roce_bsoup_old.py

import requests
from datetime import datetime
from bs4 import BeautifulSoup

operating_income_or_loss_keys = []
operating_income_or_loss_values = []
year = input("Enter your year: ")


def get_operating_income_or_loss(soup):
    for rows in soup.find_all("div", {"class": "D(tbr)"}):
        for date_row in rows.find_all("div", {"class": "D(ib)"}):
            if date_row.text == "Breakdown":
                chart_dates = date_row.find_all_next("span", limit=5)
                for dates in chart_dates[2:]:
                    reformatted_date = datetime.strptime(
                        dates.text, "%m/%d/%Y"
                    ).strftime("%m%d%Y")
                    operating_income_or_loss_keys.append(reformatted_date)

        for sub_row in rows.find_all("div", {"class": "D(tbc)"}):
            for row_item in sub_row.find_all("span", {"class": "Va(m)"}):
                if row_item.text == "Operating Income or Loss":
                    operating_income_or_loss = row_item.find_all_next("span", limit=4)
                    for item in operating_income_or_loss[1:]:
                        operating_income_or_loss_values.append(item.text)
    return


total_assets_values = []
total_current_liabilities = []
balance_sheet_keys = []


def get_total_assets(soup):
    for rows in soup.find_all("div", {"class": "D(tbr)"}):
        for date_row in rows.find_all("div", {"class": "D(ib)"}):
            if date_row.text == "Breakdown":
                chart_dates = date_row.find_all_next("span", limit=4)
                for dates in chart_dates[1:]:
                    print(dates)
                    reformatted_date = datetime.strptime(
                        dates.text, "%m/%d/%Y"
                    ).strftime("%m%d%Y")
                    balance_sheet_keys.append(reformatted_date)

    for rows in soup.find_all("div", {"class": "D(tbr)"}):
        for sub_row in rows.find_all("div", {"class": "D(tbc)"}):
            for row_item in sub_row.find_all("span", {"class": "Va(m)"}):
                if row_item.text == "Total Assets":
                    total_assets = row_item.find_all_next("span", limit=3)
                    for item in total_assets:
                        total_assets_values.append(item.text)
    return


def get_total_current_liabilities(soup):
    for rows in soup.find_all("div", {"class": "D(tbr)"}):
        for sub_row in rows.find_all("div", {"class": "D(tbc)"}):
            for row_item in sub_row.find_all("span", {"class": "Va(m)"}):
                if row_item.text == "Total Current Liabilities":
                    current_liabilities = row_item.find_all_next("span", limit=3)
                    for item in current_liabilities:
                        total_current_liabilities.append(item.text)
    return


urls = [
    "https://finance.yahoo.com/quote/AAPL/balance-sheet?p=AAPL",
    "https://finance.yahoo.com/quote/AAPL/financials?p=AAPL",
]

for url in urls:
    if "balance-sheet" in url:
        response = requests.get(url)
        soup = BeautifulSoup(response.text, "html.parser")
        get_total_assets(soup)
        get_total_current_liabilities(soup)
        balance_sheet_dict = {
            k: v
            for k, v in zip(
                balance_sheet_keys, zip(total_assets_values, total_current_liabilities)
            )
        }
        print(balance_sheet_dict)
        # output{'09292018': ('365,725,000', '116,866,000'), '09292017': ('375,319,000', '100,814,000'), '09292016': ('321,686,000', '79,006,000')}

    elif "financials" in url:
        response = requests.get(url)
        soup = BeautifulSoup(response.text, "html.parser")
        get_operating_income_or_loss(soup)
        financials_dict = {
            k: v
            for k, v in zip(
                operating_income_or_loss_keys, operating_income_or_loss_values
            )
        }
        print(financials_dict)
        # output{'09292018': '70,898,000', '09292017': '61,344,000', '09292016': '60,024,000'}

for key, values in balance_sheet_dict.items():
    if key.endswith("{}".format(year)):
        total_asset = values[0]
        current_liabilities = values[1]
        balance_sheet_keys = values[0]
        print(
            f"Year: {key}, Total assets: {total_asset}, Total current liabilities: {current_liabilities}, Operating Income or Loss: {balance_sheet_keys}"
        )
        # output Year: 09292016, Total assets: 321,686,000, Total current liabilities: 79,006,000