Automated Docstring Generation For Python Funct... (2026)

Analyzing surrounding code, such as class attributes or imported types, to provide the model with necessary context.

Using the Abstract Syntax Tree (AST) to identify function signatures and body implementation. Automated Docstring Generation for Python Funct...

In Python, docstrings serve as the primary source of truth for function behavior, parameters, and return types. Beyond mere commentary, they are programmatically accessible via the __doc__ attribute and power essential tools like Sphinx, Pydoc, and integrated development environment (IDE) tooltips. However, the "documentation debt" remains high in many projects, as developers often prioritize feature delivery over descriptive prose. Evolution of Automation Techniques Analyzing surrounding code, such as class attributes or

This paper examines the evolution and implementation of automated docstring generation for Python functions, focusing on how Large Language Models (LLMs) have transformed documentation from a manual burden into an integrated part of the development lifecycle. The Role of Docstrings in Python The Role of Docstrings in Python Despite significant

Despite significant progress, automated generation faces critical hurdles. remains the primary risk, where a model may confidently describe a side effect or exception that does not exist in the code. Furthermore, "Stale Documentation" occurs when code is updated but the automated pipeline is not re-triggered, leading to a mismatch between docstrings and implementation. Conclusion

Tools like Pyment attempted to "translate" between different docstring formats (Google, NumPy, Epytext) but struggled to interpret the actual logic of the code.

Constructing instructions that specify the desired format (e.g., "Generate a NumPy-style docstring for the following Python function").