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A python library detect and extract listing data from HTML page.

===
MDR

.. image:: https://travis-ci.org/scrapinghub/mdr.svg?branch=master
:target: https://travis-ci.org/scrapinghub/mdr

MDR is a library detect and extract listing data from HTML page. It implemented base on the Finding and Extracting Data Records from Web Pages <http://dl.acm.org/citation.cfm?id=1743635>_ but
change the similarity to tree alignment proposed by Web Data Extraction Based on Partial Tree Alignment <http://doi.acm.org/10.1145/1060745.1060761>_ and Automatic Wrapper Adaptation by Tree Edit Distance Matching <http://arxiv.org/pdf/1103.1252.pdf>_.

Requires

  • Requires python 2.
  • numpy and scipy must be installed to build this package.

Compile and test

# optionally use docker
$ docker run -ti python:2.7.13 bash

$ apt-get update && apt-get install -y python-numpy cython python-scipy
$ cd
$ git clone https://github.com/scrapinghub/mdr.git
$ cd mdr
$ pip install -r requirements.txt
$ python setup.py build
$ python setup.py install

# let's move away from this dir, otherwise it would fail with ImportError: No module named _tree
$ cd
$ cp -r mdr/tests .
# -m: use it as a library, so that it reads the get_page def from tests/__init__.py
$ python -m tests.test_mdr

.....
----------------------------------------------------------------------
Ran 5 tests in 2.689s

OK

Usage

Detect listing data


MDR assume the data record close to the elements has most text nodes::

    [1]: import requests
    [2]: from mdr import MDR
    [3]: mdr = MDR()
    [4]: r = requests.get('http://www.yelp.co.uk/biz/the-ledbury-london')
    [5]: candidates, doc = mdr.list_candidates(r.text.encode('utf8'))
    ...

    [8]: [doc.getpath(c) for c in candidates[:10]]
     ['/html/body/div[2]/div[3]/div[2]/div/div[1]/div[1]/div[2]/div[1]/div[2]/ul',
     '/html/body/div[2]/div[3]/div[2]/div/div[1]/div[2]',
     '/html/body/div[2]/div[3]/div[2]/div/div[1]/div[2]/div[2]',
     '/html/body/div[2]/div[3]/div[1]/div/div[4]/div[1]/div/div[1]/div/div[2]/div[1]/div[1]/div',
     '/html/body/div[2]/div[3]/div[1]/div/div[4]/div[2]/div/div[3]',
     '/html/body/div[2]/div[3]/div[1]/div/div[4]/div[1]/div/div[2]/ul/li[2]/div/div/ul',
     '/html/body/div[2]/div[3]/div[2]/div/div[1]/div[1]/div[2]/div[1]',
     '/html/body/div[2]/div[3]/div[2]/div/div[1]/div[2]/div[2]/div[1]/table/tbody',
     '/html/body/div[2]',
     '/html/body/div[2]/div[4]/div/div[1]']

Extract data record

MDR can find the repetiton patterns by using tree matching under certain candidate DOM tree, then it builds a mapping from HTML element to other matched elements of the DOM tree.

Used with annotation (optional)


You can annotate the seed elements with any tools (e.g. scrapely_) you like, then mdr will be able to find the other matched elements on the page.

e.g. you can find this demo page here_. the colored data in first row are annotated manually, the rest are extracted by MDR.

Author
======

Terry Peng <pengtaoo@gmail.com>

License
=======

MIT

.. _scrapely: https://github.com/scrapy/scrapely
.. _here: http://ibc.scrapinghub.com/tmp/h.html

Languages

HTML96.6%Python3.4%Shell0.0%

Contributors

Created March 29, 2017
Updated March 29, 2017
dportabella/mdr | GitHunt