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at the end of module files? Never seen that, why is it used? I understand that it's a guard that only runs when the module is executed directly, but what is the code put there? For developers to quickly visually test stuff by running the module?
Here, for example https://github.com/willmcgugan/rich/blob/master/rich/color.p...
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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
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Norvig's approach of converting thoughts into a program is what you need to focus on. It is trivial to convert a list comprehension into a loop.
In "When is Cheryl's birthday?" [1], the way he converts the problem into functional units is insane. A couple of list comprehensions shouldn't scare you. Look above and beyond the details.
[1] https://github.com/norvig/pytudes/blob/main/ipynb/Cheryl.ipy...
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The premier source of truth powering network automation. Open source under Apache 2. Public demo: https://demo.netbox.dev
NetBox[0] is a large project that does this.
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fastapi-azure-auth
Easy and secure implementation of Azure AD for your FastAPI APIs 🔒 B2C, single- and multi-tenant support.
I think, in general, most FastAPI and Pydantic related libraries are heavily typed, use poetry, GitHub pipelines, black, isort, flake8 etc. so if you want to look at the ecosystem around a package I’ll recommend a few here, that has a smaller scope than the huge libraries Pydantic/FastAPI are. All packages listed below has all these things.
FastAPI-Azure-Auth [0] is a library to do authentication and authorization through Azure AD using tokens.
ASGI—Correlation-ID[1] is a package that utilizes contextvars to store information through the asyncio stack, in order to attach correlation/request ID to every log message from a request. Available for Django in [2].
Pydantic-factories [3] is an awesome library to mock data for your pydantic models.
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django-guid
Inject an ID into every log message from a Django request. ASGI compatible, integrates with Sentry, and works with Celery
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Here's a few that haven't been mentioned yet:
- PDM: A modern Python package manager with PEP 582 support[1]
- Spleeter: Deezer source separation library including pretrained models[2]
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Here's a few that haven't been mentioned yet:
- PDM: A modern Python package manager with PEP 582 support[1]
- Spleeter: Deezer source separation library including pretrained models[2]
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