including large csvs in data splits

snow-mountain.py

@@ -62,6 +62,8 @@ for lang in _LANGUAGES:
         "train_full": f"data/experiments/{lang}/train_full.csv",
         "val_full": f"data/experiments/{lang}/val_full.csv",
         "test_common": f"data/experiments/{lang}/test_common.csv",
+        "all_verses": f"data/cleaned/{lang}/all_verses.tar.gz",
+        "short_verses": f"data/cleaned/{lang}/short_verses.tar.gz",
     }
     _FILES[lang] = file_dic
 
@@ -85,6 +87,7 @@ class Test(datasets.GeneratorBasedBuilder):
         text = lang.capitalize()+" data"
         BUILDER_CONFIGS.append(datasets.BuilderConfig(name=f"{lang}", version=VERSION, description=text))
     
+
     DEFAULT_CONFIG_NAME = "hindi" 
 
     def _info(self):
@@ -108,7 +111,7 @@ class Test(datasets.GeneratorBasedBuilder):
         
         downloaded_files = dl_manager.download(_FILES[self.config.name]) 
 
-        '''Downloads full audios here'''
+        '''Downloads full audio here'''
         audio_data = {}
         for book in BOOKS_DIC[self.config.name]:
             archive_url = f"data/cleaned/{self.config.name}/{book}.tar.gz"
@@ -153,13 +156,54 @@ class Test(datasets.GeneratorBasedBuilder):
                 },
             )
         )
+        splits.append(
+            datasets.SplitGenerator(
+                name="all_verses",
+                gen_kwargs={
+                    "filepath": downloaded_files["all_verses"],
+                    "audio_data": audio_data,
+                    "dl_manager":dl_manager,
+                },
+            )
+        )
+        splits.append(
+            datasets.SplitGenerator(
+                name="short_verses",
+                gen_kwargs={
+                    "filepath": downloaded_files["short_verses"],
+                    "audio_data": audio_data,
+                    "dl_manager":dl_manager,
+                },
+            )
+        )
         return splits
 
         
     def _generate_examples(self, filepath, audio_data, dl_manager):
+
         key = 0
+        '''Function for parsing large csv archives (all_verses, short_verses)'''
+        def parse_archive(archive):
+            temp_df = pd.DataFrame() 
+            for path, file in dl_manager.iter_archive(archive):
+                if path.endswith('_verses.csv'):
+                    verses_filepath = file 
+                    verses_lines = file.readlines()
+                    verses_lines = [line.decode("utf-8") for line in verses_lines]
+                    column_names = verses_lines[0].strip().split(",")
+                    rows = [row.split(',') for row in verses_lines[1:]]
+                    rows = [[i[0], i[1], ','.join(i[2:])]for i in rows]
+                    temp_df = pd.DataFrame(rows, columns =column_names) 
+                    break
+            return temp_df
+        
         with open(filepath) as f:
-            data_df = pd.read_csv(f,sep=',')  
+            if filepath.endswith('all_verses.tar.gz'):
+                data_df = parse_archive(filepath)
+            elif filepath.endswith('short_verses.tar.gz'):    
+                data_df = parse_archive(filepath)
+            else:    
+                data_df = pd.read_csv(f,sep=',')  
             for index,row in data_df.iterrows():
                 audio = row['path'].split('/')[-1]
                 content = ''