typeshed_stats 26.5.3

Library and command-line tool to gather stats on typeshed packages

typeshed-stats

---

A CLI tool and library to gather stats on typeshed

---

What's this project for?

This project is for easy gathering of statistics relating to typeshed's stubs. As well as being a CLI tool and library, it also powers a website where stats about typeshed's stubs are uploaded twice a day.

This project was created by Alex Waygood. It is not necessarily endorsed by any of the other typeshed maintainers.

Some examples of things you can do from the command line:

• Create a .csv file with stats on all typeshed stubs: typeshed-stats --typeshed-dir <PATH_TO_TYPESHED_CLONE> --to-file stats.csv (the .csv file extension will be automatically detected by the script to identify the format required).
• Pretty-print stats on typeshed stubs for emoji and redis to the terminal, in JSON format: typeshed-stats --typeshed-dir <PATH_TO_TYPESHED_CLONE> --to-json emoji redis
• Generate a MarkDown file detailing stats on typeshed's stubs for protobuf and the stdlib: typeshed-stats --typeshed-dir <PATH_TO_TYPESHED_CLONE> --to-file stats.md stdlib protobuf
• Open the upstream repository URLs for requests, Flask-SocketIO and CPython in your default web browser: typeshed-stats --typeshed-dir <PATH_TO_TYPESHED_CLONE> --upstream-repo requests Flask-SocketIO stdlib

Example usage of the Python-level API:

from typeshed_stats.gather import tmpdir_typeshed, gather_stats

with tmpdir_typeshed() as typeshed:
    stats_on_all_packages = gather_stats_on_multiple_packages(typeshed_dir=typeshed)

How can I use this?

1. Run pip install typeshed-stats[rich] to install the package
2. Run typeshed-stats --help for information about various options

Are there any examples of things this script can produce, other than the website?

I'm glad you asked! They're in the examples/ folder in this repo. (These examples are generated using the regenerate.py script in the scripts/ directory.)

How do I run tests/linters?

1. Clone the repo and cd into it
2. Create and activate a virtual environment
3. Run pip install -e .[dev]
4. Either run the linters/tests individually (see the .github/workflows directory for details about what's run in CI) or use the scripts/runtests.py convenience script to run them all in succession.