devpi
pydantic
devpi | pydantic | |
---|---|---|
7 | 167 | |
828 | 18,733 | |
1.3% | 2.7% | |
9.3 | 9.8 | |
17 days ago | 6 days ago | |
Python | Python | |
- | 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.
devpi
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Private Python Packages With devpi
There are cases where you want the flexibility of installing a python package via pip without having it available to the open public. This article will focus on using devpi to provide a self-hosted pip compatible python package server. Ubuntu will be used for the OS as it's a fairly common Linux distribution and easily available on Windows Linux Subsystem.
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Adding Virtual Environments to Git Repo
When not providing all dependencies yourself, you might suffer from people deleting the packages you depend on (IMHO a very rare scenario). If it is really that critical (hint: usually it isn't), create a local mirror of Pypi (full or only the packages you need). Devpi, Artifactory, etc. can do that or you just dump the necessary files into Cloud storage, so you have a backup.
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PyPI in a Box
devpi acts as a caching proxy for PyPI and takes a bit less setup than this. Plus, you can use it for storing your own packages in a separate index.
https://github.com/devpi/devpi
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Publishing to a private Python repository with Poetry
There are several open-source solutions for provisioning your own, personal PyPI server — for example, this can be done using pypiserver or devpi. However, configuring these services takes time and effort, and it costs money to deploy them. Instead, we’ll use Packagr, a cloud-hosted python package server that allows you to provision your own private Python package repository. It also supports NPM packages and even Docker registries and is very easy to set up. You can get started by creating a free trial account on Packagr — when you’ve created your account, you’ll see this:
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Is there away to install Packages when not online?
devpi-server will probably for the bill
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Python Best Practices for a New Project in 2021
> One should probably run their own package server like https://github.com/pypiserver/pypiserver
Never used pypiserver but I’ve had a good experience with https://github.com/devpi/devpi
- Devpi/devpi: Python PyPi staging server and packaging, testing, release tool
pydantic
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Advanced RAG with guided generation
First, note the method prefix_allowed_tokens_fn. This method applies a Pydantic model to constrain/guide how the LLM generates tokens. Next, see how that constrain can be applied to txtai's LLM pipeline.
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utype VS pydantic - a user suggested alternative
2 projects | 15 Feb 2024
utype is a concise alternative of pydantic with simplified parameters and usages, supporting both sync/async functions and generators parsing, and capable of using native logic operators to define logical types like AND/OR/NOT, also provides custom type parsing by register mechanism that supports libraries like pydantic, attrs and dataclasses
- Pydantic v2 ruined the elegance of Pydantic v1
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Ask HN: Pydantic has too much deprecation. Why is it popular?
I like some of the changes from v1 to v2. But then you have something like this [0] removed from the library without proper documentation or replacement, resulting in ugly workarounds in the link that wont' work properly.
[0]: https://github.com/pydantic/pydantic/discussions/6337
- OpenAI uses Pydantic for their ChatCompletions API
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🍹GinAI - Cocktails mixed with generative AI
The easiest implementation I found was to use a PyDantic class for my target schema — and use that as a parameter for the method call to “ChatCompletion.create()”. Here’s a fragment of the GinAI Python classes used.
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FastStream: Python's framework for Efficient Message Queue Handling
Also, FastStream uses Pydantic to parse input JSON-encoded data into Python objects, making it easy to work with structured data in your applications, so you can serialize your input messages just using type annotations.
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Introducing FastStream: the easiest way to write microservices for Apache Kafka and RabbitMQ in Python
Pydantic Validation: Leverage Pydantic's validation capabilities to serialize and validate incoming messages
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Cannot get Langchain to work
Not sure if it is exactly related, but there is an open issue on Github for that exact message.
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FastAPI 0.100.0:Release Notes
Well the performance increase is so huge because pydantic1 is really really slow. And for using rust, I'd have expected more tbh…
I've been benchmarking pydantic v2 against typedload (which I write) and despite the rust, it still manages to be slower than pure python in some benchmarks.
The ones on the website are still about comparing to v1 because v2 was not out yet at the time of the last release.
pydantic's author will refuse to benchmark any library that is faster (https://github.com/pydantic/pydantic/pull/3264 https://github.com/pydantic/pydantic/pull/1525 https://github.com/pydantic/pydantic/pull/1810) and keep boasting about amazing performances.
On pypy, v2 beta was really really really slow.
What are some alternatives?
pypiserver - Minimal PyPI server for uploading & downloading packages with pip/easy_install
Cerberus - Lightweight, extensible data validation library for Python
Poetry - Python packaging and dependency management made easy
nexe - 🎉 create a single executable out of your node.js apps
helm - The Kubernetes Package Manager
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
pip - The Python package installer
SQLAlchemy - The Database Toolkit for Python
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
warehouse - The Python Package Index
mypy - Optional static typing for Python