Delete load_data.py with huggingface_hub

load_data.py

@@ -1,75 +0,0 @@
-# Get chunks of data 10000 paragraphs at a time
-
-import csv
-import json
-import sys
-
-# Increase the CSV field size limit
-csv.field_size_limit(sys.maxsize) # otherwise it gives "Error: field larger than field limit (131072)"
-
-def load_data(file_path, chunk_size=10000):
-  """Reads a CSV file in chunks of specified size.
-
-  Args:
-    file_path: Path to the CSV file.
-    chunk_size: Number of rows to read at a time.
-
-  Yields:
-    A list of rows for each chunk.
-  """
-
-  with open(file_path, 'r') as csvfile:
-    reader = csv.reader(csvfile)
-
-    # # Skip the header
-    # next(reader)
-
-    chunk = []
-    first_row=True
-    for row in reader:
-      # paragraphs: convert back to list
-      if not first_row:
-          row[2] = json.loads(row[2])
-      else:
-          first_row=False
-      chunk.append(row)
-      if len(chunk) >= chunk_size:
-        yield chunk
-        chunk = []
-    
-    if chunk:  # Handle the last chunk if not empty
-      yield chunk
-
-
-if __name__ == '__main__':
-    file_path = '/content/drive/MyDrive/Research/datasets/crawled_data/crawled_data.csv'
-    chunk_size = 100  # 10000
-
-    # Example usage:
-    for chunk in load_data(file_path, chunk_size):
-        # .............................................
-        '''
-        * code to Process each chunk of data here
-        * each chunk is list of list.
-        * format of inner list of chunk is is: ['parent_url', 'page_title', 'paragraph']
-
-        e.g.
-        chunk = [
-          ['https://www.bbc.com/nepali','मुख पृष्ठ - BBC News नेपाली', 'सुर्खेत र जुम्लामा बाहेक कर्णालीका अरू जिल्लामा शिशुका लागि आवश्यक एनआईसीयू सेवा नै उपलब्ध छैन।'],
-          ['https://www.bbc.com/nepali', 'मुख पृष्ठ - BBC News नेपाली', 'नेपालले करिब एक महिना अघि नै औपचारिक पत्र पठाएर जीबी राईलाई स्वदेश फर्काइदिन गरेको आग्रहबारे मलेशियाले कुनै औपचारिक जबाफ दिएको छैन।'],
-          ...
-        ]
-
-        '''
-
-        # .............................................
-        print(f' columns : {chunk[0]}')
-
-        # First row
-        url = chunk[1][0]
-        title = chunk[1][1]
-        paragraphs = chunk[1][2]
-        print(f' row-1: url:{url},  title:{title}, \n paragraphs: {paragraphs}')
-
-        # do processing stuff
-        break