Low-level programming languages, such as C or C, often use pointers to directly manipulate memory. They enable efficient memory management and low-level data operations.
The low-level complexities of memory administration are abstracted away in Python, a high-level language. Because of this, Python lacks express pointers in an equal manner that C or C . As an alternative, Python makes use of an idea Comparable to this one known as references, which enables indirect access to objects in memory by variables. Python gives builders a sturdy toolkit without requiring them to have a thorough appreciation of low-level memory administration through the use of references and other high-level abstractions .
In Python, everything is an object, and objects are stored in memory. Effectively, when you define a variable in Python, you are creating a reference to the object. This reference actually acts as a pointer to where the object is stored in memory.
Consider the following code, for example.
a = 5 b = a
a = 5 − The Python statement "a = 5" declares a new variable and gives it the integer value of 5. Python produces a new integer object with the value 5 when this line is performed, and it then assigns a reference to that object to the variable a.
b = a − In a comparable way, the statement b = a declares a new variable b and offers it the value of a. Since an object (in this case, an integer object with value 5) is referenced through an object (a), then object (b) is likewise referenced by using an object (a). As a result, references to the identical 5-valued integer object are now shared by way of each a and b.
This is important because it means that changes made to a will also be reflected in b since they are both referencing the same object. For example −
Example
a = 5 b = a a = 6 print(b)
Output
5
As anticipated, yes? To understand the code sample above, follow these easy steps −
a = 5 − This line of code creates a new variable named a and assigns it a value of 5.
b = a − A new variable b is created and assigned the value of a. Variable b holds the integer value of 5 which is the same as variable a.
a = 6 − This changes the integer value of the variable a to a new value of 6. A now has a reference to a different integer object than b at this time.
print(b) − This commands outputs b's value to the console. The output of this line is 5 since b still has a reference to the initial integer object with the value of 5.
Memory management is an essential issue of programming, and Python makes use of computerized garbage collection to manage it. The garbage collector of Python takes care of memory allocation and deallocation automatically whereas, in C or C , developers take the responsibility for memory management.
Python's garbage collector automatically removes objects referenced through variables from memory when they are no longer needed.
This eliminates the want for guided memory management and frees builders to center their attention on writing code, rather than being traumatic about releasing memory. Ultimately, Python's automatic garbage series provides an extra simple and much less error-prone way of handling reminiscence management.
in conclusion
In summary, Python no longer has explicit pointers like C or C, but it uses references, which is the concept of comparability. Python provides everything as objects, and variables as pointers to these objects. So whenever you assign a value to a variable, it means you are pointing to something in memory. Understanding Python's reference system is important because it is a key component of how the language manages memory.
By understanding references, you can better understand how modifications to objects are propagated through the variables that reference them. This can help you write more efficient and profitable code and avoid common pitfalls related to memory management. Therefore, understanding references is an important step in becoming a proficient Python programmer.
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