[러닝-인강] Globa-Rates #5

import requests
import re
from bs4 import BeautifulSoup

def scraping():
    p = re.compile(r"\xa0")

    url = "https://www.global-rates.com/en/interest-rates/libor/american-dollar/usd-libor-interest-rate-3-months.aspx"
    resp = requests.get(    url   )
    soup = BeautifulSoup(resp.text, 'html5lib')

    # 금리 스크래핑
    selector = "form table tbody tr td table tbody tr td table tbody tr:nth-child(1) td:nth-child(1) table tbody tr td:nth-child(2)"
    result = soup.select(   selector )
    value = [ p.sub('', x.text.strip()[:-1]) for x in result[1:] ]

    # 날짜 스크래핑
    selector = "form table tbody tr td table tbody tr td table tbody tr:nth-child(1) td:nth-child(1) table tbody tr td:nth-child(1)"
    result = soup.select(   selector )
    date = [ p.sub('', x.text.replace(' ', '-')) for x in result[4:14] ]

    # 딕셔너리로 저장
    data = {     }
    for i in range(len(date)):
        data[ date[i] ] = value[i]
    return data

def read_database(filename):
    try:
        f = open(filename, "r")
        lines = f.readlines()

        # 리스트를 딕셔너리로 변환
        data = {  }
        for line in lines:
            k, v = line.split(' ')
            data[k] = v.replace('\n', '')
        return data

    except FileNotFoundError:
        return [ ]

def write_database(filename, data):
    f = open(filename, "w")
    for k, v in data.items():
        f.write(f"{k} {v}" + "\n")

# ------------------------------------------------------------------

data = read_database("result.txt")

newcommer = scraping()
data.update(newcommer)

write_database("result.txt", data)