Portfolio/Python_Scripts/PriceTracker/PriceTracker2.py

65 lines
1.6 KiB
Python

import smtplib
import pandas as pd
import requests
from bs4 import BeautifulSoup
from price_parser import Price
PRODUCT_URL_CSV = "products.csv"
SAVE_TO_CSV = True
PRICES_CSV = "prices.csv"
SEND_MAIL = True
def Get_URLs(csv_file):
df = pd.read_csv(csv_file)
return df
def Process_Products(df):
for product in df.to_dict("records"): # product["url"] is the URL
pass
def Get_Response(url):
response = requests.get(url)
return response.text
def Get_Price(html):
soup = BeautifulSoup(html, "lmxl")
el = soup.select_one(".price_color")
price = price.fromstring(el.text)
return price.amount_float
# Overload the function
def Process_Products(df):
updated_products = []
for product in df.to_dict("records"):
html = Get_Response(product["url"])
product["price"] = Get_Price(html)
product["alert"] = product["price"] < product["alert_price"]
updated_products.append((product))
return pd.DataFrame(updated_products)
def Get_Mail(df):
subject = "Price Drop Alert"
body = df[df["alert"]].to_string()
subject_and_message = f'Subject:{subject}\n\n{body}'
return subject_and_message
def Send_Mail(df):
message_text = get_mail(df)
with smtplib.SMTP("smtp.server.address", 587) as smtp:
smtp.starttls()
smtp.login(mail_user, mail_to, message_text)
def main():
df = Get_URLs(PRODUCT_URL_CSV)
df_updated = Process_Products(df)
if SAVE_TO_CSV:
df_updated.to_csv(PRICES_CSV, index=False, mode = "a")
if SEND_MAIL:
Send_Mail(df_updated)