Search Results for "python distributed list" - Page 2
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Showing 882 open source projects for "python distributed list"
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Awesome-Quant
A curated list of insanely awesome libraries, packages and resources
awesome-quant is a curated list (“awesome list”) of libraries, packages, articles, and resources for quantitative finance (“quants”). It includes tools, frameworks, research papers, blogs, datasets, etc. It aims to help people working in algorithmic trading, quant investing, financial engineering, etc., find useful open source or educational resources. Licensed under typical “awesome” list standards. -
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Locust
Scalable open source load testing tool
Locust is an open source user load testing tool written in Python. The idea behind Locust is to swarm your web site or other systems with attacks from simulated users during a test, with each user behavior defined by you using Python code. This swarming process is then monitored from a web UI in real-time, and will help identify any bottlenecks in your code before real users can come in. As it is completely event-based, Locust can have thousands or even millions of simultaneous users distributed over multiple machines swarming your system. ... -
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Tribler
Privacy enhanced BitTorrent client with P2P content discovery
Tribler is a decentralized, privacy-enhanced BitTorrent client developed by researchers at Delft University of Technology. It introduces built-in anonymity using a Tor-like onion routing network and integrates its own blockchain for economic incentives and trust management. Tribler supports standard torrenting features along with distributed search, self-contained channels, and peer reputation. Its goal is to provide a fully autonomous file-sharing network without relying on external... -
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s3-client
Sample python script to work with Amazon S3
Example Python script to work with S3. -
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Meta Package Manager
Wraps all package managers with a unifying CLI
Meta Package Manager wraps all package managers with a unifying CLI, and provides the MPM CLI, a wrapper around all package managers. MPM is like yt-dlp, but for package managers instead of videos. MPM solves XKCD #1654 - Universal Install Script. List installed packages. List duplicate installed packages. Search for packages. Install a package, remove a package, and list outdated packages. Sync local package infos. Upgrade all outdated packages. Backup list of installed packages to TOML... -
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MoviePy
Video editing with Python
...It works on Windows, Mac, and Linux, with Python 2 or Python 3. The code is hosted on Github, where you can push improvements, report bugs and ask for help. There is also a MoviePy forum on Reddit and a mailing list on librelist. MoviePy depends on the Python modules NumPy, Imageio, Decorator, and Proglog, which will be automatically installed during MoviePy's installation. The software FFMPEG should be automatically downloaded/installed (by imageio) during your first use of MoviePy (installation will take a few seconds). -
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PyGitHub
Typed interactions with the GitHub API v3
PyGitHub is a Python library to access the GitHub REST API. This library enables you to manage GitHub resources such as repositories, user profiles, and organizations in your Python applications. PyGithub is a Python library to use the Github API v3. With it, you can manage your Github resources (repositories, user profiles, organizations, etc.) from Python scripts. Should you have any question, any remark, or if you find a bug, or if there is something you can do with the API but not with... -
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Kubeflow Training Operator
Distributed ML Training and Fine-Tuning on Kubernetes
Kubeflow Training Operator is a Kubernetes-native project for fine-tuning and scalable distributed training of machine learning (ML) models created with various ML frameworks such as PyTorch, TensorFlow, XGBoost, MPI, Paddle, and others. -
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NErlNet
Nerlnet is a framework for research and development
NErlNet is a research-grade framework for distributed machine learning over IoT and edge devices. Built with Erlang (Cowboy HTTP), OpenNN, and Python (Flask), it enables simulation of clusters on a single machine or real deployment across heterogeneous devices. -
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Payloads All The Things
A list of useful payloads and bypass for Web Application Security
A list of useful payloads and bypasses for Web Application Security. Feel free to improve with your payloads and techniques. The API key is a unique identifier that is used to authenticate requests associated with your project. Some developers might hardcode them or leave it on public shares. -
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Nebulex
In-memory and distributed caching toolkit for Elixir
...Nebulex cache abstraction shields developers from directly dealing with the underlying caching implementations, such as Redis, Memcached, or even other Elixir cache implementations like Cachex. Additionally, it provides totally out-of-box features such as cache usage patterns, declarative annotation-based caching, and distributed cache topologies, among others. For intensive workloads, you may want to use :shards as the backend for the local adapter and having partitioned tables. In such a case, you have to add :shards to the dependency list. For enabling the usage of declarative annotation-based caching via decorators, you have to add :decorator to the dependency list. -
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HDF5
Official HDF5® Library Repository
HDF5 (Hierarchical Data Format v5) is a widely-used data management library and file format for storing large and complex scientific data sets efficiently. -
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Colossal-AI
Making large AI models cheaper, faster and more accessible
The Transformer architecture has improved the performance of deep learning models in domains such as Computer Vision and Natural Language Processing. Together with better performance come larger model sizes. This imposes challenges to the memory wall of the current accelerator hardware such as GPU. It is never ideal to train large models such as Vision Transformer, BERT, and GPT on a single GPU or a single machine. There is an urgent demand to train models in a distributed environment.... -
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tracecat
The open source Tines / Splunk SOAR alternative for security engineers
Tracecat is an open-source Tines / Splunk SOAR alternative for security engineers. We're building the features of Tines using enterprise-grade open-source tools. -
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TorchMetrics
Machine learning metrics for distributed, scalable PyTorch application
TorchMetrics is a collection of 80+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. Your data will always be placed on the same device as your metrics. You can log Metric objects directly in Lightning to reduce even more boilerplate. The module-based metrics contain internal metric states (similar to the parameters of the PyTorch module) that automate accumulation and synchronization across devices! Automatic accumulation over multiple batches. Automatic... -
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Ray
A unified framework for scalable computing
...Find the best model and reduce training costs by using the latest optimization algorithms. Deploy your machine learning models at scale with Ray Serve, a Python-first and framework agnostic model serving framework. Scale reinforcement learning (RL) with RLlib, a framework-agnostic RL library that ships with 30+ cutting-edge RL algorithms including A3C, DQN, and PPO. Easily build out scalable, distributed systems in Python with simple and composable primitives in Ray Core. -
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PyTorch
Open source machine learning framework
PyTorch is a Python package that offers Tensor computation (like NumPy) with strong GPU acceleration and deep neural networks built on tape-based autograd system. This project allows for fast, flexible experimentation and efficient production. PyTorch consists of torch (Tensor library), torch.autograd (tape-based automatic differentiation library), torch.jit (a compilation stack [TorchScript]), torch.nn (neural networks library), torch.multiprocessing (Python multiprocessing), and... -
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vLLM
A high-throughput and memory-efficient inference and serving engine
vLLM is a fast and easy-to-use library for LLM inference and serving. High-throughput serving with various decoding algorithms, including parallel sampling, beam search, and more. -
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Sentry
Cross-platform application monitoring and error tracking software
Sentry is a cross-platform, self-hosted error monitoring solution that helps software teams discover, monitor and fix errors in real-time. The most users and logs will have to provide are the clues, and Sentry provides the answers. Sentry offers enhanced application performance monitoring through information-laden stack traces. It lets you build better software faster and more efficiently by showing you all issues in one place and providing the trail of events that lead to errors. It also... -
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Oumi
Everything you need to build state-of-the-art foundation models
Oumi is an open-source framework that provides everything needed to build state-of-the-art foundation models, end-to-end. It aims to simplify the development of large-scale machine-learning models. -
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DBOS Transact PY
Lightweight Durable Python Workflows
dbos-transact-py is the Python counterpart to dbos-transact-ts, offering durable transactional programming with automatic state persistence in PostgreSQL. It simplifies building resilient and idempotent applications by enabling Python functions to retain their state, restart after failure, and guarantee consistency. It's designed for data-heavy and fault-intolerant use cases. -
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CoreNet
CoreNet: A library for training deep neural networks
CoreNet is Apple’s internal deep learning framework for distributed neural network training, designed for high scalability, low-latency communication, and strong hardware efficiency. It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed... -
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Ludwig
A codeless platform to train and test deep learning models
Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code. All you need to provide is a CSV file containing your data, a list of columns to use as inputs, and a list of columns to use as outputs, Ludwig will do the rest. Simple commands can be used to train models both locally and in a distributed way, and to use them to predict on new data. -
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py-pdf-parser
A Python tool to help extracting information from structured PDFs
py-pdf-parser is a Python tool designed to help extract information from structured PDFs. It provides a simple interface to define parsing rules and extract data from PDF documents. -
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Numba
NumPy aware dynamic Python compiler using LLVM
Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code. Numba translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. Numba-compiled numerical algorithms in Python can approach the speeds of C or FORTRAN. You don't need to replace the Python interpreter, run a separate compilation step, or even have a C/C++ compiler installed.
