mypyc
pydantic
mypyc | pydantic | |
---|---|---|
25 | 167 | |
1,667 | 18,733 | |
0.1% | 2.7% | |
0.0 | 9.8 | |
about 1 year ago | 6 days ago | |
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.
mypyc
- Making use of type hints
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Writing Python like it's Rust
That would be interesting! You might already be aware. But there's mypyc[0], which is an AOT compiler for Python code with type hints (that, IIRC, mypy uses to compile itself into a native extension).
Wanted to give you a head-start on the lit-review for your students I guess :)
[0] https://github.com/mypyc/mypyc
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The different uses of Python type hints
https://github.com/mypyc/mypyc
> Mypyc compiles Python modules to C extensions. It uses standard Python type hints to generate fast code. Mypyc uses mypy to perform type checking and type inference.
> Mypyc can compile anything from one module to an entire codebase. The mypy project has been using mypyc to compile mypy since 2019, giving it a 4x performance boost over regular Python.
I have not experience a 4x boost, rather between 1.5x and 2x. I guess it depends on the code.
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The Python Paradox
Funny how emergence works with tools. Give a language too few tools but viral circumstances - the ecosystem diverges (Lisps, Javascript). Give it too long an iteration time but killer guarantees, you end up with committees. Python not falling into either of these traps should be understood as nothing short of magic in emergence.
I only recently discovered that python's reference typechecker, mypy, has a small side project for typed python to emit C [1], written entirely in python. Nowadays with python's rich specializer ecosystem (LLVM, CUDA, and just generally vectorized math), the value of writing a small program in anything else diminishes quickly.
Imagine reading the C++wg release notes in the same mood that you would the python release notes.
[1] https://github.com/mypyc/mypyc
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Codon: A high-performance Python compiler
> Note that the mypyc issue tracker lives in this repository! Please don't file mypyc issues in the mypy issue tracker.
See https://github.com/mypyc/mypyc/blob/master/show_me_the_code....
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ELI5: Can’t one write a compiler for Python and make everything go brrrr?
And mypyc https://github.com/mypyc/mypyc
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Is it time for Python to have a statically-typed, compiled, fast superset?
More recent approaches include mypyc which is (on the tin) quite close to what you describe, and taichi that lives in between.
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Pholyglot version 0.0.0 (PHP to PHP+C polyglot transpiler)
Have you encountered mypyc?
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Python 3.11 is 25% faster than 3.10 on average
https://github.com/mypyc/mypyc
> Mypyc compiles Python modules to C extensions. It uses standard Python type hints to generate fast code. Mypyc uses mypy to perform type checking and type inference.
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Comparing implementations of the Monkey language VIII: The Spectacular Interpreted Special (Ruby, Python and Lua)
Regarding the large execution time mentioned in your article, I discovered (mypyc)[https://github.com/mypyc/mypyc] on this subreddit in a post from the black formatter team https://www.reddit.com/r/Python/comments/v2009i/im_that_person_who_got_black_compiled_with_mypyc/?utm_medium=android_app&utm_source=share
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?
Cython - The most widely used Python to C compiler
Cerberus - Lightweight, extensible data validation library for Python
mypy - Optional static typing for Python
nexe - 🎉 create a single executable out of your node.js apps
beartype - Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
CPython - The Python programming language
SQLAlchemy - The Database Toolkit for Python
pex - A tool for generating .pex (Python EXecutable) files, lock files and venvs.
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
pyccel - Python extension language using accelerators