For a simple word count based on whitespace-separated tokens, call split() without an argument and count the resulting items:
text = "Python makes text processing approachable."
word_count = len(text.split())
print(word_count) # 5This is a good default for ordinary prose, but it counts tokens rather than punctuation-free or language-aware words. Choose the counting rule that fits your application.
Count whitespace-separated words with split()
With no separator argument, str.split() treats runs of whitespace as separators and omits empty strings at the start or end. Repeated spaces, tabs, and newlines therefore do not inflate the count:
text = " Count thesenwordsthere. "
print(len(text.split())) # 4This method leaves punctuation attached to each token. For example, "Hello," and "world!" are counted as two tokens; the commas and exclamation mark are not removed.
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Choose a different rule when tokens are not enough
Python does not impose one universal definition of a word. If punctuation, identifiers, or editorial conventions matter, make the rule explicit.
Count runs of word characters
Use a regular expression to count each run of Python word characters:
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import re
text = "Hello, snake_case 42!"
word_count = len(re.findall(r"w+", text))
print(word_count) # 3For Unicode strings, Python’s default w includes Unicode alphanumeric characters and underscore. This means numbers and identifiers such as snake_case count as runs of word characters. It is a programming-oriented rule, not necessarily an editorial word count.
Split on runs of non-word characters
If punctuation and whitespace should act as separators, split on W+ and ignore empty results:
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import re
text = "Hello, world!"
parts = re.split(r"W+", text)
word_count = sum(bool(part) for part in parts)
print(word_count) # 2re.split() can return empty items at the beginning or end when the string starts or ends with a separator, so counting the full result length can be wrong. Here, W means the inverse of w: apostrophes and hyphens are separators, but underscore is a word character. A contraction or hyphenated phrase can consequently count differently from an editorial style guide.
Understand Unicode and language boundaries
For Unicode str patterns, Python’s s matches whitespace as defined by str.isspace(), which includes more than ordinary ASCII spaces, tabs, and newlines. The default regex shorthand classes are Unicode-aware for strings. Adding re.ASCII changes shorthand classes such as w, W, s, and d to ASCII-only behavior.
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Neither whitespace splitting nor these regular expressions provide a universal linguistic definition of a word. If the application needs language-specific handling of compounds, apostrophes, or scripts that do not conventionally separate words with spaces, define the required convention or use a tokenizer designed for that language.
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Avoid common counting errors
- Do not use
text.split(" ")as a general whitespace split. An explicit single-space separator does not collapse runs of whitespace or handle tabs and newlines the way no-argumentsplit()does. - Do not expect
split()to remove punctuation. It separates on whitespace only; punctuation remains attached to tokens. - Do not assume
bidentifies linguistic words. Python defines it using the boundary betweenwandW, or a string edge, so it follows those character rules rather than a universal natural-language standard. - Do not count every result of
re.split()blindly. Leading or trailing separators may create empty strings; filter them or count only nonempty parts.
Which method should you use?
| Counting rule | Python expression | Best suited to |
|---|---|---|
| Whitespace-separated tokens | len(text.split()) |
Simple prose and user-entered sentences |
| Runs of Python word characters | len(re.findall(r"w+", text)) |
A character-based convention that includes numbers and underscores |
| Tokens split by non-word characters | sum(bool(part) for part in re.split(r"W+", text)) |
Counting nonempty runs separated by punctuation or whitespace |
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