Datasets:
annotations_creators:
- crowdsourced
license: other
language_creators:
- crowdsourced
language:
- code
task_categories:
- text-generation
tags:
- code, swift, native iOS development, curated
size_categories:
- 100K<n<1M
source_datasets: []
pretty_name: iva-swift-codeint-clean
task_ids:
- language-modeling
IVA Swift GitHub Code Dataset
Dataset Description
This is the curated IVA Swift dataset extracted from GitHub. It contains curated Swift files gathered with the purpose to train a code generation model.
The dataset consists of 383380 swift code files from GitHub totaling ~542MB of data. The uncurated dataset was created from the public GitHub dataset on Google BiqQuery.
How to use it
To download the full dataset:
from datasets import load_dataset
dataset = load_dataset('mvasiliniuc/iva-swift-codeint-clean', split='train')
from datasets import load_dataset
dataset = load_dataset('mvasiliniuc/iva-swift-codeint-clean', split='train')
print(dataset[723])
#OUTPUT:
{
"repo_name":"jdkelley/Udacity-OnTheMap-ExampleApps",
"path":"TheMovieManager-v2/TheMovieManager/BorderedButton.swift",
"copies":"2",
"size":"2649",
"content":"...let phoneBorderedButtonExtraPadding: CGFloat = 14.0\n \n var backingColor: UIColor? = nil\n var highlightedBackingColor: UIColor? = nil\n \n // MARK: Initialization\n}",
"license":"mit",
"hash":"db1587fd117e9a835f58cf8203d8bf05",
"line_mean":29.1136363636,
"line_max":87,
"alpha_frac":0.6700641752,
"ratio":5.298,
"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 Swift Programming Language. |
has_few_assignments | boolean | True if file uses symbol '=' less than minimum times. |
Instance
{
"repo_name":"...",
"path":".../BorderedButton.swift",
"copies":"2",
"size":"2649",
"content":"...",
"license":"mit",
"hash":"db1587fd117e9a835f58cf8203d8bf05",
"line_mean":29.1136363636,
"line_max":87,
"alpha_frac":0.6700641752,
"ratio":5.298,
"autogenerated":false,
"config_or_test":false,
"has_no_keywords":false,
"has_few_assignments":false
}
Languages
The dataset contains only Swift files.
{
"Swift": [".swift"]
}
Licenses
Each entry in the dataset contains the associated license. The following is a list of licenses involved and their occurrences.
{
"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
{
"Total size": "~542 MB",
"Number of files": 383380,
"Number of files under 500 bytes": 3680,
"Average file size in bytes": 5942,
}
Curation Process
- Removal of duplication files based on file hash.
- Removal of file templates. File containing the following:
___FILENAME___, ___PACKAGENAME___, ___FILEBASENAME___, ___FILEHEADER___, ___VARIABLE
- 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:
struct ", "class ", "for ", "while ", "enum ", "func ", "typealias ", "var ", "let ", "protocol ", "public ", "private ", "internal ", "import "
- 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-swift-codeint-clean-train
- Clean Version Valid: https://huggingface.co/datasets/mvasiliniuc/iva-swift-codeint-clean-valid
Considerations for Using the Data
The dataset consists of source code from a wide range of repositories. As such they can potentially include harmful or biased code as well as sensitive information like passwords or usernames.