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"""CodeSearchNet corpus Files: proxy dataset for semantic code search""" |
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import json |
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import os |
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import datasets |
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_CITATION = """\ |
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@article{husain2019codesearchnet, |
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title={{CodeSearchNet} challenge: Evaluating the state of semantic code search}, |
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author={Husain, Hamel and Wu, Ho-Hsiang and Gazit, Tiferet and Allamanis, Miltiadis and Brockschmidt, Marc}, |
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journal={arXiv preprint arXiv:1909.09436}, |
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year={2019} |
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} |
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""" |
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_DESCRIPTION = """\ |
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CodeSearchNet corpus contains about 6 million functions from open-source code \ |
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spanning six programming languages (Go, Java, JavaScript, PHP, Python, and Ruby). \ |
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The CodeSearchNet Corpus also contains automatically generated query-like \ |
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natural language for 2 million functions, obtained from mechanically scraping \ |
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and preprocessing associated function documentation. |
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""" |
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_HOMEPAGE = "https://github.com/github/CodeSearchNet" |
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_LICENSE = "Various" |
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_DATA_DIR_URL = "data" |
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_AVAILABLE_LANGUAGES = ["python", "java", "javascript", "go", "ruby", "php"] |
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_URLs = {language: f"{language}.jsonl" for language in _AVAILABLE_LANGUAGES} |
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_URLs["all"] = _URLs.copy() |
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class CodeSearchNet(datasets.GeneratorBasedBuilder): |
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""" "Extended CodeSearchNet corpus: proxy dataset for semantic code search.""" |
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VERSION = datasets.Version("1.0.0", "Add Extended CodeSearchNet corpus dataset") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="all", |
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version=VERSION, |
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description="All available languages: Java, Go, Javascript, Python, PHP, Ruby", |
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), |
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datasets.BuilderConfig( |
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name="java", |
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version=VERSION, |
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description="Java language", |
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), |
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datasets.BuilderConfig( |
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name="go", |
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version=VERSION, |
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description="Go language", |
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), |
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datasets.BuilderConfig( |
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name="python", |
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version=VERSION, |
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description="Pyhton language", |
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), |
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datasets.BuilderConfig( |
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name="javascript", |
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version=VERSION, |
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description="Javascript language", |
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), |
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datasets.BuilderConfig( |
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name="ruby", |
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version=VERSION, |
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description="Ruby language", |
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), |
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datasets.BuilderConfig( |
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name="php", |
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version=VERSION, |
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description="PHP language", |
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), |
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] |
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DEFAULT_CONFIG_NAME = "all" |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"repository_name": datasets.Value("string"), |
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"file_path": datasets.Value("string"), |
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"language": datasets.Value("string"), |
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"url": datasets.Value("string"), |
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"contents": datasets.Value("string") |
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} |
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), |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators. |
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Note: The original data is stored in S3, and follows this unusual directory structure: |
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``` |
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. |
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βββ <language_name> # e.g. python |
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β βββ final |
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β βββ jsonl |
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β βββ test |
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β β βββ <language_name>_test_0.jsonl.gz |
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β βββ train |
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β β βββ <language_name>_train_0.jsonl.gz |
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β β βββ <language_name>_train_1.jsonl.gz |
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β β βββ ... |
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β β βββ <language_name>_train_n.jsonl.gz |
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β βββ valid |
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β βββ <language_name>_valid_0.jsonl.gz |
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βββ <language_name>_dedupe_definitions_v2.pkl |
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βββ <language_name>_licenses.pkl |
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``` |
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""" |
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data_urls = _URLs[self.config.name] |
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if isinstance(data_urls, str): |
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data_urls = {self.config.name: data_urls} |
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split2dirs = { |
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split_name: [os.path.join(_DATA_DIR_URL, split_name, path) for path in data_urls.values()] |
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for split_name in ["train", "test", "valid"] |
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} |
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downloaded_files = dl_manager.download_and_extract(split2dirs) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepaths": downloaded_files["train"], |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"filepaths": downloaded_files["test"], |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"filepaths": downloaded_files["valid"], |
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}, |
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), |
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] |
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def _generate_examples(self, filepaths): |
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"""Yields the examples by iterating through the available jsonl files.""" |
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for file_id_, filepath in enumerate(filepaths): |
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with open(filepath, encoding="utf-8") as f: |
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for row_id_, row in enumerate(f): |
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id_ = f"{file_id_}_{row_id_}" |
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data = json.loads(row) |
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yield id_, { |
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"repository_name": data["repository_name"], |
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"file_path": data["file_path"], |
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"language": data["language"], |
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"url": data["url"], |
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"contents": data["contents"], |
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} |