marshmallow
Flask
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marshmallow | Flask | |
---|---|---|
11 | 135 | |
6,893 | 66,350 | |
0.9% | 0.8% | |
8.7 | 8.7 | |
7 days ago | 6 days ago | |
Python | Python | |
MIT 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.
marshmallow
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Help making draggable items for Flask app.
Somehow get a serializer going for your database models. I used marshmallow and flask-marshmallow
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Faster time-to-market with API-first
Uses a robust data validation library: validating payloads is a complex business. Your data validation library must handle optional and required properties, string formats like ISO dates and UUIDs (both dates and UUIDs are string types in OpenAPI), and strict vs loose type validation (should a string pass as an integer if it can be casted?). Also, in the case of Python, you need to make sure 1 and 0 don’t pass for True and False when it comes to boolean properties. In my experience, the best data validation libraries in the Python ecosystem are pydantic and marshmallow. From the above-mentioned libraries, flasgger and flask-smorest work with marshmallow.
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What's best library for swagger + flask?
I also came across things like Marsmallow and Blueprints, but don't know what these are, still reading about this as I write.
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pydantic VS marshmallow - a user suggested alternative
2 projects | 21 Sep 2022
Pydantic is a data validation library, marshmallow is a data validation library. None of the other libraries in the list of pydantic alternatives is a data validation library.
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Yet another object serialization framework!
I have been working on a package that is very similar in concept to marshmallow (https://marshmallow.readthedocs.io), but which adds a versioning mechanism to track changes in object structure across time, allowing you to migrate objects between different versions.
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How to implement conditional model
Either using meta programming: https://github.com/marshmallow-code/marshmallow/issues/585
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Should I use SQLAlchemy for a side project?
You might be surprised how much I agree - I recently opened an issue there hoping to discuss something like this (still awaiting response). https://github.com/marshmallow-code/marshmallow/issues/2000
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The Pocket Guide To API Request Validation You Wish You Had Earlier
Marshmallow
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Project Althaia - looking for performance/accuracy feedback on my shallow fork of marshmallow
I created a shallow fork of everyone's favourite marshmallow, to work around some performance issues while dumping data. The performance gain I measured is around 45%, but since it's a bad idea to rely on one's own testing, I was hoping that there are some folks here who use marshmallow in their projects, and who would be willing to try it out. Doubly so if your project has some unit tests in it, to confirm that nothing is broken due to my patches.
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What's the fastest way to parse JSON to output?
I was looking at https://github.com/marshmallow-code/marshmallow That's a nice library to use to parsing?
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?
Fast JSON schema for Python - Fast JSON schema validator for Python.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
cattrs - Composable custom class converters for attrs.
Django - The Web framework for perfectionists with deadlines.
serpy - ridiculously fast object serialization
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
WTForms - A flexible forms validation and rendering library for Python.
starlette - The little ASGI framework that shines. 🌟
jsonschema - JSON Schema validation library
quart - An async Python micro framework for building web applications.
ultrajson - Ultra fast JSON decoder and encoder written in C with Python bindings
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.