shibing624 commited on
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Create source_code.py

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  1. source_code.py +117 -0
source_code.py ADDED
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+ # -*- coding: utf-8 -*-
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+ """
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+ @author:XuMing(xuming624@qq.com)
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+ @description:
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+ """
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+
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+ """Code AutoComplete Python dataset Corpus.(code_autocomplete)"""
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+
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+ import os
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+
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+ import datasets
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+
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+ _DESCRIPTION = """纯文本数据,内容:高质量编程源代码,包括Python,Java,CPP源代码"""
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+
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+ PYTHON_HOME = "https://github.com/bharathgs/Awesome-pytorch-list"
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+ JAVA_HOME = "https://github.com/akullpp/awesome-java"
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+ CPP_HOME = "https://github.com/fffaraz/awesome-cpp"
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+
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+ _CITATION = "https://github.com/shibing624/code-autocomplete"
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+
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+ _DATA_URL = "https://github.com/shibing624/code-autocomplete/releases/download/0.0.4/source_code.zip"
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+
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+
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+ class SourceCodeConfig(datasets.BuilderConfig):
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+ """BuilderConfig for NLI_zh"""
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+
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+ def __init__(self, features, data_url, citation, url, **kwargs):
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+ """BuilderConfig for NLI_zh
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+ Args:
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+ features: `list[string]`, list of the features that will appear in the
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+ feature dict. Should not include "label".
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+ data_url: `string`, url to download the zip file from.
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+ citation: `string`, citation for the data set.
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+ url: `string`, url for information about the data set.
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+ **kwargs: keyword arguments forwarded to super.
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+ """
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+ super().__init__(version=datasets.Version("1.0.0"), **kwargs)
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+ self.features = features
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+ self.data_url = data_url
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+ self.citation = citation
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+ self.url = url
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+
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+
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+ class SourceCode(datasets.GeneratorBasedBuilder):
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+ """The Natural Language Inference Chinese(NLI_zh) Corpus."""
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+
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+ BUILDER_CONFIGS = [
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+ SourceCodeConfig(
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+ name="python",
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+ description=_DESCRIPTION,
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+ features=["text"],
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+ data_url=_DATA_URL,
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+ citation=_CITATION,
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+ url=PYTHON_HOME,
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+ ),
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+ SourceCodeConfig(
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+ name="java",
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+ description=_DESCRIPTION,
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+ features=["text"],
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+ data_url=_DATA_URL,
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+ citation=_CITATION,
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+ url=JAVA_HOME,
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+ ),
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+ SourceCodeConfig(
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+ name="cpp",
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+ description=_DESCRIPTION,
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+ features=["text"],
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+ data_url=_DATA_URL,
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+ citation=_CITATION,
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+ url=CPP_HOME,
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+ ),
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+ ]
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+
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+ def _info(self):
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+ return datasets.DatasetInfo(
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+ description=self.config.description,
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+ features=datasets.Features(
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+ {
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+ "text": datasets.Value("string"),
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+ }
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+ ),
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+ homepage=self.config.url,
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+ citation=self.config.citation,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ dl_dir = dl_manager.download_and_extract(self.config.data_url) or ""
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+ dl_dir = os.path.join(dl_dir, f"source_code/{self.config.name}")
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN,
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+ gen_kwargs={
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+ "filepath": os.path.join(dl_dir, f"train.txt"),
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+ },
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.VALIDATION,
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+ gen_kwargs={
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+ "filepath": os.path.join(dl_dir, f"valid.txt"),
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+ },
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TEST,
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+ gen_kwargs={
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+ "filepath": os.path.join(dl_dir, f"test.txt"),
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+ },
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+ ),
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+ ]
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+
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+ def _generate_examples(self, filepath):
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+ """This function returns the examples in the raw (text) form."""
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+ with open(filepath, 'r', encoding="utf-8") as f:
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+ for idx, row in enumerate(f):
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+ if row.strip():
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+ yield idx, {"text": row}
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+ else:
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+ yield idx, {"text": ""}