pyright
fastapi
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pyright | fastapi | |
---|---|---|
135 | 465 | |
12,055 | 70,779 | |
2.6% | - | |
9.8 | 9.8 | |
about 14 hours ago | 6 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | 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.
pyright
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Enhance Your Project Quality with These Top Python Libraries
Pyright is a fast type checker meant for large Python source bases. It can run in a “watch” mode and performs fast incremental updates when files are modified.
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How to speed up Pyright + eglot.
However, I made it faster for my use-case by changing some settings. Neovim allows to have these settings in the setup function for LSP. I was trying to figure out how do I change these settings with doom emacs. Pyright docs suggest to have these settings in pyrightconfig.json.
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Mypy 1.6 Released
Not exactly what you are looking for but maybe useful to others.
https://github.com/microsoft/pyright/blob/main/docs/mypy-com...
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VSCodium – Libre Open Source Software Binaries of VS Code
You can use pyright instead[0]. It is the FOSS version of pyright, but having some features missing.
[0]: https://github.com/microsoft/pyright
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How do you enable semantic highlighting for Python?
Unfortunately, pyright explicitly stated that they are not interested in inlay hints or other language server features, that those will only be added to pylance. That's why I added it myself instead of submitting a pull request to pyright. See https://github.com/microsoft/pyright/issues/4325
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How do I enable an LSP for json files?
return { -- add pyright to lspconfig { "neovim/nvim-lspconfig", ---@class PluginLspOpts opts = { ---@type lspconfig.options servers = { -- Listed servers will be automatically loaded to buffers jsonls = { settings = { json = { format = { enable = true, }, }, validate = { enable = true }, }, }, pyright = { settings = { python = { analysis = { -- https://github.com/microsoft/pyright/blob/main/docs/settings.md autoSearchPaths = false, useLibraryCodeForTypes = true, diagnosticMode = "openFilesOnly", }, }, }, }, }, -- Add folding capability to use LSP for ufo plugin capabilities = { textDocument = { foldingRange = { dynamicRegistration = false, lineFoldingOnly = true, }, }, }, }, }, }
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VSCode isn't Recognizing installed Python Modules?
[{ "resource": "/Documents/Coding/VSCode/Projects/Photoeditor/PhotoEditor.py", "owner": "_generated_diagnostic_collection_name_#0", "code": { "value": "reportMissingModuleSource", "target": { "$mid": 1, "external": "https://github.com/microsoft/pyright/blob/main/docs/configuration.md#reportMissingModuleSource", "path": "/microsoft/pyright/blob/main/docs/configuration.md", "scheme": "https", "authority": "github.com", "fragment": "reportMissingModuleSource" } }, "severity": 4, "message": "Import \"requests\" could not be resolved from source", "source": "Pylance", "startLineNumber": 2, "startColumn": 8, "endLineNumber": 2, "endColumn": 16 }]
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Pyright does not respect virtualenv (astronvim)
I don't use astro, but you can configure pyright by using a pyrightconfig.json or directly in the LSP configuration.
- Eglot + pyright can not get completion on django.db.models
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Remote Development, Python IDE.
I prefer jedi over pyright as pyright has crippled documentation support outside of VSCode. I also found jedi is make correct suggestions based on inferred type in some situations where pyright would need type annotation to provide completions, pyright is significantly faster though. Jedi with mypy and flake8 is comparable to pyright I think, but unfortunately mypy wasn't working over tramp. Also isort wasn't working over tramp, but jedi, black, importmagic and flake8 all worked.
fastapi
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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?
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Fun with Avatars: Crafting the core engine | Part. 1
We will create our API using FastAPI, a modern high-performance web framework for building fast APIs with Python. It is designed to be easy to use, efficient, and highly scalable. Some key features of FastAPI include:
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Building Fast APIs with FastAPI: A Comprehensive Guide
FastAPI is a modern, fast, web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed to be easy to use, fast to run, and secure. In this blog post, we’ll explore the key features of FastAPI and walk through the process of creating a simple API using this powerful framework.
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Effortless API Documentation: Accelerating Development with FastAPI, Swagger, and ReDoc
FastAPI is a modern, fast web framework for building APIs with Python 3.7+ that automatically generates OpenAPI and JSON Schema documentation. While FastAPI simplifies API development, manually creating and updating API documentation can still be a time-consuming task. In this blog post, we’ll explore how to leverage FastAPI’s automatic documentation generation capabilities, specifically focusing on Swagger and ReDoc, and how to streamline the process of documenting your APIs.
What are some alternatives?
jedi-language-server - A Python language server exclusively for Jedi. If Jedi supports it well, this language server should too.
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
mypy - Optional static typing for Python
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
python-lsp-server - Fork of the python-language-server project, maintained by the Spyder IDE team and the community
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
python-language-server - Microsoft Language Server for Python
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
coc-jedi - coc.nvim wrapper for https://github.com/pappasam/jedi-language-server
Flask - The Python micro framework for building web applications.
pylance-release - Documentation and issues for Pylance
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.