PyJNIus
pydantic
PyJNIus | pydantic | |
---|---|---|
5 | 167 | |
1,353 | 18,733 | |
0.6% | 2.7% | |
6.7 | 9.8 | |
20 days ago | 2 days ago | |
Python | Python | |
MIT License | 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.
PyJNIus
- ImportError: DLL load failed: The specified module could not be found.
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How to implement Fingerprint in kivy python
I am not aware of any good example code for this, but you can access platform-specific APIs with pyjnius (android) and pyobjus (ios). This should allow you to implement fingerprint authentication using Google/Apple APIs for those platforms -- for Windows, Linux, MacOS you probably will need to research other solutions for doing this with Python (it doesn't really involve kivy)
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buildozer -v android debug error
[INFO]: -> running basename https://github.com/kivy/pyjnius/archive/1.3.0.zip
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Reference gathering about development for android
In terms of Kivy and Android, there are two main repositories worth checking out. The first is pyjnius which is a bridge to the Android APIs, and the second is plyer which uses pyjnius to implement Android-specific features (see plyer/platforms/android directory)
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How do I store user authentication token in my kivy app?
I have never used KeyStore to be clear, but yes, you would use pyjnius to access native Android classes/services. Just a quick google landed this issue which contains some partial autoclass that probably is something like how you'd do this..
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?
jpype - JPype is cross language bridge to allow Python programs full access to Java class libraries.
Cerberus - Lightweight, extensible data validation library for Python
plyer - Plyer is a platform-independent Python wrapper for platform-dependent APIs
nexe - 🎉 create a single executable out of your node.js apps
SWIG - SWIG is a software development tool that connects programs written in C and C++ with a variety of high-level programming languages.
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
PyCUDA - CUDA integration for Python, plus shiny features
SQLAlchemy - The Database Toolkit for Python
cffi
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
python-for-android - Turn your Python application into an Android APK
mypy - Optional static typing for Python