Open Source Python Software - Page 82
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Python Software
Browse free open source Python Software and projects below. Use the toggles on the left to filter open source Python Software by OS, license, language, programming language, and project status.
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folium
Python data, Leaflet.js maps
folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the leaflet.js library. Manipulate your data in Python, then visualize it in on a Leaflet map via folium. folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map. It enables both the binding of data to a map for choropleth visualizations as well as passing rich vector/raster/HTML visualizations as markers on the map. The library has a number of built-in tilesets from OpenStreetMap, Mapbox, and Stamen, and supports custom tilesets with Mapbox or Cloudmade API keys. folium supports both Image, Video, GeoJSON and TopoJSON overlays. To create a base map, simply pass your starting coordinates to Folium. To display it in a Jupyter notebook, simply ask for the object representation. The default tiles are set to OpenStreetMap, but Stamen Terrain, Stamen Toner, Mapbox Bright, and Mapbox Control Room, and many others tiles are built in. -
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gTTS
Python library and CLI tool to interface with Google Translate
gTTS (Google Text-to-Speech) is a Python library and command-line tool that wraps the speech functionality of Google Translate. It lets you send text to the Google Translate TTS endpoint and receive spoken audio back as MP3 data, either written to a file, a file-like object, or standard output. The library is designed to handle long texts, using a speech-specific sentence tokenizer that keeps intonation and punctuation natural while splitting requests into acceptable chunks. It supports customizable text pre-processors, which can correct pronunciations, tweak formatting, or handle domain-specific vocabulary before sending it to the API. gTTS is primarily aimed at developers who want a quick way to add cloud-backed speech to scripts, apps, or pipelines without managing any model weights locally. A small CLI utility, gtts-cli, makes it easy to test or batch-generate MP3 files right from the shell. -
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gpt-engineer
Full stack AI software engineer
gpt-engineer is an open-source platform designed to help developers automate the software development process using natural language. The platform allows users to specify software requirements in plain language, and the AI generates and executes the corresponding code. It can also handle improvements and iterative development, giving users more control over the software they’re building. Built with a terminal-based interface, gpt-engineer is customizable, enabling developers to experiment with AI-assisted programming and refine their development process. It is especially useful for automating the coding and iterative feedback loop in software development. -
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jsonschema
An implementation of the JSON Schema specification for Python
jsonschema is an implementation of the JSON Schema specification for Python. Full support for Draft 2020-12, Draft 2019-09, Draft 7, Draft 6, Draft 4 and Draft 3. Lazy validation that can iteratively report all validation errors. Programmatic querying of which properties or items failed validation. -
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lightning AI
The most intuitive, flexible, way for researchers to build models
Build in days not months with the most intuitive, flexible framework for building models and Lightning Apps (ie: ML workflow templates) which "glue" together your favorite ML lifecycle tools. Build models and build/publish end-to-end ML workflows that "glue" your favorite tools together. Models are “easy”, the “glue” work is hard. Lightning Apps are community-built templates that stitch together your favorite ML lifecycle tools into cohesive ML workflows that can run on your laptop or any cluster. Find templates (Lightning Apps), modify them and publish your own. Lightning Apps can even be full standalone ML products! Run on your laptop for free! Download the code and type 'lightning run app'. Feel free to ssh into any machine and run from there as well. In research, we often have multiple separate scripts to train models, finetune them, collect results and more. -
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llm-abliteration
Make abliterated models with transformers, easy and fast
LLM Abliteration is an open-source Python toolkit for modifying refusal behavior in large language models without conventional fine-tuning. Built with Hugging Face Transformers, it identifies refusal-related activation directions by comparing responses to harmful and harmless prompts. Researchers can analyze these directions across model layers and selectively remove their influence from model weights. The software supports dense and selected mixture-of-experts architectures, including Llama, Qwen, Mistral, and Gemma models. Batch inference and quantized model loading help reduce processing requirements. Sharded weight modifications allow larger models to be processed with limited memory. Advanced options include norm-preserving transformations, directional projection, and configurable layer strategies. Modified models can be tested and compared, although refusal removal is not guaranteed. -
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llms-from-scratch-cn
Build a large language model from 0 only with Python foundation
llms-from-scratch-cn is an educational open-source project designed to teach developers how to build large language models step by step using practical code and conceptual explanations. The repository provides a hands-on learning path that begins with the fundamentals of natural language processing and gradually progresses toward implementing full GPT-style architectures from the ground up. Rather than focusing on using pre-trained models through APIs, the project emphasizes understanding the internal mechanisms of modern language models, including tokenization, attention mechanisms, transformer architecture, and training workflows. Through a collection of notebooks, code examples, and translated learning materials, users can explore how to implement components such as multi-head attention, data loaders, and training pipelines using Python and PyTorch. -
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mergekit
Tools for merging pretrained large language models
mergekit is an open-source toolkit designed to combine multiple pretrained language models into a single unified model through parameter merging techniques. The framework enables developers to merge model checkpoints so that the resulting model inherits capabilities from several source models without requiring additional training. This approach allows researchers to combine specialized models into a more versatile system capable of performing multiple tasks. mergekit implements a variety of merging algorithms and strategies that control how model parameters are blended together during the merging process. The library is designed to operate efficiently even in environments with limited hardware resources by using memory-efficient processing methods that can run entirely on CPUs. It also provides configuration-driven workflows that allow users to experiment with different merging strategies without modifying source code. -
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mindflow
AI-powered CLI git wrapper, boilerplate code generator, chat history
I-powered CLI git wrapper, boilerplate code generator, chat history manager, and code search engine to streamline your dev workflow. The ChatGPT-powered swiss army knife for the modern developer! We provide an AI-powered CLI git wrapper, boilerplate code generator, code search engine, a conversation history manager, and much more! Configure the model used for generating responses by running mf config and selecting either GPT 3.5 Turbo (default) or GPT 4. In order to use GPT 4, you'll need to have special access to the API. If you have access, you can run mf config and select GPT 4. If you don't have access, you'll get an error message. Interact with chatGPT directly just like on the chatGPT website. We also have chat persistence, so it will remember the previous chat messages. You can provide single or multi-file context to chatGPT by passing in any number of files as a separate argument in the mf chat call. -
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minimalRL-pytorch
Implementations of basic RL algorithms with minimal lines of codes
minimalRL is a lightweight reinforcement learning repository that implements several classic algorithms using minimal PyTorch code. The project is designed primarily as an educational resource that demonstrates how reinforcement learning algorithms work internally without the complexity of large frameworks. Each algorithm implementation is contained within a single file and typically ranges from about 100 to 150 lines of code, making it easy for learners to inspect the entire implementation at once. The repository includes examples of widely used reinforcement learning methods such as REINFORCE, Deep Q-Networks, Proximal Policy Optimization, and Actor-Critic architectures. Most experiments are designed to run quickly using the CartPole environment so that users can focus on understanding algorithm logic rather than computational infrastructure. -
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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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mzitu
Python crawler that downloads image galleries and analyzes titles
mzitu is a Python-based web crawling project designed to automatically download and organize image galleries from a specific photography site. It demonstrates how to build a scraper that navigates gallery pages, retrieves image links, and saves the images locally in a structured directory layout. It focuses on automating the collection of large sets of images by programmatically parsing page content and iterating through gallery entries. mzitu also includes a simple analysis script that processes downloaded folder names to generate statistics and visualizations. Using text segmentation and frequency analysis, the project can create a word cloud representing common keywords found in the dataset. This makes the repository both a scraping example and a small data analysis experiment built around the collected content. Overall, mzitu serves as a learning-oriented implementation of Python web scraping, data processing, and visualization techniques. -
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nanobot
🐈 nanobot: The Ultra-Lightweight Clawdbot / OpenClaw
nanobot is an ultra-lightweight personal AI assistant designed to deliver powerful agent capabilities without unnecessary complexity. Built in just ~4,000 lines of clean, readable code, it offers a minimalist alternative to heavyweight agent frameworks while retaining core intelligence and extensibility. nanobot is optimized for speed and efficiency, enabling fast startup times and low resource usage across environments. Its research-ready architecture makes it easy for developers to understand, customize, and extend for experimentation or production use. With simple one-click deployment and a straightforward CLI, users can get a working AI assistant running in minutes. Inspired by Clawdbot but radically simplified, nanobot proves that capable AI agents don’t need massive codebases. -
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nesa
Run AI models end-to-end encrypted
nesa is an open-source initiative focused on building decentralized AI infrastructure that enables secure, verifiable, and privacy-preserving machine learning and inference across distributed environments. The project aims to address key challenges in modern AI systems, such as data privacy, trust, and centralization, by leveraging cryptographic techniques and decentralized architectures. NESA allows developers to run AI computations in a way that ensures data integrity and confidentiality, making it particularly relevant for applications involving sensitive or regulated data. It integrates mechanisms for verifiable computation, enabling users to confirm that AI outputs were generated correctly without exposing underlying data or models. The platform is designed to be modular and extensible, supporting integration with various machine learning frameworks and deployment environments. -
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ngxtop
Real-time metrics for nginx server
ngxtop is a command-line monitoring utility that provides real-time analytics for Nginx and similar web server access logs using a top-style interface. Instead of relying on heavy monitoring stacks, it parses live log streams and produces immediate insights into request rates, status codes, bandwidth usage, and endpoint activity. The tool is particularly useful for troubleshooting traffic spikes or diagnosing performance issues during active incidents. It automatically detects the access log location and format in many cases, enabling quick deployment with minimal configuration. Users can also customize queries, grouping logic, and filters to analyze specific traffic patterns or metrics. By combining the familiarity of the UNIX top paradigm with flexible log parsing, ngxtop offers a lightweight yet powerful approach to real-time web server observability. -
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nunif
Misc; latest version of waifu2x; 2D video to stereo 3D video
nunif is a deep learning–based image processing framework focused on image upscaling, restoration, denoising, and enhancement tasks using neural network models. The project provides a collection of AI-powered utilities designed primarily for anime-style artwork, illustrations, and high-quality image restoration workflows. It includes command-line tools and graphical interfaces for applying trained neural models to improve image resolution and visual clarity while minimizing artifacts. nunif supports GPU acceleration and batch processing, making it suitable for creators, archivists, and enthusiasts handling large image collections. The framework is highly modular, allowing developers to experiment with custom models, inference pipelines, and image-processing workflows. Its emphasis on anime and illustration enhancement has made it especially popular in digital art and media preservation communities. -
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pdfly
CLI tool to extract (meta)data from PDF and manipulate PDF files
A Python library designed for manipulating PDF files with functionalities for extraction, transformation, and document generation. -
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pspider
Simple Python framework for building multithreaded web crawlers
PSpider is a lightweight web crawling framework written in Python designed to simplify the development of custom web spiders. It focuses on providing an easy-to-understand architecture while still supporting concurrent crawling for improved performance. It uses a multithreaded model that separates the crawling workflow into several components responsible for fetching, parsing, and saving data. Tasks are managed through queues, allowing different parts of the crawler to process work asynchronously and efficiently. PSpider defines a set of modules and utility classes that help developers manage crawling tasks, filter URLs, and process scraped content. By organizing crawling tasks into structured stages, PSpider allows developers to build scalable spiders while keeping the codebase relatively compact and readable. Its modular design also makes it easier to extend the framework with additional features or integrate it into existing Python projects. -
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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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pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification
pyAudioAnalysis is an open-source Python library designed for audio signal analysis, machine learning, and music information retrieval tasks. The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio segmentation. It also includes utilities for visualizing audio features and analyzing patterns within sound recordings, which can be useful in applications such as speech recognition, music classification, and acoustic event detection. Because the library integrates machine learning algorithms with signal processing tools, it enables researchers to develop complete audio analysis pipelines using a single framework. -
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pydictor
powerful and useful hacker dictionary builder for a brute-force attack
A powerful and useful hacker dictionary builder for a brute-force attack. You can use pydictor to generate a general blast wordlist, a custom wordlist based on Web content, a social engineering wordlist, and so on; You can use the pydictor built-in tool to safe delete, merge, unique, merge and unique, count word frequency to filter the wordlist, besides, you also can specify your wordlist and use '-tool handler' to filter your wordlist. You can generate highly customized and complex wordlists by modifying multiple configuration files, adding your own dictionary, using leet mode, filter by length, char occur times, types of different char, regex, and even add customized encode scripts in /lib/encode/ folder, add your own plugin script in /plugins/ folder, add your own tool script in /tools/ folder. -
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pyfpdf
Simple PDF generation for Python (FPDF PHP port)
PyFPDF is a library for PDF document generation under Python, ported from PHP (see FPDF: "Free"-PDF, a well-known PDFlib-extension replacement with many examples, scripts, and derivatives). Compared with other PDF libraries, PyFPDF is simple, small, and versatile, with advanced capabilities, and is easy to learn, extend and maintain. -
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python-zeroconf
A pure python implementation of multicast DNS service discovery
A pure python implementation of multicast DNS service discovery. -
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pytube
A lightweight, dependency-free Python library
Pytube is a lightweight, dependency-free Python library that enables downloading YouTube videos and audio streams with minimal setup. It supports video resolution selection, progressive or adaptive streams, and caption downloads. Pytube is ideal for automation scripts, archiving tools, and media applications that need to interface with YouTube content programmatically. -
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pywinauto
Windows GUI Automation with Python (based on text properties)
pywinauto is a set of Python modules to automate the Microsoft Windows GUI. At its simplest it allows you to send mouse and keyboard actions to Windows dialogs and controls, but it has support for more complex actions like getting text data.
