httpx
Flask
httpx | Flask | |
---|---|---|
53 | 135 | |
12,274 | 66,417 | |
1.2% | 0.4% | |
8.9 | 8.7 | |
7 days ago | about 13 hours ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | 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.
httpx
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A Retrospective on Requests
For reference, it's a butterfly, not a moth.
Source: https://github.com/encode/httpx/issues/834
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Show HN: Twitter API Wrapper for Python – No API Keys Needed
Very cool, first I'm hearing of httpx https://www.python-httpx.org/
I think most people would start with trying out requests or something for this kind of work, I'm guessing that didn't work out? You've got a star from me.
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Harlequin: SQL IDE for Your Terminal
To access 10 different commands at the same time, that is tricky but definitely doable.
First thing that comes to mind, you can use aliases.
To keep it simple, lets use 3 examples instead of 10: harlequin (this project), pgcli (https://www.pgcli.com/) and httpx (https://www.python-httpx.org/)
Setup a main home for all your venvs:
cd ~
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HTTP Rate Limit
There are already some implementations for Python HTTP clients. One of them is aiometer. But it's not suitable for my use case. Since httpx already has the internal pool, it would be better to reuse the design.
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Introducing Flama for Robust Machine Learning APIs
Besides, flama also provides support for SQL databases via SQLAlchemy, an SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL. Finally, flama also provides support for HTTP clients to perform requests via httpx, a next generation HTTP client for Python.
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Embracing Modern Python for Web Development
We can use the async HTTP client provided by httpx, a fully featured HTTP client for Python with an API broadly compatible with requests, so it can be used in pretty much the same way in most cases.
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Didn't want to click on refresh to see updates, this is what I did!
httpx in place of requests library
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Python Requests 3
The main value of Requests is that it provided an abstract interface on top of HTTP, which was designed well-enough to become a standard. But today it has fallen way behind in its field, and there are much better alternatives such as HTTPX [0].
[0] https://www.python-httpx.org/
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Unlocking Performance: A Guide to Async Support in Django
HTTPX is a popular Python library that provides an asynchronous HTTP client, and it can be beneficial for enabling async support in Django. While Django itself does not require HTTPX for async support, using HTTPX in combination with Django's async views can bring several advantages:
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Show HN: Python package for interfacing with ChatGPT with minimized complexity
The underlying library for both sync and async is httpx (https://www.python-httpx.org/) which may be limited from the HTTP Client perspective but it may be possible to add rate limiting at a Session level.
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?
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
Niquests - Requests but with HTTP/3, HTTP/2, Multiplexed Connections, System CAs, Certificate Revocation, DNS over HTTPS / TLS / QUIC or UDP, Async, DNSSEC, and (much) pain removed!
Django - The Web framework for perfectionists with deadlines.
requests-html - Pythonic HTML Parsing for Humansâ„¢
requests - A simple, yet elegant, HTTP library.
starlette - The little ASGI framework that shines. 🌟
quart - An async Python micro framework for building web applications.
flask-pydantic - flask extension for integration with the awesome pydantic package
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.