helper.py

import csv
import os
import datetime
import matplotlib.pyplot as plt
import numpy as np
import page_retrival as page
import sql_commands as sql


def list_change(price_list):  # PRODS DELETE
    # Transposing the list so prices in the same category are in a list.
    return [[i[index] for i in price_list] for index in range(len(price_list[0]))]


def draw_graph(price_list, lst, date):
    # Draws graph
    colours = ["--b.", "--r.", "--g.", "--c.", "--m.", "--y.", "--k."]

    try:
        price_list = list_change(price_list)
    except TypeError:
        print("Single list")

    # x_axis = np.array(date)
    y_axis = np.array(price_list)

    for i in range(len(price_list)):
        plt.plot(date, y_axis[i], colours[i], label=lst[i])
    plt.legend()

    print('Press any key to close')
    while True:
        if plt.waitforbuttonpress():
            break
    plt.close()


def get_links():
    # gets links from user
    link_list, title_list = [], []

    file_name = input("Enter name of graph: ")
    linked_accounts = int(input("Enter amount of items you wanna be tracked: "))

    for _ in range(linked_accounts):
        url = input("Enter Amazon item URL (page of item you wanna track): ")
        links = url.rsplit("/", 1)[0]  # Removes unnecessary link lenght
        # ^ (NEED TO DO A CHECK IF ITS ALREADY SHORT)
        link_list.append(links)

        item_name = input("Enter name of Item: ")
        title_list.append(item_name)

    return link_list, title_list, file_name


def initialise_data_graph(links, prices, file_name, items, date):
    # Store Data for graph in CSV
    sql.add_following(file_name)

    for price, item in zip(prices, items):
        sql.add_items(file_name, item, price, date)

    for item, link in zip(items, links):
        sql.add_links(item, link)


def load(name):
    # gets data from folder and update if needed
    file = open(f'following/{name}.csv', 'r', encoding='UTF-8') # (CHANGE TO SQL STUFF)
    reader = csv.reader(file)

    all_prices, graph_name, url, item_date, new_price = [], [], [], [], None
    index = 0

    # Get all info (CHANGE TO SQL STUFF)
    for line in reader:
        price = []
        index += 1
        if index == 1:  # Links to find new prices
            url = line.copy()

        elif index == 2:  # get name always stored on line 2
            graph_name = line.copy()

        else:  # line 3 onwards are all the price from old on top to new at the very bottom
            price = line.copy()
            item_date.append(price[-1])
            price.remove(price[-1])
            all_prices.append(price)

    file.close()

    # Doesn't need to retrieve data if date is in file
    current_date = datetime.datetime.now().strftime('%d/%m/%Y')
    if current_date not in item_date:
        print('Retrieving new data')
        new_price, new_date = page.get_prices(url)

    # Converst prices from str to float (CHANGE TO SQL STUFF)
    for line_index, line in enumerate(all_prices):
        for price_index, price in enumerate(line):
            all_prices[line_index][price_index] = float(price)

    # Checks new prices and if its in the prices are the same to file
    if not new_price or new_price == all_prices[-1]:
        print("Drawing")
        draw_graph(all_prices, graph_name, item_date)

    else: # (CHANGE TO SQL STUFF)
        with open(f'following/{name}.csv', 'a', newline='', encoding='UTF-8') as file: 
            writer = csv.writer(file)
            print("Adding new_price to all_prices and updating the file")
            store_price = new_price.copy()  # Make a copy to avoid modifying new_price
            store_price.append(new_date)
            writer.writerow(store_price)

        load(name)


def delete(name):
    # Deletes anything that it wants to follow
    if os.path.exists(f'following/{name}.csv'):
        os.remove(f'following/{name}.csv')
        print(f'Deleted {name}')