5 Best Ways to Convert a String Representation of List into List in Python

πŸ’‘ Problem Formulation: As a Python developer, you might encounter a scenario where you have a string representation of a list, like "['apple', 'banana', 'cherry']", and you wish to convert it into an actual Python list object, resulting in ['apple', 'banana', 'cherry']. This article discusses various methods to achieve this conversion, which is essential when dealing with data serialization or parsing text files that contain list-like structures.

Method 1: Using ast.literal_eval()

The ast.literal_eval() function safely evaluates a string containing a Python literal or container display. This function parses the string as a Python expression and safely evaluates it to return a list object. It is part of Python’s Abstract Syntax Trees (AST) module and is a safe alternative to the built-in eval() function.

Here’s an example:

import ast
str_list = "['apple', 'banana', 'cherry']"
converted_list = ast.literal_eval(str_list)
print(converted_list)

Output:

['apple', 'banana', 'cherry']

This approach is safe and recommended for strings containing literal Python structures because it does not execute code, thus mitigating potential security risks associated with eval().

Method 2: Using json.loads()

For a string that is in JSON array format (which is very similar to Python’s list), the json.loads() method from the JSON module can be used to parse the string and return a list. This method is especially useful when dealing with JSON data fetched from APIs or configuration files.

Here’s an example:

import json
str_list = '["apple", "banana", "cherry"]'
converted_list = json.loads(str_list)
print(converted_list)

Output:

["apple", "banana", "cherry"]

The json.loads() method works well if the string is formatted correctly as a JSON array. It is not suitable for strings representing Python-specific data types or single-quoted strings.

Method 3: Using eval()

The eval() function, while generally discouraged due to security risks, can evaluate a string as a Python expression and convert it into a list. It should be used only if you are sure of the source of the string to avoid executing malicious code.”

Here’s an example:

str_list = "['apple', 'banana', 'cherry']"
converted_list = eval(str_list)
print(converted_list)

Output:

['apple', 'banana', 'cherry']

Due to the potential security risks associated with eval(), this method should only be employed when there is absolute trust in the input.

Method 4: Using a Custom Parser

A custom parsing function can be created to handle specific string formats where standard methods may not apply. This could involve string operations, regular expressions, or other logic tailored to the string’s pattern.

Here’s an example:

def custom_parser(str_list):
    return str_list.strip("[]").replace("'", "").split(", ")

str_list = "['apple', 'banana', 'cherry']"
converted_list = custom_parser(str_list)
print(converted_list)

Output:

['apple', 'banana', 'cherry']

This custom function manually processes the string to convert it into a list. While flexible, this method requires additional coding and may not handle all edge cases well, such as nested lists or items containing commas.

Bonus One-Liner Method 5: Using List Comprehension with strip() and split()

List comprehension offers a compact way to create a list based on existing lists. When combined with string methods strip() and split(), it can also be used to convert string representations of simple, non-nested lists into Python list objects.

Here’s an example:

str_list = "['apple', 'banana', 'cherry']"
converted_list = [item.strip(" '") for item in str_list.strip("[]").split(', ')]
print(converted_list)

Output:

['apple', 'banana', 'cherry']

This one-liner is concise and works well for simple lists but might not handle more complex strings such as nested lists or strings with varying whitespace patterns.

Summary/Discussion

  • Method 1: ast.literal_eval() Safe. Handles complex Python literals. Not for non-literal structures.
  • Method 2: json.loads(). Ideal for JSON data. Requires JSON-format compliant strings.
  • Method 3: eval(). Very flexible. Potentially dangerous if input is untrusted.
  • Method 4: Custom Parser. Highly customizable. May require extensive error handling and is less generalizable.
  • Bonus Method 5: List Comprehension. Quick for simple cases. Limited to basic list formats and not suited for complex parsing.