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Inspect your AI models visually, find bugs, give feedback 🕵️‍♀️ 💬

Project description

Giskard Client

Python Version Dependencies Status

Code style: black Security: bandit Pre-commit Semantic Versions License

Inspect your AI models visually, find bugs, give feedback 🕵️‍♀️ 💬

Very first steps

Initial

  1. Clone the project in a local directory

  2. Using pyenv setup a local python 3.7

  3. If you don't have Poetry installed run:

make download-poetry
  1. Initialize poetry and install pre-commit hooks:
make install
  1. Tests folder contain scripts that can upload data to your Giskard Backend. Run them using
make test

Or individually:

poetry run pytest tests/model_inspector/test_upload_text_classification.py

Make sure you have setup the correct URL, as well as your Giskard API token in a .env file at the root of the project.

Poetry

Want to know more about Poetry? Check its documentation.

Details about Poetry

Poetry's commands are very intuitive and easy to learn, like:

  • poetry add numpy@latest
  • poetry run pytest
  • poetry publish --build

etc

Building and releasing your package

Building a new version of the application contains steps:

  • Bump the version of your package poetry version <version>. You can pass the new version explicitly, or a rule such as major, minor, or patch. For more details, refer to the Semantic Versions standard.
  • Make a commit to GitHub.
  • Create a GitHub release.
  • And... publish 🙂 poetry publish --build

🎯 What's next

Well, that's up to you 💪🏻. I can only recommend the packages and articles that helped me.

  • Typer is great for creating CLI applications.
  • Rich makes it easy to add beautiful formatting in the terminal.
  • Pydantic – data validation and settings management using Python type hinting.
  • Loguru makes logging (stupidly) simple.
  • tqdm – fast, extensible progress bar for Python and CLI.
  • IceCream is a little library for sweet and creamy debugging.
  • orjson – ultra fast JSON parsing library.
  • Returns makes you function's output meaningful, typed, and safe!
  • Hydra is a framework for elegantly configuring complex applications.
  • FastAPI is a type-driven asynchronous web framework.

Articles:

🚀 Features

Development features

Deployment features

Open source community features

Installation

pip install -U python-client

or install with Poetry

poetry add python-client

Makefile usage

Makefile contains a lot of functions for faster development.

1. Download and remove Poetry

To download and install Poetry run:

make poetry-download

To uninstall

make poetry-remove

2. Install all dependencies and pre-commit hooks

Install requirements:

make install

Pre-commit hooks coulb be installed after git init via

make pre-commit-install

3. Codestyle

Automatic formatting uses pyupgrade, isort and black.

make codestyle

# or use synonym
make formatting

Codestyle checks only, without rewriting files:

make check-codestyle

Note: check-codestyle uses isort, black and darglint library

4. Code security

make check-safety

This command launches Poetry integrity checks as well as identifies security issues with Safety and Bandit.

make check-safety

5. Type checks

Run mypy static type checker

make mypy

6. Tests

Run pytest

make test

7. All linters

Of course there is a command to rule run all linters in one:

make lint

the same as:

make test && make check-codestyle && make mypy && make check-safety

8. Docker

make docker-build

which is equivalent to:

make docker-build VERSION=latest

Remove docker image with

make docker-remove

More information about docker.

9. Cleanup

Delete pycache files

make pycache-remove

Remove package build

make build-remove

Or to remove pycache, build and docker image run:

make clean-all

📈 Releases

You can see the list of available releases on the GitHub Releases page.

We follow Semantic Versions specification.

We use Release Drafter. As pull requests are merged, a draft release is kept up-to-date listing the changes, ready to publish when you’re ready. With the categories option, you can categorize pull requests in release notes using labels.

List of labels and corresponding titles

Label Title in Releases
enhancement, feature 🚀 Features
bug, refactoring, bugfix, fix 🔧 Fixes & Refactoring
build, ci, testing 📦 Build System & CI/CD
breaking 💥 Breaking Changes
documentation 📝 Documentation
dependencies ⬆️ Dependencies updates

You can update it in release-drafter.yml.

GitHub creates the bug, enhancement, and documentation labels for you. Dependabot creates the dependencies label. Create the remaining labels on the Issues tab of your GitHub repository, when you need them.

🛡 License

License

This project is licensed under the terms of the Apache Software License 2.0 license. See LICENSE for more details.

📃 Citation

@misc{python-client,
  author = {Giskard AI},
  title = {Inspect your AI models visually, find bugs, give feedback 🕵️‍♀️ 💬},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/Giskard-AI/python-client
}

Credits 🚀 Your next Python package needs a bleeding-edge project structure.

This project was generated with python-package-template

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