Open Source Python Education Software for Mac

Zero Install is a decentralised cross-distribution software installation system. Create one package that works everywhere! With dependency handling and automatic updates, full support for shared libraries, and integration with native package managers

AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run them in a sandbox environment, and analyze the results with statistical methods. The platform also uses multi-agent debate and automated peer review processes to refine research findings and improve paper quality. By combining literature discovery, experimentation, and writing automation, AutoResearchClaw aims to turn research ideas into conference-ready papers with minimal human intervention.

Brain Workshop is a Python implementation of the Dual N-Back mental exercise. This exercise is the only mental activity that has been scientifically shown to improve your short-term memory (working memory) and fluid intelligence.

eXe, the eLearning XHTML editor, is a freely available authoring application that assists teachers in the publishing of web content without the need to become proficient in HTML or XML markup. Resources authored in eXe can be exported to the web or LMS.

SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation. The code and the issue tracker can be found at https://github.com/eclipse-sumo/sumo/ The documentation can be found at https://sumo.dlr.de/docs/

eduActiv8 is a free Open Source multi-platform educational application that aims to assist in learning various early education topics - from learning the alphabet and new words, colours, time to a wide range of maths-related subjects. eduActiv8 is a continuation of the development of the pySioGame project just under a new name. It is being developed on GitHub at: https://github.com/imiolek-ireneusz/eduActiv8 but 'compiled' releases are published here. The latest version has been partially redesigned to improve usability, but certain activities will still be in the somewhat "prototype quality" - this will be gradually redesigned as time allows. Currently, it is available for Windows, MacOS, Linux and Android (you may need to allow unknown sources to install it on Android). Packages for multiple Linux distributions are available from: https://software.opensuse.org//download.html?project=home%3Aimiolek-i&package=eduactiv8 Support eduActiv8 at https://ko-fi.com/eduactiv8

Mnemosyne resembles a traditional flash-card program but with an important twist: it uses a sophisticated algorithm to schedule the best time for a card to come up for review.

Calculatrice graphique en français, destinée aux professeurs ou aux étudiants du collège et du lycée. Elle permet de faire du calcul formel, de tracer des courbes et des figures géométriques exportables en png, eps ou svg. Linux, Windows... Cette version n'est plus maintenue. Nous vous recommandons d'utiliser désormais la nouvelle version, nommée Géophar : http://sourceforge.net/projects/geophar

If you are looking for the childsplay application please go to http://www.childsplay.mobi

Automatically geocode pictures from your camera and a GPS track log. Following Google code closure the only official webpage is (doc, support, code) : https://github.com/notfrancois/GPicSync

Web Security Dojo is a virtual machine that provides the tools, targets, and documentation to learn and practice web application security testing. A preconfigured, stand-alone training environment ideal for classroom and conferences. No Internet required to use. Ideal for those interested in getting hands-on practice for ethical hacking, penetration testing, bug bounties, and capture the flag (CTF). A single OVA file will import into VirtualBox and VMware. There is also an Ansible script for those brave souls that want transform their stock Ubuntu into a virtual dojo. Bow to your sensei! username: dojo password: dojo

The bitcoinbook repository contains the source code for Mastering Bitcoin, the authoritative open-source book by Andreas M. Antonopoulos on Bitcoin and cryptocurrency technologies. Written in a collaborative and continuously updated format using Markdown and AsciiDoc, the book serves as a comprehensive technical guide for developers, engineers, and system architects who want to understand how Bitcoin works. It covers the protocol, cryptography, peer-to-peer architecture, wallets, mining, and application development.

This project is no longer active. See vpython.org.

This book is about interpretable machine learning. Machine learning is being built into many products and processes of our daily lives, yet decisions made by machines don't automatically come with an explanation. An explanation increases the trust in the decision and in the machine learning model. As the programmer of an algorithm you want to know whether you can trust the learned model. Did it learn generalizable features? Or are there some odd artifacts in the training data which the algorithm picked up? This book will give an overview over techniques that can be used to make black boxes as transparent as possible and explain decisions. In the first chapter algorithms that produce simple, interpretable models are introduced together with instructions how to interpret the output. The later chapters focus on analyzing complex models and their decisions. In an ideal future, machines will be able to explain their decisions and make a transition into an algorithmic age more human.

The Campaign Simulator is an attempt to statistically model and predict the outcome of an American presidential election; several users assume the roles of competitive candidates and inflict the repercussions of certain decisions on a GSS based dataset.

Learning to Learn, created by Google DeepMind, is an experimental framework that implements meta-learning—training neural networks to learn optimization strategies themselves rather than relying on manually designed algorithms like Adam or SGD. The repository provides code for training and evaluating learned optimizers that can generalize across different problem types, such as quadratic functions and image classification tasks (MNIST and CIFAR-10). Using TensorFlow, it defines a meta-optimizer model that learns by observing and adapting to the optimization trajectories of other models. The project allows users to compare performance between traditional optimizers and the learned optimizer (L2L) on various benchmarks, demonstrating how optimization strategies can be learned through experience. The design supports both single-variable and high-dimensional problems, and includes tools for evaluating how well a learned optimizer performs on unseen tasks.

"Roberge's Used Robot (RUR) : a Python Learning Environment" is a Python implementation of a "robot environment" as introduced by R. Pattis in 1981. **It is obsolete.** See https://github.com/aroberge/rur-ple

django-lms is an open-source Learning Management System (LMS) built with Django and designed for ease of use and extensibility. It allows administrators to manage courses, lessons, quizzes, and users in an educational environment. The project includes a clean UI and backend tools to help educators create and track learning content.

Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights, biases, activation functions, and gradient descent, as well as more advanced techniques like convolutional networks, recurrent networks, and reinforcement learning. It includes multiple hands-on projects, such as handwritten digit recognition, airplane detection in images, and text generation using recurrent neural networks, which demonstrate how different architectures solve real-world problems.

The Data Engineering Handbook is a comprehensive, community-curated repository that aggregates essential learning resources for anyone interested in becoming a professional data engineer. Rather than being a code project itself, it’s a learning handbook that links to books, articles, tutorials, community groups, boot camps, and real-world project examples that collectively form a roadmap to mastering data engineering skills. It includes beginner and intermediate boot camps, interview guides, data cleaning and transformation resources, and curated lists of newsletters and industry communities, making it useful both for self-study and technical interview preparation. The repository is actively maintained and widely starred, reflecting its role as a go-to reference for newcomers and experienced practitioners alike.

The data-science-on-gcp repository is a comprehensive collection of code examples and end-to-end workflows that accompany the book Data Science on the Google Cloud Platform, designed to teach developers how to build scalable data science and machine learning systems using Google Cloud services. It provides structured, chapter-aligned implementations that guide users through the full lifecycle of a data science project, including data ingestion, storage, processing, analysis, model training, and deployment. The repository is organized into multiple directories that reflect real-world pipelines, such as ingesting data, running SQL-based analytics, streaming data processing, using Spark and Dataproc, applying BigQuery ML, and deploying models with Vertex AI. It emphasizes practical, production-oriented workflows rather than isolated examples, showing how different Google Cloud services interact to form cohesive pipelines.

Guido van Robot Educational Programming Language

Canorus is a free cross-platform music score editor. It supports an unlimited number and length of staffs, polyphony, a MIDI playback of notes, chord markings, lyrics, import/export filters to formats like MIDI, MusicXML, ABC Music, MusiXTeX and LilyPond

A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.

A library of tools for doing computation in game theory.