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🔎 API Error Parser

API Error Parser is a simple Streamlit tool that helps developers and QA engineers understand API error responses faster.

Paste an HTTP status code and an API error payload, and the tool will:

  • Explain the meaning of the error
  • Extract common error fields
  • Suggest likely causes
  • Provide debugging steps

Built with Python + Streamlit.


🚀 Demo

Try the tool online:

https://api-error-parser.streamlit.app


❓ Why This Tool Exists

When an API fails, the response body is often too raw or too technical for quick debugging.

This tool turns common API errors into a more human-readable explanation, which is useful for:

  • QA engineers
  • Backend developers
  • Frontend developers
  • Automation engineers
  • Anyone debugging REST API responses

Example use cases

  • Understand what a 500 Internal Server Error may really mean
  • Parse a 422 validation_failed response body
  • Diagnose 401 unauthorized or token expiration issues
  • Investigate 429 rate limit exceeded errors

✨ Features

  • Parse HTTP status codes such as 400, 401, 403, 404, 422, 429, 500, 502, 503, and 504
  • Extract common fields like error, message, details, code, and request_id
  • Detect likely categories such as:
    • Authentication
    • Authorization
    • Validation
    • Timeout
    • Rate limit
    • Resource not found
  • Provide practical debugging suggestions

🖥 Run Locally

Install dependencies

pip install -r requirements.txt

Run the Streamlit app

streamlit run app.py

Then open your browser:

http://localhost:8501

📁 Project Structure

logcat-error-filter
│
├── app.py
├── requirements.txt
└── README.md

🔍 Search Keywords

This project targets common developer searches such as:

  • API error parser

  • HTTP error parser

  • API error response analyzer

  • understand API error message

  • HTTP 500 error meaning

  • HTTP 401 unauthorized parser

  • API validation error checker

🔗 Related Tools

You may also be interested in:

These tools help developers debug logs more efficiently.

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Parse API error responses online. Understand HTTP errors, validation failures, authentication errors, and debugging steps.

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