Open Source Python Software Development Software - Page 73

Neural Network Intelligence is an open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning and model compression. The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in different training environments like Local Machine, Remote Servers, OpenPAI, Kubeflow, FrameworkController on K8S (AKS etc.) DLWorkspace (aka. DLTS) AML (Azure Machine Learning) and other cloud options. NNI provides CommandLine Tool as well as an user friendly WebUI to manage training experiements.

nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is great for customization and teaching purposes.

This project implements in C++ a bunch of known Neural Networks. So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people.

Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels, perform exact GP inference, and study training dynamics analytically for infinitely wide networks. The library closely mirrors JAX’s stax API while extending it to return a kernel_fn alongside init_fn and apply_fn, enabling drop-in workflows for kernel computation. Kernel evaluation is highly optimized for speed and memory, and computations can be automatically distributed across accelerators with near-linear scaling.

Neuro SAN Studio is a development environment and playground for building, testing, and deploying multi-agent AI systems using the Neuro SAN framework. It provides a hands-on interface where users can design agent networks, run experiments, and observe how multiple agents collaborate to solve complex tasks. The platform is built around a data-driven approach, where entire agent systems can be defined using configuration files rather than extensive code, making it accessible to both developers and domain experts. It supports advanced orchestration through decentralized communication protocols, allowing agents to dynamically delegate tasks and adapt to changing requirements. The system also includes mechanisms for secure data handling, ensuring sensitive information is not exposed directly to language models. Neuro SAN Studio offers built-in examples, tutorials, and debugging tools, which help users quickly prototype and refine multi-agent workflows.

NeuroKiwi is the application of the Associative Model (AM, previously dubbed AMDroid), being a model storing relational change-detections. The application tries to emulate ground-up knowledge accumulation with limited or no prior knowledge of shapes or patterns.

Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and then experiment with multiple strategies—evolutionary algorithms, Bayesian optimization, bandit methods, genetic algorithms, etc. Nevergrad supports parallelization, budget scheduling, and multiple cost/resource constraints, allowing it to scale to nontrivial optimization problems. It includes visualization tools and diagnostic metrics to compare strategy performance, track parameter evolution, and detect stagnation.

NiL is a modular multi-purpose gaming engine including a multiplayer worm game a little like quake, except it's 2d and a little like worms except it's realtime.

Nxpy is a Python library that combines general purpose features with a set of tools more geared towards build automation and source code management. It provides convenient ways to invoke and control interactive and non-interactive commands, context aware backup for files you need to modify, convenience stubs for file like objects, and more. It also contains wrappers for ClearCase, Maven and Subversion, as well as tools to manipulate Maven and Visual Studio configuration files.

NickelsWebtranslator is a simple web-based application for internationalization of java-based projects. Properties files can easily be translated by a remote and widespread group of translaters (utf8-encoding). Python web application with mysql backend.

Nimporter allows the seamless import of Nim code into Python projects, enabling the use of Nim's performance and syntax within Python applications.

"No comment!" is a command-line tool that generates various comment-related metrics for source code files (e. g. comment density, blank lines per file)

Graphical debugger for programs that don't just follow one stream (e.g. threaded, web applications). Also allows debugging in headless computers, in distributed environments and for crashing applications.

Use NB-CLI to quickly build your own robot. Plug-in development, modular management. Supports multiple platforms and multiple incident response methods. Asynchronous priority development to improve operational efficiency. Simple and clear dependency injection system, built-in dependency functions reduce user code. NoneBot2 is a modern, cross-platform, and extensible Python chatbot framework. It is based on Python's type annotations and asynchronous features, and can provide convenient and flexible support for your needs. NoneBot2 is written based on Python asyncio , and has a certain degree of synchronous function compatibility based on the asynchronous mechanism. NoneBot2 provides an easy-to-use, interactive command-line tool -- nb-cli, making it easier to get started with NoneBot2 for the first time. The plug-in system is the core of NoneBot2, through which the modularization and function expansion of the robot can be realized, which is convenient for maintenance and management.

Nose plugin to create XUnit like XML test results

This python script will generate a custom python.xml file used by Notepad++ for auto-completion features when programming in python (function names, arguments, and descriptions), using your own set of imported modules.

A graphical, hierarchical note-taking application, using reStructuredText, python and PyQt.

NovaX is a set of programs that is being devloped for small company's and beginners in the fields of HTML and programming. Coded in Python and C++, this is also a good replacement for MS Office. NOTE: This requires Python to be on your PC. ( Python.org )

Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code. Numba translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. Numba-compiled numerical algorithms in Python can approach the speeds of C or FORTRAN. You don't need to replace the Python interpreter, run a separate compilation step, or even have a C/C++ compiler installed. Just apply one of the Numba decorators to your Python function, and Numba does the rest. Numba is designed to be used with NumPy arrays and functions. Numba generates specialized code for different array data types and layouts to optimize performance. Special decorators can create universal functions that broadcast over NumPy arrays just like NumPy functions do. Numba also works great with Jupyter notebooks for interactive computing, and with distributed execution frameworks, like Dask and Spark.

Linux Multimedia Framework using CORBA. Implementation mainly in C++ and Python.

interface for storing objects to relational database (mySQL at the moment); written in python; nice to use with zope application server to store the content of web-forms in a generic way

ODic stands for "Options Dictionary" and aims at creating standards for easier command line tool creation. At the moment it is focused on the 'odic' python module including new design patterns for python main functions.

Object-oriented persistent storage library for python. Merges database design and application design (as both are deeply linked).

An open-source cross-platform compiler for the Savage Innovations OOPic microcontroller.

OOpyREP is a python code generating filter and library. It reads a OpenOffice.org file and creates a python representation of the document structure as well as contents. The generated code uses the reportlab PDF library to render the document.