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CHANGELOG.rst

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Changelog
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---------
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- August 11, 2021: Version 4.1 has some more changes under the hood, most of them with no significant impact to users.
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The CI pipeline has been completely rewritten, porting the code to `Github Actions <https://github.com/features/actions>`_
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(away from `Travis CI <https://travis-ci.com/>`_), to `flake8 <https://flake8.pycqa.org>`_ and to `pytest <https://pytest.org>`_
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(away from `nose <https://nose.readthedocs.io>`_). One thing that may have an impact on users is that following the changes
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made in Version 4.0, the PETSc data structures are now much easier, removing a lot of unnecessary boilerplate code.
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- May 4, 2021: Long time, no see, but this major release 4.0 marks some improvements under the hood:
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- **Rewrote ``mesh`` and ``particle`` data type**: Creation of new arrays for each operation is now avoided by

README.rst

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.. code-block:: bash
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nosetests -v pySDC/tests
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pytest pySDC/tests
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You may need to update your ``PYTHONPATH`` by running
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conda install -c conda-forge mpich petsc4py mpi4py fenics
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Most of the code is tested automatically using `Travis-CI <https://travis-ci.org/Parallel-in-Time/pySDC>`_, so a working version of the installation process can always be found in the `install`-block of the `.travis.yml <https://github.com/Parallel-in-Time/pySDC/blob/master/.travis.yml>`_ file.
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Most of the code is tested automatically using `Github Actions <https://github.com/Parallel-in-Time/pySDC/actions>`_, so a working version of the installation process can always be found in the `ci_pipeline.yml <https://github.com/Parallel-in-Time/pySDC/blob/master/.github/workflows/ci_pipeline.yml>`_ file.
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For many examples, `LaTeX` is used for the plots, i.e. a decent installation of this is needed in order to run the tests.
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When using `fenics` or `petsc4py`, a C++ compiler is required (although installation may go through at first).
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How to cite
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-----------
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If you use pySDC or parts of it for your work, great! Let us know if we can help you with this. Also, we would greatly appreciate a citation using `this paper <https://doi.org/10.1145/3310410>`_:
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If you use pySDC or parts of it for your work, great! Let us know if we can help you with this. Also, we would greatly appreciate a citation of `this paper <https://doi.org/10.1145/3310410>`_:
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Robert Speck, **Algorithm 997: pySDC - Prototyping Spectral Deferred Corrections**,
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ACM Transactions on Mathematical Software (TOMS), Volume 45 Issue 3, August 2019,

pySDC/README_API.rst

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The Python files contained in ``core``, ``implementations`` and ``helpers`` are fully documented and their API is generated automatically with sphinx-apidoc after each update.
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The API (as well as the tutorial pages) can also be generated manually and locally by executing
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.. code-block:: none
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> ./docs/update_apidocs.sh
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> nosetests -v --with-coverage --cover-erase --cover-inclusive --cover-package=pySDC/core,pySDC/implementations,pySDC/helpers,pySDC/tutorial --cover-html --cover-html-dir=target/doc/build/test_coverage pySDC/tests
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> travis-sphinx build
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in the root directory. Then, the main index can be found in ``target/doc/build/index.html``. Anyway, here is the online version:
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The Python files contained in ``core``, ``implementations`` and ``helpers`` are fully documented and their API is generated automatically with sphinx-apidoc after each update:
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requirements.txt

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scipy>=0.17.1
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dill>=0.2.6
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# These packages are used in examples or for testing, they can be omitted if necessary
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matplotlib>=1.5.3
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matplotlib>=3.0
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numba>=0.35
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sympy>=1.0
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# These packages are required for some of the more involved examples (and data types etc.), can be omitted

setup.py

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setup(
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name='pySDC',
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version='4.0',
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version='4.1',
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description='A Python implementation of spectral deferred correction methods and the likes',
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license="BSD-2",
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long_description=long_description,
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include_package_data=True,
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install_requires=[
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'nose>=1.3.7',
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'numpy>=1.15.4',
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'scipy>=0.17.1',
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'matplotlib>=1.5.3',
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'pep8',
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'matplotlib>=3.0',
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'sympy>=1.0',
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'numba>=0.35',
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'dill>=0.2.6',

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