The World Ahead (Economist)

recipes/economist_world_ahead.recipe

@@ -0,0 +1,345 @@
+#!/usr/bin/env  python
+# License: GPLv3 Copyright: 2008, Kovid Goyal <kovid at kovidgoyal.net>
+
+try:
+    from http.cookiejar import Cookie
+except ImportError:
+    from cookielib import Cookie
+
+import json
+from html5_parser import parse
+from lxml import etree
+from collections import defaultdict
+
+from calibre import replace_entities
+from calibre.ebooks.BeautifulSoup import NavigableString, Tag
+from calibre.utils.date import parse_only_date
+from calibre.web.feeds.news import BasicNewsRecipe
+
+
+def E(parent, name, text='', **attrs):
+    ans = parent.makeelement(name, **attrs)
+    ans.text = text
+    parent.append(ans)
+    return ans
+
+
+def process_node(node, html_parent):
+    ntype = node.get('type')
+    if ntype == 'tag':
+        c = html_parent.makeelement(node['name'])
+        c.attrib.update({k: v or '' for k, v in node.get('attribs', {}).items()})
+        html_parent.append(c)
+        for nc in node.get('children', ()):
+            process_node(nc, c)
+    elif ntype == 'text':
+        text = node.get('data')
+        if text:
+            text = replace_entities(text)
+            if len(html_parent):
+                t = html_parent[-1]
+                t.tail = (t.tail or '') + text
+            else:
+                html_parent.text = (html_parent.text or '') + text
+
+
+def safe_dict(data, *names):
+    ans = data
+    for x in names:
+        ans = ans.get(x) or {}
+    return ans
+
+
+class JSONHasNoContent(ValueError):
+    pass
+
+
+def load_article_from_json(raw, root):
+    # open('/t/raw.json', 'w').write(raw)
+    try:
+        data = json.loads(raw)['props']['pageProps']['content']
+    except KeyError as e:
+        raise JSONHasNoContent(e)
+    if isinstance(data, list):
+        data = data[0]
+    body = root.xpath('//body')[0]
+    for child in tuple(body):
+        body.remove(child)
+    article = E(body, 'article')
+    E(article, 'h4', data['subheadline'], style='color: red; margin: 0')
+    E(article, 'h1', data['headline'], style='font-size: x-large')
+    E(article, 'div', data['description'], style='font-style: italic; color: #202020;')
+    E(article, 'div', (data['datePublishedString'] or '') + ' | ' + (data['dateline'] or ''), style='color: gray; margin: 1em')
+    main_image_url = safe_dict(data, 'image', 'main', 'url').get('canonical')
+    main_img_desc = safe_dict(data, 'image', 'main').get('description', '')
+    if main_image_url:
+        div = E(article, 'div')
+        try:
+            E(div, 'img', src=main_image_url)
+        except Exception:
+            pass
+    if main_img_desc != '':
+        div = E(article, 'figcaption', main_img_desc)
+    for node in data.get('text') or ():
+        process_node(node, article)
+
+
+def cleanup_html_article(root):
+    main = root.xpath('//main')[0]
+    body = root.xpath('//body')[0]
+    for child in tuple(body):
+        body.remove(child)
+    body.append(main)
+    main.set('id', '')
+    main.tag = 'article'
+    for x in root.xpath('//*[@style]'):
+        x.set('style', '')
+    for x in root.xpath('//button'):
+        x.getparent().remove(x)
+
+
+def classes(classes):
+    q = frozenset(classes.split(' '))
+    return dict(attrs={
+        'class': lambda x: x and frozenset(x.split()).intersection(q)})
+
+
+def new_tag(soup, name, attrs=()):
+    impl = getattr(soup, 'new_tag', None)
+    if impl is not None:
+        return impl(name, attrs=dict(attrs))
+    return Tag(soup, name, attrs=attrs or None)
+
+
+class NoArticles(Exception):
+    pass
+
+
+def process_url(url):
+    if url.startswith('/'):
+        url = 'https://www.economist.com' + url
+    return url
+
+
+class Economist(BasicNewsRecipe):
+
+    title = 'The Economist World Ahead'
+    language = 'en'
+    encoding = 'utf-8'
+
+    __author__ = "Kovid Goyal"
+    description = (
+        'The World Ahead is The Economist’s future-gazing publication. It prepares audiences for what is to '
+        'come with mind-stretching insights and expert analysis—all in The Economist’s clear, elegant style.'
+    )
+    extra_css = '''
+        .headline {font-size: x-large;}
+        h2 { font-size: medium;  }
+        h1 { font-size: large;  }
+        em.Bold {font-weight:bold;font-style:normal; color:#202020;}
+        em.Italic {font-style:italic; color:#202020;}
+        p.xhead {font-weight:bold;}
+        .pullquote {
+            float: right;
+            font-size: larger;
+            font-weight: bold;
+            font-style: italic;
+            page-break-inside:avoid;
+            border-bottom: 3px solid black;
+            border-top: 3px solid black;
+            width: 228px;
+            margin: 0px 0px 10px 15px;
+            padding: 7px 0px 9px;
+        }
+        .flytitle-and-title__flytitle {
+            display: block;
+            font-size: smaller;
+            color: red;
+        }
+        img {display:block; margin:0 auto;}
+        '''
+    oldest_article = 7.0
+    resolve_internal_links = True
+    remove_tags = [
+        dict(name=['script', 'noscript', 'title', 'iframe', 'cf_floatingcontent', 'aside', 'footer']),
+        dict(attrs={'aria-label': "Article Teaser"}),
+        dict(attrs={
+                'class': [
+                    'dblClkTrk', 'ec-article-info', 'share_inline_header',
+                    'related-items', 'main-content-container', 'ec-topic-widget',
+                    'teaser', 'blog-post__bottom-panel-bottom', 'blog-post__comments-label',
+                    'blog-post__foot-note', 'blog-post__sharebar', 'blog-post__bottom-panel',
+                    'newsletter-form','share-links-header','teaser--wrapped', 'latest-updates-panel__container',
+                    'latest-updates-panel__article-link','blog-post__section'
+                ]
+            }
+        ),
+        dict(attrs={
+                'class': lambda x: x and 'blog-post__siblings-list-aside' in x.split()}),
+        classes(
+            'share-links-header teaser--wrapped latest-updates-panel__container'
+            ' latest-updates-panel__article-link blog-post__section newsletter-form blog-post__bottom-panel'
+        )
+    ]
+    keep_only_tags = [dict(name='article', id=lambda x: not x)]
+    no_stylesheets = True
+    remove_attributes = ['data-reactid', 'width', 'height']
+    # economist.com has started throttling after about 60% of the total has
+    # downloaded with connection reset by peer (104) errors.
+    simultaneous_downloads = 1
+
+    needs_subscription = False
+
+    def __init__(self, *args, **kwargs):
+        BasicNewsRecipe.__init__(self, *args, **kwargs)
+        if self.output_profile.short_name.startswith('kindle'):
+            # Reduce image sizes to get file size below amazon's email
+            # sending threshold
+            self.web2disk_options.compress_news_images = True
+            self.web2disk_options.compress_news_images_auto_size = 5
+            self.log.warn('Kindle Output profile being used, reducing image quality to keep file size below amazon email threshold')
+
+
+    def get_browser(self):
+        br = BasicNewsRecipe.get_browser(self)
+        # Add a cookie indicating we have accepted Economist's cookie
+        # policy (needed when running from some European countries)
+        ck = Cookie(
+            version=0,
+            name='notice_preferences',
+            value='2:',
+            port=None,
+            port_specified=False,
+            domain='.economist.com',
+            domain_specified=False,
+            domain_initial_dot=True,
+            path='/',
+            path_specified=False,
+            secure=False,
+            expires=None,
+            discard=False,
+            comment=None,
+            comment_url=None,
+            rest={'HttpOnly': None},
+            rfc2109=False
+        )
+        br.cookiejar.set_cookie(ck)
+        br.set_handle_gzip(True)
+        return br
+
+    def preprocess_raw_html(self, raw, url):
+        # open('/t/raw.html', 'wb').write(raw.encode('utf-8'))
+        root = parse(raw)
+        script = root.xpath('//script[@id="__NEXT_DATA__"]')
+        if script:
+            try:
+                load_article_from_json(script[0].text, root)
+            except JSONHasNoContent:
+                cleanup_html_article(root)
+        for div in root.xpath('//div[@class="lazy-image"]'):
+            noscript = list(div.iter('noscript'))
+            if noscript and noscript[0].text:
+                img = list(parse(noscript[0].text).iter('img'))
+                if img:
+                    p = noscript[0].getparent()
+                    idx = p.index(noscript[0])
+                    p.insert(idx, p.makeelement('img', src=img[0].get('src')))
+                    p.remove(noscript[0])
+        for x in root.xpath('//*[name()="script" or name()="style" or name()="source" or name()="meta"]'):
+            x.getparent().remove(x)
+        # the economist uses <small> for small caps with a custom font
+        for x in root.xpath('//small'):
+            if x.text and len(x) == 0:
+                x.text = x.text.upper()
+                x.tag = 'span'
+                x.set('style', 'font-variant: small-caps')
+        for x in root.xpath('//figcaption'):
+            x.set('style', 'text-align:center; font-size:small;')
+        raw = etree.tostring(root, encoding='unicode')
+        return raw
+
+    def parse_index(self):
+        # return [('Articles', [{'title':'test',
+        #     'url':'https://www.economist.com/interactive/briefing/2022/06/11/huge-foundation-models-are-turbo-charging-ai-progress'
+        # }])]
+        url = 'https://www.economist.com/the-world-ahead'
+        # raw = open('/t/raw.html').read()
+        raw = self.index_to_soup(url, raw=True)
+        # with open('/t/raw.html', 'wb') as f:
+        #     f.write(raw)
+        soup = self.index_to_soup(raw)
+        # nav = soup.find(attrs={'class':'navigation__wrapper'})
+        # if nav is not None:
+        #     a = nav.find('a', href=lambda x: x and '/printedition/' in x)
+        #     if a is not None:
+        #         self.log('Following nav link to current edition', a['href'])
+        #         soup = self.index_to_soup(process_url(a['href']))
+        ans = self.economist_parse_index(soup)
+        if not ans:
+            raise NoArticles(
+                'Could not find any articles, either the '
+                'economist.com server is having trouble and you should '
+                'try later or the website format has changed and the '
+                'recipe needs to be updated.'
+            )
+        return ans
+
+    def economist_parse_index(self, soup):
+        script_tag = soup.find("script", id="__NEXT_DATA__")
+        if script_tag is not None:
+            data = json.loads(script_tag.string)
+            # open('/t/raw.json', 'w').write(json.dumps(data, indent=2, sort_keys=True))
+            self.title = safe_dict(data, "props", "pageProps", "content", "headline")
+            # self.cover_url = 'https://mma.prnewswire.com/media/2275620/The_Economist_The_World_Ahead_2024.jpg?w=600'
+
+            feeds = []
+
+            for coll in safe_dict(data, "props", "pageProps", "content", "collections"):
+                section = safe_dict(coll, "headline") or ''
+                self.log(section)
+                articles = []
+                for part in safe_dict(coll, "hasPart", "parts"):
+                    title = safe_dict(part, "headline") or ''
+                    url = safe_dict(part, "url", "canonical") or ''
+                    if not title or not url:
+                        continue
+                    desc = safe_dict(part, "description") or ''
+                    sub = safe_dict(part, "subheadline") or ''
+                    if sub:
+                        desc = sub + ' :: ' + desc
+                    if '/interactive/' in url:
+                        self.log('\tSkipping interactive article:', title, url)
+                        continue
+                    self.log('\t', title, '\n\t', desc, '\n\t\t', url)
+                    articles.append({'title': title, 'description':desc, 'url': url})
+                if articles:
+                    feeds.append((section, articles))
+            return feeds
+
+    def eco_find_image_tables(self, soup):
+        for x in soup.findAll('table', align=['right', 'center']):
+            if len(x.findAll('font')) in (1, 2) and len(x.findAll('img')) == 1:
+                yield x
+
+    def postprocess_html(self, soup, first):
+        for img in soup.findAll('img', srcset=True):
+            del img['srcset']
+        for table in list(self.eco_find_image_tables(soup)):
+            caption = table.find('font')
+            img = table.find('img')
+            div = new_tag(soup, 'div')
+            div['style'] = 'text-align:left;font-size:70%'
+            ns = NavigableString(self.tag_to_string(caption))
+            div.insert(0, ns)
+            div.insert(1, new_tag(soup, 'br'))
+            del img['width']
+            del img['height']
+            img.extract()
+            div.insert(2, img)
+            table.replaceWith(div)
+        return soup
+
+    def canonicalize_internal_url(self, url, is_link=True):
+        if url.endswith('/print'):
+            url = url.rpartition('/')[0]
+        return BasicNewsRecipe.canonicalize_internal_url(self, url, is_link=is_link)

recipes/toiprint.recipe

@@ -83,7 +83,15 @@ class toiprint(BasicNewsRecipe):
                         desc = 'Page No.' + url.split('_')[-3] + ' | ' + art.get('ColumnTitle', '')
                     self.log('\t', title, '\n\t', desc.replace('\n', ''))
                     feeds_dict[section].append({"title": title, "url": url, "description": desc})
-        return [(section, articles) for section, articles in feeds_dict.items()]
+        def sort_key(x):
+            section = x[0]
+            try:
+                return (
+                    'Front Page', 'Times Nation', 'Times Region', 'Times City'
+                ).index(section)
+            except Exception:
+                return 99999999
+        return (sorted(feeds_dict.items(), key=sort_key))
 
     def preprocess_raw_html(self, raw, *a):
         data = json.loads(raw)