chore: yoink everything not needed for nix package

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Technofab 2023-06-07 19:21:55 +02:00
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36 changed files with 101 additions and 3351 deletions

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# These dependencies are installed using:
#
# conda install --channel conda-forge --name <env>
#
# Conda should be used for
#
# 1. Binary python packages (numpy, pandas, pillow).
# The pypi may not always have binary packages for all platforms
# and architectures you want to support. For example, pyblake2 only
# has binary wheels for windows on pypi, whereas there are binary
# packages on conda-forge (as of Sep 2018).
# Binary wheels are becomming more common on the pypi this is
# becomming, so this is less and less of an issue. Most of the time
# it should be fine to add the dependency to pypi.txt instead.
#
# 2. Non python packages (nodejs, typescript).
# Using conda for these kinds of dependencies minimizes
# installation overhead for developers.
# https://pypi.org/project/ujson/
# UltraJSON is an ultra fast JSON encoder and decoder written
# in pure C with bindings for Python 2.5+ and 3.
# ujson
# The hot new pkdf on the block is argon2, winner of
# the https://password-hashing.net/ competition.
# argon2_cffi
# https://blake2.net/
# BLAKE2 is a cryptographic hash function faster than MD5, SHA-1,
# SHA-2, and SHA-3, yet is at least as secure as the latest standard
# SHA-3. BLAKE2 has been adopted by many projects due to its high
# speed, security, and simplicity.
# pyblake2
# needed for mypy coverage report
lxml

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# These dependencies are installed using:
#
# pip install --upgrade
#
# This list should only contain packages related to
# local development and debugging. It should not contain
# any packages required for production, building or packaging
# PuDB is a full-screen, console-based visual debugger for Python.
# https://documen.tician.de/pudb/
pudb
# Quick-and-dirty debugging output for tired programmers
# https://pypi.org/project/q/
q
# pretty-traceback manipulates Python tracebacks to make
# them more readable.
# https://pypi.org/project/pretty-traceback/
pretty-traceback
# Py-Spy: A sampling profiler for Python programs.
# https://github.com/benfred/py-spy
# This is good for coarse grained profiling (even on production)
py-spy
# SNAKEVIZ : A browser based viewer for the output of Pythons cProfile.
# https://jiffyclub.github.io/snakeviz/
# This is good for fine grained profiling (function level/micro optimizations)
snakeviz
# I've yet to find a decent memory profiler for python, feel free to
# add one after you've tested it and found it to be actually useful.
ipython # nuff said
# A command line utility to display dependency tree of the installed Python packages
# https://github.com/naiquevin/pipdeptree
#
# For graph output you will need to:
# $ sudo apt install -y graphviz
# $ pipdeptree --graph-output svg > requirements/tree.svg
pipdeptree
graphviz
# run failed tests first
pytest-cache
# to update the readme examples
rich

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# These dependencies are installed using:
#
# pip install --upgrade
#
# This file should only declare dependencies related to code
# formatting, linting, testing and packaging.
#
# No dependencies required for production should be listed here.
# http://www.pydocstyle.org/en/4.0.0/release_notes.html
# Support for Python 2.x and PyPy has been dropped (#340).
pydocstyle<4
flake8
flake8-bugbear
flake8-docstrings
flake8-builtins
flake8-comprehensions
flake8-junit-report
flake8-2020
pylint==2.12.1
pylint-ignore>=2020.1013
isort
mypy==0.942
types-setuptools
types-toml
# http://doc.pytest.org/en/latest/py27-py34-deprecation.html
# The pytest 4.6 series will be the last to support Python 2.7
# and 3.4, and is scheduled to be released by mid-2019.
# pytest 5.0 and onwards will support only Python 3.5+.
pytest; python_version >= "3.5"
pytest<5.0; python_version < "3.5"
pytest-cov
# https://github.com/pytest-dev/pytest-html/blob/master/CHANGES.rst
# pytest-html 2.0+ doesn't support python2.7
pytest-html<2.0
py
readme_renderer[md]
twine
md-toc
straitjacket>=v202008.1016
pycalver
lib3to6
# needed for mypy coverage report
lxml

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# These dependencies are installed using:
#
# pip install --upgrade
# pip install --upgrade --no-deps --target vendor/
#
# Vendored dependencies are installed both in the virtual
# environment as well as in the vendor/ directory. This way:
#
# 1. All transitive dependencies of a package are installed in
# the virtualenv (in the first installation step)
# 2. If there is a binary version of the package available, it
# will be installed into the virtualenv
# 3. In the third step only (--no-deps) the source version of
# the (--no-binary) package is installed to vendor/
#
# This allows us to:
#
# 1. Enable mypy to check modules of multiple packages.
# 2. Easily navigate to the source of a vendored dependency
# 3. Use binary versions packages instead of source versions of
# packages, simply by not including the vendor/ directory in
# the PYTHONPATH. The version from the virtualenv will then
# be loaded instead.