Open Source Python Software - Page 8
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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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Pendulum
Python datetimes made easy
Pendulum is a Python package to ease datetime's manipulation. It provides classes that are drop-in replacements for the native ones (they inherit from them). Special care has been taken to ensure timezones are handled correctly, and are based on the underlying tzinfo implementation. For example, all comparisons are done in UTC or in the timezone of the datetime being used. There are several different methods available to create a new DateTime instance. datetime() sets the time to 00:00:00 if it's not specified, and the timezone (the tz keyword argument) to UTC. Otherwise it can be a Timezone instance or simply a string timezone value. Pendulum gives access to more attributes and properties than the default datetime class. The __str__ magic method is defined to allow DateTime instances to be printed as a pretty date string when used in a string context. Simple comparison is offered up via the basic operators. -
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Arianne RPG
Arianne is an engine to develop multiplayer online games like Stendhal
Arianne is a multiplayer online engine to develop turn based and real time games, providing a simple way of creating the game server rules and clients like our MORPG Stendhal. Our engine Marauroa uses Java and SQL for hosting hundreds of players on a solo host. Stendhal is a fun friendly and free multiplayer online adventure game with a huge and rich world. With hundreds of NPCs and different quests, features like the Travel log and achievement system keep track of progress. Thousands of creatures are ready to fight, above and below ground, and as players level up they can compare themselves on a detailed stats website. The engine Marauroa provides a simple way of creating games on a portable and robust server architecture. Marauroa manages the client server communication and provides an object orientated view of the world for game developers. It handles database access in a transparent way to store player accounts, character progress and the state of the world -
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WhisperJAV
Uses Qwen3-ASR, local LLM, Whisper, TEN-VAD
WhisperJAV is an open-source speech transcription pipeline designed specifically for generating subtitles for Japanese adult video content. The project addresses challenges that standard speech recognition models face when transcribing this type of audio, which often includes low signal-to-noise ratios and large numbers of non-verbal vocalizations. Traditional automatic speech recognition systems can misinterpret these sounds as words, leading to inaccurate transcripts. WhisperJAV introduces a specialized pipeline that separates text generation from timestamp alignment, allowing the system to generate transcripts and then align them with audio using forced alignment techniques. The framework supports several speech recognition models, including Qwen-based ASR systems and fine-tuned Whisper models trained on domain-specific dialogue. -
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Coomer Downloader App
Coomer downloader
CoomerDL is an open-source command-line tool designed to download and archive content from websites supported by the Coomer platform, which aggregates publicly available content from various creators. The tool enables users to automate the retrieval of media such as images, videos, and metadata associated with creator profiles. It is built to handle large volumes of content efficiently, allowing users to download entire collections or selectively retrieve specific posts. The application typically supports features such as authentication, rate limiting, and retry mechanisms to ensure reliable downloads even when dealing with unstable connections or restricted endpoints. It is often used for personal archiving, data collection, or offline access to content that may otherwise be difficult to manage manually. The tool operates through a command-line interface, making it suitable for scripting and integration into automated workflows. -
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Open Interpreter
A natural language interface for computers
Open Interpreter is an open-source tool that provides a natural-language interface for interacting with your computer. It lets large language models (LLMs) run code locally (Python, JavaScript, shell, etc.), enabling you to ask your computer to do tasks like data analysis, file manipulation, browsing, etc. in human terms (“chat with your computer”), with safeguards. Runs locally or via configured remote LLM servers/inference backends, giving flexibility to use models you trust or have locally. It prompts you to approve code before executing, and supports both online LLM models and local inference servers. It seeks to combine convenience (like ChatGPT’s code interpreter) with control and flexibility by running on your own machine. -
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spotDL
Download your Spotify playlists and songs along with album art
spotDL is a command-line tool that allows users to download songs and playlists from Spotify by sourcing the audio from YouTube. Built in Python, it automatically matches Spotify tracks with corresponding videos on YouTube and downloads them with embedded metadata. The tool retrieves important information such as album art, song titles, artist names, and lyrics to organize downloaded files. spotDL is designed to be fast, accurate, and easy to use through a simple command-line interface. It supports downloading individual songs, albums, or entire playlists by providing Spotify URLs or search queries. By combining Spotify metadata with YouTube audio sources, spotDL provides a convenient way to build a local music library. -
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Pillow
The friendly Python Imaging Library fork
If you've ever wondered or worried about the future of Python's Imaging Library, it's time to stop. Pillow is here to answer your concerns, and offer you more. Pillow is the friendly fork of the Python Imaging Library or PIL, a library that adds image processing capabilities to your Python interpreter. Why turn to Pillow? Aside from offering extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities, Pillow is setuptools compatible. While PIL is not officially over yet, with Pillow you can be assured of continuous integration testing, publicized development activity, and regular releases to the Python Package Index. -
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Blender GIS
Blender addons to make the bridge between Blender and geographic data
Import in Blender most commons GIS data format, Shapefile vector, raster image, geotiff DEM, OpenStreetMap XML. There are a lot of possibilities to create a 3D terrain from geographic data with BlenderGIS, check the Flowchart to have an overview. Display dynamics web maps inside Blender 3d view, requests for OpenStreetMap data (buildings, roads, etc.), get true elevation data from the NASA SRTM mission. Manage georeferencing information of a scene, compute a terrain mesh by Delaunay triangulation, drop objects on a terrain mesh, make terrain analysis using shader nodes, set up new cameras from geotagged photos, set up a camera to render with Blender a new georeferenced raster. -
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Roop
One-click face swap
Take a video and replace the face with a face of your choice. You only need one image of the desired face. No dataset, and no training. -
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PassGAN
A Deep Learning Approach for Password Guessing
PassGAN is a research implementation of a generative adversarial network trained to model human password patterns. It reproduces ideas from the paper “PassGAN: A Deep Learning Approach for Password Guessing” using a modified Wasserstein GAN implementation. The repository includes scripts for training models and generating candidate password samples from learned distributions. A pretrained model based on the RockYou dataset is provided for reproducing experiments. TensorFlow and CUDA were used by the original implementation, reflecting the deep-learning tooling available when the project was created. The maintainer also documented experimental results and questioned how the approach compared with established RNN and Markov methods. Because generated candidates can be used in password-recovery attacks, the software is most appropriate for authorized security research and password-strength analysis. -
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VCClient
Software that uses AI to perform real-time voice conversion
VCClient is a real-time voice conversion system that uses machine learning models to transform a speaker’s voice into another voice with minimal latency. It is designed for live applications such as streaming, gaming, and virtual communication, where immediate feedback is essential. The system supports multiple voice conversion models, including RVC and other neural network-based approaches, allowing users to switch between different voices or customize their output. It provides both a graphical user interface and API access, making it suitable for casual users as well as developers who want to integrate voice transformation into their own applications. The project also supports GPU acceleration, enabling faster inference and smoother real-time performance on compatible hardware. Additionally, it includes tools for training and managing voice models, giving users the ability to create personalized voice profiles. -
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WanGP
AI video generator optimized for low VRAM and older GPUs use
Wan2GP is an open source AI video generation toolkit designed to make modern generative models accessible on consumer-grade hardware with limited GPU memory. It acts as a unified interface for running multiple video, image, and audio generation models, including Wan-based models as well as other systems like Hunyuan Video, Flux, and Qwen. A key focus of the project is reducing VRAM requirements, enabling some workflows to run on as little as 6 GB while still supporting older Nvidia and certain AMD GPUs. Wan2GP provides a full web-based interface that simplifies interaction with complex generative pipelines, making it easier to configure prompts, models, and rendering settings. It also integrates a wide range of utilities such as prompt enhancement, mask editing, motion design, and extraction tools for pose, depth, and flow data to support advanced video workflows. -
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WiFi DensePose
Turn WiFi signals into real-time human pose estimation and detection
WiFi DensePose is a production-oriented implementation of a WiFi-based human pose estimation system that enables real-time full-body tracking using wireless signals rather than cameras. The project demonstrates how commodity mesh routers and signal processing techniques can be leveraged to infer dense human pose information, even through obstacles such as walls. It is designed to showcase the emerging field of RF-based sensing, where machine learning models interpret wireless channel data to reconstruct human movement and posture. The repository includes components for data processing, model inference, and real-time visualization, making it suitable for research and experimental deployments. Its architecture emphasizes performance and reproducibility, allowing developers to explore non-visual motion capture systems using accessible hardware. Overall, WiFi DensePose functions as an advanced research-grade toolkit for WiFi-based human sensing and pose estimation. -
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PyMongo
PyMongo - the Official MongoDB Python driver
The PyMongo distribution contains tools for interacting with MongoDB database from Python. The bson package is an implementation of the BSON format for Python. The pymongo package is a native Python driver for MongoDB. The gridfs package is a gridfs implementation on top of pymongo. -
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Bottles
Run Windows software and games on Linux
Bottles lets you run Windows software on Linux, such as applications and games. It introduces a workflow that helps you organize by categorizing each software to your liking. Bottles provide several tools and integrations to help you manage and optimize your applications. Bottles introduces a new way to handle Windows prefixes using environments, a combination of ready-to-use settings, libraries and dependencies. -
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Heretic
Fully automatic censorship removal for language models
Heretic is an open-source Python tool that automatically removes the built-in censorship or “safety alignment” from transformer-based language models so they respond to a broader range of prompts with fewer refusals. It works by applying directional ablation techniques and a parameter optimization strategy to adjust internal model behaviors without expensive post-training or altering the core capabilities. Designed for researchers and advanced users, Heretic makes it possible to study and experiment with uncensored model responses in a reproducible, automated way. The project can decensor many popular dense and some mixture-of-experts (MoE) models, supporting workflows that would otherwise require manual tuning. Beyond simple decensoring, Heretic includes research-oriented options for analyzing model internals and interpretability data. -
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Pyxel
A retro game engine for Python
A retro game engine for Python. Thanks to its simple specifications inspired by retro gaming consoles, such as only 16 colors can be displayed and only 4 sounds can be played back at the same time, you can feel free to enjoy making pixel art style games. The motivation for the development of Pyxel is the feedback from users. Please give Pyxel a star on GitHub! Pyxel's specifications and APIs are inspired by PICO-8 and TIC-80. Pyxel is open source and free to use. Let's start making a retro game with Pyxel! Runs on Windows, Mac, Linux, and Web. Using the Pyxel Web Launcher or custom elements for HTML, you can run Pyxel in a web browser without any installation work. Pyxel supports a dedicated application distribution file format (Pyxel application file) that works across platforms. 8 musics that can combine arbitrary sounds. -
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Developer's Image Library
A full featured cross-platform image library
Developer's Image Library (DevIL) is a cross-platform image library utilizing a simple syntax to load, save, convert, manipulate, filter and display a variety of images with ease. -
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GPT4All
Run Local LLMs on Any Device. Open-source
GPT4All is an open-source project that allows users to run large language models (LLMs) locally on their desktops or laptops, eliminating the need for API calls or GPUs. The software provides a simple, user-friendly application that can be downloaded and run on various platforms, including Windows, macOS, and Ubuntu, without requiring specialized hardware. It integrates with the llama.cpp implementation and supports multiple LLMs, allowing users to interact with AI models privately. This project also supports Python integrations for easy automation and customization. GPT4All is ideal for individuals and businesses seeking private, offline access to powerful LLMs. -
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Sherlock
Hunt down social media accounts by username across social networks
Hunt down social media accounts by username across 400+ social networks. -
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Terminator - World's Fastest Autoclicker
Never be out-clicked again!
SUBMIT SUGGESTIONS HERE: https://forms.gle/3SSozEcR1p3uy6dPA -------------------------------------------------------------------------------------------- Terminator - The World's Fastest Autoclicker. Made by gamers for gamers. Terminator is the end all be all of all autoclickers. With clicks reaching up to 1000+ CPS, you will never again be outclicked. Version 3.1: * Mouse buttons can now be used again to activate/deactivate the autoclicker Version 3.0: * Modern, clean GUI * Added a left/right click option * Added a hold/toggle mode * Added a dark/light theme * Total clicks display * Active status display Version 2.1: 1. Two methods of activation: Key presses or mouse buttons 2. Activates even while simultaneously pressing other keys 3. Fixed minor bugs -
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Free LLM API resources
A list of free LLM inference resources accessible via API
Free LLM API resources repository curated by cheahjs is a community-driven index of free and open API endpoints, tools, datasets, runtimes, and utilities for working with large language models (LLMs) without cost-barriers. It collects a wide range of resources including hosted free-tier LLM APIs, documentation links, public model endpoints, open datasets useful for training or evaluation, tooling integrations, and examples showing how to interact with these services in real applications. This list helps developers, hobbyists, and researchers quickly find models they can use for prototyping, experimentation, or production proofs-of-concept without needing paid subscriptions, reducing friction for innovation. The repository typically categorizes offerings by provider, type of service (text, embeddings, vision), availability conditions (open without key, free tier with key), and usage examples to make discovery and adoption easier. -
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MakeHuman
This is the main repository for the MakeHuman application as such
This is the main source code for the MakeHuman application as such. See "Getting started" below for instructions on how to get MakeHuman up and running. Mac users should be able to use the same instructions as windows users, although this has not been thoroughly tested. At the point of writing this, the source code is almost ready for a stable release. The testing vision for this code is to build a community release that includes main application and often-used, user-contributed plug-ins. We hope that the utility of this integrated functionality is sufficient to entice a larger cohort of testers who get value-added in exchange for the possibility of uncovering deficiencies in our application. -
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ACE-Step 1.5
The most powerful local music generation model
ACE-Step 1.5 is an advanced open-source foundation model for AI-driven music generation that pushes beyond traditional limitations in speed, musical coherence, and controllability by innovating in architecture and training design. It integrates cutting-edge generative techniques—such as diffusion-based synthesis combined with compressed autoencoders and lightweight transformer elements—to produce high-quality full-length music tracks with rapid inference times, capable of generating a complete song in seconds on modern GPUs while remaining efficient enough to run on consumer-grade hardware with minimal memory requirements. Beyond straightforward text-to-music synthesis, ACE-Step 1.5 enables flexible creative workflows, including tasks like cover generation, editing existing tracks, transforming vocals to background accompaniment, and stylistic personalization using low-rank adaptation from just a few example songs. -
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AutoClip
AI-powered video clipping and highlight generation
AutoClip is an open-source, AI-powered video processing system designed to automate the extraction of “highlight” segments from full-length videos — ideal for creators who want to generate bite-sized clips, compilations, or highlight reels without manually sifting through hours of footage. The system supports downloading videos from major platforms (e.g. YouTube, Bilibili), or accepting local uploads, and then applies AI analysis to identify segments worth clipping based on content (e.g. high energy moments, speech, or other heuristics). Once highlights are identified, AutoClip can automatically cut those segments and optionally assemble them into a compilation, thus greatly reducing manual video editing effort. It uses a modern web application stack with a front end (React + TypeScript) for user interaction and a back end that handles downloading, processing, clipping, and queue management, allowing real-time progress feedback and easy deployment, e.g. via Docker.
