Home Backend Development Python Tutorial How to dynamically create an object through a string and call its methods in Python?

How to dynamically create an object through a string and call its methods in Python?

Apr 01, 2025 pm 11:18 PM
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How to dynamically create an object through a string and call its methods in Python?

This article explains how to dynamically create objects through strings in Python and call their methods, which is very useful when you need to flexibly process objects based on configuration or runtime information. It is not possible to use strings directly, so it requires the help of Python's reflection mechanism.

The core lies in the getattr function, which receives object and attribute names (strings) as parameters. If the attribute exists, the attribute value is returned; otherwise, AttributeError exception is thrown. Combined with the importlib.import_module dynamic import module, we can implement dynamic creation and call.

Example:

Suppose we have two files: my_module.py defines classes and functions; main.py is responsible for dynamic calls.

my_module.py :

 class MyClass:
    def __init__(self, name):
        self.name = name

    def my_method(self):
        print(f"Hello, {self.name}!")

def my_function():
    print("This is a function.")
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main.py :

 import importlib

module_name = "my_module"
class_name = "MyClass"
method_name = "my_method"
function_name = "my_function"

# Dynamic import module module = importlib.import_module(module_name)

# Dynamically create an object and call a method try:
    my_class = getattr(module, class_name)("World")
    getattr(my_class, method_name)() # Call method# Dynamically call the function getattr(module, function_name)()

except AttributeError as e:
    print(f"Error: {e}")
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Running main.py will output:

 <code>Hello, World! This is a function.</code>
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This code demonstrates how to dynamically import modules through the strings module_name , class_name , method_name and function_name , create objects and call their methods and functions. try...except block handles possible AttributeError exceptions, improving code robustness. This provides an effective way to build flexible Python applications.

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