Upload scrapy_engine/load_data.py with huggingface_hub

scrapy_engine/load_data.py

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+# 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