calibre/recipes/scientific_american.recipe
unkn0w7n 6c9e2d14a2 ...
2024-09-28 11:16:28 +05:30

138 lines
5.2 KiB
Python

#!/usr/bin/env python
__license__ = "GPL v3"
import json
from datetime import datetime
from urllib.parse import urljoin
from calibre.web.feeds.news import BasicNewsRecipe, prefixed_classes
class ScientificAmerican(BasicNewsRecipe):
title = "Scientific American"
description = "Popular Science. Monthly magazine. Should be downloaded around the middle of each month."
category = "science"
__author__ = "Kovid Goyal"
no_stylesheets = True
language = "en"
publisher = "Nature Publishing Group"
remove_empty_feeds = True
remove_javascript = True
timefmt = " [%B %Y]"
remove_attributes = ["height", "width"]
masthead_url = (
"https://static.scientificamerican.com/sciam/assets/Image/newsletter/salogo.png"
)
extra_css = """
[class^="article_dek-"] { font-style:italic; color:#202020; }
[class^="article_authors-"] {font-size:small; color:#202020; }
[class^="article__image-"], [class^="lead_image-"], .calibre-nuked-tag-figcaption { font-size:small; }
[class^="bio-"] { font-size:small; color:#404040; }
em, blockquote { color:#202020; }
"""
needs_subscription = "optional"
keep_only_tags = [
prefixed_classes(
'article_hed- article_dek- article_authors- lead_image- article__body- bio-'
),
]
remove_tags = [
dict(name=['button', 'svg', 'iframe', 'source'])
]
def preprocess_html(self, soup):
for h2 in soup.findAll(['h2', 'h3']):
h2.name = 'h4'
for fig in soup.findAll('figcaption'):
for p in fig.findAll('p'):
p.name = 'div'
res = '?w=600'
w = self.recipe_specific_options.get('res')
if w and isinstance(w, str):
res = '?w=' + w
for img in soup.findAll('img', src=True):
img['src'] = img['src'].split('?')[0] + res
return soup
def get_browser(self, *args):
br = BasicNewsRecipe.get_browser(self)
if self.username and self.password:
br.open("https://www.scientificamerican.com/account/login/")
br.select_form(predicate=lambda f: f.attrs.get("id") == "login")
br["emailAddress"] = self.username
br["password"] = self.password
br.submit()
return br
recipe_specific_options = {
'issue_url': {
'short': 'The issue URL ',
'long': (
'For example, https://www.scientificamerican.com/issue/sa/2024/07-01/'
'\nYou can also download special-editions, physics, health, mind magazines by pasting the URL here.'
)
},
'res': {
'short': 'For hi-res images, select a resolution from the\nfollowing options: 800, 1000, 1200 or 1500',
'long': 'This is useful for non e-ink devices, and for a lower file size\nthan the default, use 400 or 300.',
'default': '600'
}
}
def parse_index(self):
# Get the cover, date and issue URL
d = self.recipe_specific_options.get('issue_url')
if d and isinstance(d, str):
issue = d
else:
fp_soup = self.index_to_soup("https://www.scientificamerican.com")
curr_issue_link = fp_soup.find(**prefixed_classes('latest_issue_links-'))
if not curr_issue_link:
self.abort_recipe_processing("Unable to find issue link")
issue = 'https://www.scientificamerican.com' + curr_issue_link.a["href"]
soup = self.index_to_soup(issue)
script = soup.find("script", id="__DATA__")
if not script:
self.abort_recipe_processing("Unable to find script")
JSON = script.contents[0].split('JSON.parse(`')[1].replace("\\\\", "\\")
data = json.JSONDecoder().raw_decode(JSON)[0]
issue_info = (
data
.get("initialData", {})
.get("issueData", {})
)
if not issue_info:
self.abort_recipe_processing("Unable to find issue info")
self.cover_url = issue_info["image_url"] + "?w=800"
edition_date = datetime.strptime(issue_info["issue_date"], "%Y-%m-%d")
self.timefmt = f" [{edition_date:%B %Y}]"
feeds = {}
for section in issue_info.get("article_previews", {}):
for article in issue_info.get("article_previews", {}).get(section, []):
self.log('\t', article["title"])
if section.startswith('featur'):
feed_name = section.capitalize()
else:
feed_name = article["category"]
if feed_name not in feeds:
feeds[feed_name] = []
feeds[feed_name].append(
{
"title": article["title"],
"url": urljoin(
"https://www.scientificamerican.com/article/",
article["slug"],
),
"description": article["summary"],
}
)
sorted_feeds = dict(sorted(feeds.items(), key=lambda x: (not x[0].startswith('Featur'), x[0])))
return sorted_feeds.items()