👖 SnapEnv template for Python package

Awesome snapenv_core created by snapenv

It was created having in mind SnapEnv people and what the most common use-cases would be. Following its structure you'll get into developing your next FastAPI server in no time!

• a configuration module made using pydantic-settings
• a handful of Pydantic schemas to make your life as a programmer easier

Features

1. 🍬 Sklearn meta-estimator: add conformal prediction of quantiles and intervals to any scikit-learn regressor
2. 🔮 Darts forecaster: add conformally calibrated probabilistic forecasting to any scikit-learn regressor
3. 🌡️ Conformally calibrated: accurate quantiles, and intervals with reliable coverage
4. 🚦 Coherent quantiles: quantiles increase monotonically instead of crossing each other
5. 👖 Tight quantiles: selects the lowest dispersion that provides the desired coverage
6. 🎁 Data efficient: requires only a small number of calibration examples to fit
7. 🐼 Pandas support: optionally predict on DataFrames and receive DataFrame output

Using

Quick links

1. Installing

Installing

poetry add snapenv-core

pip install snapenv-core

Contributing

/// details | Prerequisites

1. Set up Git to use SSH

   1. Generate an SSH key and add the SSH key to your GitHub account.

   2. Configure SSH to automatically load your SSH keys:

      cat << EOF >> ~/.ssh/config
      
      Host *
        AddKeysToAgent yes
        IgnoreUnknown UseKeychain
        UseKeychain yes
        ForwardAgent yes
      EOF
      

2. Install Docker Desktop.

   • Linux only:
     • Export your user's user id and group id so that files created in the Dev Container are owned by your user:

       cat << EOF >> ~/.bashrc
       
       export UID=$(id --user)
       export GID=$(id --group)
       EOF
       

3. Install VS Code or PyCharm

   1. Install VS Code and VS Code's Dev Containers extension. Alternatively, install PyCharm.
   2. Optional: install a Nerd Font such as FiraCode Nerd Font and configure VS Code or configure PyCharm to use it.

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/// details | Development environments

The following development environments are supported:

1. ⭐️ GitHub Codespaces: click on Code and select Create codespace to start a Dev Container with GitHub Codespaces.
2. ⭐️ Dev Container (with container volume): click on Open in Dev Containers to clone this repository in a container volume and create a Dev Container with VS Code.
3. Dev Container: clone this repository, open it with VS Code, and run Ctrl/⌘ + ⇧ + P → Dev Containers: Reopen in Container.
4. PyCharm: clone this repository, open it with PyCharm, and configure Docker Compose as a remote interpreter with the dev service.
5. Terminal: clone this repository, open it with your terminal, and run docker compose up --detach dev to start a Dev Container in the background, and then run docker compose exec dev zsh to open a shell prompt in the Dev Container.

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/// details | Developing

• This project follows the Conventional Commits standard to automate Semantic Versioning and Keep A Changelog with Commitizen.
• Run poe from within the development environment to print a list of Poe the Poet tasks available to run on this project.
• Run poetry add {package} from within the development environment to install a run time dependency and add it to pyproject.toml and poetry.lock. Add --group test or --group dev to install a CI or development dependency, respectively.
• Run poetry update from within the development environment to upgrade all dependencies to the latest versions allowed by pyproject.toml.
• Run poe docs, poe lint and ENVIRONMENT=dev poe test before any commit, or your git push can fail. poe docs generate any new documentation for changes/additions in the python modules.
• Run cz --name cz_gitmoji commit to commit files using conventional commits with emojis.
• Run cz --name cz_gitmoji bump --changelog to bump the package's version, update the CHANGELOG.md, and create a git tag.
• Run git push --tags to push the new tag to github.

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