Open Source Python Software Development Software for Linux

"Roberge's Used Robot (RUR) : a Python Learning Environment" is a Python implementation of a "robot environment" as introduced by R. Pattis in 1981. **It is obsolete.** See https://github.com/aroberge/rur-ple

Guido van Robot Educational Programming Language

The Data Engineering Handbook is a comprehensive, community-curated repository that aggregates essential learning resources for anyone interested in becoming a professional data engineer. Rather than being a code project itself, it’s a learning handbook that links to books, articles, tutorials, community groups, boot camps, and real-world project examples that collectively form a roadmap to mastering data engineering skills. It includes beginner and intermediate boot camps, interview guides, data cleaning and transformation resources, and curated lists of newsletters and industry communities, making it useful both for self-study and technical interview preparation. The repository is actively maintained and widely starred, reflecting its role as a go-to reference for newcomers and experienced practitioners alike.

" Deep Learning " is the only comprehensive book in the field of deep learning. The full name is also called the Deep Learning AI Bible (Deep Learning) . It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. Finally, the Deep Learning book provides research directions covering theoretical topics including linear factor models, autoencoders, representation learning, structured probabilistic models, etc.

Each larger open source project has its own style guide, a series of conventions on how to write code for the project (sometimes more arbitrary). When all the code maintains a consistent style, it is more important when understanding large code bases. easy. The meaning of "style" covers a wide range, from "variables use camelCase" to "never use global variables" to "never use exceptions". The English version of the project maintains the programming style guidelines used in Google. If the project you are modifying originates from Google, you may be directed to the English version of the project page to understand the style used by the project. The Chinese version of the project uses reStructuredText plain text markup syntax, and uses Sphinx to generate document formats such as HTML / CHM / PDF.

Ansible Lint is a command-line tool for linting playbooks, roles and collections aimed towards any Ansible users. Its main goal is to promote proven practices, patterns and behaviors while avoiding common pitfalls that can easily lead to bugs or make code harder to maintain. Ansible lint is also supposed to help users upgrade their code to work with newer versions of Ansible. Due to this reason we recommend using it with the newest version of Ansible, even if the version used in production may be older. As any other linter, it is opinionated. Still, its rules are the result of community contributions and they can always be disabled based individually or by category by each user. ansible-lint checks playbooks for practices and behavior that could potentially be improved. As a community-backed project ansible-lint supports only the last two major versions of Ansible.

The purpose of this project is to create a German translation of the book <a href="http://www.byteofpython.info">"A Byte of Python"</a> originally written in English by Swaroop C H.

Main goals: * Prepare operating system based on Linux kernel and free software for use at home from scratch by building sources. Binary packages/images are also available. * Each package is installed in separate directory, so you can use different versions of applications and libraries by design. * There is only one user 'kanapi' with root permissions, so you don't have to login, remember passwords, etc. * Simple configuration * Automatic compilation.

GGI stands for "General Graphics Interface", and it is a project that aims to develop a reliable, stable and fast graphics system that works everywhere. We want to allow any program using GGI to run on any platform requiring at most a recompile.

DrPython is a highly customizable cross-platform ide to aid programming in Python. It was developed with teaching in mind, and has a clean, simple interface. It is written in Python, using wxPython as the gui.

எழில் - ஒரு தமிழ் நிரலாக்க மொழி; தமிழ் மாணவர்களுக்கு இது முதல்முறை கணி Ezhil is a Tamil script based programming language for children and teens in the K-12 grade schools. Ezhil enables learning imperative programming like BASIC or LOGO in Tamil language.

ImageJ is a public domain Java image processing program inspired by NIH Image for the Macintosh. It runs, either as an online applet or as a downloadable application, on any computer with a Java 1.1 or later. HOME @ http://rsb.info.nih.gov/ij/

C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.

PythonCard is a GUI construction kit for building cross-platform desktop applications on Windows, Mac OS X, and Linux, using the Python language.

EYE [1] is a reasoning engine supporting the Semantic Web layers [2]. It performs controlled chaining and it supports Euler paths [3]. Via N3 [4] it is interoperable with Cwm [5]. [1] http://eulersharp.sourceforge.net/README [2] http://www.w3.org/DesignIssues/diagrams/sweb-stack/2006a [3] http://mathworld.wolfram.com/KoenigsbergBridgeProblem.html [4] http://www.w3.org/TeamSubmission/n3/ [5] http://www.w3.org/2000/10/swap/doc/cwm

APLEpy stands for Algebraic Programming Language Extension for Python. It is an open source alternative to commercial products such as AMPL and GAMS. It offers the same high level of abstraction while keeping the advantages of using Python environment.

Binarytree is Python library that lets you generate, visualize, inspect and manipulate binary trees. Skip the tedious work of setting up test data, and dive straight into practicing algorithms. Heaps and BSTs (binary search trees) are also supported. Binarytree supports another representation which is more compact but without the indexing properties. Traverse trees using different algorithms.

CLUE (C Learning Undergraduate Environment) is a software allowing students to work on assignments in the C language while benefiting from support for peer testing, hyper-linked tutorials to help them understand compiler error messages, detection of "novice errors" with warnings hyper-linked to tutorials. Sponsored by National Science Foundation under award CCLI #0836863.

Cryptography Tools is a project to develop demonstration tools on classic (currently Caesar and Playfair) & modern crypto-systems, including private & public key encryptions, digital signatures, cryptographic hashes and authenticated encryption.

The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms.

Digital Preservation Software Platform (DPSP) consists of a number of open source products such as Xena and Digital Preservation Recorder. This installs and configures the complete platform for preserving digital records - just install and use! NO LONGER MAINTAINED, NO LONGER SUPPORTED

Traducción de la documentación oficial de Python y, adicionalmente, cualquier otra documentación disponible en castellano relativa a Python.

Educational programming language tools written in Python for use with PC/104 computer based robotics teaching at the middle/high school level.

This book introduces elementary algorithms and data structure. It includes side-by-side comparison of purely functional realization and their imperative counterpart. From 2020/12, I started re-writing this book. The PDF can be downloaded for preview (EN, 中文). The 1st edition in Chinese (中文) was published in 2017. I recently switched my focus to the Mathematics of programming, the new book is also available in (github). To build the book in PDF format from the sources, you need the following software pre-installed, TeXLive, The book is built with XeLaTeX, a Unicode friendly version of TeX. You need the GNU make tool, in Debian/Ubuntu like Linux, it can be installed through the apt-get command.

ExpLab is a set of tools that supports the running, documentation and evaluation of computational experiments.