README.md

---
license: apache-2.0
language:
- en
tags:
- rust
- code-search
- text-to-code
- code-to-text
- source-code
- systems
- backend
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
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: 376169830
    num_examples: 381521
  - name: validation
    num_bytes: 6478931
    num_examples: 6333
  - name: test
    num_bytes: 10118426
    num_examples: 8868
  download_size: 116295779
  dataset_size: 392767187
---

# Rust CodeSearch Dataset (Shuu12121/rust-treesitter-dedupe-filtered-datasetsV2)

## Dataset Description
This dataset contains Rust functions and methods paired with their documentation comments, extracted from open-source Rust repositories on GitHub.
It is formatted similarly to the CodeSearchNet challenge dataset.

Each entry includes:
- `code`: The source code of a rust function or method.
- `docstring`: The docstring or Javadoc associated with the function/method.
- `func_name`: The name of the function/method.
- `language`: The programming language (always "rust").
- `repo`: The GitHub repository from which the code was sourced (e.g., "owner/repo").
- `path`: The file path within the repository where the function/method is located.
- `url`: A direct URL to the function/method's source file on GitHub (approximated to master/main branch).
- `license`: The SPDX identifier of the license governing the source repository (e.g., "MIT", "Apache-2.0").
Additional metrics if available (from Lizard tool):
- `ccn`: Cyclomatic Complexity Number.
- `params`: Number of parameters of the function/method.
- `nloc`: Non-commenting lines of code.
- `token_count`: Number of tokens in the function/method.

## Dataset Structure
The dataset is divided into the following splits:

- `train`: 381,521 examples
- `validation`: 6,333 examples
- `test`: 8,868 examples

## Data Collection
The data was collected by:
1. Identifying popular and relevant Rust repositories on GitHub.
2. Cloning these repositories.
3. Parsing Rust files (`.rs`) using tree-sitter to extract functions/methods and their docstrings/Javadoc.
4. Filtering functions/methods based on code length and presence of a non-empty docstring/Javadoc.
5. Using the `lizard` tool to calculate code metrics (CCN, NLOC, params).
6. Storing the extracted data in JSONL format, including repository and license information.
7. Splitting the data by repository to ensure no data leakage between train, validation, and test sets.

## Intended Use
This dataset can be used for tasks such as:
- Training and evaluating models for code search (natural language to code).
- Code summarization / docstring generation (code to natural language).
- Studies on Rust code practices and documentation habits.

## Licensing
The code examples within this dataset are sourced from repositories with permissive licenses (typically MIT, Apache-2.0, BSD).
Each sample includes its original license information in the `license` field.
The dataset compilation itself is provided under a permissive license (e.g., MIT or CC-BY-SA-4.0),
but users should respect the original licenses of the underlying code.

## Example Usage
```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Shuu12121/rust-treesitter-dedupe-filtered-datasetsV2")

# Access a split (e.g., train)
train_data = dataset["train"]

# Print the first example
print(train_data[0])
```