Skip to main content

A nice library.

Project description

CI docs badge PyPI version Code style: black

python_ml_template

First actions:

When setting up the repo (and potentially also the venv) from scratch, a few one-time actions are needed:

  • install pip dependencies
  • pre-commit install --install-hooks -t pre-commit -t commit-msg
  • git config branch.master.mergeOptions "--squash
  • Activate gh-pages web (otherwise the CI release will error here).

Features:

The following things are already integrated via CI, but can be run manually:

  • Utest: python -m unittest

  • utest with py coverage: coverage run -m unittest

  • flake8

  • all

  • using pre-commit, added commitizen to pre-commit (remember to pre-commit install --install-hooks -t pre-commit -t commit-msg). This enforces "conventional commits" style: https://www.conventionalcommits.org/en/v1.0.0/#summary To commit, reecommended to pip install commitizen and then commit using: cz c (or cz c --retry if the last one failed).

  • docs from scratch:

    1. Add docs folder and requirements.txt with sphinx and sphinx-rtd-theme
  • Centralized version and metadata. Setup works with very few parameters

  • To enforce squash merging to master, issue git config branch.master.mergeOptions "--squash" (info: https://stackoverflow.com/a/37828622)

  • GH pages action. Make sure that the repo server has publishing enabled, otherwise it will error.

  • PyPI: need a regular and a test account. Create a token for GH actions (if global only need to do this once). Then, in the GH repo, add that token under secrets->pypi. https://pypi.org/manage/account/token/

Further feature ideas/TODOs:

TODO:

  1. CML+ Complete ML project
  2. Generalize runner to GPU, home and GitLab

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aferro_ml_lib-0.7.2.tar.gz (7.0 kB view details)

Uploaded Source

Built Distribution

aferro_ml_lib-0.7.2-py3-none-any.whl (9.3 kB view details)

Uploaded Python 3

File details

Details for the file aferro_ml_lib-0.7.2.tar.gz.

File metadata

  • Download URL: aferro_ml_lib-0.7.2.tar.gz
  • Upload date:
  • Size: 7.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.53.0 CPython/3.8.6

File hashes

Hashes for aferro_ml_lib-0.7.2.tar.gz
Algorithm Hash digest
SHA256 72367d2840141cb5970fa7e739cc3fb1d565668a33b479b01f0f7d3c6bba226c
MD5 8c3ca3ba4f449212228840810bb953e8
BLAKE2b-256 470ff05183984f8b0f504a5e1ac22f60b26260c31eb4b0d46570a57ca860946e

See more details on using hashes here.

File details

Details for the file aferro_ml_lib-0.7.2-py3-none-any.whl.

File metadata

  • Download URL: aferro_ml_lib-0.7.2-py3-none-any.whl
  • Upload date:
  • Size: 9.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.53.0 CPython/3.8.6

File hashes

Hashes for aferro_ml_lib-0.7.2-py3-none-any.whl
Algorithm Hash digest
SHA256 a4f628cccab4186674a7af5d1bf010a46f7f1823b688113e1e83736760335b9a
MD5 a3f428214f41350fba14eb40aafd3d67
BLAKE2b-256 6b77a6288ca9f64a479743861ca11f58fce7304e0927ef4813c5c11690d43123

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page