task_categories:text-generation task_ids:language-modeling annotations_creators:crowdsourced language_creators:crowdsourced size_categories:100K<n<1M language:code license:other code, kotlin, native Android development, curated, training region:us
---
annotations_creators: 
- crowdsourced
license: other
language_creators:
- crowdsourced
language:
- code
task_categories:
- text-generation
tags:
- code, kotlin, native Android development, curated, training
size_categories:
- 100K<n<1M
source_datasets: []
pretty_name: iva-kotlin-codeint-clean
task_ids:
- language-modeling
---

# IVA Kotlin GitHub Code Dataset

## Dataset Description

This is the curated train split of IVA Kotlin dataset extracted from GitHub. 
It contains curated Kotlin files gathered with the purpose to train a code generation model.

The dataset consists of 383380 Kotlin code files from GitHub.
[Here is the unsliced curated dataset](https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean) and [here is the raw dataset](https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint).

### How to use it

To download the full dataset:

```python
from datasets import load_dataset
dataset = load_dataset('mvasiliniuc/iva-kotlin-codeint-clean-train', split='train'))
```


## Data Structure

### Data Fields

|Field|Type|Description|
|---|---|---|
|repo_name|string|name of the GitHub repository|
|path|string|path of the file in GitHub repository|
|copies|string|number of occurrences in dataset|
|content|string|content of source file|
|size|string|size of the source file in bytes|
|license|string|license of GitHub repository|
|hash|string|Hash of content field.|
|line_mean|number|Mean line length of the content.
|line_max|number|Max line length of the content.
|alpha_frac|number|Fraction between mean and max line length of content.
|ratio|number|Character/token ratio of the file with tokenizer.
|autogenerated|boolean|True if the content is autogenerated by looking for keywords in the first few lines of the file.
|config_or_test|boolean|True if the content is a configuration file or a unit test.
|has_no_keywords|boolean|True if a file has none of the keywords for Kotlin Programming Language.
|has_few_assignments|boolean|True if file uses symbol '=' less than `minimum` times.

### Instance

```json
{
   "repo_name":"oboenikui/UnivCoopFeliCaReader",
   "path":"app/src/main/java/com/oboenikui/campusfelica/ScannerActivity.kt",
   "copies":"1",
   "size":"5635",
   "content":"....",
   "license":"apache-2.0",
   "hash":"e88cfd99346cbef640fc540aac3bf20b",
   "line_mean":37.8620689655,
   "line_max":199,
   "alpha_frac":0.5724933452,
   "ratio":5.0222816399,
   "autogenerated":false,
   "config_or_test":false,
   "has_no_keywords":false,
   "has_few_assignments":false
}
```

## Languages

The dataset contains only Kotlin files.

```json
{
    "Kotlin": [".kt"]
}
```

## Licenses

Each entry in the dataset contains the associated license. The following is a list of licenses involved and their occurrences.

```json
{
   "agpl-3.0":3209,
   "apache-2.0":90782,
   "artistic-2.0":130,
   "bsd-2-clause":380,
   "bsd-3-clause":3584,
   "cc0-1.0":155,
   "epl-1.0":792,
   "gpl-2.0":4432,
   "gpl-3.0":19816,
   "isc":345,
   "lgpl-2.1":118,
   "lgpl-3.0":2689,
   "mit":31470,
   "mpl-2.0":1444,
   "unlicense":654
}
```

## Dataset Statistics

```json
{
    "Total size": "~207 MB",
    "Number of files": 160000,
    "Number of files under 500 bytes": 2957,
    "Average file size in bytes": 5199,
}
```

## Curation Process

See [the unsliced curated dataset](https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean) for mode details.

## Data Splits

The dataset only contains a train split focused only on training data. For validation and unspliced versions, please check the following links:
* Clean Version Unsliced: https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean
* Clean Version Valid: https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean-valid

# Considerations for Using the Data

The dataset comprises source code from various repositories, potentially containing harmful or biased code, 
along with sensitive information such as passwords or usernames.
