Add datasets loader script

athena_data.py

@@ -0,0 +1,233 @@
+# 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)
+
+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
+
+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
+            check_output(
+                [
+                    "bash",
+                    "clone.sh",
+                    "repo_names.txt",
+                ],
+                cwd=data_dir,
+            )
+        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
+            for row_id, row in enumerate(csv_reader):
+                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)
+                    # Otherwise, parse the project
+                    g = Git(repo_path)
+                    g.checkout(self.commit)
+
+                    indexes = []
+                    files = glob(f"{repo_path}/**/*.{LANGUAGE_METADATA[LANG]['ext']}")
+                    sha = None
+                    for f in files:
+                        definitions = FUNC_PROCESSOR.get_function_definitions(str(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():
+                        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"],
+                        }
+                    data = pd.concat([repo.definitions for repo in self.repos])