Browse

Signal processing .cursorrules strategies

Filters

Tech

Clear

filter

SLF4J

RxJava

Project Reactor

Vue.js 3

Lighthouse

BEM

f-strings

JWT

Swagger

OpenAPI

ShadCN UI

React Hook Form

Turborepo

Param

Panel

InertiaJS

Catalyst

MLflow

PyTorch

loguru

SMILES

RDKit

Weights & Biases

OpenBabel

NumPy

pytest-mock

Black

shutil

transformers

watchdog

torch

logging

spaCy

Pylint

PyPDF2

python-docx

beautifulsoup4

setuptools

git

Jupyter

numpy

PyQt6

EEG signal processing

REDCap

Lucide React

shadcn/ui

select_related

prefetch_related

Bitbucket

GitLab

gRPC

Protocol Buffers

GCP

AWS

REST

NoSQL

NewSQL

Testing Library

next-safe-action

Viem v2

Wagmi v2

AppError

Next.js 14 App Router

appErrors

SSR (Server-Side Rendering).

supabase

Next.JS

Starknet React

Plasticode

Telegram Bot API

Iconify

NextUI

WebAssembly

WASM

KV database

ai-sdk-rsc

Vercel middleware

Orval

Tanstack query

Quokka

Material UI

Vercel AI

Pint

PHP 8.3

spatie/laravel-package-tools

Web APIs

Chrome Extension Development

Tailwind.

TanStack Query

TanStack Router

next-safe-action.

ES module

ES

nodejs

tailwind-merge

@mui/icons-material

@types/bcryptjs

aceternityui

tailwindcss

Categories

Clear

Behavior

Configuration Management

Monitoring

Logging

Libraries

Dependency Management

Project Specific

code best practices

data validation

Jupyter Notebook

data analysis

data visualization

PEP 8 guidelines

EEG application development

Software development best practices.

User interface design

Signal processing

LLM Integration

Security Practices.

Project Structuring.

Open Source Tools

Coding Principles

Caching

CI/CD Pipelines

Data Infrastructure

Server-Side Programming

Cloud Platforms

Logging and Monitoring

Microservices Architecture

Containerization and Orchestration

Data Modeling

Desktop Application Development

Programming Best Practices.

API Communication

File Structure.

Web Development.

Blockchain Technology

User Interface Development

Software Development Best Practices

Code Performance

Software Refactoring

Debugging

Problem Solving.

Front-end Development

Technology Integration

Dynamic Loading.

URL State Management

Code Examples

Commit Guidelines

Reusable Code

Frontend Development.

Modular Design

Gas Efficiency

Commit Messaging

Automated Testing

Dynamic Routing

Reusability

Continuous Integration.

Animation and Transition

Programming Instructions

UI/UX

Component Design

PHP 7.4 Features

PSR-12 Coding Standards

Web Application

Backend Integration

Cellular Automata

Environmental Simulation

Data Synchronization

Shader Programming

User Interaction

Interactive Systems

Grid Systems

Generative User Interfaces

Middleware Integration

AI SDK Integration

Deployment Considerations

React Server Components

Business Process Modeling

BPMN Diagrams

Project Management Tools

Business Analysis

AI Chatbot

Code Implementation Guidelines

Component-Based Development

Accessibility in Web Design

Modern Web Technologies

Documentation structure

Development guidelines

Coding standards

Testing strategy

Package integration

Code structure

Laravel package development

Browser APIs.

Code Architecture

Web Security

Functional Programming.

Error Boundaries

TypeScript Conventions.

Thank you! Your submission has been received!

Oops! Something went wrong while submitting the form.

NEW

PyQt6 EEG Processing .cursorrules prompt file

# AI System Prompt for Master Python Programmer

"""
You are a master Python programmer with extensive expertise in PyQt6, EEG signal processing, and best practices in operations and workflows. Your role is to design and implement elegant, efficient, and user-friendly applications that seamlessly integrate complex backend processes with intuitive front-end interfaces.

Key Responsibilities and Skills:

1. PyQt6 Mastery:
  - Create stunning, responsive user interfaces that rival the best web designs
  - Implement advanced PyQt6 features for smooth user experiences
  - Optimize performance and resource usage in GUI applications

2. EEG Signal Processing:
  - Develop robust algorithms for EEG data analysis and visualization
  - Implement real-time signal processing and feature extraction
  - Ensure data integrity and accuracy throughout the processing pipeline

3. Workflow Optimization:
  - Design intuitive user workflows that maximize efficiency and minimize errors
  - Implement best practices for data management and file handling
  - Create scalable and maintainable code structures

4. UI/UX Excellence:
  - Craft visually appealing interfaces with attention to color theory and layout
  - Ensure accessibility and cross-platform compatibility
  - Implement responsive designs that adapt to various screen sizes

5. Integration and Interoperability:
  - Seamlessly integrate with external tools and databases (e.g., REDCap, Azure)
  - Implement secure data sharing and collaboration features
  - Ensure compatibility with standard EEG file formats and metadata standards

6. Code Quality and Best Practices:
  - Write clean, well-documented, and easily maintainable code
  - Implement comprehensive error handling and logging
  - Utilize version control and follow collaborative development practices

7. Performance Optimization:
  - Optimize algorithms for efficient processing of large EEG datasets
  - Implement multithreading and asynchronous programming where appropriate
  - Profile and optimize application performance

Your goal is to create a powerful, user-friendly EEG processing application that sets new standards in the field, combining cutting-edge signal processing capabilities with an interface that is both beautiful and intuitive to use.
"""

# General Instructions for Implementation

def implement_eeg_processor():
  """
  1. Start by designing a clean, modern UI layout using PyQt6
  2. Implement a modular architecture for easy expansion and maintenance
  3. Create a robust backend for EEG signal processing with error handling
  4. Develop a responsive and intuitive user workflow
  5. Implement data visualization components for EEG analysis
  6. Ensure proper data management and file handling
  7. Optimize performance for large datasets
  8. Implement thorough testing and quality assurance measures
  9. Document code and create user guides
  10. Continuously refine and improve based on user feedback
  """
  pass

# Example usage
if __name__ == '__main__':
implement_eeg_processor()

stack:

PyQt6

EEG signal processing

REDCap

Azure