Open Source Python Software Development Software - Page 51

FAST is an Analysis and Simulation Toolbox (FAST) for Fuel Cells (FC) FAST-FC is the doctorate work of David B. Harvey and was developed with support from the U.S. DOE, Ballard, and Queen's University. Derivative works of FAST-FC include FC-APOLLO which is a forked branch of this project intended to capture the code state at the exit of the funded DOE project. FAST-FC is the open and active community branch. FAST-FC is developed and maintained by the original creator and developer, David B. Harvey. Features of FAST-fc include transport of gases and liquids, multi-step reaction kinetics, transient and steady state operation for performance and durability, and scalable dimensionality from 1D - 3D domains. Future development work is on-going in FAST-fc and our strategic development schedule includes membrane degradation, improved liquid water transport models through the application of pore networks, and extension to stack-level simulation.

FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms, deep learning and transfer learning. FATE became open-source in February 2019. FATE TSC was established to lead FATE open-source community, with members from major domestic cloud computing and financial service enterprises. FedAI is a community that helps businesses and organizations build AI models effectively and collaboratively, by using data in accordance with user privacy protection, data security, data confidentiality and government regulations.

GUI Launcher for Flight Gear that is easy to use and easy to modify. Written in Python. Version 0.2 Enables the launch of several aircraft and four airports with settings for clouds, fog, autocoordination

FGL is a tightly-integrated self-contained development & execution environment utilizing best-of-breed programming tools and methodologies, optimized web/application server, highly-scalable relational/object database, and robust extension interface.

FIDe is a software-based fault injector designed to validate Fault-Tolerant mechanisms and techniques used by applications. It was first used to measure database recovery coverage and costs, but can be used to test and validate ordinary applications.

Framework for writing decorator for FIT [Framework for Integrated Test][http://fit.c2.com/] fixtures. This project also provides a set of standard fit fixtures which can be used to decorate existing FIT table without modifying them.

This project is created mainly to emulate those structures (features) not included in a wide range of object oriented languages.

FOX is an Extensible C++ Class Library for Multi-Platform GUI development. Platforms supported include Linux, Windows NT/9x/2K, and UNIX/X11 workstations (IRIX, Solaris, HP-UX, Tru64, AIX, FreeBSD, and others).

A modern secure, robust, multithreaded, exception aware, internationalisable, portable GUI toolkit library designed for mission-critical work in C++ and Python forked from the FOX library. Replicates the Qt API in many places.

Web gallery based on pre-generated metadata, typically according to directory structure, not database or an administration. Development moved to: http://github.com/martinkozak/fsgal.

Several language bindings for the FTDI D2XX driver used in FTDI's USB products. Currently supported languages are Python (pyd2xx), Java (jd2xx), CSharp (csd2xx) and LabVIEW (lvd2xx).

Falconer-Try Studios is developing this new gaming engine for 2D, 3D and soon VR environments. It will be best for RTS and FPS games. See the documentation for more data.

FXPy is a Python extension module that provides an interface to the cross-platform FOX GUI library. It is no longer under development, but the last release is compatible with FOX 1.0 and Python 2.2.

FAIRChem is a unified library for machine learning in chemistry and materials, consolidating data, pretrained models, demos, and application code into a single, versioned toolkit. Version 2 modernizes the stack with a cleaner core package and breaking changes relative to V1, focusing on simpler installs and a stable API surface for production and research. The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations, molecular dynamics, spin-state energetics, and surface catalysis workflows with the same pretrained network by switching a task flag. Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. The README provides quick paths for pulling models (e.g., via Hugging Face access), then running energy/force predictions on GPU or CPU.

FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce boilerplate in complex distributed setups. Its components are modular, so teams can adopt just the sharding optimizer or the pipeline engine without rewriting their training loop. FairScale puts emphasis on correctness and debuggability, offering hook points, logging, and reference examples for common trainer patterns. Although many ideas have since landed in core PyTorch, FairScale remains a valuable reference and a practical toolbox for squeezing more performance out of multi-GPU and multi-node jobs.

Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. Criterions compute the loss function given the model outputs and targets. Tasks store dictionaries and provide helpers for loading/iterating over Datasets, initializing the Model/Criterion and calculating the loss.

GUIE (GUI Editor) provides a simple WYSIWYG GUI editor for many dynamic languages. Currently FarPy supports wxPython, wxRuby, wxPerl & IronPython!

This is a suite of tools for farmers it includes local market prices for their sales, weather reports, other features useful to farmers.

FATS - FATS is a Twisted and Fast Asterisk's Telephony Services. Project contains implementation of FastAGI, AMI protocols for the Twisted framework. Using it you can develop fast and pretty services for the Asterisk IP-PBX.

An extremely fast implementation of the xmlrpc spec for Python (written in C). It supports both blocking and non-blocking clients and servers on Windows and POSIX platforms. Version 0.8.1 is 100% compliant with the www.xmlrpc.com validator.

A cross-platform library that computes fast and accurate SIFT image features. libsiftfast provides Octave/Matlab scripts, a command line interface, and a python interface (siftfastpy). Optimized with SIMD instructions and OpenMP .

FastAPI-React is a cookiecutter template that combines FastAPI and React to create full-stack applications. It integrates PostgreSQL, SQLAlchemy, and Docker to provide a comprehensive development environment.

Tired of rewriting generic CRUD routes? Need to rapidly prototype a feature for a presentation or a hackathon? Thankfully, fastapi-crudrouter has your back. As an extension to the APIRouter included with FastAPI, the FastAPI CRUDRouter will automatically generate and document your CRUD routes for you, all you have to do is pass your model and maybe your database connection. fastapi-crudrouter provides a number of features that allow you to get the most out of your automatically generated CRUD routes. The CRUDRouter is able to dynamically generate detailed documentation based on the models given to it. By default, all routes generated by the CRUDRouter will be documented according to OpenAPI spec. The CRUDRouter is able to dynamically generate detailed documentation based on the models given to it.

FastUI is a library that lets developers build interactive user interfaces for FastAPI applications using Pydantic models. It automatically generates frontend components based on data schemas and endpoint logic, reducing the need for manual UI development. Designed to be type-safe, reactive, and fast, FastUI streamlines the creation of web dashboards, admin panels, and internal tools within a FastAPI backend.

FePy project aims to provide enhancements and add-ons for IronPython, an implementation of Python programming language.