Update Integration.py

Integration.py

@@ -537,45 +537,28 @@ class Euro2020Dataset(GeneratorBasedBuilder):
             citation="Optional citation"
         )
 
-    def download_file(url, filename):
-        with requests.get(url, stream=True) as r:
-            r.raise_for_status()
-            with open(filename, 'wb') as f:
-                for chunk in r.iter_content(chunk_size=8192):
-                    f.write(chunk)
-
-    file_url = "https://drive.google.com/uc?id=1QiF2WnnI2cxFDpLoetabx9Pe-DgUuV81"
-    download_file(file_url, 'data.parquet')
-    
-    #def _split_generators(self, dl_manager): 
-        #file_url = 'https://github.com/gchcg/Projects/raw/main/Euro2020.parquet' #"https://drive.google.com/uc?id=1QiF2WnnI2cxFDpLoetabx9Pe-DgUuV81"
-#1RKoAQwq68LASd4ret_OKYUkF4B4m6hnu
-        #downloaded_file = dl_manager.download(file_url)
+    def _split_generators(self, dl_manager): 
+        file_url = "https://drive.google.com/uc?id=1QiF2WnnI2cxFDpLoetabx9Pe-DgUuV81"
+        downloaded_file = dl_manager.download(file_url)
         #dl_path = dl_manager.download_and_extract({'train_csv': file_url})
     
-        #return [
-            #SplitGenerator(
-                #name="train",
-                #gen_kwargs={"filepath": downloaded_file},#dl_path['train_csv']},
-            #),
-        #]
+        return [
+            SplitGenerator(
+                name="train",
+                gen_kwargs={"filepath": downloaded_file},#dl_path['train_csv']},
+            ),
+        ]
 
     # Increase the maximum field size limit
     #csv.field_size_limit(sys.maxsize)
-
+    
     def _generate_examples(self, filepath):
-        table = pq.read_table(filepath)
-        df = table.to_pandas()
+        df = pd.read_parquet(filepath)
         for id, row in df.iterrows():
+        #'id' here is the index of the row in the DataFrame
+        #'row' is a Pandas Series object representing the row data
+        #Directly yield the id and row.to_dict() if the DataFrame structure matches the desired output
             yield id, row.to_dict()
-    
-    #def _generate_examples(self, filepath):
-        #df = pd.read_parquet(filepath)
-        #for id, row in df.iterrows():
-        # 'id' here is the index of the row in the DataFrame
-        # 'row' is a Pandas Series object representing the row data
-        # Directly yield the id and row.to_dict() if the DataFrame structure matches the desired output
-            #yield id, row.to_dict()
         #with open(filepath, encoding="utf-8") as f:
             #reader = pd.read_parquet(f)
             #for id, row in enumerate(reader):