Convert dataset to Parquet

README.md

@@ -50,17 +50,17 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 5850604083
+    num_bytes: 5850594255
     num_examples: 1880853
   - name: test
-    num_bytes: 308626333
+    num_bytes: 308625761
     num_examples: 100529
   - name: validation
-    num_bytes: 274564382
+    num_bytes: 274563914
     num_examples: 89154
-  download_size: 5117370511
-  dataset_size: 6433794798
-- config_name: java
+  download_size: 1963220197
+  dataset_size: 6433783930
+- config_name: go
   features:
   - name: repository_name
     dtype: string
@@ -86,17 +86,17 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 1429272535
-    num_examples: 454451
+    num_bytes: 738151570
+    num_examples: 317832
   - name: test
-    num_bytes: 82377246
-    num_examples: 26909
+    num_bytes: 32286894
+    num_examples: 14291
   - name: validation
-    num_bytes: 42358315
-    num_examples: 15328
-  download_size: 1060569153
-  dataset_size: 1554008096
-- config_name: go
+    num_bytes: 26888423
+    num_examples: 14242
+  download_size: 228520726
+  dataset_size: 797326887
+- config_name: java
   features:
   - name: repository_name
     dtype: string
@@ -122,17 +122,17 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 738153234
-    num_examples: 317832
+    num_bytes: 1429270143
+    num_examples: 454451
   - name: test
-    num_bytes: 32286998
-    num_examples: 14291
+    num_bytes: 82377090
+    num_examples: 26909
   - name: validation
-    num_bytes: 26888527
-    num_examples: 14242
-  download_size: 487525935
-  dataset_size: 797328759
-- config_name: python
+    num_bytes: 42358211
+    num_examples: 15328
+  download_size: 425659927
+  dataset_size: 1554005444
+- config_name: javascript
   features:
   - name: repository_name
     dtype: string
@@ -158,17 +158,17 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 1559645310
-    num_examples: 412178
+    num_bytes: 480285847
+    num_examples: 123889
   - name: test
-    num_bytes: 84342064
-    num_examples: 22176
+    num_bytes: 24056920
+    num_examples: 6483
   - name: validation
-    num_bytes: 92154786
-    num_examples: 23107
-  download_size: 940909997
-  dataset_size: 1736142160
-- config_name: javascript
+    num_bytes: 30168190
+    num_examples: 8253
+  download_size: 177637817
+  dataset_size: 534510957
+- config_name: php
   features:
   - name: repository_name
     dtype: string
@@ -194,17 +194,17 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 480286523
-    num_examples: 123889
+    num_bytes: 1532562114
+    num_examples: 523712
   - name: test
-    num_bytes: 24056972
-    num_examples: 6483
+    num_bytes: 80203721
+    num_examples: 28391
   - name: validation
-    num_bytes: 30168242
-    num_examples: 8253
-  download_size: 1664713350
-  dataset_size: 534511737
-- config_name: ruby
+    num_bytes: 78163768
+    num_examples: 26015
+  download_size: 507426963
+  dataset_size: 1690929603
+- config_name: python
   features:
   - name: repository_name
     dtype: string
@@ -230,17 +230,17 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 110681715
-    num_examples: 48791
+    num_bytes: 1559643126
+    num_examples: 412178
   - name: test
-    num_bytes: 5359280
-    num_examples: 2279
+    num_bytes: 84341908
+    num_examples: 22176
   - name: validation
-    num_bytes: 4830744
-    num_examples: 2209
-  download_size: 111758028
-  dataset_size: 120871739
-- config_name: php
+    num_bytes: 92154630
+    num_examples: 23107
+  download_size: 581272659
+  dataset_size: 1736139664
+- config_name: ruby
   features:
   - name: repository_name
     dtype: string
@@ -266,16 +266,16 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 1532564870
-    num_examples: 523712
+    num_bytes: 110681455
+    num_examples: 48791
   - name: test
-    num_bytes: 80203877
-    num_examples: 28391
+    num_bytes: 5359228
+    num_examples: 2279
   - name: validation
-    num_bytes: 78163924
-    num_examples: 26015
-  download_size: 851894048
-  dataset_size: 1690932671
+    num_bytes: 4830692
+    num_examples: 2209
+  download_size: 42266439
+  dataset_size: 120871375
 config_names:
 - all
 - go
@@ -284,6 +284,64 @@ config_names:
 - php
 - python
 - ruby
+configs:
+- config_name: all
+  data_files:
+  - split: train
+    path: all/train-*
+  - split: test
+    path: all/test-*
+  - split: validation
+    path: all/validation-*
+  default: true
+- config_name: go
+  data_files:
+  - split: train
+    path: go/train-*
+  - split: test
+    path: go/test-*
+  - split: validation
+    path: go/validation-*
+- config_name: java
+  data_files:
+  - split: train
+    path: java/train-*
+  - split: test
+    path: java/test-*
+  - split: validation
+    path: java/validation-*
+- config_name: javascript
+  data_files:
+  - split: train
+    path: javascript/train-*
+  - split: test
+    path: javascript/test-*
+  - split: validation
+    path: javascript/validation-*
+- config_name: php
+  data_files:
+  - split: train
+    path: php/train-*
+  - split: test
+    path: php/test-*
+  - split: validation
+    path: php/validation-*
+- config_name: python
+  data_files:
+  - split: train
+    path: python/train-*
+  - split: test
+    path: python/test-*
+  - split: validation
+    path: python/validation-*
+- config_name: ruby
+  data_files:
+  - split: train
+    path: ruby/train-*
+  - split: test
+    path: ruby/test-*
+  - split: validation
+    path: ruby/validation-*
 ---
 
 # Dataset Card for CodeSearchNet corpus

data/php.zip → all/test-00000-of-00001.parquet

@@ -1,3 +1,3 @@
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-oid sha256:c3bbf0d1b10010f88b058faea876f1f5471758399e30d58c11f78ff53660ce00
-size 851894048
+oid sha256:a4a2767a0cae74a774f5bdf7b74626c7c17052334a4de25e005e9e45981c72c0
+size 96096131

data/java.zip → all/train-00000-of-00002.parquet

@@ -1,3 +1,3 @@
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-oid sha256:05f9204b1808413fab30f0e69229e298f6de4ad468279d53a2aa5797e3a78c17
-size 1060569153
+oid sha256:b95cf6899f4a28043cf97f54a521c1dbed1f7e1c2a4813ed90320acf2fecf0aa
+size 1007776926

data/go.zip → all/train-00001-of-00002.parquet

@@ -1,3 +1,3 @@
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-oid sha256:15d23f01dc2796447e1736263e6830079289d5ef41f09988011afdcf8da6b6e5
-size 487525935
+oid sha256:07ef6ec80c1f52ea097cafb4843ea26d1442e79e7ce4083c6a8e17eb4f0d225a
+size 773741030

data/python.zip → all/validation-00000-of-00001.parquet

@@ -1,3 +1,3 @@
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-oid sha256:7223c6460bebfa85697b586da91e47bc5d64790a4d60bba5917106458ab6b40e
-size 940909997
+oid sha256:f821590fcdee74a234abdec9ba879ba4740834bf6d2d4d5a1ea06d9c74ac8a39
+size 85606110

code_search_net.py

@@ -1,218 +0,0 @@
-# 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"],
-                    }

data/javascript.zip

@@ -1,3 +0,0 @@
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-size 1664713350

data/ruby.zip → go/test-00000-of-00001.parquet

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+size 9751451

go/train-00000-of-00001.parquet

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go/validation-00000-of-00001.parquet

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java/test-00000-of-00001.parquet

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java/train-00000-of-00001.parquet

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java/validation-00000-of-00001.parquet

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javascript/test-00000-of-00001.parquet

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javascript/train-00000-of-00001.parquet

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javascript/validation-00000-of-00001.parquet

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php/test-00000-of-00001.parquet

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php/train-00000-of-00001.parquet

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php/validation-00000-of-00001.parquet

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python/test-00000-of-00001.parquet

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python/train-00000-of-00001.parquet

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ruby/test-00000-of-00001.parquet

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