Open Source Python Software Development Software - Page 68

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.

Distributed Parallel Programming for Python! This package builds on traditional Python by enabling users to write distributed, parallel programs based on MPI message passing primitives. General python objects can be messaged between processors. Ru

A message passing library addressing the special needs/capabilities of Qt applications. The basic building block for classic 3-tier applications where both client and server are Qt applications.

Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide controllable adjustment range, which thereby makes it possible to provide optional modes of recommendation aiming different kinds of users.

MRV is a python framework based on wrapping the Maya API to speed up development and ease of use within pipelines using Autodesk Maya.

This code is another way to create SOA applications through HTTP. Can execute Database SPs, MSMQ, Assemblies, IronPython script and generates RSS, JSON, Web Service, Text or Excel file through HTTP. The system has authentication and logging support.

MSCViewer is a tool intended for debugging of control flows in concurrent, distributed systems. The tool loads logs generated by various entities in the system and visualize a sequence diagram chart for events and interactions. The diagram is fully interactive: entity can be added/removed from the diagram and shuffled; events can be filtered, searched, highlighted and annotated with comments. MSCViewer features integration with a Python interpreter which allows writing Python scripts interacting with the model. This powerful feature can be used to automate validatation of distributed control flows, integrate with graphing infrastructure, etc.

Automatically Get Official Product Updates on munki Server. This MUNKI SERVER Command line Tool (Munki Updater) will check for available MUNKI Product Updates on official Servers (example Mozilla) and will allow to Download and Update older Product Versions on MUNKI Repository and distribute them on clients having older versions. munki updater readme: http://svn.code.sourceforge.net/p/munkiupdater/code-0/trunk/readme.txt ############# managed software centre installer including public repo with freeware: /bin/bash -c "$(curl -fsSL http://svn.code.sourceforge.net/p/munkiupdater/code-0/trunk/online/install-munki.sh)"

MVCPython is a framework which automatically generates a MVC architecture (MVC= Model View Controller) just from Python Classes and Object defintions. MVCPython achieves this through a strong use of Python's introspection capability.

This project is redundant. All files have been copied to MaMo Py: https://sourceforge.net/projects/marimorepy/

A collection of python libraries used by MARIMORE Inc. http://www.marimore.co.jp THIS PROJECT HAS MOVED TO https://github.com/marimore/marimorepy

The project moved here: https://github.com/vbatoufflet/machette

You assemble *blocks* in your django template, with each block wired to a tastypie resource, which in turn is mapped to a django model. Each *block* will reside in a dijit ContentPane which you must define in your template. You have a choice of 2 layouts for each *block*, Form or Grid based. Form displays a single record in either a 1, 2 or 3 column layout while Grid displays many rows in a spreadsheet like grid. You can perform edits in place on fields in both layouts. You can define the master-detail relationship between the *blocks* and enblok will automatically display the related detail *block* rows as the user navigates the master *block*'s rows. You get for free the default *CRUD* functionality for each block, together with Search. You are not limited to just a 2 level master-detail relationship, in fact enblok can support n-th level relationships but we do not advise you to go beyond 3. Read the distribution's enblok/readme.txt for further instructions.

This is a Python interface for reading and writing Magellan GPS unit map files. There is also a command line tool for creating GPS maps from OpenStreetMap data.

This script will automatically decode an obfuscated JavaScript or VBScript in HTML and scan for suspicious/malicious codes in the page.

Generate ten different malicious PDF files with phone-home functionality. Can be used with Burp Collaborator or Interact.sh. Used for penetration testing and/or red-teaming etc. I created this tool because I needed a third-party tool to generate a bunch of PDF files with various links.

Mallard is a graphical game design package, akin to many applications for Windows such as The Games Factory, RPG Maker, Game Maker, etc. It is written in Python with wxWidgets and PyGame, and therefore should support any OS which supports Python and SDL.

Adobe Malware Classifier is a command-line tool that lets antivirus analysts, IT administrators, and security researchers quickly and easily determine if a binary file contains malware, so they can develop malware detection signatures faster, reducing the time in which users' systems are vulnerable. Malware Classifier uses machine learning algorithms to classify Win32 binaries – EXEs and DLLs – into three classes: 0 for “clean,” 1 for “malicious,” or “UNKNOWN.” The tool was developed using models resultant from running the J48, J48 Graft, PART, and Ridor machine-learning algorithms on a dataset of approximately 100,000 malicious programs and 16,000 clean programs. The tool extracts seven key features from an unknown binary, feeds them to one of the four classifiers or all of them, and presents its classification of the unknown binary.

The Mandragora World Engine is a C++/Python engine which allows the easy creation of programs, including applications, simulations, and games. Able to load and run specific program modules. Will handle objects, graphics, sound, physics, GUI, and even AI.