Open Source Python Software Development Software - Page 60

A user-extendable Slack bot for GitHub organization management. HubCommander provides a chat-ops means for managing GitHub organizations. It creates a simple way to perform privileged GitHub organization management tasks without granting administrative or owner privileges to your GitHub organization members. HubCommander is based on slackhq/python-rtmbot (currently, dependent on release 0.4.0) You simply type help, and the bot will output a list of commands that the bot supports. Typing the name of the command, for example, CreateRepo, will output help text on how to execute the command. Granting outside collaborators specific permissions to repositories. Repository default branch modification. Repository PR listing. Repository deploy Key listing/creation/deletion. Repository topics creation/deletion. Repository branch protection enabling/disabling. You can add additional commands by creating plugins. For example, you can create a plugin to invite users to your organizations.

Import publications from your reference manager to Hugo. Import publications, including books, conference proceedings and journals, from your reference manager to your static site generator. Simply export a BibTeX file from your reference manager, such as Zotero, and provide this as the input.

HSPL is Human Speakable Programming Language, allowing for communication between human-to-computer and human-to-human in the same language. This project has moved to http://sourceforge.net/p/spel We are currently working on human-to-computer programming-language with mostly English base vocabulary. Though once we have that, we plan to add support for other world Languages, including Chinese, Spanish, Russian, Arabic, Hindi, among others. Eventually HSPL shall be the foundation of GIOS the General Intelligence Operating System. Which is an open source operating system, that can be used for intelligent robots, computers and technological host-bodies. Regularly post on blog about HSPL at http://weyounet.info/?s=hspl

HumbleUI is a lightweight, declarative, and composable UI framework, likely intended for building graphical user interfaces in a minimal, modular way. It emphasizes ease of use, customization, and modular components. (Note: while there is a repository, I did not find a detailed README in my search to fully confirm all capabilities.) Electron is a great landmark. Normal shortcuts, icon, its own window, file system access, notifications, OS integrations. Write once, run everywhere is no longer rejected by users. Performant enough not to noticeably lag.

Hy is a multi-paradigm general-purpose programming language in the Lisp family. It’s implemented as a kind of alternative syntax for Python. Compared to Python, Hy offers a variety of extra features, generalizations, and syntactic simplifications, as would be expected of a Lisp. Compared to other Lisps, Hy provides direct access to Python’s built-ins and third-party Python libraries, while allowing you to freely mix imperative, functional, and object-oriented styles of programming. The first thing a Python programmer will notice about Hy is that it has Lisp’s traditional parenthesis-heavy prefix syntax in place of Python’s C-like infix syntax. As in other Lisps, the value of a simplistic syntax is that it facilitates Lisp’s signature feature, metaprogramming through macros, which are functions that manipulate code objects at compile-time to produce new code objects, which are then executed as if they had been part of the original code.

This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.

A composable GAN built for developers, researchers, and artists. HyperGAN builds generative adversarial networks in PyTorch and makes them easy to train and share. HyperGAN is currently in pre-release and open beta. Everyone will have different goals when using hypergan. HyperGAN is currently beta. We are still searching for a default cross-data-set configuration. Each of the examples supports search. Automated search can help find good configurations. If you are unsure, you can start with the 2d-distribution.py. Check out random_search.py for possibilities, you'll likely want to modify it. The examples are capable of (sometimes) finding a good trainer, like 2d-distribution. Mixing and matching components seems to work.

Hylt is a file format that provides HYperLinked Text with minimal markup, meant to be both easy to view in any program and easy to keep in a version control system. The Hylt project covers the file specification, viewers, and tools to manage Hylt files.

HyperSQL is like a doxygen plus javadoc for SQL, hypermapping SQL views, packages, procedures, and functions to HTML source code listings and showing all code locations where these are used.

Python Lib to Control a I2C-LCD Display with PCF8574 expander.

Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with both RGB and optical flow input streams. The models have achieved state-of-the-art results on benchmark datasets such as UCF101 and HMDB51, and also won first place in the CVPR 2017 Charades Challenge. The project provides TensorFlow and Sonnet-based implementations, pretrained checkpoints, and example scripts for evaluating or fine-tuning models. It also offers sample data, including preprocessed video frames and optical flow arrays, to demonstrate how to run inference and visualize outputs.

A replacement for the not so useful wingraph32 with uDraw, for the Interactive Disassembler (IDA).

IDEAIS is a enteprise service bus integration plataform for software development tools and activities. It uses Web Services (SOAP/HTTP) to integrate best of the breed software development tools (Eclipse, Subversion, Bugzilla, dotProject, vTiger).

An official experimental fork of Python's integrated development environment IDLE. Worthwhile and successful changes and additions will go back into the Python distribution's IDLE at some later stage. There is no spanish inquisition.

IDXMLParser is a "sloppy dom" XML parser, that provides for an XPath *like* interface for querying XML elements and attributes, whilst not requiring any validation of the XML.

Written in C++, IFI-picloader is a US First Competition Linux port for Innovation First Inc. Robot Controller programmer using a pic 18F8520. It writes MCC18 compiled hex files to PIC and allows users to program under *nix based operating systems.

IFP (ISPF for Python) is a console based full screen text user interface and API based on IBM's ISFP.

The illegitimate child of a free-spirited comedian and a profiteering barista; a batteries included approach to compiled languages.

math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net

The IPS Framework has migrated to https://github.com/HPC-SimTools/IPS-framework The IPS framework was developed to support loosely-coupled integrated modeling of fusion plasmas (and was originally the Integrated Plasma Simulator). However, the design is quite general, and is suitable for many scientific and engineering domains. In addition to plasma physics, it is also being used in the engineering of batteries. One of the novel features of the IPS framework is its ability to support parallelism at multiple levels: components can launch individual parallel tasks, and also launch multiple tasks concurrently. The framework can execute multiple components concurrently, and even multiple simulations, all within the same pool of compute nodes.

WARNING: Project moved to http://github.com/scemama/irpf90 IRPF90 is a Fortran90 preprocessor written in Python for programming using the Implicit Reference to Parameters (IRP) method. It simplifies the development of large fortran codes in the field of scientific high performance computing.

Institute of Technology, Blanchardstown Computer Science code by the class of 2007-2011 on course BN104. In this project we are open sourcing all of our project work to the public in the hopes it can be reused, built-upon, and used in education.

Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an awesome model on GitHub, written in JAX. We'll use PerceiverIO as an example. Implement the model in PyTorch yourself, spending time and energy ensuring every detail is correct. Otherwise, wait for a PyTorch version to appear on GitHub, among the many re-implementation attempts that appear (a, b, c, d, e, f). Instantly transpile the JAX model to PyTorch. This creates an identical PyTorch equivalent of the original model.

Do you ever use print() or log() to debug your code? Of course you do. IceCream, or ic for short, makes print debugging a little sweeter. With arguments, ic() inspects itself and prints both its own arguments and the values of those arguments. Just give ic() a variable or expression and you're done. ic() returns its argument(s), so ic() can easily be inserted into pre-existing code. Additionally, ic()'s output can be entirely disabled, and later re-enabled, with ic.disable() and ic.enable() respectively. ic() continues to return its arguments when disabled, of course; no existing code with ic() breaks. To make ic() available in every file without needing to be imported in every file, you can install() it. ic() can also be imported in a manner that fails gracefully if IceCream isn't installed, like in production environments (i.e. not development).

Python script (and library) for easy and simple export of icons from web icon fonts (e.g. Font Awesome, Octicons) as PNG images. The best part is the provided shell script, but you can also use it’s functionality directly in your (probably awesome) Python project. There’s also font-awesome-to-png script for backward compatibility with the first iteration of the concept. You can use IconFont (and IconFontDownloader for that matter) directly inside your Python project. There's no proper documentation as of now, but the code is commented and should be pretty straightforward to use.