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Luigi is a Python package for building complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures and command line integration, and includes Hadoop support. It is intended to stitch together long-running tasks such as Hive, Pig, Hadoop, Spark or database jobs.
Lux is a Python library for automated data exploration. When a pandas dataframe is printed in a Jupyter notebook, Lux recommends a set of visualizations highlighting trends and patterns, shown in an interactive widget for browsing and exploring the dataset.
LWN's archive page indexes its Weekly Edition issues from June 6, 2002 onward, with links to older site archives for earlier editions. It also points to separate indexes for guest articles by author, conference coverage by name or year, and kernel, security and Python articles.
m2cgen is a tool that transforms trained machine learning models into native code across a wide range of programming languages including Java, C, Python, Go, JavaScript, C#, R, PHP, Dart, Haskell, Ruby, F#, and Rust, with zero dependencies. Its codebase is hosted in the BayesWitnesses GitHub repository, which includes navigation for installation, development guidance, supported languages, and supported model types.
Machine Learning Zoomcamp is a free, hands-on course on building, evaluating, and deploying machine learning systems. It covers the path from framing a problem to preparing data, training and evaluating models, and deploying them, using Python, scikit-learn, TensorFlow, PyTorch, FastAPI, Docker, Kubernetes and AWS Lambda. No prior machine learning experience is required.
macOS-Simple-KVM provides tools to set up a quick macOS virtual machine in QEMU, accelerated by KVM. It requires a Linux system with qemu 3.1 or later, python3, pip and the KVM modules enabled; a Mac is not required. Installation media is downloaded by running jumpstart.sh, with Catalina as the default version and options for High Sierra, Mojave or Catalina, and basic.sh starts the machine.
Madrigal is a web-based upper atmospheric science database that manages and serves archival and real-time data from various instruments. Data is locally controlled at each site, while shared metadata enables searching across all Madrigal sites. APIs for Matlab, Python and IDL allow direct data access.
Apache Mahout builds an environment for quickly creating scalable, performant machine learning applications. Its current work centers on quantum machine learning in Python, with Qumat, a high-level library for writing quantum circuits once and running them on supported backends, and QDP, a GPU-accelerated engine that turns classical data into quantum states. The earlier Mahout Classic codebase is in maintenance mode.
MarkItDown is a lightweight Python utility for converting various files to Markdown for use with LLMs and related text analysis pipelines. It preserves document structure and content as Markdown, including headings, lists, tables, and links, and supports formats such as PDF, PowerPoint, Word, Excel, images, audio, HTML, and ZIP files.
A user-friendly Python toolkit for open source intelligence, providing key features such as image geolocation, social media profiling, email breach checks, domain lookup, metadata extraction, Google dorking, Wayback Machine queries, IP geolocation with blacklist checks, reverse image search, among others.
Masto is an OSINT tool written in python to gather intelligence on Mastodon users and instances.
Python wrapper for the Mastodon API.
mat2 is an open source metadata removal tool written in Python 3. It supports a wide range of commonly used file formats, and is built as a library that powers an eponymous command line interface and multiple file manager extensions. The project is hosted on GitHub under the jvoisin/mat2 repository.
The Materials Data Facility (MDF) is a service for publishing, discovering and accessing materials science datasets. It supports minting DOIs for datasets and offers curated collections covering simulations, experimental data and machine-learning-ready data. Data can be uploaded from local storage, Globus endpoints or Google Drive, and datasets can be loaded with a Python package.
Matplotlib is a comprehensive Python library for creating static, animated, and interactive visualizations. It supports publication quality plots, interactive figures that zoom, pan and update, customizable visual styles and layouts, and exporting to many file formats. It can be embedded in JupyterLab and graphical user interfaces, and third-party packages extend and build on its functionality.
Matt Harrison is a personal blog authored by Matt Harrison. The blog covers topics including Amazon book piracy, the Effective Pandas book, Python and data science courses, and general software development content.
MCGrad is a tool for multicalibration that aims to keep machine learning model predictions calibrated globally and across segments defined by features. It requires Python 3.10+ and is installed with pip or conda; the project's own description says it has been deployed at Meta on hundreds of production models.
MediaWiki Code2Code Search is an AI-powered semantic neural retrieval tool for searching MediaWiki source code. It uses Sentence-Transformers to enable meaning-based search rather than keyword-only matching, allowing users to find functions, types, and templates across the entire MediaWiki ecosystem. It supports multiple programming languages including PHP, Python, JavaScript, Go, TypeScript and Lua, and provides sample evaluation queries for common code search tasks.
Python tool used to download, extract, and apply date, time, and location metadata to Snapchat Memories when exporting them from the app.
Mengram is an open-source project that provides human-like memory capabilities for AI agents. It supports semantic, episodic, and procedural memory types, with experience-driven procedures designed to learn from failures. The project offers a free API, Python and JavaScript SDKs, and integrations with LangChain, CrewAI, and OpenClaw.
Meshtastic is an open source, community-driven project that uses LoRa radios as an off-grid communication platform in areas without reliable communications infrastructure. Devices rebroadcast messages to form a mesh network without cell towers, WiFi or internet, and can be paired with a phone or computer via Bluetooth, WiFi or USB. Clients include Apple and Android apps, a web client and a Python CLI/SDK.
metagoofil is a Python security tool that searches Google for specific file types hosted on a target website, with optional local download of discovered files. It is intended for open source intelligence gathering, penetration testing, and identifying files organizations publicly expose to search indexers. It is a maintained fork of the original metagoofil project, preinstalled by default on Kali Linux, and deliberately excludes built-in metadata analysis in favor of external tools like exiftool.
A Python module for metric learning.
Metric Learning Algorithms in Python.
