python - 改进股票市场算法

Question

我试图让这段代码对在我的 GitHub 帐户上查看它的潜在雇主更具吸引力。该代码本质上是循环遍历一个 CSV 文件，并使用 yfinance 包装器搜索每个符号以查找 Yahoo-Finance API。它对股票进行一些检查并决定它是否是合适的投资。有很多 try except 子句，因为 API 可以在 pandas 数据框中返回空字段。目前我认为它可以改进，因为它有多个嵌套的 if 语句和许多 try except 语句。非常感谢所有反馈。

import yfinance as yf
import pandas as pd
import openpyxl
import csv
import math
import traceback

# Not a penny stock
# Earnings increase of at least 33% over 10 years using 3 year averages - 10% over 4 years since the API only contains the most recent 4 years
# Current price no more than 1.5x book value per share
# P/E ratio <= 15
# Long term debt no more than 110% current assets
# Current assets 1.5x current liabilities 

symbol_array = []
failed_search = []

with open('companylist.csv') as file:
    reader = csv.reader(file)

    ticker_data = iter(reader) # skip the first value since it is the header
    next(ticker_data)

    for row in ticker_data:
        ticker = row[0]
        print('Searching: ', ticker)

        try:
            try:
                company = yf.Ticker(ticker)
                company_info = company.info 
            except:
                print('Not a company')
                continue # skip the ticker since it is not a company or the API doesn't have any information about the security

            company_balance_sheet = company.balance_sheet
            company_earnings = company.earnings

            if company_balance_sheet.empty or company_earnings.empty:
                continue # if balance sheets or earnings reports are not available, skip the search

            column_date = company.balance_sheet.columns[0] # latest date on balance sheet to take data from

            current_assets = company.balance_sheet.at['Total Current Assets', column_date]

            try: # previous close price can be under 'previousClose' or 'regularMarketPrice' in company_info
                current_price = company_info['previousClose'] 
            except:
                current_price = company_info['regularMarketPrice']

            if current_price >= 10: # check if stock is penny stock 

                try:
                    long_term_debt = company.balance_sheet.at['Long Term Debt', column_date]
                    if math.isnan(long_term_debt):
                        long_term_debt = 0
                except:
                    long_term_debt=0

                if long_term_debt < (current_assets * 1.1):
                    
                    current_liabilities = company.balance_sheet.at['Total Current Liabilities', column_date]
                    
                    if current_liabilities < (1.5 * current_assets):

                        try:
                            pe_ratio = company_info['trailingPE'] # check if P/E ratio is available, assign pe_ratio 0 if it is not
                        except:
                            pe_ratio = 0


                        if pe_ratio <= 15:

                            try:    
                                book_value = company_info['bookValue']
                                if type(book_value) != float: # book_value can be "None" in the company_info object
                                    book_value = 0
                            except:
                                book_value = 0
                            
                            if current_price < (book_value*1.5):
                                earnings_first = company.earnings.iat[0, 1]
                                earnings_last = company.earnings.iat[len(company.earnings)-1, 1]

                                if earnings_last >= earnings_first*1.1:
                                    symbol_array.append(company_info['symbol'])
                                
                                else:
                                    print('Step 6 fail. Earnings growth too low')

                            else:
                                print('Step 5 fail. Current price too high')

                        else:
                            print('Step 4 fail. P/E ratio too high')

                    else:
                        print('Step 3 fail. Current liabilities too high')

                else:
                    print('Step 2 fail. Long term debt too high')

            else:
                print('Step 1 fail. Penny stock')

        except Exception as e:
            print(traceback.format_exc()) # code to point out any errors in the main try statement
            failed_search.append(ticker)
            print(ticker, ' failed to search.')
            print(e)

print('Failed searches:')
for failure in failed_search:
    print(failure)

print('Potential Investments:')

for symbol in symbol_array:
    print(symbol)