Upload date-data.py with huggingface_hub

date-data.py

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+import os
+import datasets
+from huggingface_hub import HfFileSystem
+from typing import List
+
+logger = datasets.logging.get_logger(name=__name__)
+fs = HfFileSystem()
+
+_CITATION = """
+"""
+
+_DESCRIPTION = """
+    This dataset contain file about datetime date. 
+    It's created with purpose is practice loading dataset from hugging face hub.
+"""
+
+
+_HOMEPAGE = """
+"""
+
+_REPO = "datasets/nguyenminh4099/date-data"
+_BRANCH = "main"
+_REPO_BRANCH = f"{_REPO}@{_BRANCH}"
+
+_REPO_URL = f"https://huggingface.co/{_REPO_PATH}/resolve/{_BRANCH}"
+_URL = os.path.join(_REPO_URL, "data", "{filename}.zip")
+
+_CONFIGS = ['all']
+_CONFIGS.extend(
+    os.path.basename(file)[:-4]
+    for file in fs.listdir(_REPO_BRANCH + "data", detail=False)
+    if file.endswith('.zip')
+)
+
+class DateDataConfig(datasets.BuilderConfig):
+    def __init__(
+        self,
+        name: str,
+        **kwargs,        
+    ):
+        super(DateDataConfig, self).__init__(
+            name=name,
+            version=datasets.Version("1.0.0"),
+            description=_DESCRIPTION,
+        )
+
+class DateDate(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [DateDataConfig(name=name) for name in _CONFIGS]
+    DEFAULT_CONFIG_NAME = 'all'
+
+    def info(self) -> datasets.DatasetInfo:
+        features = datasets.Features({
+            "id": datasets.Value('string'),
+            "dow": datasets.Value('string'),
+            "month": datasets.Value('string'),
+            "dom": datasets.Value('string'),
+            "hour": datasets.Value('int'),
+            "min": datasets.Value('int'),
+            "second": datasets.Value('int'),
+            "timezone": datasets.Value('string'),
+            "year": datasets.Value('int'),
+            "file_path": datasets.Value('string'),
+        })
+
+        return datasets.DatasetInfo(
+            features=features,
+            description=_DESCRIPTION,
+            citation=_CITATION,
+            homepage=_HOMEPAGE,
+        )
+
+    def _split_generators(
+        self,
+        dl_manager: datasets.DownloadManager,
+    ) -> List[datasets.SplitGenerator]:
+        config_names = _CONFIGS[1:] if self.config.name == 'all' else [self.config.name]
+
+        data_dirs = dl_manager.download_and_extract(
+            [_URL.format(filename=zipfile) for zipfile in config_names]
+        )
+
+        return datasets.SplitGenerator(
+            name=datasets.Split.TRAIN,
+            gen_kwargs={
+                "data_dirs": data_dirs,
+            }
+        )
+
+
+    def _generate_examples(
+        self,
+        data_dirs: List[str],
+    ) -> dict:
+        for data_dir in data_dirs:
+            print(data_dir)
+            yield self._extract_datetime("Wed Oct 16 11:08:00 +07 2024").update((('id','123'),('file_path',"null")))
+            
+
+    def _read_txt(
+        self,
+        file_name: str,
+    ) -> str:
+        with open(file=file_name, mode='r') as f:
+            return self._extract_datetime(f.read())
+
+    
+    def _extract_datetime(
+        self,
+        datetime_string: str,
+    ) -> dict:
+        datetime_string = datetime_string.strip("./ ")
+        components = datetime_string.split(' ')
+
+        return {
+            "dow": components[0],
+            "month": components[1],
+            "dom": components[2],
+            "hour": components[3],
+            "min": components[4],
+            "second": components[5],
+            "timezone": components[6],
+            "year": components[7],
+        }
+
+
+
+
+