pydantic-factories VS geospatial-data-lake

Last but not least, we moved pydantic-factories from my GitHub namespace (Goldziher) into the starlite-api GitHub organization, so its now an official package of the org.

I'm the author and sole maintainer of a library called pydantic-factories.

You can see the docs here.

Here is the link: https://github.com/Goldziher/pydantic-factories

I'm glad to say pydantic-factories is now at v1.0.0 and includes support for pydantic v1.9.0+.

So - some of you perhaps read my previous post regarding pydantic-factories, but for those who didn't- its a python package that allows you to generate mock data for your pydantic models and dataclasses. It also works for vanilla python dataclasses, so its actually not only for pydantic.

looking at your badges - i don't care your "docs" pipeline is passing, what I am not seeing is test coverage. I suggest you checkout integrating sonar-cloud with your github repository. You can see how this looks here: https://github.com/Goldziher/pydantic-factories

Here is a link to the repository - https://github.com/Goldziher/pydantic-factories, I would of course love getting more stars. But I would especially love getting more users and contributors - really do feel free to add PRs, write issues and suggestions etc.

One option is to trust on first use, checksum the installation script and at least casually verify the diff each time the checksum changes[1].

Pros:

- Protects against simple hijacking.

- Reproducible as long as the installer doesn't also call out to a moving target, such as example.com/releases/latest.

Cons:

- Build breaks as soon as the installer is bumped. If it's bumped often (or just before an important release) this can cause pain.

- TOFU may not be acceptable, but of course you could review the code thoroughly before even the first use.

[1] https://github.com/linz/geostore/blob/b3cd162605109da8a3a688...

I'd recommend a project from work, Geostore[1]. Highlights:

- 100% test coverage (with some typical exceptions like `if __name__ == "__main__":` blocks)

- Randomises test sequence and inputs reproducibly

- Passes Pylint with max McCabe complexity of 6

- Passes `mypy --strict`

- Formatted using Black and isort

[1] https://github.com/linz/geostore

The current work project[1] has all of these: Pyenv, Poetry, Pytest, pytest-cov with 100% branch coverage, pre-commit, Pylint rather than Flake8, Black, mypy (with a stricter configuration than recommended here), and finally isort. These are all super helpful.

There's also a simpler template repo[2] with almost all of these.

[1] https://github.com/linz/geostore/

[2] https://github.com/linz/template-python-hello-world

As someone who's used CDK for a few months and never handcoded CF, that sounds completely correct. If you're comfortable with Python, here's a simple but non-trivial architecture you can check out: https://github.com/linz/geospatial-data-lake/blob/master/app....