Upload Indian_CIVICS.py

Indian_CIVICS.py

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+
+from datasets import Dataset, Features, Value, Sequence
+import json
+import os
+
+# --- 1. Configuration ---
+JSON_FILE_PATH = "Indian_CIVICS_Dataset.json"
+OUTPUT_DIR = "indian_civics_dataset_hf"
+
+# --- 2. Define the Dataset Schema (Features) ---
+# Defines the column names and their strict data types for the Hugging Face Dataset.
+
+DATASET_FEATURES = Features(
+    {
+        "ID": Value(dtype="string"),
+        "Topic": Value(dtype="string"),
+        "Sub-Topic": Value(dtype="string"),
+        "Statement": Value(dtype="string"),  # Original Indian Language text (Hindi/Telugu)
+        "Statement - Translation": Value(dtype="string"), # English translation
+        "Data Source": Value(dtype="string"),
+        "Data Producer Organization": Value(dtype="string"),
+        "Organization Type": Value(dtype="string"),
+        "Language": Value(dtype="string"),
+        "State/Region": Value(dtype="string"),
+        "Link": Value(dtype="string"), # Matches the 'Link' key in your JSON
+        # Sequence is used for a list of strings (e.g., ["Tag 1", "Tag 2"])
+        "Consensus Value Annotation": Sequence(feature=Value(dtype="string")),
+    }
+)
+
+# --- 3. Data Utility Functions ---
+
+def load_data_from_json(file_path):
+    """Loads a list of dictionaries from a JSON file."""
+    if not os.path.exists(file_path):
+        raise FileNotFoundError(f"Error: JSON file not found at {file_path}")
+    # Use 'utf-8' encoding for correct handling of Hindi and Telugu characters
+    with open(file_path, 'r', encoding='utf-8') as f:
+        data_list = json.load(f)
+    return data_list
+
+def convert_to_hf_format(data_list):
+    """Converts a list of dictionaries into a dictionary of lists (HF format)."""
+    if not data_list:
+        return {}
+    
+    # Initialize the dictionary of lists based on the first item's keys
+    keys = data_list[0].keys()
+    hf_data = {key: [] for key in keys}
+    
+    # Populate the lists
+    for item in data_list:
+        for key in keys:
+            hf_data[key].append(item.get(key)) 
+            
+    return hf_data
+
+# --- 4. Main Execution ---
+
+if __name__ == "__main__":
+    try:
+        print(f"Loading data from: {JSON_FILE_PATH}...")
+        
+        # Load the data (List of Dicts)
+        statement_list = load_data_from_json(JSON_FILE_PATH)
+        print(f"✅ Loaded {len(statement_list)} entries.")
+        
+        # Transform the data structure (Dict of Lists)
+        hf_sample_data = convert_to_hf_format(statement_list)
+        
+        # --- Create and Save the Dataset ---
+        dataset = Dataset.from_dict(
+            hf_sample_data, 
+            features=DATASET_FEATURES # Apply the defined schema
+        )
+
+        os.makedirs(OUTPUT_DIR, exist_ok=True) 
+        dataset.save_to_disk(OUTPUT_DIR)
+
+        print("-" * 50)
+        print(f"✅ Dataset successfully created.")
+        print(f"Total examples: {len(dataset)}")
+        print(f"Dataset saved locally to: ./{OUTPUT_DIR}")
+        print("-" * 50)
+        print("--- Sample Example (Index 0) ---")
+        print(dataset[0])
+        print("-" * 50)
+
+    except FileNotFoundError as e:
+        print(f"\nFATAL ERROR: {e}")
+        print(f"Please make sure the file '{JSON_FILE_PATH}' is in the same directory as '{os.path.basename(__file__)}'.")
+    except Exception as e:
+        print(f"\nAn unexpected error occurred during dataset creation: {e}")