import pandas as pd
import requests

from bs4 import BeautifulSoup
from datetime import datetime, timedelta
from time import sleep
from typing import Generator

def convert_datetime_to_url_format(date: datetime) -> str:
    return date.strftime("%b%d.%Y").lower()

def scrape_news(date: datetime) -> pd.DataFrame:
    base_url = "https://www.forexfactory.com/calendar"
    formatted_date = convert_datetime_to_url_format(date)
    url = f"{base_url}?day={formatted_date}"

    # Set headers to mimic a web browser.
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)"
    }

    response = requests.get(url, headers=headers)
    if response.status_code != 200:
        print(f"Failed to retrieve news. Status code: {response.status_code}")
        return

    soup = BeautifulSoup(response.text, 'html.parser')
    rows = soup.find_all("tr", class_="calendar__row")

    previous_time = None

    times = []
    currencies = []
    titles = []

    for row in rows:
        try:
            time = row.find("td", class_="calendar__cell calendar__time").text.strip()
            currency = row.find("td", class_="calendar__cell calendar__currency").text.strip()
            title = row.find("span", class_="calendar__event-title").text.strip()

            # If the time is not present, use the previous time.
            if not time:
                time = previous_time
            else:
                previous_time = time

            print(f"Time: {time}")
            print(f"Currency: {currency}")
            print(f"Title: {title}")
            print("---------------------------")

            times.append(time)
            currencies.append(currency)
            titles.append(title)
        except AttributeError:
            print("Failed to scrape the row")
            continue
    news_data = pd.DataFrame({"Time": times, "Currency": currencies, "Title": titles})
    news_data['Date'] = date.strftime('%Y-%m-%d')
    news_data = news_data[['Date', 'Time', 'Currency', 'Title']]
    return news_data

def scrape_news_in_range(start_date: datetime, end_date: datetime) -> Generator[pd.DataFrame, None, None]:
    current_date = start_date
    while current_date <= end_date:
        print(f"Scraping data for {current_date.date}")
        news_data = scrape_news(current_date)
        yield news_data
        current_date += timedelta(days=1)
        sleep(3) # Play nice with the server.

if __name__ == '__main__':
    start_date = datetime(2023, 10, 25)
    end_date = datetime(2023, 10, 25)
    scrape_news_in_range(start_date, end_date)
    for news_data in scrape_news_in_range(start_date, end_date):
        print(news_data)