Sign In
Sign In

String Conversion in Python

String Conversion in Python
Hostman Team
Technical writer
Python
11.12.2023
Reading time: 9 min

Python is one of the most popular programming languages. It has many built-in methods and functions, including those for working with strings. 

Strings are data objects that store a sequence of characters, including letters, numbers, punctuation marks, etc. String conversion is necessary when the user cannot perform some operations on strings due to their peculiarities. For example, he cannot add two strings storing numbers and get their sum. For this purpose, it is necessary to perform the conversion first and then realize the addition. This principle works for all other data types as well.

This instruction will tell you how to convert strings to other data types.

String conversion

String conversion is the process of changing a string data type to another, implemented using Python's built-in methods. There are several cases when you might need it.

  • Information received from users

This may occur in some applications where the user, for example, fills out an input form. By default, all the specified information will be passed as a string. For further interaction with the data, you'll need to convert them to the correct type.

  • Information read from files.

In this case, the user, just as in the previous example, needs to transform the received sequence of characters, whether they are in JSON or XML files. 

  • Data from the database.

When interacting with the database, some data may also be interpreted into the program code as strings. You'll need to convert them to the appropriate data type for the code to work properly.

  • String Comparison.

If you need to compare two strings, they must be of the same data type. However, the choice of this type depends on the comparison requirements. For example, if you want to find out which of the numbers in the compared sequences are larger, you would convert strings into a numeric data format and then perform the comparison.

Based on the examples above, we can say that it is impossible to correctly perform the required operations in your code without converting strings. The Python built-in methods can help with the implementation of this process.

-

String → Integer

First, let's talk about converting a sequence of characters into numbers. The first method is int(). It allows you to convert a string to an integer in Python. Its syntax looks as follows:

int(example_string)

It takes an initial sequence of characters as an argument and then converts it to an integer.

Let's look at an example:

example_string = "112"
result = int(example_string)
print(result)

The result is shown in the picture below.

Image10

If a function argument contains not only digits but also letters or other characters, int() will not be able to perform the conversion and will generate a ValueError. However, in some cases, it can be bypassed. For example, the user passed a number in hexadecimal notation into the argument, which implies the presence of letters in this sequence. In this case, an additional argument is used that specifies the base of the number system. It will make it clear that it is indeed a number.

Let's look at this example:

example_string = "A1"
result = int(example_string, 16)
print(result)

The compiler will not generate any errors and will output the result shown in the image below.

Image4

We have successfully executed the code and the program has converted the string into a decimal integer 161.

String → Float Number

In this chapter, we will talk about converting a sequence of characters into floating-point numbers. The float() function will help us with this. Its syntax does not differ from the function discussed in the previous chapter. It's worth noting that a float number must contain a period, not a comma. Otherwise, Python simply won't be able to interpret the number passed in the string. 

Here is an example of how to use the function:

example_string = "112.112"
result = float(example_string)
print(result)

This example will convert the character sequence 112.112 into a floating point number. The result is shown in the image below.

Image5

In addition to the above function, we should mention the round() function. It allows you to specify the required number of digits after the point. 

For example, if we need the final number to contain only one digit after the dot when converting the string, we should declare the round() function and pass the corresponding argument:

example_string = "112.112"
result = round(float(example_string),1)
print(result)

After these transformations, the result is as follows:

Image3

String → List

Let's look at converting strings to lists in Python, specifically the split() function. 

Lists are comma-enumerated elements enclosed in square brackets. All elements of a list have their unique identifier (index). The data types of the elements may differ.

Now, let's talk about the split() function itself. It splits a string into a list of substrings using a delimiter. By default, it is equal to a space, but it can be changed if necessary. For this purpose, when calling the function, you should specify a unique delimiter, which will be used to form a list of the sequence of characters.

Let's try to apply this function:

example_string = "Monkey-Lion-Tiger"
example_list = example_string.split("-")
print(example_list)

This will give us a list of 3 items as shown in the image below.

Image1

String → Date

While writing code, a programmer may need to convert a string into a date. For this case, Python also has special modules.

strptime method

This method belongs to the datetime module. It creates a date and time object from a string matching the specified format. 

The syntax is as follows:

datetime.strptime (date_string, date_format)

Consider the example below, where we have a sequence of characters 2023-01-01 12:30:31 that we need to convert to date and time. First of all, initialize the module and then write the rest of the code:

from datetime import datetime

date_string = "2023-01-01 12:30:31"
date_object = datetime.strptime(date_string, "%Y-%d-%m %H:%M:%S")
print(date_object)

The date and time format in the example is %Y-%d-%m %H:%M:%S, but it may be different for you because it depends on the date format in the source string.

As you can see from the picture below, the conversion was successful.

Image2

parser.parse function

Now, let's move on to the dateutil module and its parser.parse function. It works the same way as the previous method, but there is one difference. The parser.parse function automatically determines the format of the specified date. 

The syntax of the function call looks as follows:

parser.parse(example_string)

Now let's consider its use by example, remembering to declare the module at the beginning of the code:

from dateutil import parser

date_string = "2023-01-01 12:30:31"
date_object = parser.parse(date_string)
print(date_object)

In the example, we used the familiar date and time. The result is the same as in the previous method.

Image2

String → Function

A function is a code fragment that performs a specific task and can be used many times. When this code fragment is assigned to a string type variable, you may need to convert it into a function. The built-in eval() function will help with this.

eval() analyzes all the data passed to it as an argument and executes the resulting expression if possible. 

Its syntax is as follows:

eval(expression)

Let's look at the use of eval() with an example:

example_string = "print('Hello, user!')"
eval(example_string)

In this example, we store the call to print() in the example_string variable. eval(), in turn, takes the contents of this variable as an argument and calls the read expression. 

As you can see from the picture below, the function call has been successfully executed.

Image9

Use the above function carefully. You should always control the expression that eval() accepts. If passed in from the outside, for example, by other users, it can harm your system. 

String → Bytes

Bytes are a sequence that, unlike strings, are made up of individual bytes. Their syntax is roughly the same as a regular sequence of characters. The only difference is the prefix b before the beginning of the sequence.

The encode() function will help us convert strings to bytes in Python. It will encode the character sequence and return a string of bytes. All you need to specify when calling it is the encoding. The default encoding is utf-8.

Let's look at the example:

example_string = "Hello, user!"
example_bytes = example_string.encode()
print(example_bytes)

The result is a byte version of the specified string in the example_string variable, as shown in the image below.

Image6

If you want to decode the bytes object back to its original form, use the decode() function.

String → Dictionary

A dictionary is a kind of data structure that stores data in the key-value form.

Let's look at two ways to convert a string to a dictionary in Python. 

json.loads()

The first function we consider is json.loads(). It refers to the json module. It takes an initial sequence of characters in JSON format and converts it into a dictionary.

At the beginning of your code, make sure to import the json module.

Example:

import json

json_string = '{"animal": "Dog", "breed": "Labrador", "age": 9}'
result = json.loads(json_string)
print(result)

As a result, we ended up with a dictionary with 3 pairs, demonstrated in the picture below.

Image7

ast.literal_eval()

The next method is ast.literal_eval(). It belongs to the ast module and performs the same function as the previous method.

Let's go straight to the example, remembering to import the required module at the beginning of the code:

import ast

example_string = "{'animal': 'Dog', 'breed': 'Labrador', 'age': 9 }"
result = ast.literal_eval(example_string)
print(result)

Here we have used the same data as in the previous example. As a result, we got exactly the same dictionary as when we used the json.loads() method.

Image7

The only difference between the json.loads() and the ast.literal_eval() methods is that the character sequence the latter accepts must be in dictionary format rather than JSON format.

Conclusion

In this tutorial, we covered seven types of string conversion. We have also provided examples and alternative conversion methods for each of them. We hope the information you got from this article will help you correctly interact with the string data type when writing code.

On our app platform you can deploy Python frameworks, such as Celery, Django, FastAPI and Flask. 

Python
11.12.2023
Reading time: 9 min

Similar

Python

How to Delete Characters from a String in Python

When writing Python code, developers often need to modify string data. Common string modifications include: Removing specific characters from a sequence Replacing characters with others Changing letter case Joining substrings into a single sequence In this guide, we will focus on the first transformation—deleting characters from a string in Python. It’s important to note that strings in Python are immutable, meaning that any method or function that modifies a string will return a new string object with the changes applied. Methods for Deleting Characters from a String This section covers the main methods in Python used for deleting characters from a string. We will explore the following methods: replace() translate() re.sub() For each method, we will explain the syntax and provide practical examples. replace() The first Pyhton method we will discuss is replace(). It is used to replace specific characters in a string with others. Since strings are immutable, replace() returns a new string object with the modifications applied. Syntax: original_string.replace(old, new[, count]) Where: original_string – The string where modifications will take place old – The substring to be replaced new – The substring that will replace old count (optional) – The number of occurrences to replace (if omitted, all occurrences will be replaced) First, let’s remove all spaces from the string "H o s t m a n": example_str = "H o s t m a n" result_str = example_str.replace(" ", "") print(result_str) Output: Hostman We can also use the replace() method to remove newline characters (\n). example_str = "\nHostman\nVPS" print(f'Original string: {example_str}') result_str = example_str.replace("\n", " ") print(f'String after adjustments: {result_str}') Output: Original string: Hostman VPS String after adjustments: Hostman VPS The replace() method has an optional third argument, which specifies the number of replacements to perform. example_str = "Hostman VPS Hostman VPS Hostman VPS" print(f'Original string: {example_str}') result_str = example_str.replace("Hostman VPS", "", 2) print(f'String after adjustments: {result_str}') Output: Original string: Hostman VPS Hostman VPS Hostman VPS String after adjustments: Hostman VPS Here, only two occurrences of "Hostman VPS" were removed, while the third occurrence remained unchanged. We have now explored the replace() method and demonstrated its usage in different situations. Next, let’s see how we can delete and modify characters in a string using translate(). translate( The Python translate() method functions similarly to replace() but with additional flexibility. Instead of replacing characters one at a time, it allows mapping multiple characters using a dictionary or translation table. The method returns a new string object with the modifications applied. Syntax: original_string.translate(mapping_table) In the first example, let’s remove all occurrences of the $ symbol in a string and replace them with spaces: example_str = "Hostman$Cloud$—$Cloud$Service$Provider." print(f'Original string: {example_str}') result_str = example_str.translate({ord('$'): ' '}) print(f'String after adjustments: {result_str}') Output: Original string: Hostman$Cloud$—$Cloud$Service$Provider. String after adjustments: Hostman Cloud — Cloud Service Provider. To improve code readability, we can define the mapping table before calling translate(). This is useful when dealing with multiple replacements: example_str = "\nHostman%Cloud$—$Cloud$Service$Provider.\n" print(f'Original string: {example_str}') # Define translation table example_table = {ord('\n'): None, ord('$'): ' ', ord('%'): ' '} result_str = example_str.translate(example_table) print(f'String after adjustments: {result_str}') Output: Original string: Hostman%Cloud$—$Cloud$Service$Provider. String after adjustments: Hostman Cloud — Cloud Service Provider. re.sub() In addition to replace() and translate(), we can use regular expressions for more advanced character removal and replacement. Python's built-in re module provides the sub() method, which searches for a pattern in a string and replaces it. Syntax: re.sub(pattern, replacement, original_string [, count=0, flags=0]) pattern – The regular expression pattern to match replacement – The string or character that will replace the matched pattern original_string – The string where modifications will take place count (optional) – Limits the number of replacements (default is 0, meaning replace all occurrences) flags (optional) – Used to modify the behavior of the regex search Let's remove all whitespace characters (\s) using the sub() method from the re module: import re example_str = "H o s t m a n" print(f'Original string: {example_str}') result_str = re.sub('\s', '', example_str) print(f'String after adjustments: {result_str}') Output: Original string: H o s t m a nString after adjustments: Hostman Using Slices to Remove Characters In addition to using various methods to delete characters, Python also allows the use of slices. As we know, slices extract a sequence of characters from a string. To delete characters from a string by index in Python, we can use the following slice: example_str = "\nHostman \nVPS" print(f'Original string: {example_str}') result_str = example_str[1:9] + example_str[10:] print(f'String after adjustments: {result_str}') In this example, we used slices to remove newline characters. The output of the code: Original string:HostmanVPSString after adjustments: Hostman VPS Apart from using two slice parameters, you can also use a third one, which specifies the step size for index increments. For example, if we set the step to 2, it will remove every odd-indexed character in the string. Keep in mind that indexing starts at 0. Example: example_str = "Hostman Cloud" print(f'Original string: {example_str}') result_str = example_str[::2] print(f'String after adjustments: {result_str}') Output: Original string: Hostman CloudString after adjustments: HsmnCod Conclusion In this guide, we learned how to delete characters from a string in Python using different methods, including regular expressions and slices. The choice of method depends on the specific task. For example, the replace() method is suitable for simpler cases, while re.sub() is better for more complex situations.
23 August 2025 · 5 min to read
Python

Command-Line Option and Argument Parsing using argparse in Python

Command-line interfaces (CLIs) are one of the quickest and most effective means of interacting with software. They enable you to provide commands directly which leads to quicker execution and enhanced features. Developers often build CLIs using Python for several applications, utilities, and automation scripts, ensuring they can dynamically process user input. This is where the Python argparse module steps in. The argparse Python module streamlines the process of managing command-line inputs, enabling developers to create interactive and user-friendly utilities. As part of the standard library, it allows programmers to define, process, and validate inputs seamlessly without the need for complex logic. This article will discuss some of the most important concepts, useful examples, and advanced features of the argparse module so that you can start building solid command-line tools right away. How to Use Python argparse for Command-Line Interfaces This is how to use argparse in your Python script: Step 1: Import Module First import the module into your Python parser script: import argparse This inclusion enables parsing .py arg inputs from the command line. Step 2: Create an ArgumentParser Object The ArgumentParser class is the most minimal class of the Python argumentparser module's API. To use it, begin by creating an instance of the class: parser = argparse.ArgumentParser(description="A Hostman tutorial on Python argparse.") Here: description describes what the program does and will be displayed when someone runs --help. Step 3: Add Inputs and Options Define the parameters and features your program accepts via add_argument() function: parser.add_argument('filename', type=str, help="Name of the file to process") parser.add_argument('--verbose', action='store_true', help="Enable verbose mode") Here: filename is a mandatory option. --verbose is optional, to allow you to set the flag to make it verbose. Step 4: Parse User Inputs Process the user-provided inputs by invoking the parse_args() Python method: args = parser.parse_args() This stores the command-line values as attributes of the args object for further use in your Python script.  Step 5: Access Processed Data Access the inputs and options for further use in your program: For example: print(f"File to process: {args.filename}") if args.verbose:     print("Verbose mode enabled") else:     print("Verbose mode disabled") Example CLI Usage Here are some scenarios to run this script: File Processing Without Verbose Mode python3 file.py example.txt File Processing With Verbose Mode python3 file.py example.txt --verbose Display Help If you need to see what arguments the script accepts or their description, use the --help argument: python3 file.py --help Common Examples of argparse Usage Let's explore a few practical examples of the module. Example 1: Adding Default Values Sometimes, optional inputs in command-line interfaces need predefined values for smoother execution. With this module, you can set a default value that applies when someone doesn’t provide input. This script sets a default timeout of 30 seconds if you don’t specify the --timeout parameter. import argparse # Create the argument parser parser = argparse.ArgumentParser(description="Demonstrating default argument values.") # Pass an optional argument with a default value parser.add_argument('--timeout', type=int, default=30, help="Timeout in seconds (default: 30)") # Interpret the arguments args = parser.parse_args() # Retrieve and print the timeout value print(f"Timeout value: {args.timeout} seconds") Explanation Importing Module: Importing the argparse module. Creating the ArgumentParser Instance: An ArgumentParser object is created with a description so that a short description of the program purpose is provided. This description is displayed when the user runs the program via the --help option. Including --timeout: The --timeout option is not obligatory (indicated by the -- prefix). The type=int makes the argument for --timeout an integer. The default=30 is provided so that in case the user does not enter a value, then the timeout would be 30 seconds. The help parameter adds a description to the argument, and it will also appear in the help documentation. Parsing Process: The parse_args() function processes user inputs and makes them accessible as attributes of the args object. In our example, we access args.timeout and print out its value. Case 1: Default Value Used If the --timeout option is not specified, the default value of 30 seconds is used: python file.py Case 2: Custom Value Provided For a custom value for --timeout (e.g., 60 seconds), apply: python file.py --timeout 60 Example 2: Utilizing Choices The argparse choices parameter allows you to restrict an argument to a set of beforehand known valid values. This is useful if your program features some specific modes, options, or settings to check. Here, we will specify a --mode option with two default values: basic and advanced. import argparse # Creating argument parser parser = argparse.ArgumentParser(description="Demonstrating the use of choices in argparse.") # Adding the --mode argument with predefined choices parser.add_argument('--mode', choices=['basic', 'advanced'], help="Choose the mode of operation") # Parse the arguments args = parser.parse_args() # Access and display the selected mode if args.mode: print(f"Mode selected: {args.mode}") else: print("No mode selected. Please choose 'basic' or 'advanced'.") Adding --mode: The choices argument indicates that valid options for the --mode are basic and advanced. The application will fail when the user supplies an input other than in choices. Help Text: The help parameter gives valuable information when the --help command is executed. Case 1: Valid Input To specify a valid value for --mode, utilize: python3 file.py --mode basic Case 2: No Input Provided For running the program without specifying a mode: python3 file.py Case 3: Invalid Input If a value is provided that is not in the predefined choices: python3 file.py --mode intermediate Example 3: Handling Multiple Values The nargs option causes an argument to accept more than one input. This is useful whenever your program requires a list of values for processing, i.e., numbers, filenames, or options. Here we will show how to use nargs='+' to accept a --numbers option that can take multiple integers. import argparse # Create an ArgumentParser object parser = argparse.ArgumentParser(description="Demonstrating how to handle multiple values using argparse.") # Add the --numbers argument with nargs='+' parser.add_argument('--numbers', nargs='+', type=int, help="List of numbers to process") # Parse the arguments args = parser.parse_args() # Access and display the numbers if args.numbers: print(f"Numbers provided: {args.numbers}") print(f"Sum of numbers: {sum(args.numbers)}") else: print("No numbers provided. Please use --numbers followed by a list of integers.") Adding the --numbers Option: The user can provide a list of values as arguments for --numbers. type=int interprets the input as an integer. If a non-integer input is provided, the program raises an exception. The help parameter gives the information.  Parsing Phase: After parsing the arguments, the input to --numbers is stored in the form of a list in args.numbers. Utilizing the Input: You just need to iterate over the list, calculate statistics (e.g., sum, mean), or any other calculation on the input. Case 1: Providing Multiple Numbers To specify multiple integers for the --numbers parameter, execute: python3 file.py --numbers 10 20 30 Case 2: Providing a Single Number If just one integer is specified, run: python3 file.py --numbers 5 Case 3: No Input Provided If the script is run without --numbers: python3 file.py Case 4: Invalid Input In case of inputting a non-integer value: python3 file.py --numbers 10 abc 20 Example 4: Required Optional Arguments Optional arguments (those that begin with the --) are not mandatory by default. But there are times when you would like them to be mandatory for your script to work properly. You can achieve this by passing the required=True parameter when defining the argument. In this script, --config specifies a path to a configuration file. By leveraging required=True, the script enforces that a value for --config must be provided. If omitted, the program will throw an error. import argparse # Create an ArgumentParser object parser = argparse.ArgumentParser(description="Demonstrating required optional arguments in argparse.") # Add the --config argument parser.add_argument('--config', required=True, help="Path to the configuration file") # Parse the arguments args = parser.parse_args() # Access and display the provided configuration file path print(f"Configuration file path: {args.config}") Adding the --config Option: --config is considered optional since it starts with --. However, thanks to the required=True parameter, users must include it when they run the script. The help parameter clarifies what this parameter does, and you'll see this information in the help message when you use --help. Parsing: The parse_args() method takes care of processing the arguments. If someone forgets to include --config, the program will stop and show a clear error message. Accessing the Input: The value you provide for --config gets stored in args.config. You can then use this in your script to work with the configuration file. Case 1: Valid Input For providing a valid path to the configuration file, use: python3 file.py --config settings.json Case 2: Missing the Required Argument For running the script without specifying --config, apply: python3 file.py Advanced Features  While argparse excels at handling basic command-line arguments, it also provides advanced features that enhance the functionality and usability of your CLIs. These features ensure your scripts are scalable, readable, and easy to maintain. Below are some advanced capabilities you can leverage. Handling Boolean Flags Boolean flags allow toggling features (on/off) without requiring user input. Use the action='store_true' or action='store_false' parameters to implement these flags. parser.add_argument('--debug', action='store_true', help="Enable debugging mode") Including --debug enables debugging mode, useful for many Python argparse examples. Grouping Related Arguments Use add_argument_group() to organize related arguments, improving readability in complex CLIs. group = parser.add_argument_group('File Operations') group.add_argument('--input', type=str, help="Input file") group.add_argument('--output', type=str, help="Output file") Grouped arguments appear under their own section in the --help documentation. Mutually Exclusive Arguments To ensure users select only one of several conflicting options, use the add_mutually_exclusive_group() method. group = parser.add_mutually_exclusive_group() group.add_argument('--json', action='store_true', help="Output in JSON format") group.add_argument('--xml', action='store_true', help="Output in XML format") This ensures one can choose either JSON or XML, but not both. Conclusion The argparse Python module simplifies creating reliable CLIs for handling Python program command line arguments. From the most basic option of just providing an input to more complex ones like setting choices and nargs, developers can build user-friendly and robust CLIs. Following the best practices of giving proper names to arguments and writing good docstrings would help you in making your scripts user-friendly and easier to maintain.
21 July 2025 · 10 min to read
Python

How to Get the Length of a List in Python

Lists in Python are used almost everywhere. In this tutorial we will look at four ways to find the length of a Python list: by using built‑in functions, recursion, and a loop. Knowing the length of a list is most often required to iterate through it and perform various operations on it. len() function len() is a built‑in Python function for finding the length of a list. It takes one argument—the list itself—and returns an integer equal to the list’s length. The same function also works with other iterable objects, such as strings. Country_list = ["The United States of America", "Cyprus", "Netherlands", "Germany"] count = len(Country_list) print("There are", count, "countries") Output: There are 4 countries Finding the Length of a List with a Loop You can determine a list’s length in Python with a for loop. The idea is to traverse the entire list while incrementing a counter by  1 on each iteration. Let’s wrap this in a separate function: def list_length(list): counter = 0 for i in list: counter = counter + 1 return counter Country_list = ["The United States of America", "Cyprus", "Netherlands", "Germany", "Japan"] count = list_length(Country_list) print("There are", count, "countries") Output: There are 5 countries Finding the Length of a List with Recursion The same task can be solved with recursion: def list_length_recursive(list): if not list: return 0 return 1 + list_length_recursive(list[1:]) Country_list = ["The United States of America", "Cyprus", "Netherlands","Germany", "Japan", "Poland"] count = list_length_recursive(Country_list) print("There are", count, "countries") Output: There are 6 countries How it works. The function list_length_recursive() receives a list as input. If the list is empty, it returns 0—the length of an empty list. Otherwise it calls itself recursively with the argument list[1:], a slice of the original list starting from index 1 (i.e., the list without the element at index 0). The result of that call is added to 1. With each recursive step the returned value grows by one while the list shrinks by one element. length_hint() function The length_hint() function lives in the operator module. That module contains functions analogous to Python’s internal operators: addition, subtraction, comparison, and so on. length_hint() returns the length of iterable objects such as strings, tuples, dictionaries, and lists. It works similarly to len(): from operator import length_hint Country_list = ["The United States of America", "Cyprus", "Netherlands","Germany", "Japan", "Poland", "Sweden"] count = length_hint(Country_list) print("There are", count, "countries") Output: There are 7 countries Note that length_hint() must be imported before use. Conclusion In this guide we covered four ways to determine the length of a list in Python. Under equal conditions the most efficient method is len(). The other approaches are justified mainly when you are implementing custom classes similar to list.
17 July 2025 · 3 min to read

Do you have questions,
comments, or concerns?

Our professionals are available to assist you at any moment,
whether you need help or are just unsure of where to start.
Email us
Hostman's Support