How to parse a string in python

Sometimes, we encounter situations where the data of our interest is distributed throughout a string in different segments. In order to extract these specific segments from the string, we use string parsing. String parsing involves dividing the string into smaller chunks or tokens using delimiters, allowing us to extract the desired information. This tutorial focuses on how to parse a string in Python. We will explore various methods and functions to parse data strings into lists and extract the information we need. If you want to learn more about Python Programming, visit Python Programming Tutorials.

Using split() or partition() method, we can parse a string into smaller components based on a specified delimiter or separator. You can also use the pattern matching and extraction capabilities of regular expressions (regex) to extract a specific pattern from the strings.

In this article, we will cover the following topics:

  • String Parsing using partition() method
  • String parsing using split() method
  • String Parsing using Regular expressions

The first two methods parses a string using delimiters. The third method is basically used to extract specific data from strings based on predefined patterns. Lets discuss these methods in detail.

String Parsing using partition() method

The partition() method in Python is used for string parsing by splitting a string into three parts based on a specified delimiter. It takes a delimiter as an input parameter and searches for the first occurrence of the delimiter in the string. If the delimiter is found, the method divides the string and returns a tuple consisting of three parts: the leftmost part before the delimiter, the delimiter itself and the rightmost part of the string after the delimiter.

Here’s an example to illustrate how the partition() method works:

#initialize a string
input_string = 'Pencil,Rubber,Ruler,Sharpener'

#create a new lists by parsing the string using "," delimiter

print("After string parsing: ",new_string)
After string parsing:  ('Pencil', ',', 'Rubber,Ruler,Sharpener')

In this example, the string is split at the comma (“,”) using the partition() method. The resulting tuple contains three parts: “Pencil” (the part before the comma), “,” (the comma itself), and “Rubber,Ruler,Sharpener” (the part after the comma). You can also extract these three parts in three different variables as shown below:

#initialize a string
input_string = 'Pencil,Rubber,Ruler,Sharpener'

# Parse the string using the partition() method
first, delimiter, rest = input_string.partition(',')

print("First element:", first)
print("Delimiter:", delimiter)
print("Rest of the string:", rest)
First element: Pencil
Delimiter: ,
Rest of the string: Rubber,Ruler,Sharpener

By using partition(), we can extract the first element, delimiter, and the remaining part of the string easily. This method is useful when we want to split a string into two parts based on a specific delimiter, and we need to access both parts separately.

Note that if the delimiter is not found in the input string, the partition method will return the original string as the first element, an empty string as the delimiter, and an empty string as the rest of the string.

The partition() method does not provide an option to split the string into multiple parts or handle multiple delimiters. Therefore, it is not suitable for complex parsing scenarios where you need to handle multiple delimiters.

String parsing using split() method

Another method is to use the split() function to parse a string into a list of substrings. A delimiter or separator is passed as an input parameter to the function, which splits the input string using the delimiter. Suppose you have a string consisting of a sentence: “The quick brown fox jumps over the lazy dog.”. To parse this string, you can use the split() method. By default, split() splits the string into a list of words based on whitespace characters. However, you can also specify a specific delimiter or separator to split the string.

Here’s an example code:

sentence = "The quick brown fox jumps over the lazy dog."

# Splitting the sentence into words
words = sentence.split()

print("Words:", words)


Words: ['The', 'quick', 'brown', 'fox', 'jumps', 'over', 'the', 'lazy', 'dog.']

In this example, the split() method is used without any argument, so it splits the string based on the spaces in the sentence. Each word is stored as an element in the words list. You can further process the parsed words, perform operations on them, or extract specific information based on your requirement.

You can also use some other delimiter such as comma and define the maximum number of splits in a string. Call the same split() function and now pass two arguments to this function i.e., str.split(delimiter, maximum_splits). Here, maximum_splits specifies the number of splits that you want.

# Initialize a string
input_string = 'John,Smith,28,New York,USA'

# Create a new list by parsing the string using "," delimiter
new_string = input_string.split(",", 3)

print("After string parsing:", new_string)


After string parsing: ['John', 'Smith', '28', 'New York,USA']

In this example, the input string represents information about a person, where each section is separated by a comma. By using the split() method with a maximum of 3 splits, we ensure that the first three comma-separated values are extracted as individual elements in the resulting list. The fourth section, which contains ‘New York’ and ‘USA’ separated by a comma, is treated as a single element in the list.

Defining the maximum number of splits is essential in cases where the input string has sections that may contain the delimiter character itself. By limiting the number of splits, we can ensure that such sections are treated as a single element and not further divided during the parsing process.

Unlike partition() method, the split() method provides the flexibility to handle multiple delimiters for string splitting. By passing multiple delimiters as arguments to the split() method, you can specify different delimiters that should be used to split the string.

Here is an example to demonstrate how the split() method can handle multiple delimiters:

input_string = "Apple, Banana; Mango-Orange"
delimiters = [",", ";", "-"]

# Split the string using multiple delimiters
result = input_string.split(delimiters)

['Apple', ' Banana', ' Mango', 'Orange']

In the example, the input string "Apple, Banana; Mango-Orange" is split using three delimiters: ",", ";", and "-". The split() method recognizes all three delimiters and splits the string at each occurrence of any of these delimiters. The result is a list of substrings obtained after the splits.

Note that the delimiters can be specified as individual characters or strings. Also, if multiple delimiters occur consecutively, the split() method treats them as a single delimiter and does not create empty strings in the result.

Using the split() method with multiple delimiters allows you to handle a wide range of string splitting scenarios involving different delimiters.

String Parsing using Regular expressions

Split() and partition() methods are simple options for basic string splitting based on fixed delimiters. In situations where we encounter a string with a complex structure, such as intricate punctuation or the absence of clear delimiters, traditional methods like split() or partition() may prove to be inefficient or inadequate. These methods may struggle to accurately break down the string and extract the desired information. To tackle these challenges effectively, we can use regular expressions as a powerful alternative. Regular expressions offer more flexibility in handling complex string parsing tasks by allowing us to define patterns and rules for identifying and extracting specific information from the string.

Regular expressions, often abbreviated as regex, are sequences of characters that form a search pattern. They allow you to define a pattern of characters and symbols that can be used to search, match, and manipulate text.

import re

# Define a pattern to search for
pattern = r'fox'

# Define a text string to search within
text = 'The quick brown fox jumps over the lazy dog.'

# Search for the pattern in the text
match =, text)

# Check if a match is found
if match:
    print('Match found:',
    print('No match found.')


Match found: fox

In this example, we import the re module and define a pattern 'fox'. We also define a text string 'The quick brown fox jumps over the lazy dog.'. The function is used to search for the pattern within the text. If a match is found, the method returns the matched substring.

You can use these regular expressions for string parsing in Python. Lets consider an example of email parsing. To extract the sender’s address, recipient’s address, email subject, and message from an email using regular expressions in Python, you can define specific patterns and use the re module.

Start by importing the re module, which provides functions and methods for working with regular expressions. Next, define the regular expression pattern that matches the specific pattern or structure you want to extract from the string. Here’s an example:

import re

email = """
Subject: Hello!
Message: This is the message content.

sender_match ="From: (.+)", email)
recipient_match ="To: (.+)", email)
subject_match ="Subject: (.+)", email)
message_match ="Message: (.+)", email)

if sender_match and recipient_match and subject_match and message_match:
    sender_address =
    recipient_address =
    email_subject =
    message =

    print("Sender's Address:", sender_address)
    print("Recipient's Address:", recipient_address)
    print("Email Subject:", email_subject)
    print("Message:", message)
    print("Unable to extract email information.")


Sender's Address:
Recipient's Address:
Email Subject: Hello!
Message: This is the message content.

In this example, each regular expression pattern captures the desired information from the email string. The function is used to find the first occurrence of each pattern. The .group(1) method retrieves the captured group from the match.

Note that this example assumes a specific email format where the information is structured with specific labels. You may need to modify the regular expressions to match the format of the emails you are working with. Additionally, if you expect multiple occurrences of certain patterns, you can use re.findall() instead of

Regular expressions offer a wide range of functionality beyond simple pattern matching, such as matching multiple occurrences, using wildcards and character classes, specifying optional or repeated patterns, capturing groups, and more. The re module provides various functions and methods to utilize these features, including re.findall(), re.sub(), re.split(), and others.


String parsing is the process of breaking down a string into smaller components or extracting specific information from it. In Python, there are several methods and techniques for string parsing. In this article, we have discussed three different methods i.e., split() function, partition() function and regular expressions for string parsing

Each method has its own advantages and use cases. Splitting and partitioning are simpler alternatives suitable for basic string splitting based on fixed delimiters. Regular expressions are more versatile and can handle more complex parsing tasks involving patterns and varying delimiters.

When choosing a method, consider the specific requirements of your string parsing task and select the most appropriate method based on the complexity and flexibility needed. If you have any questions regarding this article, contact us.

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