pydantic
Django
| pydantic | Django | |
|---|---|---|
| 183 | 549 | |
| 26,209 | 86,197 | |
| 2.3% | 0.7% | |
| 9.8 | 9.9 | |
| 5 days ago | 4 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.
pydantic
- Python Design Patterns for Clean Architecture
Pydantic Documentation
- I built binary serializer for Pydantic models that's up to 7× smaller than JSON
Found in issue where maintainer answered that they are only going to support JSON
https://github.com/pydantic/pydantic/discussions/4097
- Dict Unpacking in Python
- A Practical Guide on Structuring LLM Outputs with Pydantic
The solution? Leverage Pydantic, a Python library that enables runtime data validation using type annotations.
- Loading Pydantic models from JSON without running out of memory
Pydantic author here. We have plans for an improvement to pydantic where JSON is parsed iteratively, which will make way for reading a file as we parse it. Details in https://github.com/pydantic/pydantic/issues/10032.
Our JSON parser, jiter (https://github.com/pydantic/jiter) already supports iterative parsing, so it's "just" a matter of solving the lifetimes in pydantic-core to validate as we parse.
This should make pydantic around 3x faster at parsing JSON and significantly reduce the memory overhead.
- Advanced Pydantic: Generic Models, Custom Types, and Performance Tricks
Across this five-post series, we’ve journeyed from Pydantic’s basics—type validation and nested models—to advanced integrations with FastAPI, SQLAlchemy, and scalable techniques. You’ve learned how to build declarative, type-safe models, handle complex APIs, and optimize performance. To deepen your knowledge, explore the Pydantic documentation, contribute to the open-source project, or experiment with real-world use cases. Check out our GitHub repo for code samples and a Pydantic cheat sheet. Thank you for joining us—happy coding!
- Getting Started with Pydantic: Type-Safe Data Models in Python
To dive deeper, check out the Pydantic documentation for advanced features like nested models, custom validators, and settings management. Happy coding!
- Resumindo características da linguagem Python
- FastAPI, Pydantic, Psycopg3: the holy trinity for Python web APIs
Pydantic is bundled with FastAPI and is excellent for modelling, validating, and serialising API responses.
- Pydantic Settings + AWS the easy way
Pydantic Settings is a python library that extends 🚀 Pydantic for dealing with settings management.
Django
- Reflections on the Djangonaut Space Journey 🦄
After some hard work (the process is detailed here), I successfully submitted my first PR. I learned a tremendous amount during the review process. I hope to use this feedback to significantly improve my code quality and structure in future PRs.
- A first look at Django's new background tasks
Has it been merged into the GitHub repo? I wasn't aware of that and I don't see it here: https://github.com/django/django/tree/main/django/tasks/back...
- Python Concurrency: A Guide to Threads, Processes, and Asyncio
import requests from concurrent.futures import ThreadPoolExecutor URLS = [ "https://www.python.org/", "https://www.djangoproject.com/", "https://flask.palletsprojects.com/", ] def fetch_url(url: str): print(f"Fetching {url}...") response = requests.get(url) print(f"Fetched {url} with status {response.status_code}") return len(response.content) with ThreadPoolExecutor(max_workers=5) as executor: # The map function runs `fetch_url` for each item in URLS results = executor.map(fetch_url, URLS) for url, length in zip(URLS, results): print(f"URL: {url}, Length: {length}")
- Your first django PR - from scratch to improved patch
If this is your first Django contribution, please add yourself to the AUTHORS file and submit a Contributor License Agreement.
- Choosing Tech Stack in 2025: A Practical Guide
Django remains relevant for content-heavy applications and admin interfaces. The batteries-included philosophy means you get authentication, admin panels, ORM, and form handling out of the box. For rapid prototyping or building MVPs where you need traditional CRUD operations, Django's productivity is hard to beat.
- Flask vs. Django: Which Framework Should You Choose For Your Project?
Django is a full-stack web framework that provides developers with all the necessary tools and functions they need to develop both the backend and a significant part of the frontend of a web application within a single framework.
- FyneDesk: A full desktop environment for Linux written in Go
Before git abused the terminology, a branch used to refer to a long-lived/persistent commit lineage, most often implemented as a commit-level flag/attribute,
OTOH, git branches are pointers to one single commit (with the git UI tentatively converting this information sometimes into "that commit, specifically" or sometimes as "all ancestors commits leading to that commit", with more or less success and consistency).
Where it matters (besides fostering good/consistent UX) is when you merge several (topological) branches together: git won't be able to tell if you just merged A into B or B into A. Although the content is identical at code-level, the semantic/intent of the merge is lost. Similarly, once the head has progressed so much ahead and your history is riddled with merges, you can't tell from the DAG where the individual features/PR/series start and end. This makes bisecting very hard: while hunting down a regression, you would rather avoid checking-out mid-series commits that might break the build, and instead stick to the series boundaries. You can't do that natively with git. That also makes maintaining concurrent versions unnecessarily difficult, and many projects are struggling with that: have you seen for instance Django¹ prefixing each and every commit with the (long-lived) branch name? That's what you get with git while most other VCSes (like Mercurial, my preference) got right from the start.
¹: https://github.com/django/django/commits/stable/6.0.x
- Django 6.0 alpha 1 released
That is, based on the current state of affairs [1] you may get more structure around tasks in the app (or django packages running tasks) which is probably a nice thing. That said, you will still need to have a backend implementation [2] and the easiest path there is a celery wrapper.
[1] https://github.com/django/django/blob/main/django/tasks/base...
- Configuring CSP: A Test For Django 6.0
The Bakery Demo project uses pip from Python for package management, and the Wagtail dot org website uses Poetry. The differences in connecting both were very subtle, with the bakery demo being the easier of the two. The overarching requirement was that you would have cloned the most recent version of Django from its GitHub repository. For the Bakery Demo, you would need a virtual environment and an installation of Django pointing to your local editable version via pip install -e /path/to/django. This virtual environment would contain your Django, editable version of Wagtail, and Bakery Demo website. For a poetry-based installation, modifying the project's pyproject.toml to point to a locally editable version of Django (or mounted volume of it, as in a potential case of containerization)
- The Factory Timezone
"settings.py" is your local configuration. The global default is still Chicago:
* https://github.com/django/django/blob/main/django/conf/globa...
What are some alternatives?
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
pyparsing - Python library for creating PEG parsers
Masonite - The Modern And Developer Centric Python Web Framework. Be sure to read the documentation and join the Discord channel for questions: https://discord.gg/TwKeFahmPZ
typeguard - Run-time type checker for Python
Flask - The Python micro framework for building web applications.