Handling non-well-formed HTML in Scrapy with BeautifulSoup

With Scrapy, we can deal with non-well-formed HTML is many ways. This is just one of them.

BeautifulSoup has a pretty nifty feature where it tries to fix bad HTML like replacing missing tags. So if we put BeautifulSoup in the middle then whatever we get from a site is fixed before we parse it with Scrapy.

Fortunately, all we have to do is pip install Alecxe's scrapy-beautifulsoup middleware.

pip install scrapy-beautifulsoup

Then we configure Scrapy to use it from settings.py:

DOWNLOADER_MIDDLEWARES = {
    'scrapy_beautifulsoup.middleware.BeautifulSoupMiddleware': 400
}

BeautifulSoup comes with a default parser named 'html.parse'. We can change it.

BEAUTIFULSOUP_PARSER = "html5lib"  # or BEAUTIFULSOUP_PARSER = "lxml"

HTML5 is the better parser IMO but it has to be installed separately.

pip install html5lib

Gracefully dealing with different SSH keys for different domains or accounts

This problem often happens when you mix your personal ssh keys along with your company's and you work off a single workstation or laptop.

Even if the user and host are the same, they can still be distinguished in the ~/.ssh/config.

Host gitlab.com
  HostName git.company.com
  User git
  IdentityFile /home/whoever/.ssh/id_rsa.alice
  IdentitiesOnly yes

Host kitlab.com
  HostName git.company.com
  User git
  IdentityFile /home/whoever/.ssh/id_dsa.bob
  IdentitiesOnly yes

Then you can use gitlab.com and kitlab.com instead of the hostname in your git remote.

git remote add g-origin git@gitlab.com:whatever.git
git remote add k-origin git@kitlab.com:whatever.git

You probably want to include the option IdentitiesOnly yes to prevent the use of default ids.

Ref: https://blog.developer.atlassian.com/different-ssh-keys-multiple-bitbucket-accounts/

Using ElementTree(xml) with Scrapy to deal with hard to deal HTML

While Scrapy's Selectors like xpath and css are powerful there are some cases that make them cost to much effort.

An example with irregular HTML text like this:

 ['<a href="https://www.blogger.com/u/1/misc/cst2020d.html"><b>Dimensions</b></a>',  
  '<a href="https://www.blogger.com/u/1/misc/cst2020s.html"><b>Typical Circuit</b></a>',  
  '<a href="https://www.blogger.com/u/1/misc/cst2020t.html"><b>Temperature vs Current</b></a>',  
  '<a href="http://www.blogger.com/Search.aspx?arg=somepart%20ic2020" target="_blank"><b>3D\xa0model</b></a>']  

This is a sample result of calling the extract() method with Scrapy's selector. The parts we want here is the href and the link text. We want to get those.

We can:

1. Do multiple Scrapy selector calls to get the data we need or
2. Do a single Scrapy selector call and process it via XML

I went with #2. Dealing with HTML as XML should be relatively easy. Besides Python already has a way for working with XML via the ElementTree XML API.

So the Python code to solve the problem is short and simple:

import xml.etree.ElementTree as ET
....
class MySpider(scrapy.Spider):
....
    for link_item in our_raw_links:
        root = ET.fromstring(link_item)
        href = root.attrib['href']
        anchor_text = root[0].text

        cap_links.append({'text': anchor_text, 'href': href})

And Voila!