Create source_code.py

source_code.py

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