#!/usr/bin/env python # vim:fileencoding=utf-8 # License: GPLv3 Copyright: 2015, Kovid Goyal import json from pprint import pprint from calibre.ebooks.BeautifulSoup import BeautifulSoup from calibre.web.feeds.news import BasicNewsRecipe use_wayback_machine = False def absolutize(url): if url.startswith('/'): url = 'https://www.nytimes.com' + url return url class NewYorkTimesBookReview(BasicNewsRecipe): title = u'New York Times Book Review' language = 'en_US' description = 'The New York Times Sunday Book Review' __author__ = 'Kovid Goyal' no_stylesheets = True no_javascript = True ignore_duplicate_articles = {'title', 'url'} encoding = 'utf-8' extra_css = ''' .byl, .time { font-size:small; color:#202020; } .cap { font-size:small; text-align:center; } .cred { font-style:italic; font-size:small; } em, blockquote { color: #202020; } .sc { font-variant: small-caps; } .lbl { font-size:small; color:#404040; } img { display:block; margin:0 auto; } ''' articles_are_obfuscated = use_wayback_machine if use_wayback_machine: def get_obfuscated_article(self, url): from calibre.ptempfile import PersistentTemporaryFile with PersistentTemporaryFile() as tf: tf.write(self.get_nyt_page(url)) return tf.name @property def nyt_parser(self): ans = getattr(self, '_nyt_parser', None) if ans is None: from calibre.live import load_module self._nyt_parser = ans = load_module('calibre.web.site_parsers.nytimes') return ans def get_nyt_page(self, url, skip_wayback=False): if use_wayback_machine and not skip_wayback: from calibre import browser return self.nyt_parser.download_url(url, browser()) return self.index_to_soup(url, raw=True) def preprocess_raw_html(self, raw_html, url): return self.nyt_parser.extract_html(self.index_to_soup(raw_html), url) recipe_specific_options = { 'res': { 'short': ( 'For hi-res images, select a resolution from the following\noptions: ' 'popup, jumbo, mobileMasterAt3x, superJumbo' ), 'long': ( 'This is useful for non e-ink devices, and for a lower file size\nthan ' 'the default, use mediumThreeByTwo440, mediumThreeByTwo225, articleInline.' ), }, 'comp': { 'short': 'Compress News Images?', 'long': 'enter yes', 'default': 'no' } } def __init__(self, *args, **kwargs): BasicNewsRecipe.__init__(self, *args, **kwargs) c = self.recipe_specific_options.get('comp') if c and isinstance(c, str): if c.lower() == 'yes': self.compress_news_images = True def parse_index(self): # return [('Articles', [{'url': 'https://www.nytimes.com/2022/09/08/books/review/karen-armstrong-by-the-book-interview.html', 'title':'test'}])] soup = self.index_to_soup('https://www.nytimes.com/pages/books/review/index.html') # with open('/t/raw.html', 'w') as f: f.write(str(soup)) feeds = parse_toc(soup) for section_title, articles in feeds: self.log(section_title) for a in articles: self.log('\t' + a['title'], a['url']) return feeds def get_browser(self, *args, **kwargs): kwargs['user_agent'] = 'User-Agent: Mozilla/5.0 (compatible; archive.org_bot; Wayback Machine Live Record; +http://archive.org/details/archive.org_bot)' br = BasicNewsRecipe.get_browser(self, *args, **kwargs) return br def preprocess_html(self, soup): w = self.recipe_specific_options.get('res') if w and isinstance(w, str): res = '-' + w for img in soup.findAll('img', attrs={'src':True}): if '-article' in img['src']: ext = img['src'].split('?')[0].split('.')[-1] img['src'] = img['src'].rsplit('-article', 1)[0] + res + '.' + ext for c in soup.findAll('div', attrs={'class':'cap'}): for p in c.findAll(['p', 'div']): p.name = 'span' return soup def asset_to_article(asset): title = asset['headline']['default'] return {'title': title, 'url': asset['url'], 'description': asset['summary']} def preloaded_data(soup): from calibre.web.site_parsers.nytimes import clean_js_json candidates = soup.find_all('script', string=lambda x: x and 'window.__preloadedData' in x) script = candidates[0] script = str(script) raw = script[script.find('{') : script.rfind(';')].strip().rstrip(';') # } raw = clean_js_json(raw) return json.JSONDecoder(strict=False).raw_decode(raw)[0]['initialState'] def parse_toc(soup): data = preloaded_data(soup) # with open('/t/raw.json', 'w') as f: pprint(data, stream=f) article_map = {} for k, v in data.items(): if v['__typename'] == 'Article': article_map[k] = asset_to_article(v) feeds = [] for k, v in data['ROOT_QUERY'].items(): if k.startswith('workOrLocation'): for g in data[v['__ref']]['groupings']: for c in g['containers']: articles = [] for r in c['relations']: ref = r['asset']['__ref'] if ref in article_map: articles.append(article_map[ref]) if articles: feeds.append(('Highlights', articles)) articles = [] for k, v in data['ROOT_QUERY'].items(): if k.startswith('workOrLocation'): c = data[v['__ref']] section_title = c['name'] for k, v in c['collectionsPage'].items(): if k.startswith('stream'): for k, v in v.items(): if k.startswith('edges'): for q in v: r = q['node']['__ref'] if r.startswith('Article:'): articles.append(article_map[r]) if not articles: for c in c['collectionsPage']['embeddedCollections']: for e in c['stream']['edges']: for k, v in e.items(): if k.startswith('node'): articles.append(article_map[v['__ref']]) feeds.append((section_title, articles)) return feeds if __name__ == '__main__': import sys with open(sys.argv[-1]) as f: html = f.read() soup = BeautifulSoup(html) feeds = parse_toc(soup) pprint(feeds)