BasicCrawler
Semi-automated crawling bot with special features for extracting website
structure automatically.
::
from basiccrawler.crawler import BasicCrawler
SOURCE_DOMAIN='http://learningequality.org'
start_page = 'http://learningequality.org/kolibri/'
class LECrawler(BasicCrawler):
pass
crawler = LECrawler(main_source_domain=SOURCE_DOMAIN,
start_page=start_page)
web_resource_tree = crawler.crawl()
The crawler concludes will summary of the findings (according to crude
heuristics).
::
# CRAWLER RECOMMENDATIONS BASED ON URLS ENCOUNTERED:
################################################################################
1. These URLs are very common and look like global navigation links:
- http://learningequality.org/about/team/
- http://learningequality.org/about/board/
- http://learningequality.org/about/supporters/
- ...
2. These are common path fragments found in URLs paths, so could correspond to site struture:
- ...
################################################################################
The web resource tree contains the information about the site structure
at a high level (print_depth=3
) or in full detail
(print_depth=100
). For example:
::
crawler.print_tree(web_resource_tree, print_depth=4)
- path: /kolibri/ (PageWebResource)
children:
- path: / (PageWebResource)
children:
- path: /media/Rapport-Etude-Cameroun_KL_ENG.pdf (MediaWebResource)
- path: /about/ (PageWebResource)
children:
- path: /ka-lite/map/ (PageWebResource)
- path: /about/values/ (PageWebResource)
- path: /about/team/ (PageWebResource)
- path: /about/board/ (PageWebResource)
- path: /about/supporters/ (PageWebResource)
- path: /about/press/ (PageWebResource)
- path: /about/jobs/ (PageWebResource)
- path: /about/internships/ (PageWebResource)
children:
- path: https://learningequality.org/about/jobs/?gh_jid=533166 (PageWebResource)
- path: /download/ (PageWebResource)
- path: /documentation/ (PageWebResource)
- path: /hardware_grant/ (PageWebResource)
- path: /ka-lite/ (PageWebResource)
children:
- path: /ka-lite/infographic/ (PageWebResource)
- path: /translate/ (PageWebResource)
- path: https://blog.learningequality.org/?gi=2589e076ea04 (PageWebResource)
- path: /ka-lite/map/add/ (PageWebResource)
- path: /donate/ (PageWebResource)
children:
- path: /static/doc/learning_equality_irs_determination_letter.pdf (MediaWebResource)
- path: /cdn-cgi/l/email-protection (PageWebResource)
For this crawl, we didnât find too many educational materials
(docs/videos/audio/webapps), but at least we get some idea of the links
on that page. Try it on another website.
Example usage
https://github.com/learningequality/sushi-chef-tessa/blob/master/tessa_cralwer.py#L229
TODO
-
Update examples + notebooks
-
path to url / vice versa (and possibly elsewhere): consider
urllib.urlparse
? [e.g. url.startwith(source_domain)
could be
source_domain in url.domain
to make it more flexible with
subdomains
- Additional valid domains can be specified but
url_to_path_list
assumes adding CHANNEL_ROOT_DOMAIN [we may wish to expand all
links based on parent URL]
- refactor and remove need for MAIN_SOURCE_DOMAIN and use only
SOURCE_DOMAINS instead
Future feature ideas
-
Asynchronous download (not necessary but might be good for
performance on large sites)
- donât block for HTTP
- allow multiple workers getting from queue
-
content_selector hints for default on_page
handler to follow
links only within a certain subset of the HTML tree. Can have:
- site-wide selector at class level
- pass in additional
content_selector
from referring page via
context dict
-
Automatically detect standard embed tags (audio, video, pdfs) and add
links to web resource tree in default on_page
handler.
Crawler API
The goal of the BasicCrawler
class is to help with the initial
exploration of the source website. It is your responsibility to write a
subclass that uses the HTML, URL structure, and content to guide the
crawling and produce the web resource tree.
Your crawler should inherit from BasicCrawler
and define:
-
The BasicCrawler has logic for visiting pages and will print out on
the a summary of the auto inferred site stricture findings and
recommendations based on the URL structure observed during the
initial crawl.
-
Based on the number of times a link appears on different pages of the
site the crawler will suggest to you candidates for global navigation
links. Most websites have an /about page, /contact us, and other such
non-content-containing pages, which we do not want to include in the
web resource tree. You should inspect these suggestions and decide
which should be ignored (i.e. not crawled or included in the
web_resource_tree output). To ignore URLs you can edit the
attributes:
IGNORE_URLS
: crawler will ignore these URLs Edit your crawler
subclassâ code and append to IGNORE_URLS
the URLs you want to
skip (anything that is not likely to contain content).
- Run the crawler again, this time there should be less noise in the
output.
-
Note the suggestion for different paths that you might want to handle
specially (e.g. /course
, /lesson
, /content
, etc.) You can
define class methods to handle each of these URL types:
::
def on_course(self, url, page, context):
# what do you want the crawler to do when it visits the course with `url`
# in the `context` (used for extra metadata; contains reference to parent)
# The BeautifulSoup parsed contents of the `url` are provided as `page`.
def on_lesson(self, url, page, context):
# what do you want the crawler to do when it visits the lesson
def on_content(self, url, page, context):
# what do you want the crawler to do when it visits the content url
Check out the default on_page
method so see how a web resource tree
is constructed:
https://github.com/learningequality/BasicCrawler/blob/master/basiccrawler/crawler.py#L212