asgi-correlation-id
geospatial-data-lake
| asgi-correlation-id | geospatial-data-lake | |
|---|---|---|
| 6 | 5 | |
| 345 | 32 | |
| 5.8% | - | |
| 6.2 | 0.0 | |
| 2 months ago | about 1 year ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
asgi-correlation-id
- Logging in Python Like a Pro
- Ask HN: Good Python projects to read for modern Python?
- Tips for Making a Popular Open-Source Project in 2021 [Ultimate Guide]
- ASGI correlation ID middleware now supports Python 3.6 - 3.10 🎉
- v1.1 release of ASGI request ID middleware now supports Python 3.6 - 3.10 🎉
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Request ID middleware
If it sounds interesting, please take a look here: https://github.com/snok/asgi-correlation-id. Hopefully it can be useful to some of you.
geospatial-data-lake
-
A curated list of questionable installation instructions
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...
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Ask HN: Good Python projects to read for modern Python?
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
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Python Best Practices for a New Project in 2021
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
- Codecov bash uploader was compromised
-
AWS CloudFormation Best Practices
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....
What are some alternatives?
fastapi-azure-auth - Easy and secure implementation of Azure Entra ID (previously AD) for your FastAPI APIs 🔒 B2C, single- and multi-tenant support.
pydantic-factories - Simple and powerful mock data generation using pydantic or dataclasses
pytudes - Python programs, usually short, of considerable difficulty, to perfect particular skills.
template-python-hello-world - :triangular_ruler: Python Hello World | Minimal template for Python development
aws-cdk - The AWS Cloud Development Kit is a framework for defining cloud infrastructure in code
Loguru - Python logging made (stupidly) simple
dev-tasks - Automated development tasks for my own projects
django-guid - Inject an ID into every log message from a Django request. ASGI compatible, integrates with Sentry, and works with Celery
pip - The Python package installer
RVS_Spinner - A Fancy "Popup Prize-Wheel Spinner" UIControl
devpi - Python PyPi staging server and packaging, testing, release tool