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I love politics, and I love programming, so I figured why not try and combine the two for something to do? I'm making a work-in-progress (but runnable at this stage) Politico api that I call "pylitico.":

from bs4 import BeautifulSoup
import requests
import time
import ast
import re

story_link = re.compile('a href="(http:\/\/www.politico.com\/story.*)" target')
utag_regex = re.compile('var utag_data = \n(\{.*);')

today = time.strftime("%m/%d/%y")


class Article():
    def __init__(self, content_id, tags, author,
                 datestamp, section, headline, story):
        """
        :type tags: list
        :type content_id: str
        :type author: list
        :type datestamp: DateTime
        :type section: str
        :type headline: str
        :type story: str
        """

        self.content_id = content_id
        self.tags = tags
        self.author = author
        self.datestamp = datestamp
        self.section = section
        self.headline = headline
        self.story = story

    def __str__(self):
        return "{0}".format(self.headline)


class Pylitico():
    def __init__(self):
        """Creates a connection to Politico"""
        self.session = requests.Session()

    def most_read(self):
        """Collects the Most Read section of Politico, returns
            stories as list of Article class objects"""
        r = self.session.get('http://www.politico.com/congress/?tab=most-read')
        soup = BeautifulSoup(r.content, 'html.parser')
        most_read_frame = [i for i in soup.find_all('div',
                                                    {'class': 'dari-frame dari-frame-loaded'}) if
                           'most-read' in i.attrs.get('name')][0]
        links = [i.find('a').attrs.get('href') for i in
                 most_read_frame.find_all('article', {'class': 'story-frag format-xxs'})]
        stories = [self.story_parser(link) for link in links]
        return stories

    def todays_stories(self):
        """Collects stories posted on today's date, returns
            collected stories as list of Article class objects"""
        r = self.session.get('http://www.politico.com/search?q=')
        soup = BeautifulSoup(r.content, 'html.parser')
        summaries = soup.find_all('div', {'class': 'summary'})
        links = []
        for summary in summaries:
            if summary.find('time') and today in summary.find('time').text:
                links.append(summary.find('a').attrs.get('href'))
        stories = [self.story_parser(link) for link in links if 'video' not in link and 'tipsheets' not in link]
        return stories

    def story_parser(self, link):
        """Turns a POLITICO story into an Article class object."""
        r = self.session.get(link)
        soup = BeautifulSoup(r.content, 'html.parser')
        template_story = soup.find('body', id="pageStory")
        try:
            content_dict = ast.literal_eval(str(template_story.find('script')).replace(';', '').splitlines()[2])
        except AttributeError: # triggered if todays_stories() returns videos/other non-stories
            return
        all_divs = soup.find_all('div')
        for div in all_divs:
            try:
                if 'story-text' in div.attrs.get('class'):
                    story_div = div
            except TypeError:
                continue
        story_text = []
        for i in story_div.find_all('p'):
            try:
                if 'byline' not in i.attrs.get('class'):
                    story_text.append(i.text)
            except TypeError:
                story_text.append(i.text)
        story_text = ' '.join(story_text)
        a = Article(content_dict['content_id'], content_dict['content_tag'].split('|'),
                    content_dict['content_author'].split('|'),
                    content_dict['site_section'], time.strptime(content_dict['publication_date'], '%Y%m%d'),
                    content_dict['current_headline'], story_text)
        return a


session = Pylitico()
most_read_stories = session.most_read()
for _ in most_read_stories[0:1]:
    print(_.headline)
    # Manafort denies reports of chaotic Trump campaign
todays_stories = session.todays_stories()
print(todays_stories[0].headline)
# More than two decades old, The Drudge Report hits a new traffic high

What do you guys think? See any optimizations that could be made? I know that BeautifulSoup parses a bit faster if you specify lxml instead of html.parser, but I thought that potential users may not have lxml.

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1 Answer 1

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    most_read_frame = [i for i in soup.find_all('div',
                                                {'class': 'dari-frame dari-frame-loaded'}) if
                       'most-read' in i.attrs.get('name')][0]

can be made more efficient by using islice:

from itertools import islice
most_read_frame_gen = (i for i in soup.find_all('div',
                                                {'class': 'dari-frame dari-frame-loaded'}) if
                       'most-read' in i.attrs.get('name'))
most_read_frame = islice(most_read_frame_gen, 0, 1)

as it will stop iterating after it gets the first value.

Also this is a bit of bad form:

for _ in most_read_stories[0:1]:
    print(_.headline)

_ is used for throwaway variables by convention. It'd be more readable to call it something like story or even just s:

for story in most_read_stories[0:1]:
    print(story.headline)

In general, though, it looks good. You do realize you're in a bit of an 'arms race' though, right? If Politico changes the format of its site, you'll have to change your code, etc, etc. In that vein, I suggest you document what date you made it work, so potential users can judge whether it's too out of date to be worth bothering with.

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