5 Best Ways to Implement CamelCase in Python

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πŸ’‘ Problem Formulation: In Python programming, converting strings to camelCase involves capitalizing the first letter of each word except for the initial word, and removing spaces or other delimiters. This is commonly used in programming languages for defining variable names. For instance, an input string “convert this to camelcase” should transform to the output “convertThisToCamelcase”.

Method 1: Using title() and replace() Methods

To camelCase a string in Python, one can use a combination of the title() and replace() methods. The title() method capitalizes the first letter of each word, and replace() eliminates spaces. However, since title() also capitalizes the first word, additional string slicing or manipulation is necessary to ensure the proper camelCase format.

Here’s an example:

text = "make this camelcase"
camel_cased = text[0].lower() + text.title().replace(" ", "")[1:]

Output: makeThisCamelcase

This snippet takes the input string and applies the title() method to capitalize all words. Afterwards, it uses replace() to remove spaces. String slicing is used at the beginning to ensure the first letter remains lowercase.

Method 2: Using split() and capitalize()

Another method for camelCasing in Python is to split the string into words using split() and then capitalize each word except the first one using capitalize(). This allows more control over which parts of the string are modified.

Here’s an example:

text = "camelcase this string"
words = text.split()
camel_cased = words[0].lower() + ''.join(word.capitalize() for word in words[1:])

Output: camelcaseThisString

In this code, split() breaks the string into a list of words, which are then concatenated back together with the first word staying lowercase and subsequent words being capitalized through list comprehension.

Method 3: Using Regular Expressions

For more complex string patterns or when dealing with delimiters other than spaces, regular expressions (regex) can be used with the re module’s sub() method to convert strings into camelCase format efficiently.

Here’s an example:

import re
text = "convert-this_toCamelcase"
camel_cased = re.sub(r'(?<!^)([A-Z])', r' \1', text).title().replace(" ", "")

Output: ConvertThisToCamelcase

This snippet uses a regular expression to add spaces before capital letters, deals with the potential presence of underscores or hyphens, and then proceeds with the approach similar to title() and replace() as seen in Method 1.

Method 4: Using string concatenation in a loop

To avoid built-in methods altogether, one can iterate over each character of the string and build a new camelCase string by adding capital letters following spaces and omitting the spaces themselves.

Here’s an example:

text = "loop over this string"
camel_cased = ""
upper_next = False

for char in text:
    if char == " ":
        upper_next = True
    camel_cased += char.upper() if upper_next else char
    upper_next = False


Output: loopOverThisString

This code loops through each character in the string and uses a boolean flag to determine whether to capitalize the next character. Spaces are skipped and not added to the resultant string to create the camelCase format.

Bonus One-Liner Method 5: Using join() and a generator expression

A one-liner solution to create camelCase strings in Python can be achieved by using join() with a generator expression that capitalizes all words except the first by evaluating each word’s position in the string.

Here’s an example:

text = "join this into camelcase"
camel_cased = ''.join(w if i == 0 else w.capitalize() for i, w in enumerate(text.split()))

Output: joinThisIntoCamelcase

This one-liner makes use of enumerate() to keep track of the word index while iterating, capitalizing only the words that are not at the first index, and then joining them together without spaces.


  • Method 1: title() and replace(). Quick and efficient for simple strings. May require additional logic for non-space delimiters.
  • Method 2: split() and capitalize(). Provides fine control, but can be more verbose. Does not handle non-space delimiters.
  • Method 3: Regular Expressions. Powerful for complex patterns and various delimiters. Can be less readable for those not familiar with regex.
  • Method 4: Loop and Concatenation. Most flexible and does not rely on built-in methods. Can be slower and more code-heavy.
  • Method 5: Join() and Generator Expression. Elegant one-liner. Efficient and Pythonic, but might sacrifice a bit of readability for beginners.