The other day, I saw Learn regex the easy way. This is a great resource, but I felt the need to pen a post explaining that regexes are usually not the right approach.
Let’s do a little exercise. I googled “URL regex” and here’s the first Stack Overflow result:
https?:\/\/(www\.)?[-a-zA-Z0-9@:%._\+~#=]{2,256}\.[a-z]{2,6}\b([-a-zA-Z0-9@:%_\+.~#?&//=]*)
This is a bad regex. Here are some valid URLs that this regex fails to match:
- http://x.org
- http://nic.science
- http://名がドメイン.com (warning: this is a parked domain)
- http://example.org/url,with,commas
- https://en.wikipedia.org/wiki/Harry_Potter_(film_series)
- http://127.0.0.1
- http://[::1] (ipv6 loopback)
Here are some invalid URLs the regex is fine with:
This answer has been revised 9 times on Stack Overflow, and this is the best they could come up with. Go back and read the regex. Can you tell where each of these bugs are? How long did it take you? If you received a bug report in your application because one of these URLs was handled incorrectly, do you understand this regex well enough to fix it? If your application has a URL regex, go find it and see how it fares with these tests.
Complicated regexes are opaque, unmaintainable, and often wrong. The correct approach to validating a URL is as follows:
from urllib.parse import urlparse
def is_url_valid(url):
try:
urlparse(url)
return True
except:
return False
A regex is useful for validating simple patterns and for finding patterns in text. For anything beyond that it’s almost certainly a terrible choice. Say you want to…
validate an email address: try to send an email to it!
validate password strength requirements: estimate the complexity with zxcvbn!
validate a date: use your standard library! datetime.datetime.strptime
validate a credit card number: run the Luhn algorithm on it!
validate a social security number: alright, use a regex. But don’t expect the number to be assigned to someone until you ask the Social Security Administration about it!
Get the picture?
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