geospatial-data-lake
flake8-alphabetize
| geospatial-data-lake | flake8-alphabetize | |
|---|---|---|
| 5 | 2 | |
| 32 | 16 | |
| - | - | |
| 0.0 | 3.8 | |
| about 1 year ago | 12 months ago | |
| Python | Python | |
| MIT License | MIT No Attribution |
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.
geospatial-data-lake
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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
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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....
flake8-alphabetize
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My take on the study from MIT that predicts “societal collapse”
You're right that energy ultimately dissipates as heat, but the important thing is what the energy achieves in between hitting the earth as sunlight and then heading off into space as infrared. If you put a solar panel in place to turn the light into electricity and then use that electricity to write a Python plugin for Flake8 https://github.com/tlocke/flake8-alphabetize then maybe you're contributed something to the economy :-)
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Python Best Practices for a New Project in 2021
I think you mean Flake8 rather than Sense8? Anyway, gives me a chance to plug Flake8 Alphabetize, a Flake8 plugin for import ordering https://github.com/tlocke/flake8-alphabetize
What are some alternatives?
pydantic-factories - Simple and powerful mock data generation using pydantic or dataclasses
pydantic - Data validation using Python type hints
template-python-hello-world - :triangular_ruler: Python Hello World | Minimal template for Python development
flynt - A tool to automatically convert old string literal formatting to f-strings
asgi-correlation-id - Request ID propagation for ASGI apps
pyright - Static Type Checker for Python
aws-cdk - The AWS Cloud Development Kit is a framework for defining cloud infrastructure in code
dev-tasks - Automated development tasks for my own projects
helm - The Kubernetes Package Manager
pip - The Python package installer
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.