Delete tariff_scraper.py

tariff_scraper.py

@@ -1,66 +0,0 @@
-import requests
-from bs4 import BeautifulSoup
-import pandas as pd
-
-# Define the URL for PESCO tariff rates
-TARIFF_URLS = {
-    "IESCO": "https://iesco.com.pk/index.php/customer-services/tariff-guide"
-}
-
-def scrape_tariff_data_to_csv(url, output_file="tariff_data.csv"):
-    """
-    Scrape tariff data from the given URL and save it to a CSV file.
-
-    Args:
-        url (str): The URL of the tariff page to scrape.
-        output_file (str): The name of the CSV file to save data.
-
-    Returns:
-        str: The name of the CSV file if successful, or an error message.
-    """
-    try:
-        # Send an HTTP GET request to the specified URL
-        response = requests.get(url, headers={"User-Agent": "Mozilla/5.0"})
-        response.raise_for_status()  # Raise an error for HTTP issues
-
-        # Parse the webpage content using BeautifulSoup
-        soup = BeautifulSoup(response.text, 'html.parser')
-
-        # Extract table rows
-        tariff_table = soup.find('table')
-        if not tariff_table:
-            return "No table found on the webpage."
-
-        # Extract rows and normalize column counts
-        data = []
-        max_columns = 0
-        table_rows = tariff_table.find_all('tr')
-        for row in table_rows:
-            cols = [col.get_text(strip=True) for col in row.find_all(['th', 'td'])]
-            max_columns = max(max_columns, len(cols))
-            data.append(cols)
-
-        # Normalize rows to have the same number of columns
-        normalized_data = [row + [''] * (max_columns - len(row)) for row in data]
-
-        # Save the data to a CSV file
-        df = pd.DataFrame(normalized_data[1:], columns=normalized_data[0])  # Use the first row as headers
-        df.to_csv(output_file, index=False)
-
-        return output_file
-    except requests.exceptions.RequestException as e:
-        # Handle request errors (e.g., connection issues, timeout)
-        return f"Request error: {e}"
-    except Exception as e:
-        # Handle other potential errors
-        return f"An unexpected error occurred: {e}"
-
-if __name__ == "__main__":
-    # Test the scraper and save data to a CSV file
-    url = TARIFF_URLS["IESCO"]
-    output_file = "iesco_tariff_data.csv"
-    result = scrape_tariff_data_to_csv(url, output_file)
-    if result.endswith(".csv"):
-        print(f"Data successfully saved to {output_file}")
-    else:
-        print(f"Error: {result}")