Reputation: 791
Firstly, I am a complete newbie when it comes to Python. However, I have written a piece of code to look at an RSS feed, open the link and extract the text from the article. This is what I have so far:
from BeautifulSoup import BeautifulSoup
import feedparser
import urllib
# Dictionaries
links = {}
titles = {}
# Variables
n = 0
rss_url = "feed://www.gfsc.gg/_layouts/GFSC/GFSCRSSFeed.aspx?Division=ALL&Article=All&Title=News&Type=doc&List=%7b66fa9b18-776a-4e91-9f80- 30195001386c%7d%23%7b679e913e-6301-4bc4-9fd9-a788b926f565%7d%23%7b0e65f37f-1129-4c78-8f59-3db5f96409fd%7d%23%7bdd7c290d-5f17-43b7-b6fd-50089368e090%7d%23%7b4790a972-c55f-46a5-8020-396780eb8506%7d%23%7b6b67c085-7c25-458d-8a98-373e0ac71c52%7d%23%7be3b71b9c-30ce-47c0-8bfb-f3224e98b756%7d%23%7b25853d98-37d7-4ba2-83f9-78685f2070df%7d%23%7b14c41f90-c462-44cf-a773-878521aa007c%7d%23%7b7ceaf3bf-d501-4f60-a3e4-2af84d0e1528%7d%23%7baf17e955-96b7-49e9-ad8a-7ee0ac097f37%7d%23%7b3faca1d0-be40-445c-a577-c742c2d367a8%7d%23%7b6296a8d6-7cab-4609-b7f7-b6b7c3a264d6%7d%23%7b43e2b52d-e4f1-4628-84ad-0042d644deaf%7d"
# Parse the RSS feed
feed = feedparser.parse(rss_url)
# view the entire feed, one entry at a time
for post in feed.entries:
# Create variables from posts
link = post.link
title = post.title
# Add the link to the dictionary
n += 1
links[n] = link
for k,v in links.items():
# Open RSS feed
page = urllib.urlopen(v).read()
page = str(page)
soup = BeautifulSoup(page)
# Find all of the text between paragraph tags and strip out the html
page = soup.find('p').getText()
# Strip ampersand codes and WATCH:
page = re.sub('&\w+;','',page)
page = re.sub('WATCH:','',page)
# Print Page
print(page)
print(" ")
# To stop after 3rd article, just whilst testing ** to be removed **
if (k >= 3):
break
This produces the following output:
>>> (executing lines 1 to 45 of "RSS_BeautifulSoup.py")
Total deposits held with Guernsey banks at the end of June 2012 increased 2.1% in sterling terms by £2.1 billion from the end of March 2012 level of £101 billion, up to £103.1 billion. This is 9.4% lower than the same time a year ago. Total assets and liabilities increased by £2.9 billion to £131.2 billion representing a 2.3% increase over the quarter though this was 5.7% lower than the level a year ago. The higher figures reflected the effects both of volume and exchange rate factors.
The net asset value of total funds under management and administration has increased over the quarter ended 30 June 2012 by £711 million (0.3%) to reach £270.8 billion.For the year since 30 June 2011, total net asset values decreased by £3.6 billion (1.3%).
The Commission has updated the warranties on the Form REG, Form QIF and Form FTL to take into account the Commission’s Guidance Notes on Personal Questionnaires and Personal Declarations. In particular, the following warranty (varies slightly dependent on the application) has been inserted in the aforementioned forms,
>>>
The problem is that this is the first paragraph of each article, however I need to show the entire article. Any help would be gratefully received.
Upvotes: 78
Views: 263323
Reputation: 3149
This works well for specific articles where the text is all wrapped in <p>
tags. Since the web is an ugly place, it's not always the case.
Often, websites will have text scattered all over, wrapped in different types of tags (e.g. maybe in a <span>
or a <div>
, or an <li>
).
To find all text nodes in the DOM, you can use soup.find_all(text=True)
.
This is going to return some undesired text, like the contents of <script>
and <style>
tags. You'll need to filter out the text contents of elements you don't want.
blocklist = [
'style',
'script',
# other elements,
]
text_elements = [t for t in soup.find_all(text=True) if t.parent.name not in blocklist]
If you are working with a known set of tags, you can tag the opposite approach:
allowlist = [
'p'
]
text_elements = [t for t in soup.find_all(text=True) if t.parent.name in allowlist]
Upvotes: 21
Reputation: 1063
get_text
htmldata = getdata("https://www.geeksforgeeks.org/how-to-automate-an-excel-sheet-in-python/?ref=feed")
soup = BeautifulSoup(htmldata, 'html.parser')
data = ''
for data in soup.find_all("p"):
print(data.get_text())
Upvotes: 10
Reputation: 12747
You are getting close!
# Find all of the text between paragraph tags and strip out the html
page = soup.find('p').getText()
Using find (as you've noticed) stops after finding one result. You need find_all if you want all the paragraphs. If the pages are formatted consistently ( just looked over one), you could also use something like
soup.find('div',{'id':'ctl00_PlaceHolderMain_RichHtmlField1__ControlWrapper_RichHtmlField'})
to zero in on the body of the article.
Upvotes: 122