カクヨムのランキングからタイトル・★の数・評価者数をcsv出力するpythonスクリプト

kakuyomu_star.py

# ★の数/評価者数で割って平均値を知りたかった

import requests
from bs4 import BeautifulSoup
import csv
import time

# ひとまず300位まで
page_fetch_limit = 3

# ランキングから小説の固有ID一覧を抽出
def fetch_book_identifiers(page_num: int):
    r = requests.get("https://kakuyomu.jp/rankings/all/entire?page=" + str(page_num))
    soup = BeautifulSoup(r.content, "html.parser")
    
    # ID抽出
    links = soup.find_all("a", "widget-workCard-titleLabel bookWalker-work-title")

    def extract_id(raw_link):
        link = raw_link.get("href").replace("/works/", "")
        return link

    ids = map(extract_id, links)

    return ids

# 1本の小説の評価情報を抜き出し
def fetch_book_review_information(id: int):
    r = requests.get("https://kakuyomu.jp/works/" + str(id) + "#reviews")
    soup = BeautifulSoup(r.content, "html.parser")
    
    # タイトル
    title = soup.find("h1", id="workTitle").a.text

    # ★の数
    raw_points = soup.find("span", "js-total-review-point-element").text
    points = int(raw_points.replace(",", ""))

    # 評価した人の数
    raw_reviewer_count = soup.find("span", "js-review-count-element").text
    reviewer_count = int(raw_reviewer_count.replace(",", ""))

    return [
        title,
        points,
        reviewer_count
    ]

f = open('book_reviews.csv', 'w')
writer = csv.writer(f, lineterminator='\n')

for i in range(page_fetch_limit):

    # 小説のIDを取得
    ids = fetch_book_identifiers(i+1)

    # csv
    for id in ids:
        review_info = fetch_book_review_information(id)
        writer.writerow(review_info)
        
        print("proceeded: " + review_info[0])

f.close()