Shapely
fastapi
Shapely | fastapi | |
---|---|---|
7 | 468 | |
3,678 | 71,023 | |
1.1% | - | |
8.4 | 9.8 | |
17 days ago | 7 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" 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.
Shapely
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Object oriented programming in GiS
https://github.com/shapely/shapely First paragraph of readme agrees w/ me
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I used Python to control a custom stop-motion animation drawing machine
The frames' vector data is generated using a sketch made with my vsketch framework (it involves loading GeoJSON data, processing it with Shapely, and projecting it in 3D with NumPy).
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GIS Developer career path
As has been said the definition of a GIS dev is far from written in stone, but to chime in from a personal standpoint: most of what I do is data wrangling/analysis with shapely/geopandas for vectors (or pygeos / fiona for performance when data volumes get large, but seeing as Shapely 2.0 just got released one can likely skip this part) + rasterio for rasters as well as parallelising these tasks for performance if needed (ray is great for that) and then performing machine learning learning against the data (mostly with sklearn and torch).
- shapely 2.0b1 released
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Using QGIS Processing Toolbox in an Independent Application?
geopandas and the underlying geometry library shapely provide an alternative to the majority of the basic GIS functionality of qgis. See e.g. https://autogis-site.readthedocs.io/en/latest/ for a tutorial for the basics of these libraries.
- Shapely 1.8.0 released
- Trouble interpreting traceback from attempting to use DeepLabCut
fastapi
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Python: A SQLAlchemy Wrapper Component That Works With Both Flask and FastAPI Frameworks
It has been an interesting exercise developing this wrapper component. The fact that it seamlessly integrates with the FastAPI framework is just a bonus for me; I didn't plan for it since I hadn't learned FastAPI at the time. I hope you find this post useful. Thank you for reading, and stay safe as always.
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FastAPI Best Practices: A Condensed Guide with Examples
FastAPI is a modern, high-performance web framework for building APIs with Python, based on standard Python type hints.
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Building an Email Assistant Application with Burr
In this tutorial, I will demonstrate how to use Burr, an open source framework (disclosure: I helped create it), using simple OpenAI client calls to GPT4, and FastAPI to create a custom email assistant agent. We’ll describe the challenge one faces and then how you can solve for them. For the application frontend we provide a reference implementation but won’t dive into details for it.
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FastAPI Got Me an OpenAPI Spec Really... Fast
That’s when I found FastAPI.
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How to Deploy a Fast API Application to a Kubernetes Cluster using Podman and Minikube
FastAPI & Uvicorn
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Analysing FastAPI Middleware Performance
Discussion at FastAPI GitHub: https://github.com/tiangolo/fastapi/issues/2696
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LangChain, Python, and Heroku
An API application framework (such as FastAPI)
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Litestar – powerful, flexible, and highly performant Python ASGI framework
It’s been my experience that async Python frameworks tend to turn IO bound problems into CPU bound problems with a high enough request rate, because due to their nature they act as unbounded queues.
This ends up made worse if you’re using sync routes.
If you’re constrained on a resource such as a database connection pool, your framework will continue to pull http requests off the wire that a sane client will cancel and retry due to timeouts because it takes too long to get a connection out of the pool. Since there isn’t a straightforward way to cancel the execution of a route handler in every Python http framework I’ve seen exhibit this problem, the problem quickly snowballs.
This is an issue with fastapi, too- https://github.com/tiangolo/fastapi/issues/5759
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AI-Powered Image Search with CLIP, pgvector, and Fast API
Fast API.
- Ask HN: What is your go-to stack for the web?
What are some alternatives?
geopy - Geocoding library for Python.
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
GeoDjango - GeoDjango provides geospatial extensions to the Django web dev framework
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
geojson - Python bindings and utilities for GeoJSON
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
geoip2 - Python code for GeoIP2 webservice client and database reader
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
django-countries - A Django application that provides country choices for use with forms, flag icons static files, and a country field for models.
Flask - The Python micro framework for building web applications.
geocoder - :earth_asia: Python Geocoder
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.