Reputation: 653
I'd like to build a webapp to help other students at my university create their schedules. To do that I need to crawl the master schedules (one huge html page) as well as a link to a detailed description for each course into a database, preferably in python. Also, I need to log in to access the data.
Upvotes: 12
Views: 69296
Reputation: 6035
Scrapy is probably the best Python library for crawling. It can maintain state for authenticated sessions.
Dealing with binary data should be handled separately. For each file type, you'll have to handle it differently according to your own logic. For almost any kind of format, you'll probably be able to find a library. For instance take a look at PyPDF for handling PDFs. For excel files you can try xlrd.
Upvotes: 4
Reputation: 368
For this purpose there is a very useful tool called web-harvest Link to their website http://web-harvest.sourceforge.net/ I use this to crawl webpages
Upvotes: 0
Reputation: 50587
requests
for downloading the pages.
lxml
for scraping the data.If you want to use a powerful scraping framework there's Scrapy
. It has some good documentation too. It may be a little overkill depending on your task though.
Upvotes: 12
Reputation: 2425
I liked using BeatifulSoup for extracting html data
It's as easy as this:
from BeautifulSoup import BeautifulSoup
import urllib
ur = urllib.urlopen("http://pragprog.com/podcasts/feed.rss")
soup = BeautifulSoup(ur.read())
items = soup.findAll('item')
urls = [item.enclosure['url'] for item in items]
Upvotes: 3