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athena_data

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athena_data / athena_data.py
ncoop57
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b05f041
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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.
"""TODO: Add a description here."""
import ast
import csv
import datasets
import function_parser
import json
import os
import sys
csv.field_size_limit(sys.maxsize)
import pandas as pd
from function_parser.language_data import LANGUAGE_METADATA
from function_parser.parsers.java_parser import JavaParser
from function_parser.process import DataProcessor
from git import Git, Repo
from glob import glob
from tree_sitter import Language
from subprocess import check_output
LANG = "java"
JAVA_LANG = Language(
os.path.join(function_parser.__path__[0], "tree-sitter-languages.so"), LANG
)
DataProcessor.PARSER.set_language(JAVA_LANG)
FUNC_PROCESSOR = DataProcessor(
language=LANG, language_parser=LANGUAGE_METADATA[LANG]["language_parser"]
)
# TODO: Add BibTeX citation
# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
}
"""
# TODO: Add description of the dataset here
# You can copy an official description
_DESCRIPTION = """\
This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
"""
# TODO: Add a link to an official homepage for the dataset here
_HOMEPAGE = ""
# TODO: Add the licence for the dataset here if you can find it
_LICENSE = ""
# TODO: Add link to the official dataset URLs here
# The HuggingFace dataset library don't host the datasets but only point to the original files
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
_URL = "https://huggingface.co/datasets/ncoop57/athena_data/resolve/main/repos-commits.zip"
# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
class NewDataset(datasets.GeneratorBasedBuilder):
"""TODO: Short description of my dataset."""
VERSION = datasets.Version("1.1.0")
# This is an example of a dataset with multiple configurations.
# If you don't want/need to define several sub-sets in your dataset,
# just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
# If you need to make complex sub-parts in the datasets with configurable options
# You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
# BUILDER_CONFIG_CLASS = MyBuilderConfig
# You will be able to load one or the other configurations in the following list with
# data = datasets.load_dataset('my_dataset', 'first_domain')
# data = datasets.load_dataset('my_dataset', 'second_domain')
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="meta_data", version=VERSION, description="This part of my dataset covers a first domain"),
datasets.BuilderConfig(name="repos_commits", version=VERSION, description="This part of my dataset covers a second domain"),
]
DEFAULT_CONFIG_NAME = "meta_data" # It's not mandatory to have a default configuration. Just use one if it make sense.
def _info(self):
# TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
if self.config.name == "meta_data": # This is the name of the configuration selected in BUILDER_CONFIGS above
features = datasets.Features(
{
"repo": datasets.Value("string"),
"parent_commit": datasets.Value("string"),
"commit": datasets.Value("string"),
"changes": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
# These are the features of your dataset like images, labels ...
}
)
elif self.config.name == "repos_commits":
features = datasets.Features(
{
"repo": datasets.Value("string"),
"parent_commit": datasets.Value("string"),
"commit": datasets.Value("string"),
"changes": datasets.Sequence(datasets.Value("string")),
"file_path": datasets.Value("string"),
"code": datasets.Value("string"),
"code_tokens": datasets.Sequence(datasets.Value("string")),
"docstring": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description=_DESCRIPTION,
# This defines the different columns of the dataset and their types
features=features, # Here we define them above because they are different between the two configurations
# If there's a common (input, target) tuple from the features,
# specify them here. They'll be used if as_supervised=True in
# builder.as_dataset.
supervised_keys=None,
# Homepage of the dataset for documentation
homepage=_HOMEPAGE,
# License for the dataset if available
license=_LICENSE,
# Citation for the dataset
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
# If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
data_dir = dl_manager.download_and_extract(_URL)
data_dir = os.path.join(data_dir, "repos-commits")
if self.config.name == "repos_commits" and not os.path.exists(os.path.join(data_dir, "repos")):
# Clone all repositories
output = check_output(
[
"bash",
"clone.sh",
"repos.txt",
],
cwd=data_dir,
)
# print(output)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"data_dir": data_dir,
"file_path": os.path.join(data_dir, "processed_impact_methods.csv"),
},
),
]
def _generate_examples(
self, data_dir, file_path # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
):
""" Yields examples as (key, example) tuples. """
# This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
# The `key` is here for legacy reason (tfds) and is not important in itself.
with open(file_path, encoding="utf-8") as f:
csv_reader = csv.reader(f, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True)
next(csv_reader, None) # skip header
row_id = -1
for _, row in enumerate(csv_reader):
row_id += 1
repo, parent_commit, commit, changes = row
changes = ast.literal_eval(changes)
# print(changes)
if self.config.name == "meta_data":
yield row_id, {
"repo": repo,
"parent_commit": parent_commit,
"commit": commit,
"changes": changes,
}
elif self.config.name == "repos_commits":
repo_path = os.path.join(data_dir, "repos", repo)
try:
# Otherwise, parse the project
g = Git(repo_path)
g.clean(force=True, d=True)
g.checkout(commit)
except Exception as e:
print(e)
continue
indexes = []
files = glob(f"{repo_path}/**/*.{LANGUAGE_METADATA[LANG]['ext']}", recursive=True)
sha = None
for f in files:
definitions = FUNC_PROCESSOR.get_function_definitions(f)
if definitions is None:
continue
nwo, path, functions = definitions
indexes.extend(
(
FUNC_PROCESSOR.extract_function_data(func, nwo, path, sha)
for func in functions
if len(func["function_tokens"]) > 1
)
)
df = pd.DataFrame(indexes)[
["path", "function", "function_tokens", "docstring"]
].rename(
columns={
"path": "file_path",
"function": "code",
"function_tokens": "code_tokens",
"docstring": "docstring",
}
)
for _, row in df.iterrows():
row_id += 1
yield row_id, {
"repo": repo,
"parent_commit": parent_commit,
"commit": commit,
"changes": changes,
"file_path": row["file_path"],
"code": row["code"],
"code_tokens": row["code_tokens"],
"docstring": row["docstring"],
}