Search Results for "python code editor"
Sort By:
Showing 152 open source projects for "python code editor"
View related business solutions-
Veeam Data Platform v13.1 - Get Your Free TrialTry Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
1
Python Tutorial
Xiaobai Python Tutorial
Python Tutorial is a Chinese beginner-friendly Python tutorial repository focused on practical self-study. It is written for learners who want to build programming fundamentals step by step instead of collecting scattered resources without a path. The course is based on Python 3.10+ and marks newer language features from Python 3.11, 3.12, and 3.13 where relevant. -
2
Hello Python
Comprehensive tutorial repository aimed at teaching the Python program
Hello-Python is a comprehensive tutorial repository aimed at teaching the Python programming language from scratch for beginners. It includes over 100 classes and about 44 hours of video instruction, combined with code samples, projects, and a chat community for support. The material covers the fundamentals—variables, data types, loops, functions—as well as intermediate topics like date handling, list comprehensions, file IO, regular expressions, modules, and packages. ... -
3
Book1_Python-For-Beginners
The Iris Book: Addition, Subtraction, Multiplication, and Division
Book1_Python-For-Beginners is the introductory volume of the Visualize-ML series, designed to teach Python programming to newcomers with no prior coding experience. The repository emphasizes clarity and gradual skill building, starting from fundamental syntax and moving toward practical programming patterns. It integrates visual aids and annotated code examples to help learners understand not just how Python works but why certain patterns are used. -
4
Python Core 50 Courses
Structured learning path that organizes Python fundamentals
Python-Core-50-Courses is a structured learning path that organizes Python fundamentals into 50 digestible lessons designed for steady, incremental progress. The curriculum starts with the basics—syntax, variables, data types, and control flow—then advances to functions, modules, object-oriented programming, and common standard-library utilities. -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
5
Electron Fiddle
The easiest way to get started with Electron
...It also includes examples for every API available in Electron, so if you want to quickly see what a BrowserView is or how the desktopCapturer works, Fiddle has got you covered. Fiddle includes Microsoft's excellent Monaco Editor, the same editor powering Visual Studio Code. It also installs the type definitions for the currently selected version of Electron automatically, ensuring that you always have all Electron APIs only a few keystrokes away. -
6
Claude How-To
A visual, example-driven guide to Claude Code
Claude How-To is a visual, example-driven guide for learning Claude Code. It covers basic concepts, memory, slash commands, hooks, skills, subagents, MCP configuration, plugins, and advanced agent workflows. The project is designed as a practical learning path rather than a simple list of notes. It includes copy-paste templates that users can apply directly to their own projects. The guide also uses diagrams and structured examples to explain not only how features work, but why they matter... -
7
AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run them in a sandbox environment, and analyze the results with statistical methods. ... -
8
nanoGPT
The simplest, fastest repository for training/finetuning models
NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare or custom corpora. It emphasizes readability and clarity: the training loop is cleanly written, and the code avoids heavy abstractions, letting students follow the architecture step by step. ... -
9
ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
ThinkStats2 is the code and text companion for the second edition of Think Stats, an introduction to statistics and data science for Python programmers. It teaches probability and statistical reasoning through short programs, experiments, and analysis of real datasets. The material emphasizes exploratory methods that help readers ask and answer practical questions with data. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
10
The Data Engineering Handbook
Links to everything you'd ever want to learn about data engineering
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,... -
11
Google Open Source Project Style Guide
Chinese version of Google open source project style guide
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... -
12
ML for Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. The... -
13
Open Science
Open Science is an open-source, local-first, model-agnostic research
...Immutable artifact versions and detailed provenance connect results to code, inputs, execution history, environment evidence, conversation context, and review findings. -
14
Ansible-lint
Best practices checker for Ansible
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... -
15
PythonPark
Python open source project "The Road to Self-Study Programming"
PythonPark is a large, curated “learning playground” for Python — essentially a comprehensive self-study meta-repository aimed at helping learners progress in Python programming, data science, machine learning, web scraping, and software engineering practices. It aggregates tutorials, learning guides, project examples, and resources across topics: from Python basics and data structures to machine learning, web scraping, and even interview preparation and “programmer life” guidance. Because... -
16
Bats-core
Bash automated testing system
Bats is a TAP-compliant testing framework for Bash. It provides a simple way to verify that the UNIX programs you write behave as expected. A Bats test file is a Bash script with special syntax for defining test cases. Under the hood, each test case is just a function with a description. Bats is most useful when testing software is written in Bash, but you can use it to test any UNIX program. Test cases consist of standard shell commands. Bats makes use of Bash's errexit (set -e) option when... -
17
PocketFlow Tutorial Codebase Knowledge
Codebase to Tutorial
PocketFlow Tutorial Codebase Knowledge is a project that demonstrates how to build an AI agent capable of analyzing arbitrary codebases and generating beginner-friendly tutorials that explain how they work, turning complex source code into clear educational content. The repository builds on a lightweight 100-line LLM framework and uses natural language models to inspect repository structures, identify core abstractions, map dependencies, and articulate the reasoning behind code design and... -
18
ThinkDSP
Digital Signal Processing in Python, by Allen B. Downey
...Early exercises show how to decompose sounds, modify frequency components, and synthesize new audio. The repository includes chapter notebooks, solution notebooks, sample sound files, book sources, and reusable Python code. Lessons can run online through Google Colab or Binder, or locally with Conda or Poetry. Its top-down approach is intended for learners who already know basic programming and want a practical route into DSP. -
19
CodeWorld
Educational computer programming environment using Haskell
CodeWorld is an educational programming environment that uses a Haskell-inspired language to teach computational thinking through graphics and interactive animation. The web-based IDE provides immediate visual feedback: students write code that draws shapes, composes pictures, and responds to events to build simple games and simulations. Its API emphasizes mathematics and geometry rather than low-level UI details, making it approachable for classrooms and self-learners. Projects run in the... -
20
LeetCode Book
Comprehensive study guide for coding interviews
LeetCode-Book is a comprehensive study guide for coding interviews that consolidates algorithm patterns, data-structure templates, and worked LeetCode solutions. It organizes problems by topic—arrays, linked lists, stacks/queues, trees/graphs, dynamic programming, greedy, backtracking, and math—so you can study systematically. Explanations are concise but intentional, highlighting why a pattern fits, how to reason about boundary cases, and the time/space trade-offs. Many entries include... -
21
OpenScience
The open-source AI workbench for scientific research
OpenScience is an open-source AI workbench for scientific research. It lets users give an agent a research goal, then have it read literature, form hypotheses, write and run code, run experiments, analyze results, and write up findings. The workspace runs in the browser and includes a file tree, editor, terminal, session history, and scientific rendering for molecules, structures, genomes, and plots. It supports frontier, open-weight, and local models through bring-your-own-key provider configuration. The project includes research agents, domain specialists, critique agents, literature-review agents, and more than 290 scientific skills. ... -
22
Lumina
Lumina is a visual game creation environment for building 3D games.
On Arch Linux: yay -S lumina-editor-git Repo: https://github.com/spikest3r/Lumina LumenLang docs: https://lumen.olehsheremeta.com/ Lumina is a 3D game creation environment built around LumenLang. It combines a visual block-based editor with traditional programming, letting you create interactive 3D projects either visually, through code, or by mixing both. -
23
Scientific Visualization
An open access book on scientific visualization using python
The Scientific Visualization book is a freely available open-access textbook that introduces how to produce effective scientific visualizations using Python, focusing especially on leveraging the popular plotting library Matplotlib (and related tools). It goes beyond simple plotting tutorials and emphasizes design principles: how to choose colors, layout subplots, annotate graphs, and present data in a way that is both accurate and visually compelling. As such, it serves as a guide for... -
24
Web Dev for Beginners
About 24 Lessons, 12 Weeks, Get Started as a Web Developer
Web-Dev-For-Beginners is Microsoft’s open source, project-based curriculum for learning web development from scratch. Designed as a 12-week, 24-lesson course, it covers HTML, CSS, and JavaScript fundamentals through hands-on projects like terrariums, browser extensions, and space games. Each lesson includes a mix of pre-lecture quizzes, written content, assignments, challenges, and post-lecture quizzes to reinforce learning. The course also offers global accessibility with translations in... -
25
Build your own X
Master programming by recreating your favorite technologies
build-your-own-x is a massive, community-curated roadmap of hands-on tutorials that teach you to re-implement complex systems from scratch—things like databases, compilers, operating systems, interpreters, web servers, neural networks, regex engines, and more. Rather than offering abstract theory, it organizes step-by-step guides by topic and by programming language, so you can pick a project that fits your stack and skill level. The focus is on demystifying internals: you don’t just use a...
