ebay_price_tracker.py

from bs4 import BeautifulSoup
import requests 
import numpy as np
import csv
from datetime import datetime

LINK = "https://www.ebay.co.uk/sch/i.html?_from=R40&_trksid=p2380057.m570.l1313&_nkw=m1+macbook+air&_sacat=0"


def get_prices_by_link(link):
    # get source
    r = requests.get(link)
    # parse source
    page_parse = BeautifulSoup(r.text, 'html.parser')
    # find all list items from search results
    search_results = page_parse.find("ul",{"class":"srp-results"}).find_all("li",{"class":"s-item"})

    item_prices = []

    for result in search_results:
        price_as_text = result.find("span",{"class":"s-item__price"}).text
        if "to" in price_as_text:
            continue
        price = float(price_as_text[1:].replace(",",""))
        item_prices.append(price)
    return item_prices

def remove_outliers(prices, m=2):
    data = np.array(prices)
    return data[abs(data - np.mean(data)) < m * np.std(data)]

def get_average(prices):
    return np.mean(prices)

def save_to_file(prices):
    fields=[datetime.today().strftime("%B-%D-%Y"),np.around(get_average(prices),2)]
    with open('prices.csv', 'a', newline='') as f:
        writer = csv.writer(f)
        writer.writerow(fields)

if __name__ == "__main__":
    prices = get_prices_by_link(LINK)
    prices_without_outliers = remove_outliers(prices)
    print(get_average(prices_without_outliers))
    save_to_file(prices)