pyright
Flask
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pyright | Flask | |
---|---|---|
135 | 135 | |
12,006 | 66,350 | |
2.2% | 0.7% | |
9.8 | 8.7 | |
7 days ago | 1 day ago | |
Python | Python | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" 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 โwatchโ 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 โ 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.
Flask
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Ask HN: High quality Python scripts or small libraries to learn from
I'd suggest Flask or some of the smaller projects in the Pallets ecosystem:
https://github.com/pallets/flask
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Rapid Prototyping with Flask, Bootstrap and Secutio
#!/usr/bin/python # # https://flask.palletsprojects.com/en/3.0.x/installation/ # from flask import Flask, jsonify, request contacts = [ { "id": "1", "firstname": "Lorem", "lastname": "Ipsum", "email": "[email protected]", }, { "id": "2", "firstname": "Mauris", "lastname": "Quis", "email": "[email protected]", }, { "id": "3", "firstname": "Donec Purus", "lastname": "Purus", "email": "[email protected]", } ] app = Flask(__name__, static_url_path='', static_folder='public',) @app.route("/contact//save", methods=["PUT"]) def save_contact(id): data = request.json contacts[id - 1] = data return jsonify(contacts[id - 1]) @app.route("/contact/", methods=["GET"]) @app.route("/contact//edit", methods=["GET"]) def get_contact(id): return jsonify(contacts[id - 1]) @app.route('/') def root(): return app.send_static_file('index.html') if __name__ == '__main__': app.run(debug=True)
- Microdot "The impossibly small web framework for Python and MicroPython"
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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10 Github repositories to achieve Python mastery
Explore here.
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Ask HN: What would you use to build a mostly CRUD back end today?
I may use Flask-Admin initially to offload the "CRUD" operations to have an initial prototype fast but then drop it ASAP because I don't want to write a "flask-admin application" to fight against later on. If the application is mainly "CRUD", then Flask-Admin is suitable.
Now...
Would you do a breakdown/list of all the jobs you've done by sector/vertical and by function/role and by application functionality?
- [0]: https://flask.palletsprojects.com
- [1]: https://flask-admin.readthedocs.io/en/latest
- [2]: https://flask.palletsprojects.com/en/2.3.x/patterns/celery
- [3]: https://sentry.io
- [4]: https://posthog.com
- [5]: https://www.docker.com
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Implementing continuous delivery pipelines with GitHub Actions
In the lab to follow, we will be setting up an end-to-end DevOps workflow for a Flask microservice with GitHub Actions, using a self-managed custom runner for maximal control over the pipeline execution environment and automating deployments to a local Kubernetes cluster. Furthermore, we will construct separate pipelines for our "development" and "production" environments to further elaborate on the concepts of continuous deployment and delivery.
- How do you iterate on a library built locally?
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Flask Application Load Balancing using Docker Compose and Nginx
Flask Micro web Framework: You will use Flask to build a Flask web application.
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Open Source Flask-based web applications
In an earlier post I mentioned a bunch of Open Source web applications. Let's now focus on the ones written in Python using Flask the light-weight web framework.
What are some alternatives?
jedi-language-server - A Python language server exclusively for Jedi. If Jedi supports it well, this language server should too.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
mypy - Optional static typing for Python
Django - The Web framework for perfectionists with deadlines.
python-lsp-server - Fork of the python-language-server project, maintained by the Spyder IDE team and the community
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
python-language-server - Microsoft Language Server for Python
quart - An async Python micro framework for building web applications.
coc-jedi - coc.nvim wrapper for https://github.com/pappasam/jedi-language-server
starlette - The little ASGI framework that shines. ๐
pylance-release - Documentation and issues for Pylance
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.