re101 0.1.1

A back-pocket regex cookbook

A compendium of commonly-used regular expressions.

This module pertains specifically to regexes embedded inside Python and compiled with Python’s re module.

All importable objects are compiled regular expressions. For instance, nanp_phonenum matches sequences following the North American Number Plan (NANP) format. In plain English, this is what would qualify as a “North American telephone number”:

>>> # Capture sequences following the
... # North American Numbering Plan (NANP) phone number format
... from re101 import nanp_phonenum

>>> text = """
... Ross McFluff: +1 [phone] 155 Elm Street
... Ronald Heathmore: 892-345-3428 436 Finley Avenue
... Frank Burger: 541-7625 662 South Dogwood Way
... Heather Albrecht: 5483264584 919 Park Place"""

>>> nanp_phonenum.findall(text)
['+1 [phone]', '892-345-3428', '541-7625', '5483264584']

Currently, the package supports regexes related to:

• email addresses

• whitespace

• words/tokens

• phone numbers

• IP addresses

• URLs

• integers, decimals, numbers

• geographic information

Disclaimer

Use these regular expressions with care. It is unlikely that any of them cover 100.00% of the cases that they are intended to cover. They are built to handle “99.x%” of cases. With all regular expressions, a balance must be made: covering an incremental 0.1% of cases often requires a large marginal amount of work and code.

If you do notice egregious mistakes or omissions, please consider submitting an issue or pull request. See the “Contributing” file.

With regex comes responsibility. Categories of expressions that don’t belong here include credit card patterns, passwords, and social security numbers, given that the only real purpose of having these is for malicious information retrieval. You get the gist.

Please assume these expressions are “US-centric” unless noted otherwise. For instance, the zipcodes expression looks only for XXXXX or XXXXX-XXXX zip codes.

Source directory

[1] Goyvaerts, Jan & Steven Levithan. Regular Expressions Cookbook, 2nd ed. Sebastopol: O’Reilly, 2012.

[2] Friedl, Jeffrey. Mastering Regular Expressions, 3rd ed. Sebastopol: O’Reilly, 2009.

[3] Goyvaerts, Jan. Regular Expressions: The Complete Tutorial. https://www.regular-expressions.info/.

[4] Python.org documentation: re module. https://docs.python.org/3/library/re.html

[5] Kuchling, A.M. “Regular Expression HOWTO.” https://docs.python.org/3/howto/regex.html

[6] Python.org documentation: ipaddress module. Copyright 2007 Google Inc. Licensed to PSF under a Contributor Agreement. https://docs.python.org/3/library/ipaddress.html

[7] nerdsrescueme/regex.txt. https://gist.github.com/nerdsrescueme/1237767

Citations are included for “unique” regexes that are copied from a singular source. More “generic” regexes that can be found in similar form from multiple public sources may not be cited here.

Notes

It is recommended to import the module rather than its specific contents directly. A handful of object names here may conflict with common modules or objects from Python’s Standard Library.

For example, use import re101 with re101.email rather than from re101 import email, which could potentially conflict with Python’s email.py module.

Why use a full-blown repository?

You might argue that this entire package could be thrown into a single GitHub gist. Here’s why I chose to structure re101 as a Python package:

1. It makes version management and pushing updates much easier. I’ll do my best to keep a nice changelog with descriptions of added or modified expressions.

2. Easy setup and installation. Just pip install and re101 is added to site-packages within your path, making importing its objects hassle-free.

Package structure

re101
├── LICENSE
├── MANIFEST.in
├── README.rst
├── contributing.rst
├── re101/
│   ├── __init__.py
│   └── re101.py
├── setup.py
└── tests/
    ├── __init__.py
    └── test_101.py