Datasets:

rehaidib
/

PyFuncAST-Lex

language:
  - en
tags:
  - software-engineering
  - code-analysis
  - refactoring
  - AST
  - lexical-features
  - Python
  - static-analysis
task_categories:
  - feature-extraction
pretty_name: Python Function's code feature
size_categories:
  - 1M<n<10M
license: cc-by-4.0

📊 Python Function-Level AST and Lexical Features Dataset

📝 Dataset Summary

This dataset integrates function-level static analysis data from Python repositories.
It merges three data sources:

Lizard Cyclomatic Analysis: provides complexity, NLOC, and basic function metadata.
AST Extracted Features: includes detailed abstract syntax tree information such as token counts, parameters, variable extraction, and function bodies.
Lexical Features: captures lexical and structural features of each function (e.g., class structure, modifiers, incoming/outgoing calls, and statement types) and presents it in natural language.

The resulting Dataset represents each Python function as a unified row combining complexity metrics, lexical information, and AST structure — enabling advanced research in:

Code comprehension
Automated refactoring
Software quality analysis
Function-level code search
Maintainability prediction
ML model training for software engineering tasks

🧠 Intended Uses

Feature extraction for code comprehension and maintainability modeling.
Supervised learning for:
- Maintainability prediction (regression / ordinal classification).
- Refactoring-need ranking (learning-to-rank).
Benchmarking code-representation learning or graph-based refactoring tools.
Downstream tasks such as clone detection, defect prediction, and code search.

📂 Dataset Structure

Each row corresponds to one Python function identified across open-source repositories.

Columns

Column name	Description
`project_name`	Repository name
`class_name`	Class name containing the function (if applicable)
`class_modifiers`	Access modifiers of the class
`class_implements`	Interfaces implemented
`class_extends`	Class inheritance
`function_name`	Function name
`function_body`	Raw function body code
`cyclomatic_complexity`	Cyclomatic complexity measure
`NLOC`	Number of lines of code
`num_parameter`	Number of function parameters
`num_token`	Number of tokens
`num_variable`	Number of variables detected in function
`start_line` / `end_line`	Start and end line of the function in the file
`function_index`	Function index in AST parsing
`function_params`	Parameter names
`function_variable`	Variable names extracted
`function_return_type`	Return type (if inferred)
`function_body_line_type`	Mapping of statement types inside the function (e.g., Assign, If, Return)
`function_num_functions`	Number of functions declared inside
`function_num_lines`	Number of lines of function (lexical)
`outgoing_function_count` / `outgoing_function_names`	Number and names of functions called inside this function
`incoming_function_count` / `incoming_function_names`	Number and names of functions calling this function
`lexical_representation`	Present the code features as natural language.

⚙️ Data Sources

Static analysis performed on public Python repositories cloned from GitHub that apply the following characteristics (python language projects, commits > 500, and contributors > 10).
Function-level analysis uses:
- lizard for cyclomatic complexity.
- Python AST (https://docs.python.org/3/library/ast.html) parsing for structural features.
- Lexical presentation driven by structural and 15 extract code features.

🧪 Dataset Creation

Collection

Clone open-source Python repositories.
Run Lizard static analysis to generate base metrics.
Parse source files to extract AST and 15 code features.
Convert code features to natural language using rule-based code.
Merge the three sources

💡 How to Load

    from datasets import load_dataset
    data = load_dataset("rehaidib/PyFuncAST-Lex", split="train")

or manually:

    import pandas as pd
    df = pd.read_parquet("PyFuncAST-Lex.parquet")

Citation

If you use this dataset, please cite:

  @dataset{PyFuncAST-Lex,
    title        = {PyFuncAST-Lex: Python Function-Level AST and Lexical Features Dataset},
    author       = {Reem Al-Ehaidib},
    year         = {2025},
    month        = {11},
    publisher    = {Hugging Face Datasets},
    version      = {1.0},
    url          = {https://huggingface.co/datasets/rehaidib/pyfunc_code_features}
  }