Search Results for "python libraries" - Page 9
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Showing 1406 open source projects for "python libraries"
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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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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and... -
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Strawberry GraphQL
A GraphQL library for Python that leverages type annotations
Python GraphQL library based on dataclasses. Strawberry's friendly API allows to create GraphQL API rather quickly, the debug server makes it easy to quickly test and debug. Django and ASGI support allow having your API deployed in production in a matter of minutes. The quick start method provides a server and CLI to get going quickly. Strawberry comes with a mypy plugin that enables statically type-checking your GraphQL schema. A Django view is provided for adding a GraphQL endpoint to your... -
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Opacus
Training PyTorch models with differential privacy
Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the client, has little impact on training performance, and allows the client to online track the privacy budget expended at any given moment. Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source,... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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,... -
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pybind11
Seamless operability between C++11 and Python
Pybind11 is a lightweight, header‑only C++ library that simplifies and streamlines creating Python bindings for C++11+ code. It uses template meta-programming to automatically infer types, minimizing boilerplate compared to Boost.Python, and works seamlessly with major build systems -
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Polars
Dataframes powered by a multithreaded, vectorized query engine
Polars is a high-performance, multi-language DataFrame library built in Rust using Apache Arrow. It delivers blazing-fast, vectorized, and parallel data manipulation with both eager and lazy execution, making it an excellent tool for data processing in Python, Rust, Node.js, R, and SQL contexts. -
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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... -
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TensorFlow.js
TensorFlow.js is a library for machine learning in JavaScript
TensorFlow.js is a library for machine learning in JavaScript. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Retrain pre-existing ML models using your own data. Build and train models directly in JavaScript using flexible and intuitive APIs. Tensors are the core datastructure of TensorFlow.js They are a generalization of vectors and matrices to... -
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hosts
Consolidate and extend hosts files from several well-curated sources
Consolidating and extending hosts files from several well-curated sources. You can optionally pick extensions to block pornography, social media, and other categories. The unified hosts file is optionally extensible. Extensions are used to include domains by category. Currently, we offer the following categories: fakenews, social, gambling, and porn. Extensions are optional, and can be combined in various ways with the base hosts file. The combined products are stored in the alternates... -
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Metaflow
A framework for real-life data science
Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. -
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gopy
gopy generates a CPython extension module from a go package
This is an improved version that works with current versions of Go (e.g., 1.15 -- should work with any future version going forward), and uses unique int64 handles to interface with python, so that no pointers are interchanged, making everything safe for the more recent moving garbage collector. It also supports python modules having any number of Go packages, and generates a separate .py module file for each package, which link into a single common binding library. It has been tested extensively on reproducing complex Go code in large libraries -- most stuff "just works". ... -
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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++. ... -
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Lightly
A python library for self-supervised learning on images
A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training... -
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Jupyter Docker Stacks
Ready-to-run Docker images containing Jupyter applications
Jupyter Docker Stacks provides a curated set of ready-to-run Docker container images that bundle Jupyter applications with popular data science and computing tools, enabling users to quickly start working in a reproducible environment. These stacks support a range of use cases, from lightweight base notebook images to full featured environments that include scientific computing libraries, machine learning tools, and IDE-like notebook interfaces, all within Docker containers that run consistently across machines. Users can pull a particular stack image and launch a Jupyter server without worrying about installing Python, R, or complex dependencies themselves — everything needed is baked into the container. This makes the stacks especially useful for education, demos, collaborative coding, and CI/CD workflows where consistent environments are crucial, and it integrates smoothly with cloud platforms, JupyterHub deployments, and Binder for interactive sharing. -
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Albumentations
Fast image augmentation library and an easy-to-use wrapper
Albumentations is a computer vision tool that boosts the performance of deep convolutional neural networks. Albumentations is a Python library for fast and flexible image augmentations. Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection.... -
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Render Farm Deployment Kit on AWS (RFDK)
Library for use with the AWS Cloud Development Kit
The Render Farm Deployment Kit on AWS (RFDK) is an open-source software development kit (SDK) that can be used to deploy, configure, and manage your render farm infrastructure in the cloud. It offers high-level object-oriented abstractions to define render farm infrastructure using the power of Python and Typescript. The Render Farm Deployment Kit (RFDK) on AWS is an open-source software development kit that can be used to deploy, configure, and manage your render farm infrastructure in the... -
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libvips
A fast image processing library with low memory needs
...It can also load images via ImageMagick or GraphicsMagick, letting it work with formats like DICOM. It comes with bindings for C, C++, and the command-line. Full bindings are available for Ruby, Python, PHP, C# / .NET, Go, and Lua. -
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Spyder notebook plugin
Jupyter notebook integration with Spyder
Spyder plugin to use Jupyter notebooks inside Spyder. Currently, it supports basic functionality such as creating new notebooks, opening any notebook in your filesystem and saving notebooks at any location. You can also use Spyder's file switcher to easily switch between notebooks and open an IPython console connected to the kernel of a notebook to inspect its variables in the Variable Explorer. -
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Open Asset Import Library
The open-asset-importer-library repository
The Open Asset Import Library (short name: Assimp) is a portable Open-Source library to import various well-known 3D model formats in a uniform manner. The most recent version also knows how to export 3d files and is therefore suitable as a general-purpose 3D model converter. See the feature-list. open3mod is a Windows-based model viewer. It loads all file formats that Assimp supports and is perfectly suited to quickly inspect 3d assets. Assimp aims to provide a full asset conversion... -
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LocalGPT
Chat with your documents on your local device using GPT models
LocalGPT is a private, on-premises document intelligence platform for questioning, summarizing, and analyzing files with locally hosted language models. Its data remains on the user’s machine, making it suitable for confidential or offline workflows. The retrieval system combines semantic similarity, keyword matching, late chunking, contextual enrichment, and sentence-level pruning. A smart router chooses between retrieval-augmented generation and direct model responses for each query. An... -
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jlens
Companion code for the global workspace interpretability paper
Jacobian Lens is Anthropic’s reference implementation for examining what a language model’s internal activations are inclined to produce as text. It transports residual-stream vectors from selected layers and positions into the final-layer basis using an averaged input-output Jacobian. The transformed vectors are decoded through the model’s own unembedding into ranked vocabulary predictions. The package can fit new lenses, load saved ones, apply them to prompts, and merge results from... -
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Think Bayes 2
Text and code for the second edition of Think Bayes, by Allen Downey
Think Bayes 2 is the companion repository for the second edition of Allen B. Downey’s introduction to Bayesian statistics. It teaches Bayesian reasoning through computational methods instead of relying mainly on symbolic mathematics. Each chapter is presented as a Jupyter notebook where readers can study the text, run examples, and complete exercises. Separate solution materials help learners check their work and explore alternative approaches. The lessons cover probability distributions,... -
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wxWidgets
Cross-Platform C++ GUI Library
wxWidgets is a C++ library that lets developers create applications for Windows, macOS, Linux, and other platforms with a single code base. It has popular language bindings for Python, Ruby, Lua, Perl, and several other languages, and unlike other cross-platform toolkits, wxWidgets gives applications a truly native look and feel because it uses the platform's native API rather than emulating the GUI. It's also extensive, free, open-source, and mature. -
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Atheris
A Coverage-Guided, Native Python Fuzzer
Atheris is a coverage-guided fuzzer for CPython that treats Python as a first-class fuzzing target, enabling rapid discovery of crashes and logic errors in pure-Python code and native extensions. It hooks into Python’s interpreter to collect fine-grained coverage and uses that signal to evolve inputs, pushing programs into previously unexplored code paths. Because many Python libraries are thin wrappers over C/C++ code, Atheris is equally adept at surfacing memory safety issues in extension modules compiled with sanitizers. ...
