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python assignment by reference

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In Python, assignment by reference is a concept that refers to the way variables can be assigned to the same memory location. This means that when you assign one variable to another, they both point to the same object in memory. Understanding assignment by reference is crucial for avoiding unexpected behavior in your code.
In Python, objects are created in memory, and variables are references to these objects. When you assign a variable to another, you're not creating a new object but rather creating a new reference to the same object.
Let's start with a simple example:
Output:
As you can see, modifying new_list also affects original_list because they both reference the same list object in memory.
Understanding the distinction between mutable and immutable objects is crucial when dealing with assignment by reference.
Let's illustrate the difference:
Output:
In this case, modifying new_number doesn't affect original_number because integers are immutable.
Output:
Here, modifying new_list affects original_list because lists are mutable.
If you want to create a new object instead of referencing an existing one, you can use techniques like slicing (for mutable objects) or the copy module:
Output:
Output:
Understanding assignment by reference in Python is essential for writing robust and predictable code. By being aware of the mutability of objects and using appropriate techniques like slicing or the copy module, you can control whether variables reference the same object or create new objects in memory. This knowledge is crucial for avoiding unintended side effects and bugs in your code.
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In Python, objects are created in memory, and variables are references to these objects. When you assign a variable to another, you're not creating a new object but rather creating a new reference to the same object.
Let's start with a simple example:
Output:
As you can see, modifying new_list also affects original_list because they both reference the same list object in memory.
Understanding the distinction between mutable and immutable objects is crucial when dealing with assignment by reference.
Let's illustrate the difference:
Output:
In this case, modifying new_number doesn't affect original_number because integers are immutable.
Output:
Here, modifying new_list affects original_list because lists are mutable.
If you want to create a new object instead of referencing an existing one, you can use techniques like slicing (for mutable objects) or the copy module:
Output:
Output:
Understanding assignment by reference in Python is essential for writing robust and predictable code. By being aware of the mutability of objects and using appropriate techniques like slicing or the copy module, you can control whether variables reference the same object or create new objects in memory. This knowledge is crucial for avoiding unintended side effects and bugs in your code.
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