Open Source Python Software Development Software - Page 73

Logix is a programming language where the syntax can be easily modified.

LogoROS is new object-oriented operation system (currently in early development). See wiki page: https://sourceforge.net/apps/mediawiki/logoros/ and development blog: https://sourceforge.net/apps/wordpress/logoros/ for more info.

LucidEngine is a simple layer over MIDP compatible phones that will let you write simple and old fashioned games using a specific language. Every game you'll develop will basically work on all the devices (even not phones) LucidEngine as been ported.

Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more. The purpose of Luigi is to address all the plumbing typically associated with long-running batch processes. You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop jobs, dumping data to/from databases, running machine learning algorithms, or anything else. You can build pretty much any task you want, but Luigi also comes with a toolbox of several common task templates that you use. It includes support for running Python mapreduce jobs in Hadoop, as well as Hive, and Pig, jobs. It also comes with file system abstractions for HDFS, and local files that ensures all file system operations are atomic.

Luke is a Software Development Toolkit with a source code browser and tools for managing software development projects that may be missing from the typical IDE.

The Cloud Computer for your self.

Lusca is a test-framework for testing network applications under unix-like operating systems. Provides remote equipment control, automated script execution, event logging and more.

Luxor Contrib is a collection of example apps, add-ons, plug-ins, tutorials, FAQs, how-tos and other goodies for the Luxor XUL (XML User Interface Language) toolkit.

Ly: a 'lyterate' programming engine written in Python, featuring an easy-to-read syntax based on indentation. Source files look very similar to the HTML produced from them. Does chunking (arrange the code as you like, not as your compiler wants you to).

Build windows executable from your Python file, with areas that requires your program info, description, Icon etc. It is possible to load existing data sets, given they are under corresponding Pickle formats, while saving also generates an Pickle file. Info fields can meet most demands, Windowed or consoled program type. One-file or Folder package, Encryption module, Hidden-Imports, UPX Compatible, Icon, program end-name, Debug mode and more.

Disclaimer:im still working on this project please provide any feedback of bugs if you want :D helps me improve the experience for others. Also, windows might flag the exe file for a virus as it a python to exe file (might fix it later) this explains why it could be flagged as a virus on some virus detectors: https://s.id/1Cuk1 MAX StressTester is an open-source stress testing tool developed by ssit, available on the popular software development platform, SourceForge. The tool is written in Python, making it easy to use and highly customizable for stress testing purposes. The MAX StressTester tool allows users to simulate high loads of traffic on their websites or servers to test their performance and reliability under heavy usage. It can also be used to identify and diagnose performance issues, allowing developers to fine-tune their systems for optimal performance.>>> Im happy to provide source code for any other projects would want to include this into

1. Create an object-oriented python script that can represent mathematical concepts and their properties. 2. Represent all numeric values exactly. 3. Provide a variety of formats to export or embed representations of the mathematical concepts.

mcpm.sh is an open-source command-line package manager and registry designed for managing Model Context Protocol (MCP) servers across various clients and platforms. It facilitates the installation, configuration, and orchestration of MCP servers, enabling users to group servers into profiles and route requests through a unified interface. With its advanced router and profile features, mcpm.sh simplifies the management of complex MCP environments, supporting clients like Claude Desktop, Cursor, and Windsurf. The tool is built with Python and leverages the Click framework for its CLI, ensuring a robust and user-friendly experience.​

MEINC Installer turns a python application into a Windows EXE or a Unix executable. This is based on Gordon McMillian's Installer project that is no longer maintained.

MINI is a secure service discovery protocol for the M2MI ad-hoc networking library and written in Java (and soon, Python).

Goal of this project is to create a debugger for MIPS. Transition from python project to C after completion. Tailored for UIUC CS 232 course.

MITMf aims to provide a one-stop-shop for Man-In-The-Middle and network attacks while updating and improving existing attacks and techniques. Originally built to address the significant shortcomings of other tools (e.g Ettercap, Mallory), it's been almost completely rewritten from scratch to provide a modular and easily extendible framework that anyone can use to implement their own MITM attack. The framework contains a built-in SMB, HTTP and DNS server that can be controlled and used by the various plugins, it also contains a modified version of the SSLStrip proxy that allows for HTTP modification and a partial HSTS bypass. As of version 0.9.8, MITMf supports active packet filtering and manipulation (basically what better filters did, only better), allowing users to modify any type of traffic or protocol. The configuration file can be edited on-the-fly while MITMf is running, the changes will be passed down through the framework.

All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated. Usable as remote kernel (Jupyter) or remote machine (VS Code) via SSH. Easy to deploy on Mac, Linux, and Windows via Docker. Jupyter, JupyterLab, and Visual Studio Code web-based IDEs.By default, the workspace container has no resource constraints and can use as much of a given resource as the host’s kernel scheduler allows.

MLBox is a powerful Automated Machine Learning python library. Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation. MLBox has been developed and used by many active community members. Your help is very valuable to make it better for everyone.

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. MMF is built on top of PyTorch that brings all of its power in your hands. MMF is not strongly opinionated. So you can use all of your PyTorch knowledge here. MMF is created to be easily extensible and composable. Through our modular design, you can use specific components from MMF that you care about. Our configuration system allows MMF to easily adapt to your needs.

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks, which means you can train a model with one framework and deploy it with another. During the model conversion, we generate some code snippets to simplify later retraining or inference. We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform.

MOCOP is a server based, rich-client, platform independent application development platform. It uses Python and comes with batteries included for developing multi-tanent server based applications.

Mondo: Shared Library Monitor

A Python-based macro processing tool to extend C-like languages with DSLs. MP reduces the amount of work necessary to extend C by extracting the relevant blocks to process and calling user-supplied Python functions to handle the macro.