Algorithm-a-Day : Day 15 : Email Address Parsing with Regex

Of course, inspired by: XKCD #208
And on that note: XKCD4ME  (Python script)
 
Github :: Email Regex 

ABOUT REGULAR EXPRESSIONS
-------------------------
  Regular expressions are a very powerful tool for finding and replacing
substring patterns in strings. Regex's are a language of their own,
separate from anything we've been using so far, but luckily they are mostly
uniform across programming languages.

(Find that prime solving regex)

PYTHON
------
  The regex we're given is:
    \b([a-zA-Z0-9-_.]+)@(\w+[.][a-zA-Z.]+)
but more specifically in a Pythonic context we can look at it directly as:
    r"\b([a-zA-Z0-9-_.]+)@(\w+[.][a-zA-Z.]+)"

  The r"" type of string is called a raw string, and it doesn't accept
special characters. The string r"haha this won't \n print a new line"
will print:
    haha this won't \n print a new line
Essentially, backslashes are not interpreted. This is important for regex's
because backslashes also have special meaning, which means that in a regular
string you would have to double-escape your special characters. We won't
bother with that, and just go ahead and use raw strings.
  See line 6. Holy moon language. Note that we could have written the regex
like this:
    regex = r"""\b
		([a-zA-Z0-9-_.]+)
		@
		(\w
		[.]
		[a-zA-Z.]+)
		"""

and then called it like this:
    pattern = re.compile(regex, 'VERBOSE')
Verbose mode allows whitespace and newlines to be ignored in the given regex.
This lets us break up longer regex's into more digestable chunks.
We can also comment them, like this:
    regex = r"""\b                  # Match the start of a word.
		([a-zA-Z0-9-_.]+)  # Match one or more characters from small
				            # 'a' to 'z', capital 'A' to 'Z', and 
				            # a few special characters.
		@                         # Match the 'at symbol' (or 'amphere').
		(\w		            # Match any letter or digit.
		[.]		            # Match a period. This has to be in a []!
		[a-zA-Z.]+)	    # Match one or more letter or period.
		"""

The last condition is important because some URLs from other countries have
multiple extentions to them. For example, a Yahoo email address from Japan
would end in: @yahoo.co.jp
  The rest is straight forward; we compile the regex, ask it for matches,
then store said matches after some string working.
  Try poking around at the regex itself to see what makes the script
explode and what doesn't. Then, try making one that parses URLs. Maybe to run
across an HTML file? Your life as a professional scraper begins today!