Upload date-data.py

date-data.py

@@ -1,6 +1,8 @@
 import os
 import re
+import sys
 import datasets
+import pandas as pd
 from huggingface_hub import HfFileSystem
 from typing import List
 
@@ -10,11 +12,12 @@ fs = HfFileSystem()
 _CITATION = """
 """
 
-_DESCRIPTION = """This dataset contain file about datetime date. 
+_DESCRIPTION = """\
+    This dataset contain file about datetime date. 
     It's created with purpose is practice loading dataset from hugging face hub."""
 
-
-_HOMEPAGE = """
+_HOMEPAGE = """\
+    https://github.com/minhnv4099
 """
 
 _REPO = "datasets/nguyenminh4099/date-data"
@@ -22,7 +25,10 @@ _BRANCH = "main"
 _REPO_BRANCH = f"{_REPO}@{_BRANCH}"
 
 _REPO_URL = f"https://huggingface.co/{_REPO}/resolve/{_BRANCH}"
-_URL = os.path.join(_REPO_URL, "data", "{filename}.zip")
+_URLS = {
+    'zipfile': os.path.join(_REPO_URL, "data", "{}.zip"),
+    'metadata': _REPO_URL + "/metadata.parquet",
+}
 
 _CONFIGS = ['all']
 _CONFIGS.extend(
@@ -31,6 +37,8 @@ _CONFIGS.extend(
     if file.endswith('.zip')
 )
 
+
+# TODO: Define Dataset Builder config
 class DateDataConfig(datasets.BuilderConfig):
     def __init__(
         self,
@@ -40,11 +48,26 @@ class DateDataConfig(datasets.BuilderConfig):
         super(DateDataConfig, self).__init__(
             name=name,
             version=datasets.Version("1.0.0"),
-            description=_DESCRIPTION,
         )
+        # self.metadata = metadata
+        # self.url = kwargs.get('url', "https://huggingface.co/datasets/nguyenminh4099/date-data")
+        # self.data_url = kwargs.get('data_url', None)
+        # self.description = kwargs.get('description', _DESCRIPTION)
+        # logger.info('call BuilderConfig')
+
 
-class DateDate(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [DateDataConfig(name=name) for name in _CONFIGS]
+# TODO: Define Dataset Builder
+class DateData(datasets.GeneratorBasedBuilder):
+    logger.info('call dataset builder')
+
+    BUILDER_CONFIGS = [
+        DateDataConfig(
+            name=name,
+            # metadata=_URLS['metadata'],
+            # data_url=_URLS['zipfile'].format(name),
+        ) 
+        for name in _CONFIGS
+    ]
     DEFAULT_CONFIG_NAME = 'all'
 
     def _info(self) -> datasets.DatasetInfo:
@@ -60,6 +83,7 @@ class DateDate(datasets.GeneratorBasedBuilder):
             "year": datasets.Value('string'),
             "file_path": datasets.Value('string'),
         })
+        print(self.config)
         return datasets.DatasetInfo(
             features=features,
             description=_DESCRIPTION,
@@ -71,36 +95,69 @@ class DateDate(datasets.GeneratorBasedBuilder):
         self,
         dl_manager: datasets.DownloadManager,
     ) -> List[datasets.SplitGenerator]:
-        config_names = _CONFIGS[1:] if self.config.name == 'all' else [self.config.name]
+        logger.info("Call _split_generators")
+    
+        configs = _CONFIGS[1:5] if self.config.name == 'all' else [self.config.name]
+        data_files = {
+            config : _URLS['zipfile'].format(config)
+            for config in configs
+        }
+        data_dict = dl_manager.download_and_extract(data_files)
+        print(data_dict)
 
-        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,
+                    "metadata": _URLS['metadata'],
+                    "data_dict": data_dict,
                 }
             )
         ]
 
     def _generate_examples(
         self,
-        data_dirs: List[str],
+        metadata: str,
+        data_dict: dict,
     ) -> dict:
-        print(data_dirs)
-        for i, data_dir in enumerate(data_dirs):
-            sample = self._extract_datetime("Wed Oct 16 11:08:00 +07 2024")
-            sample.update((('id','123'),('file_path',"null")))
-            print(data_dir)
-            yield i, sample
+        logger.info("Call _generate_examples")
+        infos = datasets.load_dataset(
+            "parquet",
+            data_files=[metadata],
+            split='train',
+        )
+        metadata_df = infos.to_pandas()
+        data_df = pd.DataFrame(
+            {
+                "shard" : list(data_dict.keys()),
+                "data_dir" : list(data_dict.values()),
+            },
+            columns=['shard', 'data_dir'],
+            index=range(len(data_dict))
+        )
+
+        metadata_df = metadata_df.merge(
+            right=data_df,
+            how='right',
+            left_on='shard',
+            right_on='shard',
+            sort=True,
+        )
+
+        for i, sample in enumerate(metadata_df.itertuples()):
+            file_name = os.path.join(
+                sample.data_dir, sample.id + ".txt"
+            )
+            example = self._read_txt(file_name=file_name)
+            example['id'] = sample.id
+            example['file_path'] = file_name
+            
+            yield i, example
 
     def _read_txt(
         self,
         file_name: str,
-    ) -> str:
+    ) -> dict:
         with open(file=file_name, mode='r') as f:
             return self._extract_datetime(f.read())
     
@@ -121,3 +178,4 @@ class DateDate(datasets.GeneratorBasedBuilder):
             "timezone": components[6],
             "year": components[7],
         }
+DateData()