Browse free open source Python Libraries and projects below. Use the toggles on the left to filter open source Python Libraries by OS, license, language, programming language, and project status.

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  • 1
    jlens

    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 parallel fitting jobs. Interactive layer-by-position views reveal how token rankings evolve across the network and compare them with the model’s final output. It supports open-weight Hugging Face decoder models, with Qwen used in the included examples. The repository also provides synthetic evaluation data and an end-to-end notebook, but it is not maintained.
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  • 2

    jpathpy

    Select items from JSON by using JPath syntax

    Package ``jpathpy`` is easy way for selecting items from objects, that can be iterate by keys or indices (such as dictionaries or lists). See full doc at <https://github.com/vowatchka/jpathpy>.
    5.0 out of 5 stars 1 Review
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  • 3
    jsondata

    jsondata

    Modular JSON by trees and branches, pointers and patches

    The 'jsondata' package provides for the modular in-memory processing of JSON data by trees, branches, pointers, and patches. The main interface classes are: - JSONData - Core for RFC7159 based data structures. Provides modular data components. - JSONDataSerializer - Core for RFC7159 based data persistence. Provides modular data serialization. - JSONPointer - RFC6901 for addressing by pointer paths. Provides pointer arithmetics. - JSON Relative Pointer - draft-handrews-relative-json-pointer/2018, contained in JSONPointer. - JSONPatch - RFC6902 for modification by patch lists. Provides the assembly of modular patch entries and the serialization of resulting patch lists. - JSONDiff - Diff utility for JSON data. - JSONSearch - Search utility JSON patterns. Online documents: https://jsondata.sourceforge.io/
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  • 4
    kagglehub

    kagglehub

    Python library to access Kaggle resources

    kagglehub is a Python library for accessing Kaggle resources directly from Python code. It provides a simple API for downloading datasets, models, competition files, and notebook outputs without requiring users to manually manage every URL or file path. The library is designed to work both inside and outside Kaggle Notebooks, with native behavior that can adapt when it runs in Kaggle’s hosted notebook environment. It is useful for machine learning workflows where data, models, and notebook artifacts need to be pulled into scripts, experiments, or pipelines. kagglehub also supports authentication so users can access private or restricted resources when their account has permission. Its main value is making Kaggle assets easier to consume programmatically in Python-first data science and AI development workflows.
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  • 5
    kubectl-aliases

    kubectl-aliases

    Programmatically generated handy kubectl aliases

    kubectl-aliases is a small but extremely handy project that generates hundreds of shell aliases for kubectl so you no longer have to type long commands and flags repeatedly. It ships a prebuilt .kubectl_aliases file for Bash/Zsh, plus variants for Fish and Nushell, which you drop into your home directory and source from your shell config. The aliases are programmatically generated from permutations of common verbs, resources, flags, and options, so you get short forms like kgpo for kubectl get pod and more complex ones that include namespaces, label selectors, and output formats. This dramatically speeds up interactive Kubernetes workflows, especially when you spend a lot of time inspecting pods, services, deployments, and logs. The repository also includes a Python script used to generate the aliases, which advanced users can tweak if they want a custom alias set. It is distributed under the Apache-2.0 license and is widely used by Kubernetes practitioners.
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  • 6
    latexify

    latexify

    A library to generate LaTeX expression from Python code

    latexify_py converts small, math-heavy pieces of Python code into human-readable LaTeX that mirrors the intent of the computation, not just its surface syntax. It parses Python functions and expressions into an abstract syntax tree (AST), applies symbolic rewrites for common mathematical constructs, and then emits LaTeX that compiles cleanly in standard environments. Typical use cases include turning analytical utilities—like probability mass functions, activation formulas, or recurrence relations—into equations suitable for papers, notebooks, and slide decks. The tool aims to preserve semantics such as exponentiation, summations, products, piecewise definitions, and function application while hiding Pythonic scaffolding. Users can control rendering details for names and operators so the output conforms to a project’s notation style. Because it works directly from Python source, it enables a tight authoring loop.
    Downloads: 0 This Week
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  • 7
    leak-check

    leak-check

    Personal Information “Leakage ” Detection Interface

    leak-check is a utility designed to help developers detect memory leaks and resource mismanagement in applications. It provides tools to monitor allocations, track usage patterns, and identify potential leaks during runtime. The project focuses on improving application stability by highlighting inefficiencies in memory handling. It can be integrated into development workflows to catch issues early in the debugging process. leak-check is particularly useful in performance-critical applications where memory management is essential. Its design emphasizes simplicity and practical diagnostics rather than complex instrumentation. It helps developers maintain efficient and reliable systems.
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  • 8
    learn2learn

    learn2learn

    A PyTorch Library for Meta-learning Research

    Learn2Learn is a PyTorch-based library focused on meta-learning and few-shot learning research. It provides reusable components and meta-learning algorithms, making it easier to build, train, and evaluate models that can quickly adapt to new tasks with minimal data. Learn2Learn is widely used in research for tasks such as few-shot classification, reinforcement learning, and optimization.
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  • 9
    learn_python3_spider

    learn_python3_spider

    Python crawler tutorial series, learning Python crawlers from 0 to 1

    learn_python3_spider is a tutorial and example-code collection for learning web scraping with Python 3 from beginner to advanced topics. It introduces request capture, browser and mobile traffic inspection, and core scraping libraries such as Requests, BeautifulSoup, Selenium, Appium, and Scrapy. Lessons also cover JSON parsing, regular expressions, concurrency, proxy usage, login handling, and CAPTCHA-related techniques. Data can be stored with CSV, MySQL, or MongoDB examples. More advanced material explores anti-scraping defenses, JavaScript analysis, WebSocket data, and distributed crawlers. The repository includes practical source-code examples for scraping several real-world websites and services.
    Downloads: 0 This Week
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  • 10
    libtmux

    libtmux

    Python API / wrapper for tmux

    libtmux is a typed Python library that provides a wrapper for interacting programmatically with tmux, a terminal multiplexer. You can use it to manage tmux servers, sessions, windows, and panes. Additionally, libtmux powers tmuxp, a tmux workspace manager. libtmux builds upon tmux’s target and formats to create an object mapping to traverse, inspect and interact with live tmux sessions.
    Downloads: 0 This Week
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  • 11

    lv2gen

    Generate boilerplate for LV2 plugins

    A python package for describing audio and synth plugins and generating boilerplate code from that description, including LV2’s manifest.ttl and a simplified GUI for the`Mod Dwarf.
    Downloads: 0 This Week
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  • 12

    math toolkit

    A C++ and Python library for finance, statistics and linear algebra.

    A lightweight C++ and Python library for finance, statistics and linear algebra. Finance features include compound rate present/future value, annuity, various present/future value coefficients ... Statistics features include mean, median, variance, standard deviation, covariance, correlation, linear regression, probabilities and random variates of various distributions ... Linear algebra features include matrix arithmetic, inverse, determinant, rank, linear system solution, lu/qr decomposition, svd, eigen values/vectors ... And some auxiliary features like random number generators, equation solution, numerical integration, permutation/combination and gcd/lcm etc. It is aimed to be a convenient and handy toolkit to check out your ideas.
    Downloads: 0 This Week
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  • 13

    mds-utils

    General purpose utilities for C++ and Python developers

    This library is intended to become a collection of several C++ utilities. At present it contains: 1. a tool for detecting machine endianity. 2. utilities for the Boost uBLAS library. Amongst them, some type traits for detecting different uBLAS matrix types. 3. some useful classes that allow to treat the old C FILE pointer as a C++ stream. 4. C++ wrappers of the main Python objects, independent of those in Boost Python. Wrappers are provided also for NumPy arrays. 5. C++ classes that help on treating Python file objects as C++ streams. 6. a review and refactor of the indexing support in Python extensions. Now access in write mode is supported too. More details on the Doxygen documentation. Documentation is available through doxygen. Once downloaded and uncompressed, issue the "doxygen" command from the root folder. The documentation will be into "doc/html". An online version of this documentation is available at the link here below (mds-utils Web Site).
    Downloads: 0 This Week
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  • 14
    mediapy

    mediapy

    This Python library makes it easy to display images and videos

    Read/write/show images and videos in an IPython/Jupyter notebook.
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  • 15
    mini-filter-driver-framework

    mini-filter-driver-framework

    A mini filter driver development framework for you

    EaseFilter File System Filter Driver Framework is a set of file system filter driver software development kit which includes file monitor filter driver, file access control filter driver, transparent file encryption filter driver, process filter driver and registry filter driver. The File Security Solution with the EaseFilter Comprehensive File Security SDK encompasses file security, digital rights management, encryption, file monitoring, file auditing, file tracking, data loss prevention, process monitoring and protection, and system configuration protection. EaseFilter file system filter driver is a kernel-mode component that runs as part of the Windows executive above the file system. The EaseFilter file system filter driver can intercept requests targeted at a file system or another file system filter driver. By intercepting the request before it reaches its intended target, the filter driver can extend or replace functionality provided by the original target of the request.
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  • 16
    mosdepth

    mosdepth

    fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing

    mosdepth is a fast BAM/CRAM depth calculation tool for genomic data, allowing efficient computation of sequencing coverage.
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  • 17
    nJES is a complete CPython rewrite of JES (Jython Environment for Students), originally written by Mark Guzdial and Barbara Ericson. The primary objective of the rewrite is to enhance performance while maintaining full forward compatibility with JES.
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  • 18
    neovim-remote

    neovim-remote

    This package provides an executable called nvr

    neovim-remote is a command-line tool that lets users control existing Neovim processes from the shell. It provides an executable called nvr, which supports remote file opening, command execution, key sending, and expression evaluation. The tool solves a common terminal workflow problem by opening files inside an already running Neovim session instead of starting nested editor instances. It can be used from shell commands, terminal buffers, scripts, and Git editor workflows. If no target Neovim server is available, it can start a new process depending on configuration. The project is especially useful for Neovim users who want editor reuse, remote control, and smoother command-line integration.
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  • 19
    node2vec

    node2vec

    Learn continuous vector embeddings for nodes in a graph using biased R

    The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction. The repository contains reference code accompanying the research paper node2vec: Scalable Feature Learning for Networks (KDD 2016). It allows researchers and practitioners to apply node2vec to various graph datasets and evaluate embedding quality on downstream tasks. By bridging ideas from graph theory and word embedding models, this project demonstrates how graph-based machine learning can be made efficient and flexible.
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  • 20
    Defunct
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  • 21
    notebooker

    notebooker

    Productionise & schedule your Jupyter Notebooks

    Productionise and schedule your Jupyter Notebooks, just as interactively as you wrote them. Notebooker is a webapp which can execute and parametrise Jupyter Notebooks as soon as they have been committed to git. The results are stored in MongoDB and searchable via the web interface, essentially turning your Jupyter Notebook into a production-style web-based report in a few clicks.
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  • 22
    numpy_exercises

    numpy_exercises

    Numpy exercises

    numpy_exercises is a collection of short practice problems designed to teach numerical computing through individual NumPy functions. The material is organized as Jupyter notebooks so learners can work interactively and compare their answers with companion solution notebooks. Exercises cover array creation, manipulation, string operations, help utilities, input and output, and linear algebra. Additional sections address discrete Fourier transforms, logic functions, mathematics, random sampling, and set routines. Sorting, searching, counting, and statistics are also included. Rather than presenting a single application, the repository serves as a structured hands-on workbook for building practical familiarity with the NumPy API.
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  • 23
    New Python bindings for the popular OpenCV image processing library.
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  • 24
    osm4scala

    osm4scala

    Reading OpenStreetMap Pbf files.

    Scala and polyglot Spark library (Scala, PySpark, SparkSQL, ... ) focused on reading OpenStreetMap Pbf files.
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  • 25
    C++ library for working with OWL ontologies
    5.0 out of 5 stars 1 Review
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