Browse

database implementation .cursorrules strategies

Filters

Tech

Clear

RBAC

obsidian

Discord.py

Loguru

VCRPy

Pytest

CliRunner

Pytest-Recording

Clear

web development

QA best practices

code review

security reviews

Database migrations

Electricity system visualization

Open source software

Australian projects

Async programming

Python development guidelines

Scheduler and task runner

.NET Development

Test Driven Development

Automation Testing

Testing Best Practices

Web Testing

Commit Message Conventions

Code Writing Guidelines

Development Best Practices

Dependencies Management

Python Conventions

Database Modeling

Authentication Security

Python Full-Stack Development.

Framework Development

Asynchronous Processing

Svelte

Overview

Scalable Architecture

Development Environment

Deployment Strategy

Digital Transactions

React Native

Event Management

AI Algorithms

Documentation and Best Practices

Real-Time Features

Maintenance and Support

Firebase Integration

Project Setup

Social Features

Internal Linking

Blogging

External Linking

Page Speed

Schema Markup

Core Web Vitals

Mobile Optimization

User Engagement

Content Optimization

URL Structure

Real-time Graphics

Visual Experience Tools

Full-Stack Development

Error Handling and Validation

Code Style and Structure

Front-End Development

Web Development Strategies

Server Side Rendering

Server-side Logic

Code Patterns

Turborepo

Radix UI

Server-side Development

PostgreSQL

Prisma

Shadcn UI

Forms and Validation

Next.js Best Practices

Web Development Guide

Type Checking

JavaScript Best Practices

Testing Guidelines

APIs

Scheduling

Convex

Cron Jobs

HTTP Requests

CSS Frameworks

Exporting Components

File Upload

Error Logging

Module Exportation

Code Formatting and Style

Package Management

Testing and Validation

Workspace Structure

UI Optimization

Performance Testing

Game Mechanics

Terminal Games

Ruby Programming

Software Development Guidelines

Beginner Programming

Programming Education

Code Feedback

Coding Basics

Learning to Code

Problem Solving

AI Workflows

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.