sdk-python
examples
sdk-python | examples | |
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8 | 143 | |
410 | 7,776 | |
10.2% | 1.0% | |
8.2 | 5.3 | |
5 days ago | 11 days ago | |
Python | Jupyter Notebook | |
MIT License | Apache License 2.0 |
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.
sdk-python
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The Many Problems with Celery
My problem with Temporal is that it doesn't support gevent https://github.com/temporalio/sdk-python/issues/59
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Pydantic V2 rewritten in Rust is 5-50x faster than Pydantic V1
> Unless Pydantic is downloading all OS binaries with the package and loading the right one at runtime, this would become a "problem" as well.
Nah, it's not that bad. I built a Rust-backed Python library used by many [0], and with setuptools-rust (maturin wasn't flexible enough at the time) and cibuildwheel and GH actions, the wheels are built/shipped with the shared libraries embedded and the end user never has to worry or even be aware of its presence.
Pydantic has already been shipping a binary mode with an option for pure Python, so maybe they'll keep the pure Python mode around.
0 - https://github.com/temporalio/sdk-python
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Python SDK: The Release
Either way, let us know how it goes! Building something cool? We’d love to hear about it! Our forum has a new Show & Tell section. If you want to share, we’ll send you some sweet swag. Have feedback on how we can do better? We want to know that too. Raise an issue in the SDK or samples repos, or send us an email ([email protected]).
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Making Python fast for free – adventures with mypyc
We built to logic backing the Temporal Python SDK[0] in Rust and leverage PyO3. Unfortunately Maturin didn't let us do some of the advanced things we needed to do for wheel creation (at the time, unsure now), so we use setuptools-rust with Poetry.
0 - https://github.com/temporalio/sdk-python
- GitHub - temporalio/sdk-python: Temporal Python SDK
- Temporal Python SDK Beta 2 – Fault-tolerant asyncio-based workflows
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Red Engine – modern scheduling framework for Python applications
Going to shamelessly plug Temporal’s Python SDK which was designed for asyncio.
https://github.com/temporalio/sdk-python
Disclaimer: I work for Temporal
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Temporal raises $100M Series B to invest in open source and communities
hey sorry for taking a while to respond, was busy with personal stuff and hope you see this.
1. yes. its on the order of months. start watching https://github.com/temporalio/sdk-python
2. temporal itself will not produce something like that, because we much rather have a lively community of third party maintainers/startups do that and be their supporters rather than competitors. interested?
examples
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
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Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
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Releasing The Force Of Machine Learning: A Novice’s Guide 😃
TensorFlow: An open-source machine learning framework for high-performance numerical computations, especially well-suited for deep learning.
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MLOps in practice: building and deploying a machine learning app
The tool used to build the model per se was TensorFlow, a very powerful and end-to-end open source platform for machine learning with a rich ecosystem of tools. And in order to to create the needed script using TensorFlow Jupyter Notebook was used, which is a web-based interactive computing platform.
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🔥14 Excellent Open-source Projects for Developers😎
10. TensorFlow - Make Machine Learning Work for You 🤖
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GPU Survival Toolkit for the AI age: The bare minimum every developer must know
AI models, particularly those built on deep learning frameworks like TensorFlow, exhibit a high degree of parallelism. Neural network training involves numerous matrix operations, and GPUs, with their expansive core count, excel in parallelizing these operations. TensorFlow, along with other popular deep learning frameworks, optimizes to leverage GPU power for accelerating model training and inference.
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
#2 TensorFlow
- Are there people out there who still like Sam atlman - AI IS AT DANGER
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Tensorflow help
I am on a new ftc team trying to get vision to work. I used the ftc machine learning tool chain but I have yet to get a good result with at best a 10% accuracy rate. I have changed everything possible in the tool chain with little luck. To fix this, I have tried making my own .tflite model using the google colab from https://www.tensorflow.org/. When ever I try to run the same code with my own .tflite model, it gives me the error "User code threw an uncaught exception: IllegalStateException - Error getting native address of native library: task_vision_jni". It gives me the same error with official tensor flow tflite test models, and when I put them on a raspberry pi, both worked just fine. Does anyone have a fix to this error or even just tips for the machine learning toolchain?
What are some alternatives?
sdk-java - Temporal Java SDK
cppflow - Run TensorFlow models in C++ without installation and without Bazel
arq - Fast job queuing and RPC in python with asyncio and redis.
mlpack - mlpack: a fast, header-only C++ machine learning library
matrix-mul-test - Testing matmul performance on the M1 Mac
awesome-teachable-machine - Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
samples-python - Samples for working with the Temporal Python SDK
face-api.js - JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
shiv - shiv is a command line utility for building fully self contained Python zipapps as outlined in PEP 441, but with all their dependencies included.
Selenium WebDriver - A browser automation framework and ecosystem.
sdk-java - The official Java library for the Modzy Machine Learning Operations (MLOps) Platform
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing