Author name: Vikram Chiluka

delattr() Function in Python:

The delattr() function removes the specified attribute from the given object.

In Python, there is another operator that performs the same function as the delattr() method and that is the

del operator.

del operator versus delattr () function:

Dynamic deletion: The del function is more explicit and efficient, and the delattr() function allows for dynamic attribute deletion.

Speed: When the programs are considered and executed, there is a slight difference in execution speed. Depending on the machine, del is slightly faster than delattr().

byte-code Instructions: del uses fewer byte-code instructions than delattr ().

So we conclude the comparison by saying that del is slightly faster than delattr, but delattr() has an advantage when it comes to dynamic deletion of attributes, which the del operator does not support.

Syntax:

delattr(object, attribute)

Parameters

object: This is Required. It is an object.

attribute: This is Required. The name of the attribute to be removed

Return Value:

delattr() does not return any outcome (returns None). It only deletes one attribute (if the object allows it).

delattr() Function with Examples in Python

• Using Built-in Functions (Static Input)
• Using Built-in Functions (User Input)

Method #1: Using Built-in Functions (Static Input)

Approach:

• Create a class to say Employdetails.
• Take a variable and initialize it with some random number(id).
• Take another variable and initialize it with some random name(ename).
• Take another variable and initialize it with some random job role(jobrole).
• Create an object for the given class and store it in a variable.
• Print the value of the attribute by using the above-declared object.
• Pass the above class name and attribute name to the delattr() function to delete a given attribute from the class.
• Print the value of the attribute by using the above-declared object after deleting.
• The Exit of the Program.

Below is the implementation:

# Create a class say Employdetails.
class Employdetails:
    # Take a variable and initialize it with some random number(id).
    id = 10
    # Take another variable and initialize it with some random name(ename).
    ename = 'virat'
    # Take another variable and initialize it with some random jobrole(jobrole).
    jobrole = 'developer'


# Create an object for the given class and store it in a variable.
classobj = Employdetails()
# Print the value of the attribute by using the above declared object.
print("The attribute is :",classobj.ename)
# Pass the above class name and attribute name to the delattr() function to delete
# given attribute from the class.
delattr(Employdetails, 'ename')
# Print the value of the attribute by using the above declared object after deleting.
print("The given attribute after deleting from class = ",classobj.ename)

Output:

The attribute is : virat
Traceback (most recent call last):
File "jdoodle.py", line 19, in <module>
print("The given attribute after deleting from class = ",classobj.ename)
AttributeError: 'Employdetails' object has no attribute 'ename'

Explanation:

Here first it prints the given attribute 'ename'.
Then delete that attribute from the class 'Employdetails'.
Again try to print the given attribute 'ename'.
Now, it raises an error since the attribute 'ename' got deleted from it.

bytearray() Function in Python:

The function bytearray() returns a bytearray object.

It can either convert objects to bytearray objects or create an empty bytearray object of the specified size.

The source parameter can be used to initialize the byte array in a variety of ways, including:

String: str. encode() is used to convert the string to bytes () Encoding and, optionally, errors must also be provided.

Integer: Creates an array of the specified size, with all elements set to null.

Object: The object’s read-only buffer will be used to initialize the byte array.

Iterable: Creates an array with the same size as the iterable count and initialized with the iterable elements. It must be iterable over integers between 0 <= x < 256

No source(arguments): Makes a 0-dimensional array.

Syntax:

bytearray(x, encoding, error)

Parameters

x: When creating the bytearray object, this is the source that will be used. If it is an integer, it will create an empty bytearray object of the specified size.

If it’s a String, make sure to specify the source’s encoding.

encoding: It is the string’s encoding

error: Specifies what should happen if the encoding fails.

Return Value: 

The bytearray() method returns a bytearray of the specified size and initialization values.

Examples:

Example1:

Input:

Given Number = 5

Output:

The bytearray object of the given number 5 = bytearray(b'\x00\x00\x00\x00\x00')

Example2:

Input:

Given String = "good morning btechgeeks"
# string with 'utf-8' encoding

Output:

The bytearray object of the given string =  bytearray(b'good morning btechgeeks')

bytearray() Function with Examples in Python

• Using Built-in Functions (Static Input)
• Using Built-in Functions (User Input)

Method #1: Using Built-in Functions (Static Input)

Approach:

• Give the number as static input and store it in a variable.
• Pass the given number as an argument to the bytearray() method that returns a bytearray object of the given number.
• Store it in another variable.
• Print the bytearray object of the given number.
• The Exit of the Program.

Below is the implementation:

# Give the number as static input and store it in a variable.
gvn_numb = 5
# Pass the given number as an argument to the bytearray() method that returns
# a bytearray object of the given number.
# Store it in another variable.
rslt = bytearray(gvn_numb)
# Print the bytearray object of the given number. 
print("The bytearray object of the given number", gvn_numb, "=", rslt)

Output:

The bytearray object of the given number 5 = bytearray(b'\x00\x00\x00\x00\x00')

For Strings

Approach:

• Give the string as static input and store it in a variable.
• Pass the given string, ‘utf-8’ as the arguments to the bytearray() method that returns a bytearray object of the given string.
• Store it in another variable.
• Print the bytearray object of the given string.
• The Exit of the Program.

Below is the implementation:

# Give the string as static input and store it in a variable.
gvn_str = "good morning btechgeeks"
# Pass the given string, 'utf-8' as the arguments to the bytearray() method
# that returns a bytearray object of the given string.
# string with 'utf-8' encoding
# Store it in another variable.
rslt = bytearray(gvn_str, 'utf-8')
# Print the bytearray object of the given string. 
print("The bytearray object of the given string = ", rslt)

Output:

The bytearray object of the given string =  bytearray(b'good morning btechgeeks')

For Lists

Similarly, do the same for the list

gvn_lst = [1, 4, 7, 6]
rslt = bytearray(gvn_lst)
print("The bytearray object of the given gvn_lst = ", rslt)

Output:

The bytearray object of the given gvn_lst =  bytearray(b'\x01\x04\x07\x06')

Method #2: Using Built-in Functions (User Input)

Approach:

• Give the number as user input using the int(input()) function and store it in a variable.
• Pass the given number as an argument to the bytearray() method that returns a bytearray object of the given number.
• Store it in another variable.
• Print the bytearray object of the given number.
• The Exit of the Program.

Below is the implementation:

# Give the number as user input using the int(input()) function and store it in a variable.
gvn_numb = int(input("Enter some random number = "))
# Pass the given number as an argument to the bytearray() method that returns
# a bytearray object of the given number.
# Store it in another variable.
rslt = bytearray(gvn_numb)
# Print the bytearray object of the given number. 
print("The bytearray object of the given number", gvn_numb, "=", rslt)

Output:

Enter some random number = 3
The bytearray object of the given number 3 = bytearray(b'\x00\x00\x00')

For Strings

Approach:

• Give the string as user input using the input() function and store it in a variable.
• Pass the given string, ‘utf-8’ as the arguments to the bytearray() method that returns a bytearray object of the given string.
• Store it in another variable.
• Print the bytearray object of the given string.
• The Exit of the Program.

Below is the implementation:

# Give the string as user input using the input() function and store it in a variable.
gvn_str =input("Enter some random string = ")
# Pass the given string, 'utf-8' as the arguments to the bytearray() method
# that returns a bytearray object of the given string.
# string with 'utf-8' encoding
# Store it in another variable.
rslt = bytearray(gvn_str, 'utf-8')
# Print the bytearray object of the given string. 
print("The bytearray object of the given string = ", rslt)

Output:

Enter some random string = hello all
The bytearray object of the given string = bytearray(b'hello all')

dict() Function in Python:

The dict() function is used to create a dictionary.

A dictionary is an unordered, changeable, and indexed collection.

Syntax:

dict(keyword arguments)

Parameters

keyword arguments: This is Required. You can use as many keyword arguments as you want, separated by a comma: key = value, key = value…

Return Value:

dict() does not return any results (returns None).

Examples:

Example1:

Input:

Given key-value pairs = (emp_name="sunny", emp_id=2122, jobrole="software developer")

Output:

The result dictionary is :
{'emp_name': 'sunny', 'emp_id': 2122, 'jobrole': 'software developer'}

Example2:

Input:

Given key-value pairs = (one="hello", two="good", three="morning")

Output:

The result dictionary is :
{'one': 'hello', 'two': 'good', 'three': 'morning'}

dict() Function with Examples in Python

• Using Built-in Functions (Static Input)
• Using Built-in Functions (User Input)

Method #1: Using Built-in Functions (Static Input)

Approach:

• Pass some random key-value pairs as the arguments to the dict() function and store it in a variable.
• Print the above result.
• The Exit of the Program.

Below is the implementation:

# Pass some random key-value pairs as the arguments to the dict() function
# and store it in a variable.
rslt = dict(emp_name="sunny", emp_id=2122,  jobrole="software developer")
# Print the above result
print("The result dictionary is :")
print(rslt)

Output:

The result dictionary is :
{'emp_name': 'sunny', 'emp_id': 2122, 'jobrole': 'software developer'}

Method #2: Using Built-in Functions (User Input)

Approach:

• Take a dictionary and initialize it with an empty dictionary using dict() or {}.
• Give the number of keys as user input using int(input()) and store it in a variable.
• Loop till the given number of keys using for loop.
• Inside the for loop scan the key and value as user input using input(), split() functions, and store them in two separate variables.
• Initialize the key with the value of the dictionary.
• Print the above-given dictionary.
• The Exit of the Program.

Below is the implementation:

# Take a dictionary and initialize it with an empty dictionary using dict() or {}.
gvn_dict = dict()
# Give the number of keys as user input using int(input()) and store it in a variable.
numb_of_kys = int(
    input('Enter some random number of keys of the dictionary = '))
# Loop till the given number of keys using for loop.
for p in range(numb_of_kys):
        # Inside the for loop scan the key and value as
    # user input using input(),split() functions
    # and store them in two separate variables.
    keyy, valuee = input(
        'Enter key and value separated by spaces = ').split()
    # Initialize the key with the value of the dictionary.
    gvn_dict[keyy] = valuee
print("The result dictionary is :")
print(gvn_dict)

Output:

Enter some random number of keys of the dictionary = 3
Enter key and value separated by spaces = one hello
Enter key and value separated by spaces = two good
Enter key and value separated by spaces = three morning
The result dictionary is :
{'one': 'hello', 'two': 'good', 'three': 'morning'}

In Python, the random module is used to generate random numbers. This is not truly random; rather, it is used to generate pseudo-random numbers. This implies that these numbers can be determined at random.

random getrandbits() Method in Python:

getrandbits() method returns an integer of the specified size (in bits).

Syntax:

random.getrandbits(num)

Parameters:

num: This is Required. A number indicating the size of the returned integer in bits.

Examples:

Example1:

Input:

Given number(size) = 6

Output:

The random integer =  56

Example2:

Input:

Given number(size) = 10

Output:

The random integer = 59

Random getrandbits() Method with Examples in Python

• Using Built-in Functions (Static Input)
• Using Built-in Functions (User Input)

Method #1: Using Built-in Functions (Static Input)

Approach:

• Import random module using the import keyword.
• Give the number(size) as static input and store it in a variable.
• Pass the given number as an argument to the random.getrandbits() method that returns an integer of the given size in bits.
• Store it in another variable.
• Print an integer with a size of a given number of bits.
• The Exit of the Program.

Below is the implementation:

# Import random module using the import keyword.
import random
# Give the number(size) as static input and store it in a variable.
gvn_numb = 6
# Pass the given number as an argument to the random.getrandbits() method that
# returns an integer of the given size in bits.
# Store it in another variable.
rslt = random.getrandbits(gvn_numb)
# Print an integer with a size of a given number of bits.
print("The random integer = ", rslt)

Output:

The random integer =  56

Method #2: Using Built-in Functions (User Input)

Approach:

• Import random module using the import keyword.
• Give the number(size) as user input using the int(input()) function and store it in a variable.
• Pass the given number as an argument to the random.getrandbits() method that returns an integer of the given size in bits.
• Store it in another variable.
• Print an integer with a size of a given number of bits.
• The Exit of the Program.

Below is the implementation:

# Import random module using the import keyword.
import random
# Give the number as user input using the int(input()) function and
# store it in a variable.
gvn_numb = int(input("Enter some random number = "))
# Pass the given number as an argument to the random.getrandbits() method that
# returns an integer of the given size in bits.
# Store it in another variable.
rslt = random.getrandbits(gvn_numb)
# Print an integer with a size of a given number of bits.
print("The random integer = ", rslt)

Output:

Enter some random number = 10
The random integer = 59

random setstate() Method in Python:

The setstate() method is used to return the random number generator’s state back to the specified state.

To capture the state, use the getstate() method.

Syntax:

random.setstate(state)

Parameters

state: This is Required. It is a state object. The setstate() method returns the random number generator’s state to this state.

Examples:

Example1:

Input:

Given list = [10, 40, 60, 80, 90]
Given length = 2

Output:

[10, 80]
[10, 80]

Example2:

Input:

Given list = [25, 35, 9, 45, 65]
Given length = 3

Output:

[45, 35, 65]
[45, 35, 65]

Random setstate() Method with Examples in Python

• Using Built-in Functions (Static Input)
• Using Built-in Functions (User Input)

Method #1: Using Built-in Functions (Static Input)

Approach:

• Import random module using the import keyword.
• Using the random() function print a random number.
• Capture the state of the object using the random.getstate() method.
• Using the random() function print the other random number.
• Restore back the state of the object using the random.setstate() method.
• Again print the same random value when the state was captured using the random() function.
• The Exit of the Program.

Below is the implementation:

# Import random module using the import keyword.
import random

# Using the random() function print a random number.
print(random.random())

# Capture the state of the object using the random.getstate() method
rslt_state = random.getstate()

# Using the random() function print the other random number.
print(random.random())

# Restore back the state of the object using the random.setstate() method
random.setstate(rslt_state)
# Again print the same random value when the state was captured using the random()
# function
print(random.random())

Output:

0.05457533761313371
0.8804207213354224
0.8804207213354224

Practical implementation

Approach:

• Import random module using the import keyword.
• Give the list as static input and store it in a variable.
• Using the getstate() method, you can capture the current state.
• Store it in another variable.
• Print a list of random items of the specified length using the random.sample() method.
• Using the setstate() method, you can restore the captured state by passing the above state as a parameter to the random.setstate() method.
• Print the same random list of items using the random.sample() method.
• The Exit of the Program.

Below is the implementation:

# Import random module using the import keyword.
import random
# Give the list as static input and store it in a variable.
gvn_lst = [10, 40, 60, 80, 90]
# Using the getstate() method, you can capture the current state.
# Store it in another variable.
rslt_state = random.getstate()

# Print a list of random items of the specified length using the random.sample()
# method.
print(random.sample(gvn_lst, 2))

# Using the setstate() method, you can restore the captured state by passing the
# above state as a parameter to the random.setstate() method.
random.setstate(rslt_state)

# Print the same random list of items using the random.sample() method.
print(random.sample(gvn_lst, 2))

Output:

[10, 80]
[10, 80]

Method #2: Using Built-in Functions (User Input)

Approach:

• Import random module using the import keyword.
• Give the list as user input using list(),map(),input(),and split() functions.
• Store it in a variable.
• Using the getstate() method, you can capture the current state.
• Store it in another variable.
• Print a list of random items of the specified length using the random.sample() method.
• Using the setstate() method, you can restore the captured state by passing the above state as a parameter to the random.setstate() method.
• Print the same random list of items using the random.sample() method.
• The Exit of the Program.

Below is the implementation:

# Import random module using the import keyword.
import random
# Give the list as user input using list(),map(),input(),and split() functions.
# Store it in a variable.
gvn_lst = list(map(int, input(
    'Enter some random List Elements separated by spaces = ').split()))

# Using the getstate() method, you can capture the current state.
# Store it in another variable.
rslt_state = random.getstate()

# Print a list of random items of the specified length using the random.sample()
# method.
print(random.sample(gvn_lst, 3))

# Using the setstate() method, you can restore the captured state by passing the
# above state as a parameter to the random.setstate() method.
random.setstate(rslt_state)

# Print the same random list of items using the random.sample() method.
print(random.sample(gvn_lst, 3))

Output:

Enter some random List Elements separated by spaces = 25 35 9 45 65
[45, 35, 65]
[45, 35, 65]

random getstate() Method in Python:

The getstate() method returns an object containing the random number generator’s current state.

Use this method to capture the state, and then use the setstate() method to restore the state using the captured state.

Syntax:

random.getstate()

Parameters: This method doesn’t accept any parameters.

Examples:

Example1:

Input:

Given list = [10, 40, 60, 80, 90]

Output:

The random value =  90
The random value =  90

Example2:

Input:

Given list = [4, 6, 7, 9]

Output:

The random value = 7
The random value = 7

Random getstate() Method with Examples in Python

• Using Built-in Functions (Static Input)
• Using Built-in Functions (User Input)

Method #1: Using Built-in Functions (Static Input)

Approach:

• Import random module using the import keyword.
• Take a variable and initialize it with the random.getstate() method.
• Store it in a variable.
• It returns an object containing the random number generator’s current state.
• The Exit of the Program.

Below is the implementation:

# Import random module using the import keyword.
import random
# Take a variable and initialize it with the random.getstate() method.
# Store it in a variable.
# It returns an object containing the random number generator's current state.
a = random.getstate()
# Print the above result.
print(a)

Output:

(3, (2147483648, 2958650141, 1960736957, 2406743242, 2338959518, 3100388841, 1559261609, 2563037375, 2413032651, 2215975886, 1233119298, 2664317713, 2518715920, 1830558827, 732301835, 2271834001, 477455944, 921190001, 2858915895, 1580594191, 2936610823, 830667092, 4267652607, 3188563536, 441884984, 3644227226, 1048416985, 2890800050, 3130673655, 2625238051, 143315499, 779359520, 3444435108, 2864567679, 909868605, 1012010189, 3423481953, 4223076182, 141792975, 3552015843, 2254426651, 3627627260, 849125639, 1338840319, 4212732878, 3901314486, 1181210278, 684170455, 1584197225, 3020481743, 2853168588, 2783295314, 139795924, 4204032875, 934190350, 4108077174, 4178893516, 635531203, 2774432906, 1552622764, 2798767114, 1502888489, 3411305313, 2327347547, 4251459828, 2139438774, 4059783449, 1667094461, 3040735816, 893811547, 3798851047, 4185862502, 4290300119, 3228889436, 2788096306, 2395234615, 3209691111, 1070621771, 4015492403, 1848205985, 2400506323, 1385218858, 432017518, 1281006427, 820871546, 1945186639, 371217988, 1728844683, 1947809014, 1346204442, 442723165, 1999068426, 748674435, 2541361738, 2101616097, 769414680, 2831793506, 3524254620, 3049409168, 268951963, 2480400780, 4134107257, 1395477400, 3208207529, 3672445503, 3042969053, 1455397993, 917486726, 1922145706, 312960687, 2844244167, 4071632580, 2736256639, 1696698640, 2024593033, 1736046284, 4086243646, 4037248239, 1270948158, 2164832490, 2111024381, 1270584048, 2382608650, 3893966371, 2084875755, 3107150917, 1675442663, 2825997409, 317702383, 1018988413, 4263608476, 3168541027, 1853724402, 1145291118, 3751201164, 3532950860, 3981155907, 860374305, 2235681923, 2469242486, 1479030325, 3322428502, 3538847454, 2373501168, 1473785534, 1900401009, 1981092293, 3360828321, 482289429, 511973115, 4226523106, 2849499981, 1531287833, 1100249872, 4099483976, 3563434329, 558857975, 125626307, 3861619247, 1444702088, 4205975899, 3378371888, 4265560375, 2713139064, 740237244, 3458131473, 1901892214, 1342841988, 4099573694, 3315194634, 643611024, 4220356547, 3201457242, 1494690431, 2092718697, 1842544099, 2598552989, 4124953268, 3782395520, 647390867, 4217717487, 4220203037, 1007377947, 955588895, 2702341482, 4286159512, 2905988446, 2879841895, 3344876835, 89543556, 3220383365, 1868030775, 3983284672, 3956984449, 2317460400, 167380551, 1771720079, 632723239, 1358564073, 2700988368, 1456709041, 693492112, 2979610345, 3392835350, 1149002431, 203160637, 1934690762, 863425861, 2849572944, 2284497373, 1944080956, 2763450977, 1922145001, 2391900062, 333992930, 143804593, 3920248640, 3305379844, 2977480379, 2607396026, 2131874869, 2145138140, 1039856457, 863538755, 628747354, 3491817509, 154418846, 708726202, 2532063751, 239244789, 2858989690, 1909129016, 551562958, 689142146, 3459240983, 3657147974, 1201513610, 3559321006, 4125253396, 2541356945, 3418921110, 3848089689, 1313908835, 780119980, 2020042542, 2488123905, 2606764201, 2327619300, 2947282177, 540600019, 3730060989, 3813975070, 3876213007, 1084348454, 1332754607, 2012756408, 3396091293, 2727579719, 1399912370, 3369527132, 39070895, 2137512711, 2397705301, 3619684312, 304257835, 1469764078, 2071876341, 2208006222, 3321184261, 1173041128, 80410882, 2196528881, 37450925, 1324727098, 938565820, 2001584763, 3445531763, 491309020, 2676250001, 3483999310, 3998026213, 2461849369, 1400917992, 2191225491, 3563047168, 1212510207, 3488893261, 4118346218, 2207458670, 610723019, 2193695526, 1656574465, 2508898313, 466950484, 3482137648, 1394424081, 1822863820, 1445585358, 3648394106, 122465902, 1080557842, 699414654, 540127462, 1438041739, 1480910531, 4049362348, 1464557834, 3282349027, 853769337, 3353260359, 1914341744, 1019045686, 1270702168, 2147663044, 1106348083, 1688025031, 1690734555, 68198436, 1542301714, 2728642266, 4018559368, 2349097565, 16986703, 3336263888, 2748219259, 24837213, 3283346282, 2945318103, 1704028596, 897286349, 2850090079, 349682702, 3436121433, 3925184939, 1003643225, 754956135, 2631670969, 2397410243, 3450445780, 2312750999, 1299829746, 2763342980, 579312767, 3309267677, 1136498792, 1191114908, 3099205926, 3532865163, 345234544, 169322608, 978276397, 2696096112, 94617221, 2395199781, 991909812, 1024226657, 2219405889, 2271433807, 830613526, 3361259827, 2835737402, 1884999903, 1132224281, 413696493, 3188730185, 2834955258, 3624376277, 1198984184, 4060062947, 3949446077, 3739235065, 1789864174, 4280528658, 2586971248, 1750948931, 2116754654, 2954515174, 413201971, 3583432039, 798521670, 2169603564, 4270760492, 183831111, 4139248474, 3255497557, 1183474278, 1913795851, 1325547141, 3677776936, 3936474002, 1744949980, 2121139632, 4223244743, 4159957234, 2417668346, 2494743507, 2688374620, 3914019604, 4205889545, 2002219821, 1782600588, 117214336, 1177160969, 2965640493, 3912747464, 3942434582, 2336600933, 402520833, 82142402, 3280186928, 3357713478, 1621510120, 3539990616, 3669223424, 1183079917, 3777658477, 1030599448, 918419720, 1502509046, 3388662706, 2083364976, 3911933145, 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2701483246, 2162759624, 2432829348, 943743719, 2742103927, 2939613990, 2166572670, 3006186435, 1873072507, 34183711, 2468723527, 1423146305, 1777041617, 1121418387, 3894651432, 1131983113, 3245961893, 2377445864, 3927853875, 405695582, 3138955469, 1122563736, 1440982335, 1614720491, 1668620793, 3527067702, 3196877256, 1266205401, 2986550769, 4120358291, 1687916565, 1641057278, 2744272320, 1392196246, 2071479158, 4046990526, 3219630994, 1961086429, 1050005143, 149972892, 860756166, 1852412778, 3925332087, 3128578942, 188892714, 2534576442, 1123988891, 3476163348, 2544528605, 1202973395, 3527935356, 3885621558, 4157810548, 3288956832, 1586522375, 922189393, 1324140453, 4241189222, 770650455, 600493778, 2605721103, 2518507483, 1772347558, 2479514605, 2584110305, 4087275637, 3642681286, 2906292783, 751075597, 1222970586, 1791021249, 3780292328, 460147566, 1511703923, 3245139228, 3403378617, 673327266, 1330969073, 2815509917, 1526336993, 284258121, 1907931962, 1439704745, 2744932518, 256613349, 3888237198, 4169828707, 2503468627, 4079210735, 2689086452, 3119155530, 8454111, 771423642, 1158892081, 1075216921, 3940546501, 2419067660, 2469028139, 1853751035, 2052089636, 2815255744, 2630641543, 1185441581, 2781137579, 3023782122, 1941429619, 3727081123, 3957897539, 2718042759, 3286134537, 3962321570, 3128242110, 4272396116, 424628196, 2199184920, 491543448, 714790904, 624), None)

Practical implementation

Approach:

• Import random module using the import keyword.
• Give the list as static input and store it in a variable.
• Get the state of the object using the random.getstate() method.
• Store it in another variable.
• Print a value at random from the given list using the random.choice() method.
• Set the state of the object using the random.setstate() method.
• Again print the same random value from the given list using the random.choice() method.
• The Exit of the Program.

Below is the implementation:

# Import random module using the import keyword.
import random
# Give the list as static input and store it in a variable.
gvn_lst = [10, 40, 60, 80, 90]
# Get the state of the object using the random.getstate() method.
# Store it in a variable.
rslt_state = random.getstate()
# Print a value at random from the given list using the random.choice() method
print("The random value = ", random.choice(gvn_lst))
# Set the state of the object using the random.setstate() method.
random.setstate(rslt_state)
# Again print the same random value from the given list using the
# random.choice() method
print("The random value = ", random.choice(gvn_lst))

Output:

The random value =  90
The random value =  90

Method #2: Using Built-in Functions (User Input)

Approach:

• Import random module using the import keyword.
• Give the list as user input using list(),map(),input(),and split() functions.
• Store it in a variable.
• Get the state of the object using the random.getstate() method.
• Store it in another variable.
• Print a value at random from the given list using the random.choice() method.
• Set the state of the object using the random.setstate() method.
• Again print the same random value from the given list using the random.choice() method.
• The Exit of the Program.

Below is the implementation:

# Import random module using the import keyword.
import random
# Give the list as user input using list(),map(),input(),and split() functions.
# Store it in a variable.
gvn_lst = list(map(int, input(
    'Enter some random List Elements separated by spaces = ').split()))

# Get the state of the object using the random.getstate() method.
# Store it in a variable.
rslt_state = random.getstate()
# Print a value at random from the given list using the random.choice() method
print("The random value = ", random.choice(gvn_lst))
# Set the state of the object using the random.setstate() method.
random.setstate(rslt_state)
# Again print the same random value from the given list using the
# random.choice() method
print("The random value = ", random.choice(gvn_lst))

Output:

Enter some random List Elements separated by spaces = 4 6 7 9
The random value = 7
The random value = 7

random seed() Method in Python:

The random number generator is initialized using the seed() method.

To generate a random number, the random number generator requires a starting number (a seed value).

The random number generator defaults to using the current system time.

To change the random number generator’s starting number, use the seed() method.

Note: Please keep in mind that if you use the same seed value twice, you will get the same random number both times.

How Does the Seed Function Work?
The seed function saves the state of a random function so that it can generate the same random numbers on multiple executions of the code on the same or different machines (for a specific seed value). The previous value number generated by the generator serves as the seed value. When there is no previous value, it uses the current system time for the first time.

Syntax:

random.seed(x, version)

Parameters

x: This is Optional. A seed value is required to generate a random number.
If it is an integer, it is used directly; otherwise, it must be converted to an integer.
The default value is None, and if None is specified, the generator will use the current system time.

version: An integer that specifies how to convert a parameter to an integer.
The default value is 2.

Examples:

Example1:

Input:

Given seed value = 12

Output:

The random number =  0.4745706786885481

Example2:

Input:

Given seed value = 20

Output:

The random number =  0.9056396761745207

Random seed() Method with Examples in Python

• Using Built-in Functions (Static Input)
• Using Built-in Functions (User Input)

Method #1: Using Built-in Functions (Static Input)

Approach:

• Import random module using the import keyword.
• Give the number (seed value) as static input and store it in a variable.
• Pass the given number as an argument to the random.seed() method to generate a random number, the random number generator requires a starting number (given seed value).
• Print the random number using the random() function after applying the seed method.
• The generator generates a random number based on the seed value, so if the seed value is 12, the first random number will always be 0.4745706786885481.
• The Exit of the Program.

Below is the implementation:

# Import random module using the import keyword.
import random
# Give the number (seed value) as static input and store it in a variable.
gvn_numb = 12
# Pass the given number as an argument to the random.seed() method to generate
# a random number, the random number generator requires a starting number
# (given seed value).
random.seed(gvn_numb)
# Print the random number using the random() function after applying the seed()
# method.
# The generator generates a random number based on the seed value, so if the seed
# value is 12, the first random number will always be 0.4745706786885481
print("The random number = ", random.random())

Output:

The random number =  0.4745706786885481

If you use the same seed value twice, you’ll get the same random number both times.

import random
random.seed(12)
print(random.random())
random.seed(12)
print(random.random())

Output:

0.4745706786885481
0.4745706786885481

Method #2: Using Built-in Functions (User Input)

Approach:

• Import random module using the import keyword.
• Give the number (seed value) as user input using the int(input()) function and store it in a variable.
• Pass the given number as an argument to the random.seed() method to generate a random number, the random number generator requires a starting number (given seed value).
• Print the random number using the random() function after applying the seed method.
• The generator generates a random number based on the seed value, so if the seed value is 12, the first random number will always be 0.4745706786885481.
• The Exit of the Program.

Below is the implementation:

# Import random module using the import keyword.
import random
# Give the number (seed value) as user input using the int(input()) function 
# and store it in a variable.
gvn_numb = int(input("Enter some random number = "))
# Pass the given number as an argument to the random.seed() method to generate
# a random number, the random number generator requires a starting number
# (given seed value).
random.seed(gvn_numb)
# Print the random number using the random() function after applying the seed()
# method.
# The generator generates a random number based on the seed value, so if the seed
# value is 20, the first random number will always be 0.9056396761745207
print("The random number = ", random.random())

Output:

Enter some random number = 20
The random number = 0.9056396761745207

statistics.variance() Method in Python:

The statistics.variance() method computes the variance from a data sample (from a population).

A high variance indicates that the data is dispersed, whereas a low variance indicates that the data is tightly clustered around the mean.

Look at the statistics.pvariance() method to calculate the variance of an entire population.

Syntax:

statistics.variance(data, xbar)

Parameters

data: This is Required. It is the data values that will be used (it can be any sequence, list, or iterator).

xbar: This is Optional. The arithmetic mean of the given data. If omitted (or set to None), the mean is calculated automatically.

Note: It should be noted that if the data has fewer than two values, StatisticsError is returned.

Return Value:

Returns a float value representing the given data’s sample variance.

Examples:

Example1:

Input:

Given list = [10, 20, 40, 15, 30]

Output:

The variance of the given list items [10, 20, 40, 15, 30] =  145

Example2:

Input:

Given list = [3, 2, 5, 6, 1, 1, 3]

Output:

The variance of the given list items [3, 2, 5, 6, 1, 1, 3] = 3.6666666666666665

statistics.variance() Method with Examples in Python

• Using Built-in Functions (Static Input)
• Using Built-in Functions (User Input)

Method #1: Using Built-in Functions (Static Input)

Approach:

• Import statistics module using the import keyword.
• Give the list as static input and store it in a variable.
• Pass the given list as an argument to the statistics.variance() method that computes the variance of the given list items.
• Store it in another variable.
• Print the variance of the given list items.
• The Exit of the Program.

Below is the implementation:

# Import statistics module using the import keyword.
import statistics
# Give the list as static input and store it in a variable.
gvn_lst = [10, 20, 40, 15, 30]
# Pass the given list as an argument to the statistics.variance() method that
# computes the variance of the given list items.
# Store it in another variable.
rslt = statistics.variance(gvn_lst)
# Print the variance of the given list items.
print("The variance of the given list items", gvn_lst, "= ", rslt)

Output:

The variance of the given list items [10, 20, 40, 15, 30] =  145

Method #2: Using Built-in Functions (User Input)

Approach:

• Import statistics module using the import keyword.
• Give the list as user input using list(),map(),input(),and split() functions.
• Store it in another variable.
• Pass the given list as an argument to the statistics.variance() method that computes the variance of the given list items.
• Store it in another variable.
• Print the variance of the given list items.
• The Exit of the Program.

Below is the implementation:

# Import statistics module using the import keyword.
import statistics
# Give the list as user input using list(),map(),input(),and split() functions.
# Store it in a variable.
gvn_lst = list(map(int, input(
    'Enter some random List Elements separated by spaces = ').split()))

# Pass the given list as an argument to the statistics.variance() method that
# computes the variance of the given list items.
# Store it in another variable.
rslt = statistics.variance(gvn_lst)
# Print the variance of the given list items.
print("The variance of the given list items", gvn_lst, "= ", rslt)

Output:

Enter some random List Elements separated by spaces = 3 2 5 6 1 1 3
The variance of the given list items [3, 2, 5, 6, 1, 1, 3] = 3.6666666666666665

statistics.pvariance() Method in Python:

The statistics.pvariance() method computes the variance of a whole population.

A high variance indicates that the data is dispersed, whereas a low variance indicates that the data is tightly clustered around the mean.

Examine the statistics.variance() method to determine the variance from a sample of data.

Syntax:

statistics.pvariance(data, xbar)

Parameters

data: This is Required. It is the data values that will be used (it can be any sequence, list, or iterator).

xbar: This is Optional. The arithmetic mean of the given data (can also be a second moment around a point that is not the mean). If omitted (or set to None), the mean is calculated automatically.

Note: It is important to note that if the data is empty, it returns a StatisticsError.

Return Value:

Returns a  float value representing the given data’s population variance.

Examples:

Example1:

Input:

Given list = [10, 20, 40, 15, 30]

Output:

The variance of the given list items [10, 20, 40, 15, 30] =  116

Example2:

Input:

Given list = [1, 6, 9, 7]

Output:

The variance of the given list items [1, 6, 9, 7] = 8.6875

statistics.pvariance() Method with Examples in Python

• Using Built-in Functions (Static Input)
• Using Built-in Functions (User Input)

Method #1: Using Built-in Functions (Static Input)

Approach:

• Import statistics module using the import keyword.
• Give the list as static input and store it in a variable.
• Pass the given list as an argument to the statistics.pvariance() method that computes the variance of a whole population.
• Store it in another variable.
• Print the variance of the given list items.
• The Exit of the Program.

Below is the implementation:

# Import statistics module using the import keyword.
import statistics
# Give the list as static input and store it in a variable.
gvn_lst = [10, 20, 40, 15, 30]
# Pass the given list as an argument to the statistics.pvariance() method that
# computes the variance of a whole population.
# Store it in another variable.
rslt = statistics.pvariance(gvn_lst)
# Print the variance of the given list items.
print("The variance of the given list items", gvn_lst, "= ", rslt)

Output:

The variance of the given list items [10, 20, 40, 15, 30] =  116

Method #2: Using Built-in Functions (User Input)

Approach:

• Import statistics module using the import keyword.
• Give the list as user input using list(),map(),input(),and split() functions.
• Store it in another variable.
• Pass the given list as an argument to the statistics.pvariance() method that computes the variance of a whole population.
• Store it in another variable.
• Print the variance of the given list items.
• The Exit of the Program.

Below is the implementation:

# Import statistics module using the import keyword.
import statistics
# Give the list as user input using list(),map(),input(),and split() functions.
# Store it in a variable.
gvn_lst = list(map(int, input(
    'Enter some random List Elements separated by spaces = ').split()))

# Pass the given list as an argument to the statistics.pvariance() method that
# computes the variance of a whole population.
# Store it in another variable.
rslt = statistics.pvariance(gvn_lst)
# Print the variance of the given list items.
print("The variance of the given list items", gvn_lst, "= ", rslt)

Output:

Enter some random List Elements separated by spaces = 1 6 9 7
The variance of the given list items [1, 6, 9, 7] = 8.6875

statistics.stdev() Method in Python:

Statistics.stdev() computes the standard deviation from a sample of data.

The standard deviation measures how evenly distributed the numbers are.

A high standard deviation indicates that the data is dispersed, whereas a low standard deviation indicates that the data is tightly clustered around the mean.

Tip: Unlike variance, the standard deviation is expressed in the same units as the data.

The standard deviation is equal to the square root of the sample variance.

Look at the statistics.pstdev() method to calculate the standard deviation of an entire population.

Syntax:

statistics.stdev(data, xbar)

Parameters

data: This is Required. It is the data values that will be used (it can be any sequence, list, or iterator).

xbar: This is Optional. The arithmetic mean of the given data. If omitted (or set to None), the mean is calculated automatically.

Note: It should be noted that if the data has fewer than two values, StatisticsError is returned.

Return Value:

Returns a float value representing the given data’s standard deviation.

Examples:

Example1:

Input:

Given list = [10, 20, 40, 15, 30]

Output:

The standard deviation of the given list items [10, 20, 40, 15, 30] =  12.041594578792296

Example2:

Input:

Given list = [-2, 5, 8, 9, 0, -1]

Output:

The standard deviation of the given list items [-2, 5, 8, 9, 0, -1] = 4.792355023020171

statistics.stdev() Method with Examples in Python

• Using Built-in Functions (Static Input)
• Using Built-in Functions (User Input)

Method #1: Using Built-in Functions (Static Input)

Approach:

• Import statistics module using the import keyword.
• Give the list as static input and store it in a variable.
• Pass the given list as an argument to the statistics.stdev() method that computes the standard deviation from a sample of data(here given list).
• Store it in another variable.
• Print the standard deviation of the given list items.
• The Exit of the Program.

Below is the implementation:

# Import statistics module using the import keyword.
import statistics
# Give the list as static input and store it in a variable.
gvn_lst = [10, 20, 40, 15, 30]
# Pass the given list as an argument to the statistics.stdev() method that
# computes the standard deviation from a sample of data(here given list).
# Store it in another variable.
rslt = statistics.stdev(gvn_lst)
# Print the standard deviation of the given list items.
print("The standard deviation of the given list items", gvn_lst, "= ", rslt)

Output:

The standard deviation of the given list items [10, 20, 40, 15, 30] =  12.041594578792296

Method #2: Using Built-in Functions (User Input)

Approach:

• Import statistics module using the import keyword.
• Give the list as user input using list(),map(),input(),and split() functions.
• Store it in another variable.
• Pass the given list as an argument to the statistics.stdev() method that computes the standard deviation from a sample of data(here given list).
• Store it in another variable.
• Print the standard deviation of the given list items.
• The Exit of the Program.

Below is the implementation:

# Import statistics module using the import keyword.
import statistics
# Give the list as user input using list(),map(),input(),and split() functions.
# Store it in a variable.
gvn_lst = list(map(int, input(
    'Enter some random List Elements separated by spaces = ').split()))

# Pass the given list as an argument to the statistics.stdev() method that
# computes the standard deviation from a sample of data(here given list).
# Store it in another variable.
rslt = statistics.stdev(gvn_lst)
# Print the standard deviation of the given list items.
print("The standard deviation of the given list items", gvn_lst, "= ", rslt)

Output:

Enter some random List Elements separated by spaces = -2 5 8 9 0 -1
The standard deviation of the given list items [-2, 5, 8, 9, 0, -1] = 4.792355023020171