx-autogen source/api_reference.md -t source/_templates -o source/modules && cd ../
# You can also specify other tool versions:
# nodejs: "19"
# rust: "1.64"
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4 changes: 2 additions & 2 deletions README.rst
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@@ -1,4 +1,4 @@
.. image:: docs/source/logo/coffea_logo.svg
.. image:: logo/coffea_logo.svg
:align: center
:width: 250px
:alt: logo
Expand Down Expand Up @@ -50,7 +50,7 @@ coffea also supplies facilities for horizontally scaling an analysis in order to
time-to-insight in a way that is largely independent of the resource the analysis
is being executed on. By making use of modern *big-data* technologies like
`Apache Spark <https://spark.apache.org/>`_, `parsl <https://github.com/Parsl/parsl>`_,
`Dask <https://dask.org>`_ , and `Work Queue <http://ccl.cse.nd.edu/software/workqueue>`_,
`Dask <https://dask.org>`_ , and `TaskVine <https://ccl.cse.nd.edu/software/taskvine>`_,
it is possible with coffea to scale a HEP analysis from a testing
on a laptop to: a large multi-core server, computing clusters, and super-computers without
the need to alter or otherwise adapt the analysis code itself.
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1,629 changes: 1,629 additions & 0 deletions binder/advanced_numba.ipynb

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