clean-architecture
h3-py
clean-architecture | h3-py | |
---|---|---|
1 | 1 | |
465 | 756 | |
- | 0.7% | |
0.0 | 6.6 | |
about 1 year ago | 15 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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.
clean-architecture
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Python code architecture in apis development
In order to try to understand how the industry is working I started looking around for some github repos, I found this one (which is exactly what i was looking for) and some youtube talks but i would like to have more examples.
h3-py
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Command-line data analytics made easy with SPyQL
Another advantage of SPyQL is that we can leverage the Python ecosystem. Let's try to do some more geographical statistics. Let's count towers by H3 cell (resolution 5) for Europe. First, we need to install the H3 lib:
What are some alternatives?
awesome-python - An opinionated list of awesome Python frameworks, libraries, software and resources.
leafmap - A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment
wild-workouts-go-ddd-example - Go DDD example application. Complete project to show how to apply DDD, Clean Architecture, and CQRS by practical refactoring.
geemap - A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
implementing-the-clean-architecture
BlenderGIS - Blender addons to make the bridge between Blender and geographic data
eventsourcing - A library for event sourcing in Python.
felicette - Satellite imagery for dummies.
domain-driven-hexagon - Learn Domain-Driven Design, software architecture, design patterns, best practices. Code examples included
spyql - Query data on the command line with SQL-like SELECTs powered by Python expressions