metadata

dataset_info:
  features:
    - name: function_name
      dtype: string
    - name: docstring
      dtype: string
    - name: masked_code
      dtype: string
    - name: implementation
      dtype: string
    - name: start_line
      dtype: int32
    - name: end_line
      dtype: int32
    - name: file_content
      dtype: string
  splits:
    - name: train
      num_bytes: 420616564
      num_examples: 2760
  download_size: 64655948
  dataset_size: 420616564
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Stack-Smol-Docstrings

This dataset contains Python functions extracted from the-stack-smol, filtered for high-quality docstrings and implementations. Each sample includes the function's docstring, implementation, and a masked version of the code where the function is replaced with a comment.

The dataset is designed for code completion tasks where a model needs to restore a function that has been replaced with a comment. The model is provided with:

The full file context with the function replaced by a comment
The docstring of the function
The function name

The model's task is to generate code that replaces the comment with a proper implementation of the function based on the docstring and surrounding context.

Dataset Structure

Each sample contains:

function_name: Name of the function
docstring: The function's docstring
masked_code: The full file with the function replaced by a comment
implementation: The original function implementation
start_line: The starting line number of the function in the original file
end_line: The ending line number of the function in the original file
file_content: The full original file content

Quality Filtering

Functions are filtered based on:

Docstring quality (length, structure, descriptiveness)
Implementation quality (no SQL strings, reasonable number of variables, sufficient complexity)