Product code looks like abcd2343, how to split by letters and numbers?

Question

I have a list of product codes in a text file, on each line is the product code that looks like:

abcd2343 abw34324 abc3243-23A

So it is letters followed by numbers and other characters.

I want to split on the first occurrence of a number.

Answer 1

import re s='abcd2343 abw34324 abc3243-23A' re.split('(\d+)',s)  > ['abcd', '2343', ' abw', '34324', ' abc', '3243', '-', '23', 'A'] 

Or, if you want to split on the first occurrence of a digit:

re.findall('\d*\D+',s) > ['abcd', '2343 abw', '34324 abc', '3243-', '23A'] 

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• \d+ matches 1-or-more digits.
• \d*\D+ matches 0-or-more digits followed by 1-or-more non-digits.
• \d+|\D+ matches 1-or-more digits or 1-or-more non-digits.

Consult the docs for more about Python's regex syntax.

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re.split(pat, s) will split the string s using pat as the delimiter. If pat begins and ends with parentheses (so as to be a "capturing group"), then re.split will return the substrings matched by pat as well. For instance, compare:

re.split('\d+', s) > ['abcd', ' abw', ' abc', '-', 'A']   # <-- just the non-matching parts  re.split('(\d+)', s) > ['abcd', '2343', ' abw', '34324', ' abc', '3243', '-', '23', 'A']  # <-- both the non-matching parts and the captured groups 

In contrast, re.findall(pat, s) returns only the parts of s that match pat:

re.findall('\d+', s) > ['2343', '34324', '3243', '23'] 

Thus, if s ends with a digit, you could avoid ending with an empty string by using re.findall('\d+|\D+', s) instead of re.split('(\d+)', s):

s='abcd2343 abw34324 abc3243-23A 123'  re.split('(\d+)', s) > ['abcd', '2343', ' abw', '34324', ' abc', '3243', '-', '23', 'A ', '123', '']  re.findall('\d+|\D+', s) > ['abcd', '2343', ' abw', '34324', ' abc', '3243', '-', '23', 'A ', '123'] 

Answer 2

This function handles float and negative numbers as well.

def separate_number_chars(s):     res = re.split('([-+]?\d+\.\d+)|([-+]?\d+)', s.strip())     res_f = [r.strip() for r in res if r is not None and r.strip() != '']     return res_f 

For example:

utils.separate_number_chars('-12.1grams') > ['-12.1', 'grams']