Datasets:
Tasks:
Text Generation
Formats:
json
Sub-tasks:
language-modeling
Languages:
code
Size:
100K - 1M
License:
annotations_creators: | |
- crowdsourced | |
license: other | |
language_creators: | |
- crowdsourced | |
language: | |
- code | |
task_categories: | |
- text-generation | |
tags: | |
- code, kotlin, native Android development, curated | |
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 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 totaling ~542MB of data. | |
The [uncurated](https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint) dataset was created from the public GitHub dataset on Google BiqQuery. | |
### How to use it | |
To download the full dataset: | |
```python | |
from datasets import load_dataset | |
dataset = load_dataset('mvasiliniuc/iva-kotlin-codeint-clean', split='train') | |
``` | |
Other details are available for each field: | |
```python | |
from datasets import load_dataset | |
dataset = load_dataset('mvasiliniuc/iva-kotlin-codeint-clean', split='train') | |
print(dataset[723]) | |
#OUTPUT: | |
{ | |
"repo_name":"oboenikui/UnivCoopFeliCaReader", | |
"path":"app/src/main/java/com/oboenikui/campusfelica/ScannerActivity.kt", | |
"copies":"1", | |
"size":"5635", | |
"content":"....public override fun onPause() {\n if (this.isFinishing) {\n adapter.disableForegroundDispatch(this)\n }\n super.onPause()\n }\n\n override ...}\n", | |
"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 | |
} | |
``` | |
## 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":4052, | |
"apache-2.0":114641, | |
"artistic-2.0":159, | |
"bsd-2-clause":474, | |
"bsd-3-clause":4571, | |
"cc0-1.0":198, | |
"epl-1.0":991, | |
"gpl-2.0":5625, | |
"gpl-3.0":25102, | |
"isc":436, | |
"lgpl-2.1":146, | |
"lgpl-3.0":3406, | |
"mit":39399, | |
"mpl-2.0":1819, | |
"unlicense":824 | |
} | |
``` | |
## Dataset Statistics | |
```json | |
{ | |
"Total size": "~261 MB", | |
"Number of files": 201843, | |
"Number of files under 500 bytes": 3697, | |
"Average file size in bytes": 5205, | |
} | |
``` | |
## Curation Process | |
* Removal of duplication files based on file hash. | |
* Removal of file templates. File containing the following: [${PACKAGE_NAME}, ${NAME}, ${VIEWHOLDER_CLASS}, ${ITEM_CLASS}] | |
* Removal of the files containing the following words in the first 10 lines: `generated, auto-generated", "autogenerated", "automatically generated` | |
* Removal of the files containing the following words in the first 10 lines with a probability of 0.7: `test", "unit test", "config", "XCTest", "JUnit` | |
* Removal of file with the rate of alphanumeric characters below 0.3 of the file. | |
* Removal of near duplication based MinHash and Jaccard similarity. | |
* Removal of files with mean line length above 100. | |
* Removal of files without mention of keywords with a probability of 0.7: [`"fun ", "val ", "var ", "if ", "else ", "while ", "for ", "return ", "class ", "data ", "struct ", "interface ", "when ", "catch "`] | |
* Removal of files that use the assignment operator `=` less than 3 times. | |
* Removal of files with the ratio between the number of characters and number of tokens after tokenization lower than 1.5. | |
Curation process is a derivation of the one used in CodeParrot project: https://huggingface.co/codeparrot | |
## Data Splits | |
The dataset only contains a train split which is separated into train and valid which can be found here: | |
* Clean Version Train: https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean-train | |
* 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. | |