Pulling & Reading Date from UDF that Compare it to Live Data

[snippsat]

This will just iterate over all rows,and return only last row.

def readfile(filepath):
  
    with open(r'C:\Users\...\Desktop\AAPLcsv.csv', 'r') as file:
        reader = csv.reader(file)
        next(reader, None)#skip header
        for index, row in enumerate(reader):
            return row

Have to collect all row in list before return.

def readfile(filepath=''):
    apple_stock = []
    with open('apple.csv', 'r') as file:
        reader = csv.reader(file)
        next(reader, None)#skip header
        for index, row in enumerate(reader):
            apple_stock.append(row)
    return apple_stock

To do a test made apple.csv:

Output:
header
2,Name,a,1
1,John,b,204.4444
2,Eric,c,200.2899932861328
3,Brad,d,177.9499969482422

Added count and show live price.

#import all necessary modules
import csv
from yahoo_fin import stock_info as live
import pandas as pd
from datetime import date
import datetime

def readfile(filepath=''):
    apple_stock = []
    with open('apple.csv', 'r') as file:
        reader = csv.reader(file)
        next(reader, None)#skip header
        for index, row in enumerate(reader):
            apple_stock.append(row)
    return apple_stock

if __name__ == "__main__":
    #get Apple's latest quote price
    path = r'apple.csv'
    price = live.get_live_price("AAPL")
    count = 0
    for index, row in enumerate(readfile(path)):
        if float(row[3]) < price:
            print(row[3])
            count += 1
    print('-' * 10)
    print(f'Live price now is: {price} count below from {path} is: {count}')

Output:
1
200.2899932861328
177.9499969482422
----------
Live price now is: 202.58999633789062 count below from apple.csv is: 3