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chore: yoink everything not needed for nix package
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36 changed files with 101 additions and 3351 deletions
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# These dependencies are installed using:
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#
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# conda install --channel conda-forge --name <env>
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#
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# Conda should be used for
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#
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# 1. Binary python packages (numpy, pandas, pillow).
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# The pypi may not always have binary packages for all platforms
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# and architectures you want to support. For example, pyblake2 only
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# has binary wheels for windows on pypi, whereas there are binary
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# packages on conda-forge (as of Sep 2018).
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# Binary wheels are becomming more common on the pypi this is
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# becomming, so this is less and less of an issue. Most of the time
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# it should be fine to add the dependency to pypi.txt instead.
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#
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# 2. Non python packages (nodejs, typescript).
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# Using conda for these kinds of dependencies minimizes
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# installation overhead for developers.
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# https://pypi.org/project/ujson/
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# UltraJSON is an ultra fast JSON encoder and decoder written
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# in pure C with bindings for Python 2.5+ and 3.
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# ujson
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# The hot new pkdf on the block is argon2, winner of
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# the https://password-hashing.net/ competition.
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# argon2_cffi
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# https://blake2.net/
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# BLAKE2 is a cryptographic hash function faster than MD5, SHA-1,
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# SHA-2, and SHA-3, yet is at least as secure as the latest standard
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# SHA-3. BLAKE2 has been adopted by many projects due to its high
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# speed, security, and simplicity.
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# pyblake2
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# needed for mypy coverage report
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lxml
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# These dependencies are installed using:
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#
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# pip install --upgrade
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#
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# This list should only contain packages related to
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# local development and debugging. It should not contain
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# any packages required for production, building or packaging
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# PuDB is a full-screen, console-based visual debugger for Python.
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# https://documen.tician.de/pudb/
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pudb
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# Quick-and-dirty debugging output for tired programmers
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# https://pypi.org/project/q/
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q
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# pretty-traceback manipulates Python tracebacks to make
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# them more readable.
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# https://pypi.org/project/pretty-traceback/
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pretty-traceback
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# Py-Spy: A sampling profiler for Python programs.
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# https://github.com/benfred/py-spy
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# This is good for coarse grained profiling (even on production)
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py-spy
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# SNAKEVIZ : A browser based viewer for the output of Python’s cProfile.
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# https://jiffyclub.github.io/snakeviz/
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# This is good for fine grained profiling (function level/micro optimizations)
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snakeviz
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# I've yet to find a decent memory profiler for python, feel free to
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# add one after you've tested it and found it to be actually useful.
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ipython # nuff said
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# A command line utility to display dependency tree of the installed Python packages
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# https://github.com/naiquevin/pipdeptree
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#
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# For graph output you will need to:
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# $ sudo apt install -y graphviz
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# $ pipdeptree --graph-output svg > requirements/tree.svg
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pipdeptree
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graphviz
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# run failed tests first
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pytest-cache
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# to update the readme examples
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rich
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# These dependencies are installed using:
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#
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# pip install --upgrade
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#
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# This file should only declare dependencies related to code
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# formatting, linting, testing and packaging.
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#
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# No dependencies required for production should be listed here.
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# http://www.pydocstyle.org/en/4.0.0/release_notes.html
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# Support for Python 2.x and PyPy has been dropped (#340).
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pydocstyle<4
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flake8
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flake8-bugbear
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flake8-docstrings
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flake8-builtins
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flake8-comprehensions
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flake8-junit-report
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flake8-2020
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pylint==2.12.1
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pylint-ignore>=2020.1013
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isort
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mypy==0.942
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types-setuptools
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types-toml
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# http://doc.pytest.org/en/latest/py27-py34-deprecation.html
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# The pytest 4.6 series will be the last to support Python 2.7
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# and 3.4, and is scheduled to be released by mid-2019.
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# pytest 5.0 and onwards will support only Python 3.5+.
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pytest; python_version >= "3.5"
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pytest<5.0; python_version < "3.5"
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pytest-cov
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# https://github.com/pytest-dev/pytest-html/blob/master/CHANGES.rst
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# pytest-html 2.0+ doesn't support python2.7
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pytest-html<2.0
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py
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readme_renderer[md]
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twine
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md-toc
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straitjacket>=v202008.1016
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pycalver
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lib3to6
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# needed for mypy coverage report
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lxml
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# These dependencies are installed using:
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#
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# pip install --upgrade
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# pip install --upgrade --no-deps --target vendor/
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#
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# Vendored dependencies are installed both in the virtual
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# environment as well as in the vendor/ directory. This way:
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#
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# 1. All transitive dependencies of a package are installed in
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# the virtualenv (in the first installation step)
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# 2. If there is a binary version of the package available, it
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# will be installed into the virtualenv
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# 3. In the third step only (--no-deps) the source version of
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# the (--no-binary) package is installed to vendor/
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#
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# This allows us to:
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#
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# 1. Enable mypy to check modules of multiple packages.
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# 2. Easily navigate to the source of a vendored dependency
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# 3. Use binary versions packages instead of source versions of
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# packages, simply by not including the vendor/ directory in
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# the PYTHONPATH. The version from the virtualenv will then
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# be loaded instead.
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