Python an Immutable Object

Summary

This video delves into the concept of object immutability in Python, using the example of an integer object with the value 2. It clarifies the misconception that variables can change by demonstrating that when 'first_number' is reassigned the value 5, a new object is created and the reference is updated, leaving the original object unreferenced and eligible for garbage collection. The video emphasizes the importance of understanding object references and the role of the garbage collector in managing memory, encouraging viewers to revisit these concepts as they advance in their Python journey.

Takeaways

• 🔑 The video assumes viewers have seen the previous one, which introduced key concepts for understanding this video's content.
• 📚 The previous video explained how assigning a value to a variable creates an execution space, an object reference, and an object, binding them together.
• 🔢 The video discusses the concept of an 'integer object', which is immutable, meaning its value cannot be changed once created.
• 🤔 The notion of immutability may seem counterintuitive when we can change the value of a variable in Python, but the video clarifies this by explaining the process of object reference reassignment.
• 🎯 When a variable is reassigned a new value, Python creates a new object for that value, and the object reference is updated to point to the new object, leaving the old object unbound.
• 🗑️ Unbound objects are eventually cleaned up by Python's garbage collector, which frees up memory space by removing objects that are no longer referenced.
• 🧩 The video uses the analogy of an execution space to illustrate how Python manages memory and object references, providing a deeper understanding of what happens 'under the hood'.
• 📈 The video encourages viewers to start with a simpler model of variables and objects and to revisit the concept of immutability as their understanding of Python deepens.
• 🔄 The process of variable assignment and reassignment in Python involves more steps than might be initially apparent, including object creation and reference updating.
• 🔗 The video suggests visiting a supporting website and subscribing to the YouTube channel for further updates and resources on Python programming.

Q & A

What is the key concept introduced in the previous video that is essential for understanding this video?

The key concept introduced in the previous video is the process of assigning values to variables, which involves creating an execution space, generating an object reference, and binding the object reference to an object with a specific value.

What does it mean for an object to be immutable in Python?

An object being immutable in Python means that once it is created, its value cannot be changed. This is in contrast to the common perception of variable assignment where it appears that the value of a variable can be changed.

How does Python handle the assignment of a new value to a variable that was previously assigned to an immutable object?

When a new value is assigned to a variable that was previously bound to an immutable object, Python creates a new object with the new value and updates the object reference to point to this new object, leaving the old object unbound and available for garbage collection.

What is the role of the garbage collector in Python's memory management?

The garbage collector in Python is responsible for identifying and removing objects that are no longer referenced by any variables or object references, thus freeing up memory space for other programs to use.

Why is it important to understand the difference between the simple model of variable assignment and the more complex reality of object references and immutability?

Understanding the difference between the simple model of variable assignment and the complex reality of object references and immutability is important because it provides a deeper insight into how Python manages memory and how variables actually work under the hood, which can help in writing more efficient and error-free code.

What happens when an object reference is overwritten with a new address during variable assignment?

When an object reference is overwritten with a new address, the previous binding to the old object is removed, and the object reference now points to the new object. The old object, if no other references point to it, becomes eligible for garbage collection.

How does the concept of immutability relate to the performance and efficiency of Python programs?

The concept of immutability can contribute to the performance and efficiency of Python programs by preventing unintended side effects and allowing for certain optimizations, such as the reuse of immutable objects and the avoidance of unnecessary memory allocation.

What is the practical implication of understanding the difference between the simple model of variable assignment and the actual process in Python?

The practical implication of understanding the difference is that it helps programmers to anticipate how their code will behave, especially in complex scenarios involving data structures and object-oriented programming, leading to better design and debugging strategies.

Why might a programmer initially be confused by the concept of immutability when they can seemingly change the value of a variable?

A programmer might initially be confused by the concept of immutability because the act of changing a variable's value in Python actually involves creating a new object and updating the object reference, rather than changing the value of the existing object, which can seem counterintuitive to the common understanding of variable assignment.

How can the understanding of object references and immutability help in managing memory more effectively in Python?

Understanding object references and immutability can help in managing memory more effectively by allowing programmers to write code that minimizes unnecessary object creation and takes advantage of Python's garbage collection, thus optimizing memory usage and performance.

Outlines

00:00

🔗 Understanding Object References and Immutability

This paragraph discusses the concept of object references and immutability in Python. It explains that when a variable is assigned a value, an object reference is created, and the object is given a value. The object reference is bound to the object, and the object's value is stored in the execution space. The paragraph highlights that integer objects in Python are immutable, meaning their values cannot be changed once created. It uses an example to illustrate how assigning a new value to a variable does not change the original object but instead creates a new object with the new value. The concept of garbage collection is introduced to explain how Python manages memory by removing objects that are no longer referenced, thus freeing up memory space.

05:01

🔄 Simplifying Python's Execution Space for Beginners

The second paragraph serves as a reminder that while the detailed explanation of Python's execution space and immutability is accurate, it can be overwhelming for beginners. It suggests that starting with a simpler model of variables and assignments is sufficient for those new to Python. The paragraph reassures viewers that they can return to the more complex understanding of objects and object references later on. It also encourages viewers to visit the supporting website and subscribe to the YouTube channel for updates on new video uploads.

Keywords

💡Execution Space

Execution space refers to the memory area where a program's objects and variables reside during runtime. In the video, it is mentioned that when the program statement assigns 'first number' to 2, an execution space is created, and an object reference and object are generated. The object reference is given the name 'first number', and the object is assigned the value of 2. This concept is central to understanding how Python handles memory allocation and object references.

💡Object Reference

An object reference is a variable that holds the memory address of an object. In the context of the video, 'first number' is an object reference that is bound to an object containing the value 2. The video explains that object references are pointers to the location of objects in the execution space, and they are crucial for accessing and manipulating the data stored in objects.

💡Immutable

The term 'immutable' is used to describe objects whose state cannot be altered after they are created. In the video, it is explained that integer objects in Python are immutable, meaning once an integer object is created (like the object holding the value 2), its value cannot be changed. This is a fundamental concept in Python that contrasts with the apparent mutability seen when reassigning values to variables.

💡Garbage Collector

The garbage collector is a component of Python that automatically manages memory by identifying and disposing of objects that are no longer referenced. The video describes how, after an object reference like 'first number' is reassigned to a new object (with the value 5), the previous object (holding the value 2) becomes unreferenced. The garbage collector then clears this object from memory, preventing memory leaks.

💡Assignment Statement

An assignment statement is a fundamental operation in programming where a value is bound to a variable. In the video, the script discusses how an assignment statement like 'first number = 2' creates an object and an object reference, and how subsequent assignment statements can change the object reference to point to new objects, as seen with 'first number = 5'.

💡Variable

A variable is a storage location paired with an associated symbolic name, which contains some known or unknown quantity of information referred to as a value. The video uses the term 'variable' to explain how 'first number' is a variable that initially stores the value 2 but can later store the value 5, demonstrating the mutable nature of variables in contrast to the immutability of the objects they reference.

💡Memory Address

A memory address is a reference or pointer to a specific location in a computer's memory. In the video, it is mentioned that the object reference 'first number' is loaded with the address of the location of the object in the execution space. This address is what binds the object reference to the actual data stored in memory.

💡Binding

Binding in the context of the video refers to the association between an object reference (like 'first number') and an object (like the object with the value 2). The video explains that when an object reference is given the address of an object, they are bound together, allowing the program to access the object's data through the reference.

💡Integer Object

An integer object is a specific type of object in Python that holds integer values. The video emphasizes that once an integer object is created, its value is immutable, which means it cannot be changed. This is demonstrated when the script shows that reassigning 'first number' to 5 results in the creation of a new integer object with the value 5, rather than changing the value of the existing object with the value 2.

💡Reassignment

Reassignment in programming is the process of assigning a new value to an already declared variable. The video uses the concept of reassignment to illustrate how the variable 'first number' can be reassigned from 2 to 5, which results in the creation of a new object and the old object becoming eligible for garbage collection due to it no longer being referenced.

Highlights

Understanding Python's execution space and object references is crucial for grasping programming concepts.

The video assumes viewers have watched the previous one for foundational concepts.

Assigning a value to a variable creates an object reference and an object in the execution space.

The object reference is bound to the object, which holds the assigned value.

Integer objects in Python are immutable, meaning their values cannot be changed once created.

The concept of immutability may seem counterintuitive when variables appear to change.

When a variable is reassigned, a new object is created, and the reference is updated, not the original object.

The original object, now unreferenced, becomes eligible for garbage collection.

Garbage collection is Python's mechanism for cleaning up unused objects and freeing memory.

For beginners, it's acceptable to think of variables as mutable, but understanding immutability is important.

The video encourages revisiting the concept of immutability as one progresses in learning Python.

The video provides a simplified model for understanding Python entities and their relationships.

The video explains the process of variable assignment and reassignment in Python's execution space.

The video uses animations to illustrate the movement of values and references in memory.

The video emphasizes the importance of understanding how Python manages memory and objects.

The video suggests that viewers check out the supporting website and subscribe to the YouTube channel for updates.

Transcripts

for this video it is assumed you've

watched the previous one in the playlist

as it introduced concepts that are key

to understanding what goes on in this

particular video here so if we remember

very briefly the last video looked at

assigning to two available call first

number ie this program statements here

and we should know that produced an

execution space and we generated an

object reference and an object and the

object reference is given the name first

number and the object is given the value

of two and we then load up the object

reference with the address of the

location of the object in the execution

space and we say these are bound

together now there was a fuller

explanation as I say in the previous

video so you didn't quite know what was

going on there I strongly recommend you

stop this video we're gonna look at the

previous one now something important

happens here you see what we're dealing

with is an object which is referred to

as an integer object because we're

storing an integer in it ie 2 is an

example of an integer and this sounds a

bit bizarre but once this integer object

is created its value cannot be changed

the integer object is said to be

immutable meaning it cannot be changed

but this seems not to make much sense

for example if we just forget this

execution space for a moment and let's

have a look at this if I have a variable

called first number and I assigned that

to we've looked at a model before which

has a variable called first number and

this assignment statement copies the 2

into the variable and we can see the

animation moving the value into my model

of what a variable is if I then execute

this program statement or should I say

when Python now execute this we can see

the first number is being assigned 5 so

5 is copied to first number and of

course what this will mean is the 5 will

move and replace the 2 so that variable

has changed so what's all this

we've been referring to as being

immutable because we can clearly see

here that the variable was changed

ie it first of all store two and then it

start five well let's go back and have a

look at this a game with the execution

space here we can see first number

assigned to this will create this

execution space here and of course we

will have an object reference and the

knob ship being created and the object

reference is given the name first number

and the 2 is moved to the center of the

object to the core of the object Python

then arranges for the object reference

to have the address of the object as

represented by this arrow which points

to the object in the execution space so

these are then bound so what happens

here if I say first number is assigned 5

well what will actually happen is this

when this executes another object is

created and that object is given the

value 5 now keep your eye on the object

reference first number what will happen

is another address will come in over

writing what's there before now the

consequence here is first number is the

object reference and it no longer has

the address of the object that contains

2 so it can't be bound so that bound

line is removed because this object

reference is now bound to 5 as we can

see here now a careful look at the

object containing 2 shows that nothing

is bound to it so what we need to do we

need to mark this now the trouble is

because that is not bound to an object

reference we don't know where it is in

the execution space there is nothing to

point to it now if this was allowed to

happen

ie we create objects and then through

our code we end up changing the pointer

that appears in the object reference

will have objects cluttering up the

execution space so what python does and

as programmers we don't have to worry

about this he's done for us it's garbage

collector

now what does that mean well it simply

means that every now and then panting

goes around having a look at its

execution space ie it's kind of memory

earlier and says well I've got an object

here well this thing is clogging up the

memory and nobody seems to be pointing

to it I know what I'll do I'll get rid

of it and that's precisely what happens

I'm not getting rid of it out of the

memory simply frees up the memory frees

up space to be used by other programs

and this is quite important freeing up

memory space especially on computers

where you can do lots of processing

however we can simply go with this model

here where that is assigned to first

numb but when we have this statement

five is assigned to it so the question

is are we okay to go with this for now

when we're starting off on understanding

your Python entities of course we are we

could think of variables as being

changed as you see here but this notion

of something being immutable is quite

important and we'll come back to that as

and when we move through our

understanding of the Python language

just to remind you what actually happens

is this

that's quite a lot of things happening

isn't there you see first number was

assigned to and then first number was

assigned five so it looks like well

that's pretty straightforward but in

fact when we look at the execution space

and we consider what went on under the

bonnet or under the hood of Python we

can see it was a little bit more

involved than possibly you might have

been expecting

however there'll be no harm if you just

go with the simpler model for the time

being and return to this understanding

of objects and object references at some

later date

check out the supporting website for

these videos and consider subscribing to

the YouTube channel that you'll get an

automatic update every time I upload a

new video on Piper