Key Facts
- Category
- Development
- Input Types
- textarea, select, checkbox
- Output Type
- json
- Sample Coverage
- 4
- API Ready
- Yes
Overview
The Docstring Extractor is a tool that automatically extracts and parses documentation comments from source code in JavaScript, TypeScript, Python, and Java. It supports JSDoc, Python docstrings, and JavaDoc formats, outputting structured JSON with metadata like function names, parameters, and return types for easy integration into documentation workflows.
When to Use
- •When generating API documentation from source code comments.
- •When auditing codebases to check for documentation completeness and consistency.
- •When migrating or standardizing documentation across different programming languages.
How It Works
- •Paste your source code into the input field or upload a file.
- •Select the programming language manually or use auto-detect for mixed code.
- •Optionally enable 'Include Full Documentation Text' to retain original comments.
- •Click extract to parse the documentation and receive a JSON output with extracted metadata.
Use Cases
Examples
1. Extract JSDoc from a JavaScript Module
Frontend Developer- Background
- A developer has a JavaScript file with JSDoc comments describing functions for a web application.
- Problem
- Manually copying documentation for API reference is tedious and prone to errors.
- How to Use
- Paste the JavaScript code into the tool and select 'JavaScript' as the language hint.
- Outcome
- A JSON object with extracted function names, @param tags, @return descriptions, and line numbers for quick reference.
2. Parse Python Docstrings for Backend API
- Background
- A Python project contains functions with triple-quoted docstrings outlining Args, Returns, and Raises sections.
- Problem
- Need to generate a structured API reference without manually parsing each docstring.
- How to Use
- Input the Python source code and let the tool auto-detect the language to extract documentation.
- Outcome
- JSON output with parsed parameters, return types, and exception details, ready for documentation generation.
3. Analyze JavaDoc in Java Classes
- Background
- A Java codebase has classes with JavaDoc comments that include @param, @return, and @throws tags.
- Problem
- Assessing documentation coverage across methods to identify gaps in the project.
- How to Use
- Upload the Java source files and extract metadata to review documented symbols.
- Outcome
- Insights into documented methods, parameters, and exceptions, with visibility and completeness metrics in JSON format.
Try with Samples
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FAQ
What programming languages are supported?
JavaScript, TypeScript, Python, and Java.
What types of documentation comments does it extract?
JSDoc for JavaScript/TypeScript, triple-quoted docstrings for Python, and JavaDoc for Java.
Can it handle code with multiple languages?
Yes, use auto-detect or specify the language hint for accurate parsing.
What information is included in the JSON output?
Function/class names, descriptions, parameters, return values, exceptions, examples, line numbers, and visibility.
Is the output customizable?
You can choose to include the full original documentation text via a checkbox option.