Browse

RQ .cursorrules prompt files

A research question (RQ) guides a study or investigation, ensuring focused and relevant data collection to generate meaningful insights and conclusions.

Filters

All

React

Tailwind CSS

Filters

Tech

Clear

React

Tailwind CSS

Node.js

Tailwind

Shadcn UI

JavaScript

Python

Radix UI

Next.js

Vite

JSX

WebP

Zod

Docker

Next.js App Router

Supabase

CSS

PostgreSQL

Redis

FastAPI

HTML

Pydantic

pytest

Git

Jest

react-hook-form

Solidity

Vercel

SQLAlchemy

Tailwind Aria

Suspense

SvelteKit

Vue.js

GitHub Actions

Celery

ESLint

PHP

TailwindCSS

Pinia

PEP 8

asyncpg

TypeScript

SQL

Playwright

Svelte

Prettier

Radix

DaisyUI

Vitest

JSDoc

JSON

ARIA

Drizzle ORM

Vue Router

VueUse

Astro

Svelte 5

tRPC

Expo

CORS

aiomysql

GitLab CI

Django

Typescript

scikit-learn

pandas

GitHub

RabbitMQ

Java

WebP.

tanStackQuery

Phoenix LiveView

Ecto

File System Watcher

Plug

Finch

Gettext

Phoenix

Elixir

Jason

Phoenix LiveDashboard

Sobelow

ExCoveralls

DNS Cluster

ExUnit

Release Please

Swoosh

Credo

LeftHook

ES6

npm

Laravel

styled-components

RESTful API

Shadcn

Markdown

OpenZeppelin

Slither

Hardhat

Mythril

Clear

Syntax

Programming Rules

Code Libraries

Documentation Practices

Component-based Architecture

Payment Integration

AI Integration

Frontend Frameworks

User Flow Management

API Design

Payment Processing.

Strategic Planning

database implementation

CI/CD.

best practices

testing strategies

Code style

code structure

concurrency

parallelism

containerization

module usage

data import

environment setup

file handling

coding examples

Security Awareness

Performance Optimization.

Vite

VueUse

Tailwind

Best Practices.

Vue.js

DaisyUI

Component Naming

Descriptive Naming

File Structure

API Requests

Error handling

Project structure

AI-friendly practices

Dependency management

Configuration management

Modular design

Code style consistency

CSS Frameworks.

UI Libraries

Deployment Strategies

Type Hints

Testing and Integration

Security Practices

Mobile UI Development

UI Testing

App Deployment

Software Deployment

full stack development

code readability

performant coding

secure coding

software development best practices

AI programming assistant

JavaScript Libraries.

Programming Principles

API best practices.

Functional programming

Scalable API development

Performance optimization

Asynchronous programming

File Path Usage

Workflow Efficiency

Go programming

API development

Middleware implementation

Go concurrency

Input validation

Maintainability

Security best practices

Three.js Integration

Frontend development

State management

Modern JavaScript features

Software architecture

Full-stack development

Web development best practices

Code clarity

Programming Conventions

AI

Culinary

Web Applications

Project Guidelines

Cross-platform Development

Mobile Applications

Workflows

GitHub

Scripts

json file

package.json

dependencies

scripts

devDependencies

Thank you! Your submission has been received!

Oops! Something went wrong while submitting the form.

NEW

Python FastAPI Guide .cursorrules prompt file

You are an expert in Python, FastAPI, microservices architecture, and serverless environments.

Advanced Principles

Design services to be stateless; leverage external storage and caches (e.g., Redis) for state persistence.
Implement API gateways and reverse proxies (e.g., NGINX, Traefik) for handling traffic to microservices.
Use circuit breakers and retries for resilient service communication.
Favor serverless deployment for reduced infrastructure overhead in scalable environments.
Use asynchronous workers (e.g., Celery, RQ) for handling background tasks efficiently.
Microservices and API Gateway Integration
Integrate FastAPI services with API Gateway solutions like Kong or AWS API Gateway.
Use API Gateway for rate limiting, request transformation, and security filtering.
Design APIs with clear separation of concerns to align with microservices principles.
Implement inter-service communication using message brokers (e.g., RabbitMQ, Kafka) for event-driven architectures.
Serverless and Cloud-Native Patterns
Optimize FastAPI apps for serverless environments (e.g., AWS Lambda, Azure Functions) by minimizing cold start times.
Package FastAPI applications using lightweight containers or as a standalone binary for deployment in serverless setups.
Use managed services (e.g., AWS DynamoDB, Azure Cosmos DB) for scaling databases without operational overhead.
Implement automatic scaling with serverless functions to handle variable loads effectively.
Advanced Middleware and Security
Implement custom middleware for detailed logging, tracing, and monitoring of API requests.
Use OpenTelemetry or similar libraries for distributed tracing in microservices architectures.
Apply security best practices: OAuth2 for secure API access, rate limiting, and DDoS protection.
Use security headers (e.g., CORS, CSP) and implement content validation using tools like OWASP Zap.
Optimizing for Performance and Scalability
Leverage FastAPI’s async capabilities for handling large volumes of simultaneous connections efficiently.
Optimize backend services for high throughput and low latency; use databases optimized for read-heavy workloads (e.g., Elasticsearch).
Use caching layers (e.g., Redis, Memcached) to reduce load on primary databases and improve API response times.
Apply load balancing and service mesh technologies (e.g., Istio, Linkerd) for better service-to-service communication and fault tolerance.
Monitoring and Logging
Use Prometheus and Grafana for monitoring FastAPI applications and setting up alerts.
Implement structured logging for better log analysis and observability.
Integrate with centralized logging systems (e.g., ELK Stack, AWS CloudWatch) for aggregated logging and monitoring.
Key Conventions

Follow microservices principles for building scalable and maintainable services.
Optimize FastAPI applications for serverless and cloud-native deployments.
Apply advanced security, monitoring, and optimization techniques to ensure robust, performant APIs.

Refer to FastAPI, microservices, and serverless documentation for best practices and advanced usage patterns.

stack:

Python

FastAPI

microservices architecture

Redis

NGINX