Datasets:
code_search_net

	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.

	# Lint as: python3
	"""CodeSearchNet corpus: proxy dataset for semantic code search"""

	# TODO: add licensing info in the examples
	# TODO: log richer informations (especially while extracting the jsonl.gz files)
	# TODO: enable custom configs; such as: "java+python"
	# TODO: enable fetching examples with a given license, eg: "java_MIT"


	import json
	import os

	import datasets


	_CITATION = """\
	@article{husain2019codesearchnet,
	title={{CodeSearchNet} challenge: Evaluating the state of semantic code search},
	author={Husain, Hamel and Wu, Ho-Hsiang and Gazit, Tiferet and Allamanis, Miltiadis and Brockschmidt, Marc},
	journal={arXiv preprint arXiv:1909.09436},
	year={2019}
	}
	"""

	_DESCRIPTION = """\
	CodeSearchNet corpus contains about 6 million functions from open-source code \
	spanning six programming languages (Go, Java, JavaScript, PHP, Python, and Ruby). \
	The CodeSearchNet Corpus also contains automatically generated query-like \
	natural language for 2 million functions, obtained from mechanically scraping \
	and preprocessing associated function documentation.
	"""

	_HOMEPAGE = "https://github.com/github/CodeSearchNet"

	_LICENSE = "Various"

	_DATA_DIR_URL = "data/"
	_AVAILABLE_LANGUAGES = ["python", "java", "javascript", "go", "ruby", "php"]
	_URLs = {language: _DATA_DIR_URL + f"{language}.zip" for language in _AVAILABLE_LANGUAGES}
	# URLs for "all" are just the concatenation of URLs for all languages
	_URLs["all"] = _URLs.copy()


	class CodeSearchNet(datasets.GeneratorBasedBuilder):
	""" "CodeSearchNet corpus: proxy dataset for semantic code search."""

	VERSION = datasets.Version("1.0.0", "Add CodeSearchNet corpus dataset")
	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="all",
	version=VERSION,
	description="All available languages: Java, Go, Javascript, Python, PHP, Ruby",
	),
	datasets.BuilderConfig(
	name="java",
	version=VERSION,
	description="Java language",
	),
	datasets.BuilderConfig(
	name="go",
	version=VERSION,
	description="Go language",
	),
	datasets.BuilderConfig(
	name="python",
	version=VERSION,
	description="Pyhton language",
	),
	datasets.BuilderConfig(
	name="javascript",
	version=VERSION,
	description="Javascript language",
	),
	datasets.BuilderConfig(
	name="ruby",
	version=VERSION,
	description="Ruby language",
	),
	datasets.BuilderConfig(
	name="php",
	version=VERSION,
	description="PHP language",
	),
	]

	DEFAULT_CONFIG_NAME = "all"

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"repository_name": datasets.Value("string"),
	"func_path_in_repository": datasets.Value("string"),
	"func_name": datasets.Value("string"),
	"whole_func_string": datasets.Value("string"),
	"language": datasets.Value("string"),
	"func_code_string": datasets.Value("string"),
	"func_code_tokens": datasets.Sequence(datasets.Value("string")),
	"func_documentation_string": datasets.Value("string"),
	"func_documentation_tokens": datasets.Sequence(datasets.Value("string")),
	"split_name": datasets.Value("string"),
	"func_code_url": datasets.Value("string"),
	# TODO - add licensing info in the examples
	}
	),
	# No default supervised keys
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators.

	Note: The original data is stored in S3, and follows this unusual directory structure:
	```
	.
	├── <language_name> # e.g. python
	│ └── final
	│ └── jsonl
	│ ├── test
	│ │ └── <language_name>_test_0.jsonl.gz
	│ ├── train
	│ │ ├── <language_name>_train_0.jsonl.gz
	│ │ ├── <language_name>_train_1.jsonl.gz
	│ │ ├── ...
	│ │ └── <language_name>_train_n.jsonl.gz
	│ └── valid
	│ └── <language_name>_valid_0.jsonl.gz
	├── <language_name>_dedupe_definitions_v2.pkl
	└── <language_name>_licenses.pkl
	```
	"""
	data_urls = _URLs[self.config.name]
	if isinstance(data_urls, str):
	data_urls = {self.config.name: data_urls}
	# Download & extract the language archives
	data_dirs = [
	os.path.join(directory, lang, "final", "jsonl")
	for lang, directory in dl_manager.download_and_extract(data_urls).items()
	]

	split2dirs = {
	split_name: [os.path.join(directory, split_name) for directory in data_dirs]
	for split_name in ["train", "test", "valid"]
	}

	split2paths = dl_manager.extract(
	{
	split_name: [
	os.path.join(directory, entry_name)
	for directory in split_dirs
	for entry_name in os.listdir(directory)
	]
	for split_name, split_dirs in split2dirs.items()
	}
	)

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepaths": split2paths["train"],
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepaths": split2paths["test"],
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepaths": split2paths["valid"],
	},
	),
	]

	def _generate_examples(self, filepaths):
	"""Yields the examples by iterating through the available jsonl files."""
	for file_id_, filepath in enumerate(filepaths):
	with open(filepath, encoding="utf-8") as f:
	for row_id_, row in enumerate(f):
	# Key of the example = file_id + row_id,
	# to ensure all examples have a distinct key
	id_ = f"{file_id_}_{row_id_}"
	data = json.loads(row)
	yield id_, {
	"repository_name": data["repo"],
	"func_path_in_repository": data["path"],
	"func_name": data["func_name"],
	"whole_func_string": data["original_string"],
	"language": data["language"],
	"func_code_string": data["code"],
	"func_code_tokens": data["code_tokens"],
	"func_documentation_string": data["docstring"],
	"func_documentation_tokens": data["docstring_tokens"],
	"split_name": data["partition"],
	"func_code_url": data["url"],
	}