test

zillow.py

@@ -48,7 +48,7 @@ _LICENSE = ""
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 # _URLS = {
-#     "first_domain": "https://files.zillowstatic.com/research/public_csvs/zhvf_growth/Metro_zhvf_growth_uc_sfrcondo_tier_0.33_0.67_sm_sa_month.csv",
+#     "home_value_forecasts": "https://files.zillowstatic.com/research/public_csvs/zhvf_growth/Metro_zhvf_growth_uc_sfrcondo_tier_0.33_0.67_sm_sa_month.csv",
 #     # "second_domain": "https://huggingface.co/great-new-dataset-second_domain.zip",
 # }
 
@@ -68,11 +68,11 @@ class NewDataset(datasets.GeneratorBasedBuilder):
     # BUILDER_CONFIG_CLASS = MyBuilderConfig
 
     # You will be able to load one or the other configurations in the following list with
-    # data = datasets.load_dataset('my_dataset', 'first_domain')
+    # data = datasets.load_dataset('my_dataset', 'home_value_forecasts')
     # data = datasets.load_dataset('my_dataset', 'second_domain')
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(
-            name="first_domain",
+            name="home_value_forecasts",
             version=VERSION,
             description="This part of my dataset covers a first domain",
         ),
@@ -83,12 +83,12 @@ class NewDataset(datasets.GeneratorBasedBuilder):
         # ),
     ]
 
-    DEFAULT_CONFIG_NAME = "first_domain"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+    DEFAULT_CONFIG_NAME = "home_value_forecasts"  # It's not mandatory to have a default configuration. Just use one if it make sense.
 
     def _info(self):
         # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
         if (
-            self.config.name == "first_domain"
+            self.config.name == "home_value_forecasts"
         ):  # This is the name of the configuration selected in BUILDER_CONFIGS above
             features = datasets.Features(
                 {
@@ -111,7 +111,7 @@ class NewDataset(datasets.GeneratorBasedBuilder):
                     # These are the features of your dataset like images, labels ...
                 }
             )
-        # else:  # This is an example to show how to have different features for "first_domain" and "second_domain"
+        # else:  # This is an example to show how to have different features for "home_value_forecasts" and "second_domain"
         #     features = datasets.Features(
         #         {
         #             "sentence": datasets.Value("string"),
@@ -147,7 +147,7 @@ class NewDataset(datasets.GeneratorBasedBuilder):
         # urls = _URLS[self.config.name]
         # data_dir = dl_manager.download_and_extract(urls)
         # file_train = dl_manager.download(os.path.join('./data/home_value_forecasts', "Metro_zhvf_growth_uc_sfrcondo_tier_0.33_0.67_month.csv"))
-        file_path = os.path.join('processed/home_value_forecasts', "final.jsonl")
+        file_path = os.path.join('processed', self.config.name, "final.jsonl")
         # print('*********************')
         # print(file_path)
 
@@ -188,7 +188,7 @@ class NewDataset(datasets.GeneratorBasedBuilder):
         with open(filepath, encoding="utf-8") as f:
             for key, row in enumerate(f):
                 data = json.loads(row)
-                if self.config.name == "first_domain":
+                if self.config.name == "home_value_forecasts":
                     # Yields examples as (key, example) tuples
                     yield key, {
                         "RegionID": data["RegionID"],