Backend Development

This project provides automation scripts and workflows tailored for the @findhow packages, adapted from the original Deno automation repository. It aims to deliver consistent and efficient automation solutions for the @findhow ecosystem.

Comprehensive guidelines for Elixir engineers, covering best practices, tools, and workflows for building robust and scalable applications.

Comprehensive guidelines and best practices for developing scalable and maintainable Elixir applications using Phoenix framework and Docker. Includes coding standards, preferred libraries, performance optimization, and testing strategies.

Guidelines and best practices for using ES Modules in Node.js, focusing on modularity, performance, and security.

A comprehensive guide to building scalable backend systems using Go, covering best practices, performance optimization, and modern architectural patterns.

Comprehensive guide for building secure, scalable, and maintainable REST APIs using Go's net/http package and the new ServeMux introduced in Go 1.22. Follow best practices for RESTful API design, error handling, input validation, and concurrency.

A comprehensive guide to setting up a Go project with HTMX, including best practices, folder structure, and additional instructions for efficient development.

Best practices and guidelines for integrating HTMX with Go and Fiber, including project structure, coding standards, and performance optimization.

A comprehensive guide to setting up HTMX with best practices, folder structure, and additional instructions for optimal performance and maintainability.

A comprehensive guide to integrating HTMX with Flask, including best practices, folder structure, and additional instructions for building modern web applications.

Best practices and guidelines for integrating HTMX with Django to build dynamic web applications efficiently.

A comprehensive guide for Java developers using Spring Boot and JPA, focusing on best practices, SOLID principles, and OWASP security standards.

A comprehensive guide for building scalable, serverless applications using Knative, Istio, Typesense, and GPU acceleration. This project focuses on creating a robust, efficient, and secure AI-powered search application with a responsive HTMX-based frontend.

Comprehensive guide and best practices for developing Laravel packages using PHP 8.3, focusing on code quality, developer experience, and seamless integration.

Comprehensive guide and best practices for building modern web applications using the TALL stack: Laravel, Livewire, Alpine.js, and Tailwind CSS. This guide emphasizes Laravel and PHP best practices, performance optimization, and security measures.

A robust backend system built with Node.js and MongoDB for managing user pools, entries, picks, and scoring in a competitive gaming environment.

A comprehensive full-stack application built with Node.js, MongoDB, JWT for authentication, Express.js for the backend, and React.js for the frontend. This project includes a robust admin panel, secure authentication, and efficient data management.

Best practices and guidelines for developing scalable APIs using Python and FastAPI.

Comprehensive guidelines for developing scalable, maintainable, and high-performance APIs using Python and FastAPI. Includes best practices for coding standards, error handling, performance optimization, and dependency management.

Comprehensive best practices and guidelines for developing robust and maintainable Python 3.12 applications using FastAPI, Pydantic, SQLAlchemy, and other essential libraries.

Comprehensive guide on best practices for developing scalable and maintainable web applications using Python and Django.

Comprehensive guide on best practices for developing scalable and efficient APIs using FastAPI, focusing on functional programming, modularization, and performance optimization.

A comprehensive guide to building scalable APIs with Python and FastAPI, including best practices, project structure, and performance optimization techniques.

A comprehensive guide on integrating JSON data handling in Python using Flask, including examples and environment setup.

Comprehensive guide and best practices for TypeScript development using the NestJS framework, focusing on clean code, design patterns, and efficient testing strategies.

A comprehensive guide for developing WordPress plugins using PHP, Guzzle for HTTP requests, and Gutenberg for block editor integration. Follow best practices for coding standards, type hinting, and functional programming paradigms.

PressThat is a macOS system tray application designed to streamline the process of managing and viewing draft posts on your WordPress website. It offers a seamless connection to your WordPress site, allowing you to quickly access and manage your content directly from your desktop.

Comprehensive guidelines and best practices for Python-based LLM (Large Language Models) and ML (Machine Learning) workflows. This document covers coding standards, technology stack, modular design, code quality, ML/AI-specific guidelines, performance optimization, and API development with FastAPI.

This rule set provides guidelines and best practices for building Netlify projects and sites. It covers various aspects such as general rules, different types of compute systems (serverless, edge, background, and scheduled functions), Netlify Blobs for storage, Netlify Image CDN for image optimization, environment variables management, file - based uploads, and procedures for creating, initializing, and linking sites.

This set of rules provides guidelines and best practices for building Convex projects. It covers database schema design, function registration, query and mutation operations, and includes real - world examples like a chat - app backend. Rules detail function syntax, validator usage, API design, and more, ensuring proper development and efficient use of Convex features.

This rule is about implementing an 'environmental region grid' for a z80 cellular automata simulation. It includes defining region structures, creating a region grid, mapping soup cells to regions, modifying the simulation loop, implementing parameter - specific logic, enhancing the WASM interface, developing a user interface, creating a region visualization system, implementing data synchronization, and updating shader code. This system adds complexity and control, allowing users to explore large - scale influences on cellular automata behavior.

This set of rules is for Java backend development. It includes project configuration, AI developer profile, technical stack details, and comprehensive development guidelines based on 'Effective Java'. Also, it covers best - practices in concurrency, functional programming, and data - oriented programming.

This set of rules provides comprehensive guidelines for Drupal 11 development, covering code style, naming conventions, API usage, theming, performance, security, and documentation. It emphasizes using Drupal 11 APIs, Symfony services, and following Drupal's coding standards and best - practices to ensure functional, secure, and efficient development.

These rules cover general guidelines, best practices, testing, performance optimization, development workflow, documentation, dependencies, and environment configuration for Solidity smart contract development using Foundry. They emphasize code quality, security, and efficiency.

This set of rules is for ABP .NET backend development. It covers code style, naming conventions, C# and .NET usage, syntax and formatting, error handling, API design, performance optimization, key conventions, testing, security, and API documentation. It emphasizes following ABP Framework's recommended practices and integrating with related technologies like Entity Framework Core and AutoMapper.

This set of rules provides best practices for FastAPI development. It includes using Pydantic models for schemas, implementing dependency injection, utilizing async/await, following a specific folder structure, using type hints, validating input, handling background tasks, CORS, and security, adhering to PEP 8, and conducting comprehensive tests.

This document outlines best practices for LangChain application development, covering code organization, common patterns, performance, security, testing, common pitfalls, and tooling. It aims to ensure code quality, maintainability, performance, security, and overall project success.

This rule guide covers various aspects of Spring development, including code organization, design patterns, performance optimization, security, testing, and tooling. It provides best practices, anti - patterns, and practical tips to help developers build high - quality Spring applications.

This document outlines best practices for CUDA development, covering code organization, common patterns, performance optimization, security, testing, and more, based on NVIDIA's guide with detailed recommendations.

This rule set provides comprehensive guidelines for Streamlit application development, covering code organization, design patterns, performance optimization, security, testing, and tooling. It helps developers build maintainable, high - performance, and secure Streamlit applications.

This document offers guidelines for AWS CLI use in resource development and management. It covers code organization, design patterns, performance, security, testing, and more, aiming to enhance code quality, security, and operational efficiency.

This document provides best practices for using Terraform with Cloudflare. It covers code organization, patterns, performance, security, testing, and more. It advises on structuring directories, naming files, handling modules, and avoiding anti - patterns. It also offers guidance on state management, error handling, and using recommended tools and CI/CD integration.

This document offers coding standards, best - practices, and architectural guidelines for Python backend dev with Bottle. It covers code org, design patterns, performance, security, testing, common pitfalls, and tooling. Adhering to these can enhance code quality, maintainability, and security of Bottle apps.

This guide details best practices for Supabase development. It covers code organization, common patterns, performance, security, testing, and tooling. It also warns about common pitfalls and provides advice on database workflow design and additional best - practices for building robust, scalable, and secure applications.

This document details best practices for Firebase - based app development. It covers code organization, common patterns, performance, security, testing, pitfalls, and tooling. Suggestions include modular code, using design patterns, optimizing performance, enforcing security rules, and using proper testing techniques. Following these can create robust, scalable, and secure apps.

This document provides comprehensive best - practices for Java development. It covers code organization, common patterns, performance, security, testing, pitfalls, and tooling. Following these guidelines helps write clean, efficient, and secure Java code, and can be adjusted according to project needs and team preferences.

These rules cover various aspects of LangChain JS development. It includes monitoring with LangSmith, building stateful agents with LangGraph, maintaining code quality through testing and linting, and using LCEL for chain composition. Also, it provides guidance on code organization, design patterns, performance optimization, security, testing, and tooling.

These rules cover various aspects of PyQt development. They include consistent importing, adhering to naming conventions, separating GUI and business logic, using Qt Designer, and more. Also, they involve code organization, handling performance, security, testing, and avoiding common pitfalls. Specific recommendations like using QThread for heavy - process are provided.

This document details best practices for GCP app and infrastructure development. It covers code organization, common patterns, performance, security, testing, common pitfalls, and tooling. For example, it suggests standard module structures, design patterns, caching, and input validation, aiming to help developers build robust and scalable projects.

This set of rules provides best practices for Django ORM development. It covers code organization, common patterns, performance optimization, security, testing, and tooling. It emphasizes proper directory structure, naming conventions, and avoiding anti - patterns. It also details techniques for performance, security, and how to use various tools for development, testing, and deployment.

This document provides best practices for Express.js app development. It covers code organization, design patterns, performance optimization, security, testing, and common pitfalls. Topics include directory structure, error handling, caching, input validation, and various testing strategies to ensure high - quality, secure, and performant applications.

This document details best - practices for AWS infrastructure development with Terraform. It covers code organization, patterns, performance, security, testing, common pitfalls, and tooling. For example, it suggests proper directory and file naming, using reusable modules, and following security measures like IAM least - privilege. Adhering to these guidelines ensures maintainable, secure, and efficient code.

These rules guide Sentry integration in applications. It includes connecting to Sentry, setting up source code management and source maps. It also covers code organization, design patterns, performance optimization, security practices, testing approaches, and tooling. Adhering to these rules can enhance application reliability, performance, and security.

This document offers comprehensive best - practices for the ELK stack. It covers code organization, common patterns, performance, security, testing, pitfalls, and tooling. For example, it details directory structures, naming conventions, and design patterns. It also provides optimization techniques, security measures, and testing approaches to build a robust and secure ELK environment.

These rules cover AWS ECS development, including general principles like treating infrastructure as code and ensuring idempotency. It details code organization, common patterns, performance optimization, security, testing, and tooling. For example, it suggests using Terraform for infrastructure, microservices architecture, and automated CI/CD pipelines.

This guide provides comprehensive rules for Tornado backend development. It covers code organization, design patterns, performance optimization, security, testing, and tooling. Topics include directory structure, naming conventions, asynchronous operations, input validation, and more. It also offers best practices and common pitfalls to avoid in Tornado projects.

This document details best practices for the Hugging Face Transformers library. It covers code organization, common patterns, performance, security, testing, and more. It emphasizes single - model file policy, offers optimization techniques, and warns against common pitfalls like prompt injection and incorrect tokenization.

This document provides best practices for LlamaIndex - JS projects. It covers code organization (directory structure, naming conventions), common patterns, anti - patterns, performance optimization, security, testing, and tooling. Following these guidelines helps build robust, efficient, and secure AI applications.

This document provides best practices for ASP.NET Core development. It covers code organization, design patterns, performance optimization, security, testing, and tooling. It emphasizes using dependency injection, following naming conventions, and handling common issues like security vulnerabilities and performance bottlenecks. Adhering to these guidelines ensures code clarity, maintainability, and security.

This document offers guidance on LlamaIndex app development. It covers code organization, common patterns, performance, security, testing, and more. It details directory structures, naming conventions, optimization techniques, and best practices for input validation, authentication, and deployment. Also warns about common pitfalls and suggests tools and environments for development.

This guide details best practices for Apollo GraphQL API development. It covers schema design, security, performance optimization, code organization, testing, and more. It also provides tips on avoiding common pitfalls, using tools, and following additional practices like versioning and documentation.

This document details best practices for using the `notion-api` library. It covers code organization, design patterns, performance optimization, security, testing, and more. Follow these guidelines to create maintainable, performant, secure, and testable Notion integrations, and avoid common pitfalls and errors.

This document details best practices for tinygrad library development. It covers general principles like readability and TDD, code organization, design patterns, performance optimization, security, testing, and tooling. Adhering to these guidelines ensures code readability, maintainability, and optimal performance in tinygrad projects.

This rule offers best - practices for Databricks application development. It covers code organization, common patterns, performance optimization, security, testing, and tooling. For example, it details directory structure, design patterns, and security measures. Following these can help build maintainable, efficient, and secure applications.

These rules cover best practices for CrewAI development. It includes general coding practices, code organization, design patterns, anti - patterns, performance, security, testing, and tooling. It also details how to use LLMs with CrewAI, such as configuration and available models, aiming to ensure efficient, secure, and maintainable development.

This document provides guidelines for Kubernetes development and operations. It covers code organization, design patterns, common task approaches, anti - patterns, performance, security, testing, and tooling. It emphasizes clarity, maintainability, security, and performance in the Kubernetes ecosystem.

This document provides best practices and coding standards for developing applications with the `openai` library. It covers code organization, common patterns, performance, security, testing, pitfalls, and tooling. Following these guidelines can lead to more maintainable, performant, and secure code.

This rule provides comprehensive guidelines for TensorFlow development. It covers code organization, design patterns, state management, error handling, performance optimization, security, testing, and tooling. For example, it recommends modular design, using Keras layers, and validating input data. It also offers tips on GPU utilization, memory management, and deployment best practices.

This guide offers best practices for Railway app development and deployment. It covers code organization, patterns, performance, security, testing, and tooling. It details directory structure, naming conventions, and recommends using environment variables. It also provides strategies to avoid anti - patterns, optimize performance, and ensure security and proper testing.

These rules cover various aspects of Amazon EC2 development. It includes general principles like treating infrastructure as code and security - first. Also details on code organization, design patterns, anti - patterns, performance optimization, security, testing, and tooling. It helps developers build reliable, efficient, and secure EC2 - based applications.

This document provides best practices for PySide app development. It covers general guidelines like following PEP 8, code organization, common patterns, performance, security, testing, and tooling. It emphasizes modularity, resource management, and security, with advice on avoiding common pitfalls and using recommended tools for development, testing, and deployment.

This document details best practices for Numba library. It covers code organization (directory, file naming, module), common patterns, performance optimization, security, testing, pitfalls, and tooling. For example, use @njit for performance, avoid object mode, and follow strict file - naming rules. It helps developers write efficient, maintainable, and secure code.

This document details best practices for Sanic framework app development. It covers code organization, design patterns, performance optimization, security, testing, and more. Following these guidelines helps build maintainable, performant, and secure apps. Also warns against common pitfalls and provides tooling advice.