Search Results for "coding" - Page 28
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Showing 2276 open source projects for "coding"
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Godot Minimal Theme
Godot Minimal Theme
...It has been tested and confirmed compatible with several recent Godot versions (4.3, 4.4, 4.5), and many users believe it significantly improves the usability and aesthetic of the Godot editor, especially for extended coding or scene-building sessions. By offering a well-tuned default set of UI parameters (color scheme, font recommendations, layout tweaks), it saves users the trouble of configuring their own setup — and ensures consistency across different projects or machines. Because it’s open source, users can further customize or fork it to suit their personal preferences. -
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EasyR1
An Efficient, Scalable, Multi-Modality RL Training Framework
EasyR1 is a streamlined training framework for building “R1-style” reasoning models from open-source LLMs with minimal boilerplate. It focuses on the full reasoning stack—data preparation, supervised fine-tuning, preference or outcome-based optimization, and lightweight evaluation—so you can iterate quickly on chain-of-thought–heavy tasks. The project’s philosophy is practicality: sensible defaults, one-command recipes, and compatibility with popular base models let you stand up experiments... -
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Laravel Pint
Laravel Pint is an opinionated PHP code style fixer for minimalists.
...Pint is automatically installed with all new Laravel applications so you may start using it immediately. By default, Pint does not require any configuration and will fix code style issues in your code by following the opinionated coding style of Laravel. Pint is included in recent releases of the Laravel framework, so installation is typically unnecessary. However, for older applications, you may install Laravel Pint via Composer. You can instruct Pint to fix code style issues by invoking the pint binary that is available in your project's vendor/bin directory. ... -
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Simple StyleGan2 for Pytorch
Simplest working implementation of Stylegan2
Simple Pytorch implementation of Stylegan2 that can be completely trained from the command-line, no coding needed. You will need a machine with a GPU and CUDA installed. You can also specify the location where intermediate results and model checkpoints should be stored. You can increase the network capacity (which defaults to 16) to improve generation results, at the cost of more memory. By default, if the training gets cut off, it will automatically resume from the last checkpointed file. ... -
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PyScaffold
Python project template generator with batteries included
PyScaffold is a project generator for bootstrapping high-quality Python packages, ready to be shared on PyPI and installable via pip. It is easy to use and encourages the adoption of the best tools and practices of the Python ecosystem, helping you and your team to stay sane, happy and productive. The best part? It is stable and has been used by thousands of developers for over half a decade! Checkout out this demo project, which was set up using PyScaffold and if you are still not convinced... -
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Nano ID
A secure, URL-friendly, unique string ID generator for JavaScript
...Instead of using the unsafe Math.random(), Nano ID uses the crypto module in Node.js and the Web Crypto API in browsers. These modules use unpredictable hardware random generator. Uniformity, random % alphabet is a popular mistake to make when coding an ID generator. The distribution will not be even; there will be a lower chance for some symbols to appear compared to others. So, it will reduce the number of tries when brute-forcing. Nano ID uses a better algorithm and is tested for uniformity. -
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AWS IoT Device Defender Library
Client library for using AWS IoT Defender service on embedded devices
...This library has gone through code quality checks including verification that no function has a GNU Complexity score over 8, and checks against deviations from mandatory rules in the MISRA coding standard. Deviations from the MISRA C:2012 guidelines are documented under MISRA Deviations. This library has also undergone static code analysis using Coverity static analysis. -
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DeepSpec
A full-stack codebase for training and evaluating speculative decoding
...It then trains a draft model using configuration files for different algorithms and target model setups. The evaluation pipeline measures speculative decoding performance across benchmark tasks such as math, coding, instruction-following, and chat-style datasets. Overall, it is useful for researchers and engineers studying faster language model inference through speculative decoding methods. -
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Claude Engineer v3
Claude Engineer is an interactive command-line interface (CLI)
Claude Engineer v3 is a self-improving AI software development assistant built around Claude 3.5 Sonnet. It provides both a command-line interface and a modern web interface for coding-related workflows. The project is designed to let Claude identify missing capabilities, generate new tools, load them dynamically, and use them in later conversations. It includes real-time token tracking, conversation state management, tool usage indicators, and structured configuration options. The web interface supports image upload, Markdown rendering, syntax highlighting, and responsive design. ... -
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Duel Agents
CLI, SDK, and IDE plugins for Duel Agents
...Developers can also build on top of it with the SDK and OpenAI-compatible or Anthropic-compatible request patterns. It is useful for users who want a centralized model-routing layer across coding tools, scripts, and agent workflows. -
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EASY LLM CLI
An open-source AI agent that is compatible with multiple LLM models
...The project supports providers such as Gemini, OpenAI, and custom APIs that follow the OpenAI-compatible format. It is useful for developers who want a flexible AI assistant without being locked into one model vendor. The CLI can help with coding tasks, command workflows, file understanding, and project navigation. Its main value is bringing multi-provider AI assistance into a practical terminal environment. -
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pytudes
Python programs, usually short, of considerable difficulty
...It is useful for programmers who want to study elegant Python code while learning how experienced developers approach problem solving. Many examples emphasize clarity and compactness rather than framework-heavy engineering. pytudes is best understood as a learning library, a coding style reference, and a set of practical programming studies. -
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GitHubPoster
Make everything a GitHub svg poster and Skyline
...The project is built around loaders that import data and render it as visually recognizable contribution-style graphics. It is useful for people who want to display habits, reading, coding, health, language learning, or other quantified-life records in a GitHub-inspired format. It can be run locally from the command line and can also be automated through GitHub Actions. Its modular approach makes it possible for contributors to add new data sources over time. -
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deepsec
Deepsec is a security harness for finding vulnerabilities
deepsec is an agent-powered security harness for finding vulnerabilities in large codebases. It is designed to run on the user’s own infrastructure, using coding agents to perform deep, project-aware security review rather than only basic pattern matching. The tool initializes a project-specific security context, scans code in batches, processes findings, and can optionally revalidate results to reduce false positives. For large repositories, it supports parallel work across worker machines and can resume interrupted scans without repeating completed work. ... -
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Markplane
AI-native, markdown-first project management
...It eliminates the need for external SaaS tools by treating the repository itself as the source of truth for tasks, epics, and project state. The system is designed to integrate seamlessly with AI coding assistants by compressing project information into token-efficient summaries that models can understand and act on. It enables developers to manage their workflow entirely within their existing tools, avoiding context switching between code and project management platforms. The inclusion of an MCP server allows AI systems to query, update, and manage project data directly through natural language interactions. ... -
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clawchief
Turn your OpenClaw into a Chief of Staff
...The architecture likely includes task planning, delegation logic, and feedback loops that enable iterative refinement of outputs. It is particularly useful in scenarios where multiple agents must collaborate on interdependent tasks, such as coding, research, or automation pipelines. The system may also include monitoring tools to track agent performance and identify failures or inefficiencies. -
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Bulletproof React
A simple, scalable, and powerful architecture for building production
Bulletproof React is a best-practice template and architectural guideline for building scalable, maintainable, and production-ready React applications. It provides a well-structured project setup that emphasizes separation of concerns, modular design, and consistent coding standards. The project incorporates modern development patterns, including state management strategies, API integration, and testing frameworks, ensuring that applications are robust and easy to maintain. It also includes guidelines for organizing codebases, making it easier for teams to collaborate and scale projects over time. ... -
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claude-token-efficient
One CLAUDE.md file. Keeps Claude responses terse
claude-token-efficient is a lightweight configuration-based optimization project designed to reduce the verbosity and token usage of Claude-powered coding workflows through a structured instruction file. Instead of modifying model architecture or APIs, it uses a drop-in CLAUDE.md file that constrains how the model responds, enforcing concise output and eliminating unnecessary phrasing patterns. The approach focuses on removing redundant explanations, overly polite language, and repeated context, which are common contributors to excessive token consumption in AI-generated responses. ... -
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Hacking with Swift
The project source code for Hacking with iOS
HackingWithSwift is an extensive open-source repository that accompanies a popular tutorial series focused on teaching Swift programming for iOS development. It contains a large collection of example projects, exercises, and complete applications that guide learners from beginner to advanced levels. The repository is structured into different learning tracks, including UIKit-based development and modern SwiftUI approaches, allowing developers to explore multiple paradigms within the Apple... -
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Sandbox Agent
Run Coding Agents in Sandboxes
Sandbox Agent by Rivet is an experimental framework for running AI agents in controlled, isolated environments where they can safely execute code, interact with tools, and perform autonomous tasks without risking system integrity. It is designed to provide a secure sandbox that allows agents to test actions, manipulate files, and run commands while enforcing strict boundaries and monitoring capabilities. The project focuses on enabling more reliable and auditable agent behavior by separating... -
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Talk to Figma MCP
AI bridge enabling Cursor agents to read and modify Figma designs
cursor-talk-to-figma-mcp is an open source integration that connects AI coding agents with Figma through the Model Context Protocol (MCP). It allows AI tools such as Cursor or other compatible agents to directly communicate with Figma documents and interact with design elements programmatically. Through this integration, an AI assistant can read the structure of a design, retrieve information about nodes or selections, and perform modifications to the layout or content. cursor-talk-to-figma-mcp includes an MCP server and a Figma plugin that communicate through a WebSocket connection, enabling real-time interaction between the AI environment and the design canvas. ... -
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course.fast.ai
The fast.ai course notebooks
course22 is the official repository containing the notebooks, slides, and supporting materials for the 2022 edition of the fast.ai course Practical Deep Learning for Coders. The repository serves as the core educational resource for the course, providing learners with hands-on exercises and coding tutorials that accompany each lecture. The project emphasizes learning deep learning through experimentation rather than purely theoretical study, encouraging students to build models and analyze results directly in Jupyter notebooks. The repository includes lesson notebooks, slide presentations, spreadsheets, and supplementary materials that help students understand neural networks, computer vision, and natural language processing tasks. ... -
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Amazing-Python-Scripts
Curated collection of Amazing Python scripts
...The project includes scripts ranging from beginner-level utilities to more advanced applications involving machine learning, data processing, and system automation. Its goal is to provide developers with useful coding examples that can solve everyday problems, automate repetitive tasks, or serve as learning exercises. The repository encourages community contributions, allowing developers to add their own scripts and improve existing ones through pull requests. Examples include scripts for sentiment analysis, data scraping, web automation, log analysis, and interactive applications such as games or voice-controlled tools. ... -
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Jupyter Docker Stacks
Ready-to-run Docker images containing Jupyter applications
...Users can pull a particular stack image and launch a Jupyter server without worrying about installing Python, R, or complex dependencies themselves — everything needed is baked into the container. This makes the stacks especially useful for education, demos, collaborative coding, and CI/CD workflows where consistent environments are crucial, and it integrates smoothly with cloud platforms, JupyterHub deployments, and Binder for interactive sharing. -
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Unstract
No-code LLM Platform to launch APIs and ETL Pipelines
Unstract is a powerful open-source, no-code platform built to automate the extraction and structuring of unstructured documents using large language models and flexible workflows, enabling developers and data teams to turn messy files into organized JSON content without complex coding. It integrates a visual Prompt Studio environment where users can iteratively design extraction schemas, compare outputs from different models, and monitor costs and accuracy side by side, making it easier to refine prompts and extraction logic before deploying at scale. Unstract supports deploying structured extraction as REST API endpoints or embedding it into data engineering ETL pipelines, which allows it to plug directly into data warehouses, cloud storage, or downstream analytics systems. ...
