Browse

B+ tree .cursorrules prompt files

A B+ tree is a self-balancing tree data structure that maintains sorted data and allows efficient insertion, deletion, and search operations, optimizing database and file systems performance.

Filters

All

React

Tailwind CSS

Filters

Tech

Clear

React

Tailwind CSS

Node.js

Tailwind

JavaScript

Shadcn UI

Next.js

Radix UI

Python

WebP

Zod

JSX

Vite

CSS

Supabase

HTML

Jest

Next.js App Router

PostgreSQL

Docker

Redis

Pydantic

Tailwind Aria

TailwindCSS

FastAPI

Git

ESLint

pytest

react-hook-form

Solidity

Vercel

JSDoc

GitHub Actions

Typescript

Prettier

Suspense

Vitest

ARIA

Zustand

React Testing Library

Celery

Radix

Shadcn

SQLAlchemy

PHP

SvelteKit

JSON

Vue.js

Pinia

MongoDB

tRPC

Clerk

Expo

PEP 8

SSR

Prisma

dotenv

GitLab CI

SQLite

SQL

Playwright

tanStackQuery

DaisyUI

Laravel

RESTful API

Drizzle ORM

VueUse

Express

asyncpg

TypeScript

scikit-learn

pandas

GitHub

RabbitMQ

Rust

Java

GraphQL

Svelte

Elixir

ES6

Nuxt 3

styled-components

Vue Router

Astro

Svelte 5

Markdown

OpenZeppelin

Drizzle

Stripe

Flexbox

CORS

Lighthouse

JWT

Swagger

aiomysql

Ruff

Langchain

Django

matplotlib

Clear

Web Development

Frontend Development

Code Style

Programming

Naming Conventions

Testing

State Management

Backend Development

Code Optimization

Software Engineering

Accessibility

Programming Best Practices

Responsive Design

Code Structure

Version Control

Database Management

UI Design

API Development

Code Quality

TypeScript Best Practices

Authentication

TypeScript

Security

Syntax and Formatting

JavaScript

Best Practices

Data Fetching

Internationalization

Coding Best Practices

React

performance optimization

Performance Optimization

Software Development

Coding Standards

API Integration

Object-Oriented Programming

Code Review

Testing and Debugging

Image Optimization

SEO

Game Development

Code Readability

Deployment

Clean Code

User Interface

JavaScript Frameworks

UI Components

UI and Styling

Declarative Programming

Code Modularity

Security Best Practices

Web Application Development

Error Handling

UI Development

JavaScript Libraries

Design Patterns

TypeScript Guidelines

Server-Side Rendering

TypeScript Usage

Programming Guidelines

Modularization

Code Documentation

error handling

functional programming

Coding Style

Scalability

Form Validation

SEO Optimization

Smart Contracts

Dependency Injection

Test-Driven Development

Static Site Generation

Routing

File Organization

Code Organization

Coding Guidelines

Testing and Quality Assurance

Technical Writing

API Design

Node.js

Full Stack Development

Python development

CI/CD

UI/UX design

Functional Programming

Documentation

Python

Validation

Performance

Code Formatting

Python programming

Code Maintainability

Build and Deployment

Decentralized Applications

Artificial Intelligence

Project Management

Web Vitals

Server Components

Blockchain

Coding Practices

Show

5

rules

Thank you! Your submission has been received!

Oops! Something went wrong while submitting the form.

NEW

Python Containerization .cursorrules prompt file

Python and Database Algorithms Expert Guide

You are an expert in Python, database algorithms, and containerization technologies.

Code Style and Structure

Write clean, Pythonic code with type hints and docstrings.
Follow PEP 8 guidelines for code formatting.
Use functional programming patterns where appropriate; prefer composition over inheritance.
Implement modular design to separate concerns (e.g., storage engine, query processor, transaction manager).
Use descriptive variable names (e.g., is_transaction_active, has_index).
Structure your project with clear separation: src/, tests/, docs/, etc.

Naming Conventions

Use snake_case for function and variable names.
Use PascalCase for class names.
Use UPPER_CASE for constants.

Python Best Practices

Leverage Python's built-in data structures (lists, dicts, sets) effectively.
Use list comprehensions and generator expressions for concise, readable code.
Implement context managers (with statement) for resource management.
Utilize collections module for specialized data structures.

Database Algorithm Implementation

Implement B-tree or B+ tree for efficient indexing.
Use WAL (Write-Ahead Logging) for ACID compliance.
Implement MVCC (Multi-Version Concurrency Control) for transaction isolation.
Create a simple query parser and execution engine.
Develop a basic storage engine (e.g., append-only file, LSM tree).

Performance Optimization

Use cProfile for performance profiling.
Implement connection pooling for database connections.
Use appropriate data structures for different operations (e.g., hash tables for quick lookups).
Implement query optimization techniques (e.g., join order optimization).

Testing

Write unit tests for individual components (e.g., B-tree operations, WAL recovery).
Implement integration tests for database operations.
Use property-based testing for complex algorithms.
Employ fuzzing techniques to test edge cases and improve robustness.