Best way to strip punctuation from a string

python

regex

string-manipulation

performance

byNikita Barsukov·Nov 1, 2024

Efficiently remove all punctuation from a string using Python's str.translate method:

import string

# Let's cook up some clean text!
clean_text = "Hello, world!".translate(str.maketrans('', '', string.punctuation))

print(clean_text)  # "Hello world" - Looks appetizing, doesn't it?

This one-liner wields the power of str.maketrans to cleanse your strings of the punctuation curse! Here is your immediate potion for eliminating pesky pests known as punctuations.

Digging into the details

So let's sneak under the hood and gaze the mechanics:

Tactics behind the method

Speed demon: The translate method, with its C-level raw power, lifts the heavy load with the help of a translation table. It's known to leave many competitors in the dust.
Reuse & recycle: Creating a mapping with maketrans just once and putting it in your magic bag for later usage smells like smartness and optimized code. It's like good magic: takes effort once, saves energy later.
Uniformity: Thanks string.punctuation for serving up a glossary of punctuation marks. Write to your heart's content knowing you always can deliver spotless texts.

Let's regex!

For those with an attraction towards the flexible and powerful allure of regex:

import re

# It ain't simple, but it sure does the clean-up job!
clean_text_regex = re.sub('[^\w\s]', '', "Hello, world!")
print(clean_text_regex)  # "Hello world" - Deja Vu, anyone?

Can't resist using the same pattern over and over? Let's make this run faster. Compile your regex:

# We've been through this before, why repeat the hard work!
pattern = re.compile('[^\w\s]')
clean_text = pattern.sub('', "Hello, world!")

# Impressive, isn't it? Now give your CPU a break!

Let this be a reminder for all regex users: always use raw strings (r'') to avoid crossing wires with those pesky escape sequences.

Riding the C-train

Who knows, maybe Python's translate method isn't fast enough for you. Alright, speed demon, how about coding your custom C extensions? Buckle up cause it's gonna be an exciting ride! But remember, with great speed comes greater deployment complexity.

Putting it all in perspective

We mustn't forget to weigh our options:

translate: Speedy Gonzales in the realm of string cleaning with the slight cost of readability. No room for pattern customization, it's a one-trick pony.
re.sub: A toolbox for the crafty, enabling complex patterns rubber stamping at a slightly slower pace.
Custom C extension: Pure grease lighting speed! But beware, C language knowledge required, and complexity goes up a notch.

Remember: Each method has its time and place. Choose wisely!

The Road Less Traveled

Working with non-standard punctuation or different languages? Expand or customize the string.punctuation set, or use Unicode property escapes with your regex (\p{P} for punctuation) to ensure that no punctuation escapes your diligent cleaning routine.

Emojis and other symbols

Are there emojis and symbols in your text? Brace yourself; They won't vanish using the standard methods shared above. Expand your regex patterns or employ Unicode categories to evict these characters:

# Emojis can hide, but they can't escape the regex!
clean_text = re.sub('[\p{P}\p{S}]', '', "Hello, world! 🚀")

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