---
language:
- code
- en
multilinguality:
- multiprogramming languages
task_categories:
- text-generation
license: mit
dataset_info:
  features:
  - name: identifier
    dtype: string
  - name: return_type
    dtype: string
  - name: repo
    dtype: string
  - name: path
    dtype: string
  - name: language
    dtype: string
  - name: code
    dtype: string
  - name: code_tokens
    dtype: string
  - name: original_docstring
    dtype: string
  - name: comment
    dtype: string
  - name: docstring_tokens
    dtype: string
  - name: docstring
    dtype: string
  - name: original_string
    dtype: string
pretty_name: The Vault Function
viewer: false
---



## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Statistics](#dataset-statistics)
- [Usage](#usage)
- [Additional Information](#additional-information)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)


## Dataset Description

- **Repository:** [FSoft-AI4Code/TheVault](https://github.com/FSoft-AI4Code/TheVault)
- **Paper:** [The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation](https://arxiv.org/abs/2305.06156)
- **Contact:** support.ailab@fpt.com
- **Website:** https://www.fpt-aicenter.com/ai-residency/

<p align="center">
  <img src="https://raw.githubusercontent.com/FSoft-AI4Code/TheVault/main/assets/the-vault-4-logo-png.png" width="300px" alt="logo">
</p>

<div align="center">
  
# The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation
</div>


## Dataset Summary
The Vault dataset is a comprehensive, large-scale, multilingual parallel dataset that features high-quality code-text pairs derived from The Stack, the largest permissively-licensed source code dataset.

We provide The Vault which contains code snippets from 10 popular programming languages such as Java, JavaScript, Python, Ruby, Rust, Golang, C#, C++, C, and PHP. This dataset provides multiple code-snippet levels, metadata, and 11 docstring styles for enhanced usability and versatility.

## Supported Tasks
The Vault can be used for pretraining LLMs or downstream code-text interaction tasks. A number of tasks related to code understanding and geneartion can be constructed using The Vault such as *code summarization*, *text-to-code generation* and *code search*.

## Languages
The natural language text (docstring) is in English.

10 programming languages are supported in The Vault: `Python`, `Java`, `JavaScript`, `PHP`, `C`, `C#`, `C++`, `Go`, `Ruby`, `Rust`

## Dataset Structure
### Data Instances
```
{

    "hexsha": "5c47f0b4c173a8fd03e4e633d9b3dd8211e67ad0",
    "repo": "neumanna94/beepboop",
    "path": "js/scripts.js",
    "license": [
        "MIT"
    ],
    "language": "JavaScript",
    "identifier": "beepBoopSelector",
    "code": "function beepBoopSelector(inputString, bbFunction){\n  if(bbFunction==1){\n    return beepBoop(inputString);\n  } else if(bbFunction==2){\n    return beepBoop2(inputString);\n  } else if(bbFunction==3){\n    return beepBoop3(inputString);\n  } else {\n  }\n}",
    "code_tokens": [
        "function",
        "beepBoopSelector",
        "(",
        "inputString",
        ",",
        "bbFunction",
        ")",
        "{",
        "if",
        "(",
        "bbFunction",
        "==",
        "1",
        ")",
        "{",
        "return",
        "beepBoop",
        "(",
        "inputString",
        ")",
        ";",
        "}",
        "else",
        "if",
        "(",
        "bbFunction",
        "==",
        "2",
        ")",
        "{",
        "return",
        "beepBoop2",
        "(",
        "inputString",
        ")",
        ";",
        "}",
        "else",
        "if",
        "(",
        "bbFunction",
        "==",
        "3",
        ")",
        "{",
        "return",
        "beepBoop3",
        "(",
        "inputString",
        ")",
        ";",
        "}",
        "else",
        "{",
        "}",
        "}"
    ],
}

```
### Data Fields

Data fields for function level:
- **hexsha** (string): the unique git hash of file
- **repo** (string): the owner/repo
- **path** (string): the full path to the original file
- **license** (list): licenses in the repo
- **language** (string): the programming language
- **identifier** (string): the function or method name
- **code** (string): the part of the original that is code
- **code_tokens** (list): tokenized version of `code`
- **original_comment** (string): original text of comment ,
- **comment** (string): clean version of comment,
- **comment_tokens** (list): tokenized version of `comment`,
- **start_point** (int): start position of `original_comment` in `code`,
- **end_point** (int): end position of `original_comment` in `code`,
- **prev_context** (dict): block of code before `original_comment`,
- **next_context** (dict):  block of code after `original_comment`


### Data Splits

In this repo, the inline level data is not split, and contain in only train set.

## Dataset Statistics


| Languages  | Number of inline comments  |
|:-----------|---------------------------:|
|Python      |   14,013,238               |
|Java        |   17,062,277               |
|JavaScript  |    1,438,110               |
|PHP         |    5,873,744               |
|C           |    6,778,239               |
|C#          |    6,274,389               |
|C++         |   10,343,650               |
|Go          |    4,390,342               |
|Ruby        |      767,563               |
|Rust        |    2,063,784               |
|TOTAL       | **69,005,336**             |

## Usage
You can load The Vault dataset using datasets library: ```pip install datasets```

```python
from datasets import load_dataset

# Load full function level dataset (40M samples)
dataset = load_dataset("Fsoft-AIC/the-vault-inline")


# specific language (e.g. Python) 
dataset = load_dataset("Fsoft-AIC/the-vault-inline", languages=['Python'])

# dataset streaming
data = load_dataset("Fsoft-AIC/the-vault-inline", streaming= True)
for sample in iter(data['train']): 
    print(sample)
```

A back up dataset can be downloaded in azure storage. See [Download The Vault from Azure blob storage](https://github.com/FSoft-AI4Code/TheVault#download-via-link).

## Additional information
### Licensing Information
MIT License

### Citation Information

```
@article{manh2023vault,
  title={The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation},
  author={Manh, Dung Nguyen and Hai, Nam Le and Dau, Anh TV and Nguyen, Anh Minh and Nghiem, Khanh and Guo, Jin and Bui, Nghi DQ},
  journal={arXiv preprint arXiv:2305.06156},
  year={2023}
}
```

### Contributions
This dataset is developed by [FSOFT AI4Code team](https://github.com/FSoft-AI4Code).