Python Literals

Python Literals can be defined as data that is given in a variable or constant.

Python supports the following literals:

1. String literals:

String literals can be formed by enclosing a text in the quotes. We can use both single as well as double quotes to create a string.

Example:

1. "Aman" , '12345'  

Types of Strings:

There are two types of Strings supported in Python:

a) Single-line String- Strings that are terminated within a single-line are known as Single line Strings.

Example:

1. text1='hello'  

b) Multi-line String - A piece of text that is written in multiple lines is known as multiple lines string.

There are two ways to create multiline strings:

1) Adding black slash at the end of each line.

Example:

1. text1='hello\    
2. user'    
3. print(text1)  

'hellouser'  

2) Using triple quotation marks:-

Example:

1. str2='''''welcome  
2. to  
3. SSSIT'''    
4. print str2   

Output:

welcome  
to  
SSSIT  

II. Numeric literals:

Numeric Literals are immutable. Numeric literals can belong to following four different numerical types.

Int(signed integers)	Long(long integers)	float(floating point)	Complex(complex)
Numbers( can be both positive and negative) with no fractional part.eg: 100	Integers of unlimited size followed by lowercase or uppercase L eg: 87032845L	Real numbers with both integer and fractional part eg: -26.2	In the form of a+bj where a forms the real part and b forms the imaginary part of the complex number. eg: 3.14j

Example - Numeric Literals

1. x = 0b10100 #Binary Literals  
2. y = 100 #Decimal Literal   
3. z = 0o215 #Octal Literal  
4. u = 0x12d #Hexadecimal Literal  
5.   
6. #Float Literal  
7. float_1 = 100.5   
8. float_2 = 1.5e2  
9.   
10. #Complex Literal   
11. a = 5+3.14j  
12.   
13. print(x, y, z, u)  
14. print(float_1, float_2)  
15. print(a, a.imag, a.real)  

Output:

20 100 141 301
100.5 150.0
(5+3.14j) 3.14 5.0

III. Boolean literals:

A Boolean literal can have any of the two values: True or False.

Example - Boolean Literals

1. x = (1 == True)  
2. y = (2 == False)  
3. z = (3 == True)  
4. a = True + 10  
5. b = False + 10  
6.   
7. print("x is", x)  
8. print("y is", y)  
9. print("z is", z)  
10. print("a:", a)  
11. print("b:", b)  

Output:

x is True
y is False
z is False
a: 11
b: 10

IV. Special literals.

Python contains one special literal i.e., None.

None is used to specify to that field that is not created. It is also used for the end of lists in Python.

Example - Special Literals

1. val1=10    
2. val2=None    
3. print(val1)     
4. print(val2)  

Output:

10
None

V. Literal Collections.

Python provides the four types of literal collection such as List literals, Tuple literals, Dict literals, and Set literals.

List:

• List contains items of different data types. Lists are mutable i.e., modifiable.
• The values stored in List are separated by comma(,) and enclosed within square brackets([]). We can store different types of data in a List.

Example - List literals

1. list=['John',678,20.4,'Peter']    
2. list1=[456,'Andrew']    
3. print(list)    
4. print(list + list1)  

Output:

['John', 678, 20.4, 'Peter']
['John', 678, 20.4, 'Peter', 456, 'Andrew']

Dictionary:

• Python dictionary stores the data in the key-value pair.
• It is enclosed by curly-braces {} and each pair is separated by the commas(,).

Example

1. dict = {'name': 'Pater', 'Age':18,'Roll_nu':101}  
2. print(dict)  

Output:

{'name': 'Pater', 'Age': 18, 'Roll_nu': 101}

Tuple:

• Python tuple is a collection of different data-type. It is immutable which means it cannot be modified after creation.
• It is enclosed by the parentheses () and each element is separated by the comma(,).

Example

1. tup = (10,20,"Dev",[2,3,4])  
2. print(tup)  

Output:

(10, 20, 'Dev', [2, 3, 4])

Set:

• Python set is the collection of the unordered dataset.
• It is enclosed by the {} and each element is separated by the comma(,).

Example: - Set Literals

1. set = {'apple','grapes','guava','papaya'}  
2. print(set)  

Output:

{'guava', 'apple', 'papaya', 'grapes'}

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Python Keywords

Python Keywords

Python Keywords are special reserved words that convey a special meaning to the compiler/interpreter. Each keyword has a special meaning and a specific operation. These keywords can't be used as a variable. Following is the List of Python Keywords.

True	False	None	and	as
asset	def	class	continue	break
else	finally	elif	del	except
global	for	if	from	import
raise	try	or	return	pass
nonlocal	in	not	is	lambda

Consider the following explanation of keywords.

1. True - It represents the Boolean true, if the given condition is true, then it returns "True". Non-zero values are treated as true.
2. False - It represents the Boolean false; if the given condition is false, then it returns "False". Zero value is treated as false
3. None - It denotes the null value or void. An empty list or Zero can't be treated as None.
4. and - It is a logical operator. It is used to check the multiple conditions. It returns true if both conditions are true. Consider the following truth table.

A	B	A and B
True	True	True
True	False	False
False	True	False
False	False	False

5. or - It is a logical operator in Python. It returns true if one of the conditions is true. Consider the following truth table.

A	B	A and B
True	True	True
True	False	True
False	True	True
False	False	False

6. not - It is a logical operator and inverts the truth value. Consider the following truth table.

A	Not A
True	False
False	True

7. assert - This keyword is used as the debugging tool in Python. It checks the correctness of the code. It raises an AssertionError if found any error in the code and also prints the message with an error.

Example:

1. a = 10  
2. b = 0  
3. print('a is dividing by Zero')  
4. assert b != 0  
5. print(a / b)  

Output:

a is dividing by Zero
Runtime Exception:
Traceback (most recent call last):
  File "/home/40545678b342ce3b70beb1224bed345f.py", line 4, in  
    assert b != 0, "Divide by 0 error"
AssertionError: Divide by 0 error

8. def - This keyword is used to declare the function in Python. If followed by the function name.

1. def my_func(a,b):  
2.     c = a+b  
3.     print(c)  
4. my_func(10,20)  

Output:

30

9. class - It is used to represents the class in Python. The class is the blueprint of the objects. It is the collection of the variable and methods. Consider the following class.

1. class Myclass:  
2.    #Variables……..  
3.    def function_name(self):  
4.       #statements………  

10. continue - It is used to stop the execution of the current iteration. Consider the following example.

1. a = 0  
2. while a < 4:  
3.   a += 1   
4.   if a == 2:  
5.     continue  
6.   print(a)  

Output:

1
3
4

11. break - It is used to terminate the loop execution and control transfer to the end of the loop. Consider the following example.

Example

1. for i in range(5):  
2.     if(i==3):  
3.         break  
4.     print(i)  
5. print("End of execution")  

Output:

0
1
2
End of execution

12. If - It is used to represent the conditional statement. The execution of a particular block is decided by if statement. Consider the following example.

Example

1. i = 18  
2. if (1 < 12):  
3. print("I am less than 18")  

Output:

I am less than 18

13. else - The else statement is used with the if statement. When if statement returns false, then else block is executed. Consider the following example.

Example:

1. n = 11  
2. if(n%2 == 0):  
3.     print("Even")  
4. else:  
5.     print("odd")  

Output:

Odd

14. elif - This Keyword is used to check the multiple conditions. It is short for else-if. If the previous condition is false, then check until the true condition is found. Condition the following example.

Example:

1. marks = int(input("Enter the marks:"))  
2. if(marks>=90):  
3.     print("Excellent")  
4. elif(marks<90 and marks>=75):  
5.     print("Very Good")  
6. elif(marks<75 and marks>=60):  
7.     print("Good")  
8. else:  
9.     print("Average")  

Output:

Enter the marks:85
Very Good

15. del - It is used to delete the reference of the object. Consider the following example.

Example:

1. a=10  
2. b=12  
3. del a  
4. print(b)  
5. # a is no longer exist  
6. print(a)    

Output:

12
NameError: name 'a' is not defined

16. try, except - The try-except is used to handle the exceptions. The exceptions are run-time errors. Consider the following example.

Example:

1. a = 0  
2. try:  
3.    b = 1/a  
4. except Exception as e:  
5.    print(e)  

Output:

division by zero

17. raise - The raise keyword is used to through the exception forcefully. Consider the following example.

Example

1. a = 5  
2. if (a>2):  
3.    raise Exception('a should not exceed 2 ')  

Output:

Exception: a should not exceed 2

18. finally - The finally keyword is used to create a block of code that will always be executed no matter the else block raises an error or not. Consider the following example.

Example:

1. a=0  
2. b=5  
3. try:  
4.     c = b/a  
5.     print(c)  
6. except Exception as e:  
7.     print(e)  
8. finally:  
9.     print('Finally always executed')  

Output:

division by zero
Finally always executed

19. for, while - Both keywords are used for iteration. The for keyword is used to iterate over the sequences (list, tuple, dictionary, string). A while loop is executed until the condition returns false. Consider the following example.

Example: For loop

1. list = [1,2,3,4,5]  
2. for i in list:  
3.     print(i)  

Output:

1
2
3
4
5

Example: While loop

1. a = 0  
2. while(a<5):  
3.     print(a)  
4.     a = a+1  

Output:

0
1
2
3
4

20. import - The import keyword is used to import modules in the current Python script. The module contains a runnable Python code.

Example:

1. import math  
2. print(math.sqrt(25))  

Output:

5

21. from - This keyword is used to import the specific function or attributes in the current Python script.

Example:

1. from math import sqrt  
2. print(sqrt(25))  

Output:

5

22. as - It is used to create a name alias. It provides the user-define name while importing a module.

Example:

1. import calendar as cal  
2. print(cal.month_name[5])  

Output:

May

23. pass - The pass keyword is used to execute nothing or create a placeholder for future code. If we declare an empty class or function, it will through an error, so we use the pass keyword to declare an empty class or function.

Example:

1. class my_class:  
2.     pass  
3.   
4. def my_func():   
5.     pass   

24. return - The return keyword is used to return the result value or none to called function.

Example:

1. def sum(a,b):  
2.     c = a+b  
3.     return c  
4.       
5. print("The sum is:",sum(25,15))  

Output:

The sum is: 40

25. is - This keyword is used to check if the two-variable refers to the same object. It returns the true if they refer to the same object otherwise false. Consider the following example.

Example

1. x = 5  
2. y = 5  
3.   
4. a = []  
5. b = []  
6. print(x is y)  
7. print(a is b)  

Output:

True
False

Note: A mutable data-types do not refer to the same object.

26. global - The global keyword is used to create a global variable inside the function. Any function can access the global. Consider the following example.

Example

1. def my_func():  
2.     global a   
3.     a = 10  
4.     b = 20  
5.     c = a+b  
6.     print(c)  
7.       
8. my_func()  
9.   
10. def func():  
11.     print(a)  
12.       
13. func()  

Output:

30
10

27. nonlocal - The nonlocal is similar to the global and used to work with a variable inside the nested function(function inside a function). Consider the following example.

Example

1. def outside_function():    
2.     a = 20     
3.     def inside_function():    
4.         nonlocal a    
5.         a = 30    
6.         print("Inner function: ",a)    
7.     inside_function()    
8.     print("Outer function: ",a)    
9. outside_function()   

Output:

Inner function:  30
Outer function:  30

28. lambda - The lambda keyword is used to create the anonymous function in Python. It is an inline function without a name. Consider the following example.

Example

1. a = lambda x: x**2  
2. for i in range(1,6):  
3.   print(a(i))  

Output:

1
4
9
16
25

29. yield - The yield keyword is used with the Python generator. It stops the function's execution and returns value to the caller. Consider the following example.

Example

1. def fun_Generator():  
2.   yield 1  
3.   yield 2  
4.   yield 3  
5.   
6.   
7. # Driver code to check above generator function   
8. for value in fun_Generator():  
9.   print(value)  

Output:

1
2
3

30. with - The with keyword is used in the exception handling. It makes code cleaner and more readable. The advantage of using with, we don't need to call close(). Consider the following example.

Example

1. with open('file_path', 'w') as file:   
2.     file.write('hello world !')  

31. None - The None keyword is used to define the null value. It is remembered that None does not indicate 0, false, or any empty data-types. It is an object of its data type, which is Consider the following example.

Example:

1. def return_none():  
2.   a = 10  
3.   b = 20  
4.   c = a + b  
5.   
6. x = return_none()  
7. print(x)  

Output:

None

We have covered all Python keywords. This is the brief introduction of Python Keywords. We will learn more in the upcoming tutorials.

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