scrapper.py

import os
from datetime import datetime
import pandas as pd


BASE_URL = "https://www.zse.co.zw/price-sheet/"


def fetch_data_from_url(url):
    """
    Fetch the market prices from the Zimbabwe Stock Exchange Website
    """
    try:
        response = pd.read_html(url, skiprows=1)

        dataframe = response[0][3:]

        # The response has 8 columns but only concerned with few

        dataframe.columns = [
            "Name",
            "None",
            "None",
            "Opening_Price",
            "Closing_Price",
            "Volume_Traded",
        ]

        # Lets filter the columns we are concerned with
        df_trades = dataframe[
            ["Name", "Opening_Price", "Closing_Price", "Volume_Traded"]
        ]
        # Drop all the columns with no data or missing all data
        dataframe = df_trades.dropna(how="all").set_index("Name")
    except Exception as e:
        pass

    return dataframe


def current_date():
    """
    Generate the current date for use in saving the price sheet
    """
    now = datetime.now()
    current_date = now.strftime("%m-%d-%Y")
    return current_date


def check_or_create_directory(dataframe, current_date):
    """
    Create or save in the folder with other files
    """
    os.makedirs("csv-daily-pricesheets", exist_ok=True)
    # Save the data into both the CSV and Excel folders
    dataframe.to_csv(f"csv-daily-pricesheets/{current_date}.csv")
    dataframe.to_csv(f"xls-daily-price-sheets/{current_date}.xlsx")


def main():
    dataframe = fetch_data_from_url(BASE_URL)
    check_or_create_directory(dataframe, current_date())


if __name__ == "__main__":
    main()