Search Results for "python libraries" - Page 7
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Showing 4734 open source projects for "python libraries"
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1
Behaviour Suite Reinforcement Learning
bsuite is a collection of carefully-designed experiments
bsuite is a research framework developed by Google DeepMind that provides a comprehensive collection of experiments for evaluating the core capabilities of reinforcement learning (RL) agents. Its main goal is to identify, measure, and analyze fundamental aspects of learning efficiency and generalization in RL algorithms. The library enables researchers to benchmark their agents on standardized tasks, facilitating reproducible and transparent comparisons across different approaches. Each... -
2
OSXPhotos
Python app to work with pictures and associated metadata
OSXPhotos provides the ability to interact with and query Apple's Photos.app library on macOS and Linux. You can query the Photos library database — for example, file name, file path, and metadata such as keywords/tags, persons/faces, albums, etc. You can also easily export both the original and edited photos. OSXPhotos also works with iPhoto libraries though some features are available only for Photos. Limited support is also provided for exporting photos and metadata from iPhoto libraries.... -
3
Writer Framework
No-code in the front, Python in the back. An open-source framework
Writer Framework is an open source platform designed to help developers build AI-powered applications by combining a visual interface builder with a Python-based backend architecture. It follows a hybrid approach where user interfaces are created using a drag-and-drop editor while business logic is implemented in Python, allowing teams to balance speed and flexibility without sacrificing control. The framework is particularly focused on AI use cases, enabling developers to integrate large... -
4
urllib3
Python HTTP library with thread-safe connection pooling
urllib3 is a powerful, user-friendly HTTP client for Python. Much of the Python ecosystem already uses urllib3 and you should too. Thread safety, connection pooling. Client-side TLS/SSL verification. File uploads with multipart encoding. Helpers for retrying requests and dealing with HTTP redirects. Support for gzip, deflate, brotli, and zstd encoding. Proxy support for HTTP and SOCKS. 100% test coverage. Professional support for urllib3 is available as part of the Tidelift Subscription.... -
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5
AutoKeras
AutoML library for deep learning
AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras only support Python 3. If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0. AutoKeras supports several tasks with extremely simple interface. AutoKeras would search for the... -
6
MyPy
Optional static typing for Python
...Advanced configuration via mypy.ini or pyproject.toml enables per-module strictness, plugin hooks for popular libraries, and fine-grained control of inference and error reporting. Documentation covers everything from newcomer guides to strict mode recipes and release notes. The ecosystem includes typed stubs, third-party plugins, and broad community support that makes mypy a default choice for large Python projects. -
7
PettingZoo
An API standard for multi-agent reinforcement learning environments
PettingZoo is a standardized API and library for multi-agent reinforcement learning (MARL) environments. It provides a broad set of environments and tools to facilitate the development and evaluation of multi-agent algorithms. -
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Recommenders 2023
Best Practices on Recommendation Systems
Recommenders objective is to assist researchers, developers and enthusiasts in prototyping, experimenting with and bringing to production a range of classic and state-of-the-art recommendation systems. Recommenders is a project under the Linux Foundation of AI and Data. -
9
Claude Cookbooks
A collection of notebooks/recipes showcasing ways of using Claude
Claude Cookbooks is a curated collection of practical examples, notebooks, and implementation guides that demonstrate how to effectively use Claude’s API across a wide range of tasks. It serves as both a learning resource and a reference library, helping developers understand how to apply AI capabilities such as classification, summarization, and retrieval-augmented generation in real-world scenarios. The repository includes structured examples for integrating Claude with external tools,... -
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10
JC
CLI tool and python library
CLI tool and python library that converts the output of popular command-line tools and file types to JSON or Dictionaries. This allows piping of output to tools like jq and simplifying automation scripts. jc JSONifies the output of many CLI tools and file types for easier parsing in scripts. This allows further command-line processing of output with tools like jq or jello by piping commands. The JC parsers can also be used as python modules. In this case, the output will be a python... -
11
BindsNET
Simulation of spiking neural networks (SNNs) using PyTorch
A Python package used for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch Tensor functionality. BindsNET is a spiking neural network simulation library geared towards the development of biologically inspired algorithms for machine learning. This package is used as part of ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems in the Biologically Inspired Neural & Dynamical Systems (BINDS) lab. -
12
TextDistance
Compute distance between sequences
Python library for comparing the distance between two or more sequences by many algorithms. For main algorithms, text distance try to call known external libraries (fastest first) if available (installed in your system) and possible (this implementation can compare this type of sequences). Install text distance with extras for this feature. -
13
dm_control
DeepMind's software stack for physics-based simulation
DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo. DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo physics. The MuJoCo Python bindings support three different OpenGL rendering backends: EGL (headless, hardware-accelerated), GLFW (windowed, hardware-accelerated), and OSMesa (purely software-based). At least one of these three backends must be available in order render... -
14
pipx
Install and run Python applications in isolated environments
pipx is a tool to help you install and run end-user applications written in Python. It's roughly similar to macOS's brew, JavaScript's npx, and Linux's apt. It's closely related to pip. In fact, it uses pip, but is focused on installing and managing Python packages that can be run from the command line directly as applications. pip is a general-purpose package installer for both libraries and apps with no environment isolation. pipx is made specifically for application installation, as it adds isolation yet still makes the apps available in your shell: pipx creates an isolated environment for each application and its associated packages. pipx does not ship with pip, but installing it is often an important part of bootstrapping your system. ... -
15
Lutris
Lutris desktop client in Python
Lutris is a video game preservation platform aiming to keep your video game collection up and running for the years to come. Over the years, video games have gone through many different hardware and software platforms. By offering the best software available to run your games, Lutris makes it easy to run all your games, old and new. We provide emulators, compatibility layers and game engine re-implementations needed to run games in the most optimal way, often offering an enhanced experience... -
16
GeoAI
GeoAI: Artificial Intelligence for Geospatial Data
GeoAI is a comprehensive open-source Python package designed to integrate artificial intelligence techniques with geospatial data analysis, enabling users to perform advanced geographic modeling and visualization tasks with ease. It provides a unified framework that combines machine learning libraries such as PyTorch and Transformers with geospatial tools, allowing users to process satellite imagery, aerial photos, and vector datasets in a streamlined workflow. -
17
Tensorforce
A TensorFlow library for applied reinforcement learning
Tensorforce is an open-source deep reinforcement learning framework built on TensorFlow, emphasizing modularized design and straightforward usability for applied research and practice. -
18
geemap
A Python package for interactive geospaital analysis and visualization
A Python package for interactive geospatial analysis and visualization with Google Earth Engine. Geemap is a Python package for geospatial analysis and visualization with Google Earth Engine (GEE), which is a cloud computing platform with a multi-petabyte catalog of satellite imagery and geospatial datasets. During the past few years, GEE has become very popular in the geospatial community and it has empowered numerous environmental applications at local, regional, and global scales. GEE... -
19
Pottery
Redis for humans
Redis is awesome, but Redis commands are not always intuitive. Pottery is a Pythonic way to access Redis. If you know how to use Python dicts, then you already know how to use Pottery. Pottery is useful for accessing Redis more easily, and also for implementing microservice resilience patterns, and it has been battle-tested in production at scale. -
20
Transcrypt
Python 3.7 to JavaScript compiler
...Extensive documentation with many code examples. Apache 2.0 license. Pip-install and go! Seamless integration with the universe of high-quality web-oriented JavaScript libraries, rather than the desktop-oriented Python ones. -
21
PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
22
Pretty Jupyter
Creates dynamic html report from jupyter notebook.
Pretty Jupyter is an easy-to-use package that allows to create beautiful & dynamic HTML reports. Most of the features require little to no work to get working and greatly improve the quality of the output report, or even the developer’s comfort when creating the report. For example, tabs make some visualizations much more comfortable. The features are integrated directly into the output page, therefore there is no need to have an interpreter running in the backend. This makes the HTML easily... -
23
Umi-OCR
OCR software, free and offline
Umi-OCR is a free and open-source optical character recognition (OCR) tool designed to provide fast, offline text extraction from images, screenshots, PDFs, and more without requiring a network connection. It includes a highly efficient offline OCR engine with built-in multilingual recognition libraries, so users can extract text across multiple languages with high accuracy directly on their machines. The software supports flexible usage patterns including screenshot capture OCR, batch... -
24
Jittor
Jittor is a high-performance deep learning framework
...A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. ... -
25
Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best...
