In Python, operations on variables look similar to a mathematical expressions with some minor differences. Therefore, all the rules of basic mathematical properties like Associative property, Commutative property, etc. apply in Python too but you need to be explicit.
There are couple of operators like Arithmetic operations, Assignments operations, Comparison operations (Relational operations), Logical operations and Identity-Membership operations. We'll see them in detail below.
The basic Arithmetic operations in Python are addition, subtraction, multiplication, division, floored division, modulus and exponential operations.
Note: These can be performed only on numbers with some exceptions for strings and lists.
Addition is the most basic operation of arithmetics, done with an addition operator (+).
Addition is commutative and associative, so the order in which terms are added does not matter.
Numeric addition is of O(n) complexity since you need to add all the n digits and the carry too.
Note: This is true only for adding numbers.
>>> var_1, var_2 = 41, 1 # Parallel variable assignment
>>> total = var_1 + var_2
>>> total
42
>>>In Python, we can take addition to one step further. Python supports addition of strings and lists too.
>>> list_1 = [1, 2, 3]
>>> list_2 = [4, 5, 6]
>>> total = list_1 + list_2 # This is called List extension
>>> total
[1, 2, 3, 4, 5, 6]
>>>and
>>> str_1 = "Hello"
>>> str_2 = "World"
>>> total = str_1 + str_2 # This is called String concatenation
>>> total
'HelloWorld'
>>>Note: You can perform addition only on values of same datatype. Performing addition on variables of different datatype will throw TypeError.
Subtraction is opposite of addition, done with minus operator (-). Subtraction is neither commutative nor associative, so the order in which terms are subtracted does matter alot. Subtraction is only supported by numbers in Python.
Similar to addition, subtraction also has O(n) complexity in python except here you borrow instead of carrying.
>>> var_1, var_2 = 43, 1
>>> total = var_1 - var_2
>>> total
42
>>>Multiplication is also commutative and associative like addition and it is distributive as well. It is done with multiplication operator (*).
Multiplication is different, it has O(n²) complexity.
>>> var_1, var_2 = 42, 1
>>> total = var_1 * var_2
>>> total
42
>>>Just like addition, multiplication can be performed on strings and lists.
>>> list_1 = [1, 2, 3]
>>> total = list_1 * 3
>>> total
[1, 2, 3, 1, 2, 3, 1, 2, 3]
>>>and
>>> str_1 = "Ha"
>>> total = str_1 * 3
>>> total
'HaHaHa'
>>>Note: You can perform multiplication of lists and strings with integers only.
Division is essentially opposite of multiplication, done with slash operator (/). Like subtraction, division is also neither commutative nor associative, so the order in which terms are divided does matter alot. Division is only supported by numbers in Python and output of division operation always returns a float value.
Division is similar to multiplication in terms of complexity, O(n²). Read this for a beautiful explanation of Big O complexity for division.
>>> var_1, var_2 = 420, 10
>>> total = var_1 / var_2
>>> total
42.0
>>>Note: Division returns quotient in float.
Floored division is just like normal division but this return an integral part of the output value. Means it always returns an integer part before the decimal. Floored division is carried out with "//" operator in Python. Complexity of floored division is same as that of normal division.
# Normal Division:
>>> var_1, var_2 = 25, 9
>>> total = var_1 / var_2
>>> total
2.7777777777777777
>>>
# Floored Division:
>>> var_1, var_2 = 25, 9
>>> total = var_1 // var_2
>>> total
2
>>>Note: Floored division returns quotient as integer without rounding-off the value.
Modulus or Modulo operation returns remainder. It is carried out using "%" operator in Python. The output of a modulus operation could be either float or integer depending upon the type of the operands.
>>> var_1, var_2 = 420, 10
>>> total = var_1 % var_2
>>> total
0
>>>Exponentiation or Powers in python are represented using "**" (double asterisk) operator. Like modulus, the output of exponentiation operation could also be either float or integer depending upon the type of the operands.
>>> var_1, var_2 = 2, 3
>>> total = var_1 ** var_2
>>> total
8
>>>Assignments operations are carried out using Augmented assignment or Compound assignment.
An augmented assignment is generally used to replace a statement where an operator takes a variable operates on it and then assigns the result back to the same variable.
We can perform Assignment operations for basic arithmetic operators since this method is a short-hand (shortcut) for writing the arithmetic expression. Also Assignment operations are neither commutative nor associative so the sequence of operands does matter a lot.
Note: Please remember all the execution or operations on objects in Python happen from right to left.
This is how we write Addition assignment.
>>> var_1, var_2 = 41, 1
>>> var_1 += var_2
>>> var_1
42
>>>
# This is basically
>>> var_1 = var_1 + var_2Note: Please note that the first object (object to the left-hand side) gets assigned with the output.
This is how we write Subtraction assignment. Execution is similar to that of Addition assignment.
>>> var_1, var_2 = 43, 1
>>> var_1 -= var_2
>>> var_1
42
>>>
# This is basically
>>> var_1 = var_1 - var_2This is how we write Multiplication assignment. Again execution is similar to that of above assignment methods.
>>> var_1, var_2 = 42, 1
>>> var_1 *= var_2
>>> var_1
42
>>>
# This is basically
>>> var_1 = var_1 * var_2This is how we write Division assignment. Similar execution as above. This too will return float as output by default.
>>> var_1, var_2 = 420, 10
>>> var_1 /= var_2
>>> var_1
42.0
>>>
# This is basically
>>> var_1 = var_1 / var_2This is how we write Floored division assignment.
>>> var_1, var_2 = 420.0, 10.0
>>> var_1 //= var_2
>>> var_1
42
>>>
# This is basically
>>> var_1 = var_1 // var_2This is how we write Modulus assignment.
>>> var_1, var_2 = 420, 10
>>> var_1 %= var_2
>>> var_1
0
>>>
# This is basically
>>> var_1 = var_1 % var_2This is how we write Exponentiation assignment.
>>> var_1, var_2 = 2, 3
>>> var_1 **= var_2
>>> var_1
8
>>>
# This is basically
>>> var_1 = var_1 ** var_2Comparison operations or Relational operations are carried out to check the similarities in Python object. These return boolean and are usually used in If - Else conditional loops.
Read more here. This article will help you understand how, when and why to use Comparison operations.
Equal to operations are carried out using the Equality, "==" (double equal to) operator in Python. Equal to is commutative.
>>> var_1, var_2 = 69, 69
>>> output = var_1 == var_2
>>> output
True
>>>
>>> var_1, var_2 = 420, 69
>>> output = var_1 == var_2
>>> output
False
>>>Not equal to operations are carried out using "!=" operator in Python. Like Equal to, Not equal to is commutative too.
>>> var_1, var_2 = 69, 69
>>> output = var_1 != var_2
>>> output
False
>>>
>>> var_1, var_2 = 420, 69
>>> output = var_1 != var_2
>>> output
True
>>> These are the obvious ones.
# Less than operation
>>> var_1, var_2 = 69, 420
>>> output = var_1 < var_2
>>> output
True
>>>
# Greater than operation
>>> var_1, var_2 = 619, 69
>>> output = var_1 > var_2
>>> output
True
>>>
# Less than equal to operation
>>> var_1, var_2 = 420, 420
>>> output = var_1 <= var_2
>>> output
True
>>>
# Greater than equal to operation
>>> var_1, var_2 = 619, 69
>>> output = var_1 >= var_2
>>> output
True
>>>Logical operations are the ones which usually revolves around the concepts of logical gates in Digital Electronics and kinda works exactly like the same. These are usually* used along in the Comparison operations.
The output of the logical operations is often in 0 and 1.
None, False, 0 (integer/float), [] (empty list) and {} (empty dictionary) are considered to be 0 in Logical operations and rest are considered as 1.
Note: Booleans are subclass (child class) of Integers, hence in Python 0 and 1 can also be resolved or treated as False and True respectively.
If all values are True output will be True. Treat AND operation as multiplication (at least for understanding). See this table:
| Operand 1 | AND | Operand 2 | Output |
|---|---|---|---|
| 0 | . | 0 | 0 |
| 0 | . | 1 | 0 |
| 1 | . | 0 | 0 |
| 1 | . | 1 | 1 |
>>> var_1, var_2 = 420, 420 # Non - Zero values represent True
>>> output = var_1 and var_2
>>> output
420 # This represents 1 or True
>>>
>>> var_1, var_2 = [], 420
>>> output = var_1 and var_2
>>> output
[] # This represents 0 or False
>>> Important Tip: If both the operands are False, first operand will be considered as the output.
If all values are False output will be False. Treat OR operation as addition (at least for understanding). See this table:
| Operand 1 | OR | Operand 2 | Output |
|---|---|---|---|
| 0 | + | 0 | 0 |
| 0 | + | 1 | 1 |
| 1 | + | 0 | 1 |
| 1 | + | 1 | 1 |
>>> var_1, var_2 = 420, 420 # Non - Zero values represent True
>>> output = var_1 or var_2
>>> output
420 # This represents 1 or True
>>>
>>> var_1, var_2 = [], 0
>>> output = var_1 or var_2
>>> output
0 # This represents 0 or False
>>> Important Tip: If both the operands are False, last operand will be considered as the output.
This is a simple negation.
>>> var_1 = 420 # Non - Zero value represent True
>>> output = not var_1
>>> output
False
>>>
>>> var_1 = 0 # False value
>>> output = not var_1
>>> output
1 # This represents True
>>> Identity operator works on the id of the object. If the identity of the objects (ids) is same then it'll return True else False. It is carried out using the "is" keyword.
>>> x = ["a", "b", "c"]
>>> y = ["a", "b", "c"]
>>> x is y
False
>>>This returns False because although the object (["a", "b", "c"]) look equal but they're not referencing to the same object i.e their ids are different.
>>> id(x)
139644023985664
>>> id(y)
139644025323776Please do no get confused Identity of an object and Equality of the object. Objects may look equal but cannot be the same. Well there are few exceptions to this clause, integers from -5 to 256, strings and Singetons would return True for the above test. This is because of the way Python is implemented and this is one of the implementation detail.
In python, "in" is the membership operator where it checks if an object is present in a Container object. If the object is present in the other object then it'll return True, else False.
>>> x = ["a", "b", "c"]
>>> "a" in x
True
>>> "z" in x
False
>>>It doesn't matter how many objects are present in the container, if the object is present it will return True.