Ship a clean logging system for your app in 10 minutes
Beginner
10 min
English
Generate a production-ready, structured logging module with log levels and request tracing you can drop straight into your codebase.
Steps
- Open ChatGPT or Claude in a new chat.
- Paste the prompt template below into the message box.
- Replace {language}, {framework}, and {logging_library} with your stack (e.g. Python, FastAPI, structlog).
- Send the prompt and read the generated module top to bottom.
- Copy the logger module file into your project (e.g. utils/logger.py or lib/logger.ts).
- Add the initialization snippet to one route or handler in your app.
- Run your app locally and trigger one request; confirm a structured JSON log line appears in your console or log file.
- If a field is missing (e.g. request_id), ask the AI to add it and paste the updated snippet back in.
Prompts to Use
You are a senior backend engineer. Build a logging module for {language} using the {framework} framework and the {logging_library} library. Requirements: structured JSON output, log levels (debug, info, warn, error), log rotation or file output option controlled by an env var, and a correlation/request ID injected per request so every log line for one request shares an ID. Output: 1) a single {language} module file with clear inline comments, under 80 lines, no dependencies beyond {logging_library}; 2) a short snippet showing how to initialize the logger and attach the request ID in one route handler. Do not include unrelated features like metrics or tracing.
Tools Used
Some tool links may earn AiA a commission — never affecting rankings.