---
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: 2029823478
    num_examples: 764189
  - name: validation
    num_bytes: 158726194
    num_examples: 125016
  - name: test
    num_bytes: 75240901
    num_examples: 75350
  download_size: 411968838
  dataset_size: 2263790573
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---

# Java Code Dataset

## Dataset Description

This dataset contains Java functions with their documentation comments extracted from GitHub repositories.

### Features

- `code`: The Java function code
- `docstring`: Documentation comment for the function
- `func_name`: Function name
- `language`: Programming language (always "Java")
- `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: 764189 examples
- validation: 125016 examples
- test: 75350 examples

## Usage

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Shuu12121/java-codesearch-dataset-open")

# Access the training split
train_data = dataset["train"]

# Example: Print the first sample
print(train_data[0])
```

## Source

This dataset was created by scraping Java 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.