geospatial-data-lake
global_tectonics
geospatial-data-lake | global_tectonics | |
---|---|---|
5 | 2 | |
32 | 121 | |
- | - | |
0.0 | 2.8 | |
about 1 year ago | 7 months ago | |
Python | QML | |
MIT License | GNU General Public License v3.0 only |
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....
global_tectonics
What are some alternatives?
pydantic-factories - Simple and powerful mock data generation using pydantic or dataclasses
atlas - OSM in memory
template-python-hello-world - :triangular_ruler: Python Hello World | Minimal template for Python development
felicette - Satellite imagery for dummies.
asgi-correlation-id - Request ID propagation for ASGI apps
awesome-earthobservation-code - A curated list of awesome tools, tutorials, code, projects, links, stuff about Earth Observation, Geospatial Satellite Imagery
aws-cdk - The AWS Cloud Development Kit is a framework for defining cloud infrastructure in code
gdal - GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
dev-tasks - Automated development tasks for my own projects
leaflet-geoman - 🍂🗺️ The most powerful leaflet plugin for drawing and editing geometry layers
pip - The Python package installer
ogcapi-features - An open standard for querying geospatial information on the web.