In Python, turning a string into an integer is a common task. While the built-in int() function is often enough, different scenarios call for different techniques. Whether you're handling formatted strings, numbers from files, or batch conversions, Python offers several methods that cover just about every situation. Some are more flexible, others are more secure. Here's a look at the main ways to handle string-to-int conversion, depending on what you're working with.

7 Methods to Convert String to Int in Python

Converting to Float First, Then to Int

If the string contains a decimal, int() alone will cause an error. But if your goal is to extract the whole number part, passing the string through float() first solves the issue:

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s = "42.7"

num = int(float(s)) # 42

This drops everything after the decimal. It doesn’t round—so "99.9" becomes 99, not 100.

This works well when you're handling strings that might contain decimal values, but your goal is to work with integers. It’s useful in data parsing or when converting numbers from input forms that don’t restrict decimal input.

Using ast.literal_eval() from the ast Module

Python’s ast module includes a function called literal_eval() that safely evaluates a string containing a Python literal and returns its actual value. For converting strings like "123" into an integer, it works without a problem:

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import ast

s = "123"

num = ast.literal_eval(s)

This isn’t limited to integers. It can handle floats, booleans, lists, dictionaries—basically any valid literal that Python understands. Unlike eval(), it won’t run arbitrary code, so it’s safer for use on strings that come from external sources or saved configurations.

However, it's not designed for custom formats or loose syntax. Any deviation from Python’s literal rules will raise a ValueError or SyntaxError.

Using json.loads() for JSON-style Numbers

If your string data originates from JSON, json.loads() offers a clean and safe way to convert it into a number:

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import json

s = "300"

num = json.loads(s) # 300

This works perfectly if the number is a valid JSON numeric string. But JSON has stricter rules than Python’s int() function. For example, JSON doesn’t allow leading zeros:

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s = "0123"

num = json.loads(s) # Raises JSONDecodeError

So while it's accurate and dependable when working with JSON-encoded content, it’s not forgiving. Any extra characters or formatting inconsistencies will cause it to fail.

Using the Built-in int() Function

This is the standard method for turning a plain numeric string into an integer:

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s = "456"

num = int(s)

It also handles different number bases. You can convert binary, octal, or hexadecimal strings by passing the base as a second argument:

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s = "1A"

num = int(s, 16) # 26

Or:

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s = "1011"

num = int(s, 2) # 11

This method is direct and efficient, but it’s strict. Any string that includes spaces, commas, decimal points, or characters outside the expected format will raise a ValueError. It's best for clean numeric strings that you're confident won't include any unexpected extras.

Using eval() When Input Is Fully Controlled

eval() is capable of evaluating any Python expression stored as a string. That includes numeric values, expressions, or strings representing values in different bases:

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s = "0x10"

num = eval(s) # 16

It also handles mathematical expressions:

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s = "50 + 25"

num = eval(s) # 75

But this method comes with a clear warning. If the input isn't fully controlled or sanitized, eval() can execute dangerous code. Anything beyond your direct control—like user input or external sources—should not be passed to eval() under any circumstances. It's meant for situations where you fully trust the content and need the extra flexibility it provides.

Converting a List of Strings Using List Comprehension

For multiple strings, list comprehension is a clean way to apply conversion in one line:

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string_list = ["1", "2", "3"]

int_list = [int(i) for i in string_list]

This format is efficient, easy to read, and widely used when working with bulk data. If the list includes decimal numbers in string form, and you're looking to convert them to whole numbers, you can combine float() and int() directly in the comprehension:

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string_list = ["10.5", "20.1"]

int_list = [int(float(i)) for i in string_list] # [10, 20]

This keeps your code compact while handling values that aren't plain integers.

Using map() with a Lambda or Function Reference

Another method for batch conversion is map(), which applies a function to every item in an iterable. If you’re converting a list of numeric strings to integers, this works just as well as list comprehension:

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string_list = ["4", "5", "6"]

int_list = list(map(int, string_list))

It’s equally valid to use a lambda if the conversion requires an extra step:

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string_list = ["7.2", "8.5"]

int_list = list(map(lambda x: int(float(x)), string_list)) # [7, 8]

map() becomes useful when the transformation is being passed as an argument to another function, or when you’re applying multiple functions in a row. It doesn’t add new capabilities over list comprehension, but it can sometimes make the structure of your code easier to manage.

Conclusion

Python gives you several ways to convert strings to integers. Whether you're handling plain numbers, decimals, JSON content, or batches of values, there’s a method that fits. Some are simple and direct, like int(), while others, like literal_eval() or json.loads()—offer extra structure or safety for specific contexts.

For more complex conversions, combining functions like float() and int() can help manage strings that carry decimal points. And when processing multiple strings, tools like list comprehension and map() keep your code short and clear.