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---
dataset_info:
features:
- name: code
dtype: string
- name: docstring
dtype: string
- name: func_name
dtype: string
- name: language
dtype: string
- name: repo
dtype: string
- name: path
dtype: string
- name: url
dtype: string
- name: license
dtype: string
splits:
- name: train
num_bytes: 1319884423
num_examples: 858128
- name: validation
num_bytes: 20659872
num_examples: 13376
- name: test
num_bytes: 25958039
num_examples: 18051
download_size: 387807991
dataset_size: 1366502334
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
license: apache-2.0
task_categories:
- translation
language:
- en
tags:
- code
---
# Python Code Dataset
## Dataset Description
This dataset contains Python functions with their documentation comments extracted from GitHub repositories.
### Features
- `code`: The Python function code
- `docstring`: Documentation comment for the function
- `func_name`: Function name
- `language`: Programming language (always "Python")
- `repo`: Source repository name
- `path`: File path within the repository
- `url`: GitHub URL to the source file
- `license`: License of the source code
## Dataset Structure
The dataset contains the following splits:
- train: 858128 examples
- validation: 13376 examples
- test: 18051 examples
## Usage
```python
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("USERNAME/DATASET_NAME")
# Access the training split
train_data = dataset["train"]
# Example: Print the first sample
print(train_data[0])
```
## Source
This dataset was created by scraping Python code from GitHub repositories. Each function includes its documentation comment and license information.
## License
This dataset contains code from various repositories with different licenses. Each sample includes its original license information in the `license` field. |