---
license: other
language:
- code
pretty_name: KExercises
size_categories:
- 100M<n<1B
task_categories:
- text-generation
---
# Dataset Summary
KStack is the bigest collection of permissvly licesed Kotlin code.
![banner](https://huggingface.co/datasets/JetBrains/KStack/resolve/main/banner.png)
## Columns description
The dataset contains following columns: 

 - `size` - size of file in bytes  
 - `content` - text (content) of the file after PII extraction  
 - `repo_id` - GitHub id of the repository  
 - `path` - path to a file  
 - `owner` - repo owner on GitHub  
 - `name` - repo name on GitHub  
 - `commit_sha` - hash of the commit from which the revision of the file is taken  
 - `stars` - Number of stars in the repo on the moment of collection  
 - `forks` - Number of forks in the repo on the moment of collection  
 - `issues` - Number of issues in the repo on the moment of collection  
 - `is_fork` - Flag if the repo is a fork or not by GitHub definition  
 - `main_language` - Main language of the repo defined by GitHub  
 - `languages_distribution` - JSON with the distribution of the files by size in bytes in the repo  

## Comparison with the Stack v2
In the table below one can find the comparsion of the between Kotlin part of the Stack v2 and KStack:
|              | Files | Repositories | Lines | Tokens |
|--------------|:-----:|:------------:|:-----:|:------:|
| The Stack v2 | 2M    | 109457       | 162M  | 1.7B   |
| Kstack       | 4M    | 168902       | 292M  | 3.1B   |

# Dataset Creation

## Collection procedure
We collected repositories from GitHub with the main language being Kotlin, as well as repositories with Kotlin files that have received 10 or more stars (as of February 2024). Additionally, we gathered repositories with Kotlin files from Stack v1.2. Kotlin files were identified using go-enry, and include files with extensions such as .kt, .kts, and .gradle.kts. It is estimated that we have collected 97% of available Kotlin repositories as of February 2024.

## Initial filtering
We conducted full deduplication, using the hash of file content, as well as near deduplication using the same method as in Stack v1.2. We then aggregated the files from one near-deduplicated cluster into a single file from that cluster.

## Detecting permissive licenses
We filtered permissive repositories based on the licenses detected by GitHub, and using go-license-detector if GitHub did not have license information available. 
The list of permissive licenses used in dataset could be found here.

## Personal and Sensitive Information
We used star-pii model to filter out personal info.

## Opt-out
If you want your data to be removed from dataset, or have any other questions, please reach out to Sergey Titov<sergey.titov@jetbrains.com>