Back in 1991, Python 1.0 was released with the goal of emphasizing code readability and to make programming accessible to a wider audience. Looking at other languages at the time, the bar was set really high for those who are new to programming.
At the time, you had to manage memory yourself, know how pointers worked, and worked with rigid syntax.
Python solved a lot of these problems by introducing the idea that programmers should have everything at their fingertips; one way they did this was by forcing everything to be an object and giving you all the functionality (type conversion, data manipulation) built-in.
Understanding objects
In many programming languages, an object combines state (data) and behavior (functions) into a single unit. It’s best demonstrated with an example - we’ll use a bank account as an example.
In a bank account, you have your money (data) and ways to interact with your money (withdraw, deposit - these are functions). If this were to be represented in Python, it would look something like this:
class BankAccount:
def __init__(self, balance):
self.balance = balance
def deposit(self, amount):
self.balance += amountWe’re able to define how we withdraw and deposit money within the class.
Everything is an object
To someone who’s new to programming, the consistency of the Python syntax makes sense:
5.bit_length()
"hello".upper()
[1, 2, 3].append(4)But in languages like C or C++, you can’t necessarily do these things straight out of the gates. For example, in C, you’d have to implement append functionality yourself:
#include <stdio.h>
#include <stdlib.h>
int main() {
int size = 3;
int *numbers = malloc(size * sizeof(int));
numbers[0] = 1;
numbers[1] = 2;
numbers[2] = 3;
// Increase size
size += 1;
numbers = realloc(numbers, size * sizeof(int));
numbers[3] = 4;
for (int i = 0; i < size; i++) {
printf("%d ", numbers[i]);
}
free(numbers);
}Okay, so… why is this important?
When working with Python, you may run into some weird quirks, like why copying variables aren’t actual copies. For instance:
>>> a = [1, 2, 3]
>>> b = a
>>> b.append(4)
>>> a
[1, 2, 3, 4]Keeping in mind that everything is an object helps explain performance differences. In Python, an integer isn’t 4 bytes like in C - it’s a full object:
>>> import sys
>>> x = 5
>>> sys.getsizeof(x) # in bytes
28» This topic sets the foundation for understanding mutability - check out the article here.
Happy coding!
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