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# 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.
"""GitHub Code dataset."""
import os
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from huggingface_hub import HfApi, HfFolder
from datasets.data_files import DataFilesDict
_REPO_NAME = "lvwerra/github-code"
_LANG_TO_EXTENSION = {
"Assembly": [".asm"],
"Batchfile": [".bat", ".cmd"],
"C": [".c", ".h"],
"C#": [".cs"],
"C++": [".cpp", ".hpp", ".c++", ".h++", ".cc", ".hh", ".C", ".H"],
"CMake": [".cmake"],
"CSS": [".css"],
"Dockerfile": [".dockerfile", "Dockerfile"],
"FORTRAN": ['.f90', '.f', '.f03', '.f08', '.f77', '.f95', '.for', '.fpp'],
"GO": [".go"],
"Haskell": [".hs"],
"HTML":[".html"],
"Java": [".java"],
"JavaScript": [".js"],
"Julia": [".jl"],
"Lua": [".lua"],
"Makefile": ["Makefile"],
"Markdown": [".md", ".markdown"],
"PHP": [".php", ".php3", ".php4", ".php5", ".phps", ".phpt"],
"Perl": [".pl", ".pm", ".pod", ".perl"],
"PowerShell": ['.ps1', '.psd1', '.psm1'],
"Python": [".py"],
"Ruby": [".rb"],
"Rust": [".rs"],
"SQL": [".sql"],
"Scala": [".scala"],
"Shell": [".sh", ".bash", ".command", ".zsh"],
"TypeScript": [".ts", ".tsx"],
"TeX": [".tex"],
"Visual Basic": [".vb"]
}
_LICENSES = ['mit',
'apache-2.0',
'gpl-3.0',
'gpl-2.0',
'bsd-3-clause',
'agpl-3.0',
'lgpl-3.0',
'lgpl-2.1',
'bsd-2-clause',
'cc0-1.0',
'epl-1.0',
'mpl-2.0',
'unlicense',
'isc',
'artistic-2.0']
_DESCRIPTION = """\
The GitHub Code dataest consists of 115M code files from GitHub in 32 programming \
languages with 60 extensions totalling in 1TB of text data. The dataset was created \
from the GitHub dataset on BiqQuery.
"""
_HOMEPAGE = "https://cloud.google.com/blog/topics/public-datasets/github-on-bigquery-analyze-all-the-open-source-code/"
_EXTENSION_TO_LANG = {}
for lang in _LANG_TO_EXTENSION:
for extension in _LANG_TO_EXTENSION[lang]:
_EXTENSION_TO_LANG[extension] = lang
_LANG_CONFIGS = ["all"] + list(_LANG_TO_EXTENSION.keys())
_LICENSE_CONFIGS = ["all"] + _LICENSES
class GithubCodeConfig(datasets.BuilderConfig):
"""BuilderConfig for the GitHub Code dataset."""
def __init__(self, *args, languages=["all"], licenses=["all"], **kwargs):
"""BuilderConfig for the GitHub Code dataset.
Args:
languages (:obj:`List[str]`): List of languages to load.
licenses (:obj:`List[str]`): List of licenses to load.
**kwargs: keyword arguments forwarded to super.
"""
super().__init__(
*args,
name="+".join(languages)+"-"+"+".join(licenses),
**kwargs,
)
languages = set(languages)
licenses = set(licenses)
assert all([language in _LANG_CONFIGS for language in languages]), f"Language not in {_LANG_CONFIGS}."
assert all([license in _LICENSE_CONFIGS for license in licenses]), f"License not in {_LICENSE_CONFIGS}."
if "all" in languages:
assert len(languages)==1, "Passed 'all' together with other languages."
self.filter_languages = False
else:
self.filter_languages = True
if "all" in licenses:
assert len(licenses)==1, "Passed 'all' together with other licenses."
self.filter_licenses = False
else:
self.filter_licenses = True
self.languages = set(languages)
self.licenses = set(licenses)
class GithubCode(datasets.GeneratorBasedBuilder):
"""GitHub Code dataset."""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIG_CLASS = GithubCodeConfig
BUILDER_CONFIGS = [GithubCodeConfig(languages=[lang], licenses=[license]) for lang in _LANG_CONFIGS
for license in _LICENSE_CONFIGS]
DEFAULT_CONFIG_NAME = "all-all"
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features({"code": datasets.Value("string"),
"repo_name": datasets.Value("string"),
"path": datasets.Value("string"),
"language": datasets.Value("string"),
"license": datasets.Value("string"),
"size": datasets.Value("int32")}),
supervised_keys=None,
homepage=_HOMEPAGE,
license="Multiple: see the 'license' field of each sample.",
)
def _split_generators(self, dl_manager):
hfh_dataset_info = HfApi(datasets.config.HF_ENDPOINT).dataset_info(
_REPO_NAME,
timeout=100.0,
)
patterns = datasets.data_files.get_patterns_in_dataset_repository(hfh_dataset_info)
data_files = datasets.data_files.DataFilesDict.from_hf_repo(
patterns,
dataset_info=hfh_dataset_info,
)
files = dl_manager.download_and_extract(data_files["train"])
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"files": files,
},
),
]
def _generate_examples(self, files):
key = 0
for file_idx, file in enumerate(files):
with open(file, "rb") as f:
parquet_file = pq.ParquetFile(f)
for batch_idx, record_batch in enumerate(parquet_file.iter_batches(batch_size=10_000)):
pa_table = pa.Table.from_batches([record_batch])
for row_index in range(pa_table.num_rows):
row = pa_table.slice(row_index, 1).to_pydict()
lang = lang_from_name(row['path'][0])
license = row["license"][0]
if self.config.filter_languages and not lang in self.config.languages:
continue
if self.config.filter_licenses and not license in self.config.licenses:
continue
yield key, {"code": row['content'][0],
"repo_name": row['repo_name'][0],
"path": row['path'][0],
"license": license,
"language": lang,
"size": int(row['size'][0])}
key += 1
def lang_from_name(name):
for extension in _EXTENSION_TO_LANG:
if name.endswith(extension):
return _EXTENSION_TO_LANG[extension] |