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hrishikesh1990 — Tue, 09 Aug 2022 12:36:00 +0000

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What is a while loop in Python?

hrishikesh1990 — Mon, 25 Jul 2022 09:06:57 +0000

Table of Content

While loop in Python
Single statement
While loop with else statement
Infinite while loop
Closing Thoughts

While loop in Python

The while loop in python is used to iterate over a block of code till the given condition is True. And as soon as the condition turns False, the next statement immediately after the loop is executed. It comes under indefinite iteration.

Indefinite iteration means that the number of times the loop is supposed to be executed is not specified in advance.

Syntax of while loop in Python:

while expression:
       statement(s)

The expression is executed in the Boolean context and if it is true, then the statement is executed. The expression is checked again when the loop is executed and will continue this process until the expression returns False.

Input:

count = 0
while (count < 5):
    count = count + 1
    print("Flexiple")

Output:

Flexiple
Flexiple
Flexiple
Flexiple
Flexiple

The expression count<5 is True till count=4 but as soon as the value of count becomes 5, the expression is not satisfied and the loop ends.

Single statement

Similar to the syntax of the if statement, if the while block consists of a single statement then it may be declared in the same line as the while header. And if there are multiple statements, then each statement can be separated by semicolons.

Input:

count = 0
while (count < 5): count += 1; print("Flexiple")

Output:

Flexiple
Flexiple
Flexiple
Flexiple
Flexiple

While loop with else statement in Python

Python also allows programmers to use the else statement within the while loop. Like in the for loop, if the expression becomes false in the while loop, the else block is executed.

Input:

count = 0
while (count < 5):
    count = count + 1
    print("Flexiple")

else:  
    print("The else statement is executed.")

Output:

Flexiple
Flexiple
Flexiple
Flexiple
Flexiple
The else statement is executed.

If the break control statement is used with the while loop, then the else statement will not be executed. As soon as the condition becomes false, the break statement will ignore the else statement and end the loop and the statement after the loop will be executed.

Input:

count = 0
while (count < 5):
    count = count + 1
    print("Flexiple")
    break

else:  
    print("The else statement is executed.")

Output:

Flexiple
Flexiple
Flexiple
Flexiple
Flexiple

Infinite while loop in Python

If the expression in the while loop never becomes False, then the loop will never end and it becomes an infinite while loop.

Input:

count = 1
while (count > 0):
    count = count + 1
    print("Flexiple")

Output:

Flexiple
Flexiple
Flexiple...

Since the value of count will always be greater than 0, this loop will never end and will keep printing ‘Flexiple’ infinitely.

Closing Thoughts

In this tutorial, we read about the while loop in Python and various situations where the while loop can be used. We can use the control statements with the while loop to change how the loop behaves. One can read about other Python concepts here.

Looping Statements in Python

hrishikesh1990 — Wed, 13 Jul 2022 08:36:07 +0000

The flow of the programs written in any programming language is sequential by default. The first statement in a function is executed first, followed by the second, and so on. There may be a situation when the programmer needs to execute a block of code several times. For this purpose, The programming languages provide various kinds of loops that are able to repeat some particular code numerous numbers of times. Here, we are going to talk about looping statements in Python.

In a programming language, a looping statement contains instructions that continually repeat until a certain condition is reached. Read on to find out more about them.

Table of Content

Looping statements in Python
For Loop
While Loop
Nested Loop

Looping statements in Python

Looping simplifies complicated problems into smooth ones. It allows programmers to modify the flow of the program so that rather than writing the same code, again and again, programmers are able to repeat the code a finite number of times.

In Python, there are three different types of loops: for loop, while loop, and nested loop.

Here, we will read about these different types of loops and how to use them.

For Loop

The for loop is used in the case where a programmer needs to execute a part of the code until the given condition is satisfied. The for loop is also called a pre-tested loop. It is best to use for loop if the number of iterations is known in advance.

In Python, there is no C style for loop, i.e., for (i=0; i<n; i++).

Syntax:

for variable in sequence:
    statements(s)

Input:

a = 5
for i in range(0, a):
    print(i)

Output:

The for loop runs till the value of i is less than a. As the value of i is 5, the loop ends.

While Loop

The while loop is to be used in situations where the number of iterations is unknown at first. The block of statements is executed in the while loop until the condition specified in the while loop is satisfied. It is also called a pre-tested loop.

In Python, the while loop executes the statement or group of statements repeatedly while the given condition is True. And when the condition becomes false, the loop ends and moves to the next statement after the loop.

Syntax:

While condition:
       statement(s)

Input:

count = 0
while (count < 5):   
    count = count + 1
    print("Flexiple")

Output:

Flexiple
Flexiple
Flexiple
Flexiple
Flexiple

The loop prints ‘Flexiple’ till the value of count becomes 5 and the condition is False.

Nested Looping statements in Python

The Python programming language allows programmers to use one looping statement inside another looping statement.

Syntax:

#for loop statement

for variable in sequence:

    for variable in sequence:

       statement(s)

       statement(s)

  
  
  while loop statement


while condition:

    while condition:

       statement(s)

       statement(s)

Input:

for i in range(1, 7):

    for j in range(i):

         print(i, end=' ')

    print()

Output:

1

2 2

3 3 3

4 4 4 4

5 5 5 5 5

6 6 6 6 6 6

Closing Thoughts

In this tutorial, we read about different looping statements in Python and their uses. The looping statements are used to repeat a specific block of code various number of times. One can read about other Python concepts here.

What are the Control Statements in Python?

hrishikesh1990 — Thu, 07 Jul 2022 08:42:37 +0000

In Python, Loops are used to iterate repeatedly over a block of code. In order to change the way a loop is executed from its usual behavior, control statements are used. Control statements are used to control the flow of the execution of the loop based on a condition. There are many types of control statements in Python and in this tutorial, we will discuss all of them.

Control Statements in Python

Break statement
Continue statement
Pass statement

Break statement

The break statement in Python is used to terminate or abandon the loop containing the statement and brings the control out of the loop. It is used with both the while and the for loops, especially with nested loops (loop within a loop) to quit the loop. It terminates the inner loop and control shifts to the statement in the outer loop.

Input:

age = “\n Please enter your age: ”
while True:
       age = input
       if age >= 18:
              break
       else:
             print (“You’re not eligible to vote”)

Output:

Please enter your age: 17 You’re not eligible to vote
Please enter your age: 18

In the above example, if the age entered is equal to or more than 18, it breaks out of the loop.

Continue statement

When a program encounters a continue statement in Python, it skips the execution of the current iteration when the condition is met and lets the loop continue to move to the next iteration. It is used to continue running the program even after the program encounters a break during execution.

Input:

for letter in 'Flexi ple': 
if letter == ' ': 
        continue 
    print ('Letters: ', letter)

Output:

Letters: F
Letters: l
Letters: e
Letters: x
Letters: i
Letters: p
Letters: l
Letters: e

In this example, the program will skip the space ‘ ‘ in the word and continue with the rest of the iteration.

Pass statement

The pass statement is a null operator and is used when the programmer wants to do nothing when the condition is satisfied. This control statement in Python does not terminate or skip the execution, it simply passes to the next iteration.

A loop cannot be left empty otherwise the interpreter will throw an error and to avoid this, a programmer can use the pass statement.

Input:

for letter in 'Flexiple': 
if letter == 'x': 
        pass 
    print ('Letters: ', letter)

Output:

Letters: F
Letters: l
Letters: e
Letters: x
Letters: i
Letters: p
Letters: l
Letters: e

As you can see in the above example, even though the condition was met, the pass statement didn’t do anything and execution moved to the next iteration.

Closing Thoughts

In this tutorial, we read about the different types of control statements in Python - break, continue and pass. Different control statements have different functions and can be used according to the need in the program. One can read about other Python concepts here.

Different Assignment operators in Python

hrishikesh1990 — Fri, 01 Jul 2022 08:42:21 +0000

Assignment operators in Python are in-fix which are used to perform operations on variables or operands and assign values to the operand on the left side of the operator. It performs arithmetic, logical, and bitwise computations.

Assignment Operators in Python

Simple assignment operator in Python
Add and equal operator
Subtract and equal operator
Multiply and equal operator
Divide and equal operator
Modulus and equal operator
Double divide and equal operator
Exponent assign operator
Bitwise and operator
Bitwise OR operator
Bitwise XOR Assignment operator
Bitwise right shift assignment operator
Bitwise left shift assignment operator

Simple assignment operator in Python

The Simple assignment operator in Python is denoted by = and is used to assign values from the right side of the operator to the value on the left side.

Input:

a = b + c

Add and equal operator

This operator adds the value on the right side to the value on the left side and stores the result in the operand on the left side.

Input:

a = 5
a += 10
print (a)

Output:

Subtract and equal operator

This operator subtracts the value on the right side from the value on the left side and stores the result in the operand on the left side.

Input:

a = 10
a -= 5
print (a)

Output:

Multiply and equal operator

The Multiply and equal operator multiplies the right operand with the left operand and then stores the result in the left operand.

Input:

a = 5
a *= 2
print (a)

Output:

Divide and equal operator

It divides the left operand with the right operand and then stores the quotient in the left operand.

Input:

a = 10
a /= 2
print (a)

Output:

Modulus and equal operator

The modulus and equal operator finds the modulus from the left and right operand and stores the final result in the left operand.

Input:

a = 10
a %= 3
print (a)

Output:

Double divide and equal operator

The double divide and equal or the divide floor and equal operator divides the left operand with the right operand and stores the floor result in the left operand.

Input:

a = 11
a //= 3
print (a)

Output:

Exponent assign operator

It performs exponential or power calculation and assigns value to the left operand.

Input:

a = 2
a **= 3
print (a)

Output:

Bitwise And operator

Performs Bitwise And operation on both variables and stores the result in the left operand. The Bitwise And operation compares the corresponding bits of the left operand to the bits of the right operand and if both bits are 1, the corresponding result is also 1 otherwise 0.

Input:

a = 3
b = 5
a &= b
print (a)

Output:

The binary value of 3 is 0011 and the binary value of 5 is 0101, so when the Bitwise And operation is performed on both the values, we get 0111, which is 7 in decimal.

Bitwise OR operator

Performs Bitwise OR operator on both variables and stores the result in the left operand. The Bitwise OR operation compares the corresponding bits of the left operand to the bits of the right operand and if any one of the bit is 1, the corresponding result is also 1 otherwise 0.

Input:

a = 5
b = 10
a |= b
print (a)

Output:

The binary value of 5 is 0101 and the binary value of 10 is 1010, so when the Bitwise OR operation is performed on both the values, we get 1111, which is 15 in decimal.

Bitwise XOR operator

Performs Bitwise XOR operator on both variables and stores the result in the left operand. The Bitwise XOR operation compares the corresponding bits of the left operand to the bits of the right operand and if only one of the bit is 1, the corresponding result is also 1 otherwise 0.

Input:

a = 5
b = 9
a ^= b
print (a)

Output:

The binary value of 5 is 0101 and the binary value of 9 is 1001, so when the Bitwise XOR operation is performed on both the values, we get 1100, which is 12 in decimal.

Bitwise right shift assignment operator

This operator performs a Bitwise right shift on the operands and stores the result in the left operand.

Input:

a = 15
b = 2
a >>= b
print (a)

Output:

The binary value of 15 is 1111, so when the Bitwise right shift operation is performed on ‘a’, we get 0011, which is 3 in decimal.

Bitwise left shift assignment operator

This operator performs a Bitwise left shift on the operands and stores the result in the left operand.

Input:

a = 15
b = 1
a <<= b
print (a)

Output:

The binary value of 15 is 1111, so when the Bitwise right shift operation is performed on ‘a’, we get 00011110, which is 30 in decimal.

Closing Thoughts

In this tutorial, we read about different types of assignment operators in Python which are special symbols used to perform arithmetic, logical and bitwise operations on the operands and store the result in the left side operand. One can read about other Python concepts here.

Different Comparison operators in Python

hrishikesh1990 — Wed, 29 Jun 2022 11:03:56 +0000

Comparison operators, also known as relational operators in Python, compare the values on either side of them and returns a boolean value. They tell whether a statement is True or False according to the condition. In this tutorial, we will discuss 6 different types of comparison operators in Python.

List of comparison operators in Python

Greater than
Less than
Equal to
Not equal to
Greater than or equal to
Less than or equal to

Greater than

Denoted by >, the greater than operator checks if the value on the left side is greater than the value on the right side. It returns True if the condition is satisfied, otherwise returns False.

Input:

x = 5
y = 10
res = x > y
res1 = y > x
print (res)
print (res1)

Output:

FALSE
TRUE

Less than

The less than operator is denoted by < sign and compares the values present on either side. If the value present on the left side is smaller than the value on the right side, it returns True otherwise it returns False.

Input:

x = 5
y = 10
res = x < y
res1 = y < x
print (res)
print (res1)

Output:

TRUE
FALSE

If you compare two different data types, for example, int (5) and float (5.0), both greater than and less than operator will return False as both values are equal.

And when comparing strings like, “Nick” and “nick”, the operators compare their ASCII values. Since the ASCII value of “A” is 65 and “a” is 97, “nick” is greater than “Nick”.

Equal to

This operator is denoted by == and it returns True if both the values present on either side are equal.

Input:

x = 5
y = 5
z = ‘5’
res = x == y
res2 = x == z
print (res)
print (res2)

Output:

TRUE
FALSE

This operator returns False when x and z are compared and that is because x is an integer and z is a string. Hence, they are unequal.

Not equal to

Symbolic representation of Not equal to operator is != and it returns True if one value is not equal to the other present in the condition.

Input:

x = 5
y = 10
res = x != y
print (res)

Output:

FALSE

Greater than or equal to

This operator (>=) only returns True if the value on the left side is greater or equal to the value on the right side.

Input:

x = 5
y = 5
z = 10
res = x >= y
res2 = x >= z
print (res)
print (res2)

Output:

TRUE
FALSE

Less than or equal to

The last operator in the list is less than or equal to (<=). It compares the values and returns True if the value on the left side is smaller than or equal to the value to the value on the right side.

Input:

x = 5
y = 5
z = 10
res = x <= y
res1 = x <= z
print (res)
print (res1)

Output:

TRUE
TRUE

We can also compare Tuples with these operators. The Tuple with more elements will be greater and if both have the same number of elements then the operator compares elements with each other.

Input:

tup1 = (1,2,3)
tup2 = (1,2,3)
tup3 = (1,2)
tup4 = (1,5,3)
print (tup1 == tup2)
print (tup3 <= tup1)
print (tup1 >= tup4)

Output:

In the 3rd case, the tup1 and tup4 have the same number of elements. Then, the operator compares elements. It compares the first element (1 and 1). Since both are equal, it moves to the second element (2 and 5). Now that 5 is greater than 2, it stops here and returns False.

Closing Thoughts

We discussed 6 different types of Comparison operators in Python. The comparison operators compare the value and return a boolean value. One can read about other Python concepts here.

Different Arithmetic operators in Python

hrishikesh1990 — Wed, 22 Jun 2022 10:53:19 +0000

In this tutorial, we will discuss all the basic Arithmetic operators in Python. This is a relatively easy concept. We have used these operations in Mathematics in our school, now we will see how to use these operators in Python to perform basic arithmetic operations.

Addition
Subtraction
Multiplication
Division
Modulus
Exponentiation
Floor division
Order of precedence
Closing Thoughts

Addition

This operator is used to add two values present on either side of the operator.

Input:

x = 2
y = 3
sum = x + y
print (sum)

Output:

Subtraction

This operator is used to subtract the value present on the right side of the operator from the value present on the left side of the operator.

Input:

x = 5
y = 2
sub = x - y
print (sub)

Output:

Multiplication

This operator is used to find the product of the two values present on either side of the operator.

Input:

x = 2
y = 3
mul = x * y
print (mul)

Output:

Division

This operator is used to find the quotient. The value present on the left side of the operator acts as a Dividend and the one on the right side is Divisor.

Input:

x = 5
y = 2
div = x / y
print (div)

Output:

2.5

A division operation always results in a floating-point number.

Modulus

This operator is used to find the remainder. The value present on the left side of the operator acts as a Dividend and the one on the right side is Divisor.

Input:

x = 8
y = 3
mod = x % y
print (mod)

a = -5
b = 2
res1 = a % b
print (res1)

m = 5
n = -2
res2 = m % n
print (res2)

Output:

2
       -1
       1

The remainder will be positive if the Dividend is positive and vice-versa. Even if the Divisor is negative but the Dividend is positive, the remainder will be positive.

Exponentiation

This operator is used to raise the first value to the power of the second operator

Input:

x = 2
y = 3
exp = x ** y
print (exp)

Output:

Floor division

The Floor Division operator is used to floor the result to the nearest integer.

Input:

x = 5
y = 2
flo = x // y
print (flo)

Output:

2.0

Order of precedence of Arithmetic operators in Python

Arithmetic Operators in Python follow a basic order of precedence. When more than one operator is used, they are executed according to this order:

Operator	Purpose
()	Parentheses
**	Exponent
%, *, /, //	Modulos, Multiplication, Division and Floor division
+, -	Addition and Subtraction

The operator listed at the top of the table will be executed first.

Input:

print (((5 + 4) / 3) * 2)

Output:

Here, as you can see according to the order of precedence, Parentheses will be computed first. So inside the innermost parenthesis, there is an addition operator.

Closing Thoughts on Arithmetic Operators in Python

We discussed 7 different types of Arithmetic operators in Python. Make sure you remember the order of precedence because that affects the outcome of all operations performed in Python. One can read about other Python concepts here.

Python Reserved Words List - Your Complete Guide

hrishikesh1990 — Mon, 20 Jun 2022 10:04:54 +0000

There is a restriction while naming identifiers that there are some restricted words that are built-in to Python which cannot be used as an identifier. Python reserved words (also called keywords) a predefined meaning and syntax in the language which Python uses for its syntax and internal processing. In this tutorial, we will discuss what those keywords are.

Reserved words
Keywords
Display all keywords
Check if the name is included in the reserved word list
Closing Thoughts

Reserved words in Python

Here is the list of all the reserved words in Python.

Note - This list may change with different versions of Python. Python 3 has 33 while Python 2 has 30 reserved words. The print was removed from Python 2 keywords and added as a built-in Python function.

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

All the keywords except True, False and None are in lowercase and they must be written as they are. These cannot be used as variable names, function names, or any other identifiers.

If any of the keywords is used as a variable, then we will get the error message SyntaxError: invalid syntax

Keywords

False

It is a boolean operator that represents the opposite of True.

Input:

print (5 == 10)

Output:

FALSE

Since the values are not actually equal, it returns False.

def

The def function is used to define a function or a method in Python.

Input:

def welcome(name):
       print (f"{name}, Welcome to Flexiple")

welcome ("Ben")

Output:

Ben, Welcome to Flexiple

A function 'welcome' is defined using the def statement.

if

An if statement is used to make a conditional statement. If the condition is True, then some action is performed.

Input:

age = 19
If age >= 18:
       print ("You are eligible to vote.")

Output:

You are eligible to vote.

Since the age is greater than 18, the condition is True and the print command is executed.

raise

The raise statement is used to raise an error. These errors are visible in the traceback and they cancel the execution of the program if not handled properly.

Input:

enter = "nick"
if not type(enter) is int:
       raise TypeError("Only integers are allowed.")

Output:

TypeError: Only integers are allowed

TypeError is raised if the variable does not contain integers.

None

There is no null value in Python. The None is an object that represents the absence of a value. It is like an empty object.

Input:

age = None
if age is None:
       print ("Invalid result")

Output:

Invalid result

The age variable has no value to it. This satisfies the condition in the if statement.

del

The del statement is used to delete an object in Python.

Input:

name = [‘Ben’, ‘Nick’, ‘Steph’]
del name[1]
print (name)

Output:

[‘Ben’, ‘Steph’]

'Nick' is removed from the list.

import

This statement is used to import modules to the project.

Input:

import numpy
import math

This statement will import the NumPy and the math library into the project.

return

This keyword is used to exit a function or a method and return some value.

Input:

def sub(x, y):
       return x + y
print (sub(5, 4))

Output:

The function returns the sum of the two variables.

True

It is a boolean operator that represents if the value is True

Input:

print (10 == 10)

Output:

TRUE

The values are same so it returns True.

elif

Shorthand for else if, checks if some other condition holds when the condition in the if statement is false.

Input:

age = 18
if age > 18:
       print ("You are eligible to vote.")
elif age == 18:
       print ("You can vote if you are a registered voter.")
else: 
print ("You are not eligible to vote.")

Output:

You can vote if you are a registered voter.

The condition in the if statement was not True. Hence, the elif statement looked for other conditions that are True.

in

The in statement is used to check if an element is present in an iterable like list or tuple.

Input:

name = ['Ben', 'Nick', 'Steph']
exist = 'Steph' in name
print (exist)

Output:

TRUE

'Steph' is present in the name list.

try

The try statement is used to make a try… except statement. The try statement starts a block of code that is tried to execute. If it fails, the except block catches the error.

Input:

a = 5
b = 0 
try:
       div = a/b
except ZeroDivisionError:
       print ("Divisor cannot be zero.")

Output:

Divisor cannot be zero.

The divisor is 0, which is not possible. So the except block catches the error.

and

It is one of the logical operators that returns True if both of the statements are True.

The Truth table for the and operator is as follows:

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

Input:

a = 5
b = 10
c = 20
stat1 = b > a
stat2 = c > b
result = stat1 and stat2
print (result)

Output:

TRUE

Both the statements are True and that is why the and operator returns True.

else

Conditional statement that tells to perform alternate action if the condition in the if statement is False.

Input:

age = 16
if age >=18:
       print ("You are eligible to vote.")
else:
       print ("You are not eligible to vote.")

Output:

You are not eligible to vote.

The condition in the if statement was not True, so the alternate action is executed.

is

This statement is used to check if the two variables are equal.

Input:

a = 5
b = 5
print (a is b)

Output:

TRUE

Both the variables point to the same memory place.

while

This statement is used to start a while loop. It continues iteration until a condition is no longer True.

Input:

num = [1, 2, 3]
i = 0

while i < len(num):
       print (num[i])
       i = i + 1

Output:

1
2
3

The loop will run till the value of i is greater than the length of the list.

as

The as statement in Python re-assigns a returned object to a new identifier. Basically, it creates an alias.

Input:

import datetime as dt

today = dt.date.today()
print(today)

The datetime is identified as dt in the code.

except

Part of the type… except errorhandling structure in Python. Tells what to do when an exception occurs.

Input:

a = 5
b = 0 
try:
       div = a/b
except ZeroDivisionError:
       print ("Divisor cannot be zero.")

Output:

Divisor cannot be zero.

As the divisor was zero, the except code block caught the error.

lambda

A lambda function in Python is an anonymous function. It can take any number of arguments but only have a single expression.

Input:

numbers = [1, 2, 3]
cube_nums = map(lambda x: x ** 3, numbers)
print(list(cube_nums))

Output:

[1, 8, 27]

The cube of the variable is an anonymous function.

with

The with statement is used to simplify the exception handling.

Input:

with open("file.txt", "r") as file:
    lines = file.read()

assert

The assert statement in Python is used for debugging.

Input:

def divide(a, b):
    assert b != 0, "Divisor cannot be zero."
    return a / b

divide (5, 0)

Output:

Divisor cannot be zero.

finally

The finally statement is an optional part of try… except error. It always executes the code regardless of whether an error was thrown or not.

Input:

a = 5
b = 0 
try:
       div = a/b
except ZeroDivisionError:
       print ("Divisor cannot be zero.")
finally:
       print ("Error handling complete.")

Output:

Divisor cannot be zero.
Error handling complete.

The print statement under the finally will always execute no matter if there is an error or not.

nonlocal

This keyword is used in functions inside functions to create anonymous functions.

Input:

def outer():
  x = "Welcome"
  def inner():
    nonlocal x
    x = "to Flexiple"
  inner() 
  return x
print(outer())

Output:

to Flexiple

yield

The yield function ends a function and returns an iterator.

Input:

def nums():
    i = 0
    while True:
        yield i
        i += 1

for num in nums():
    print(num)

Output:

This is an infinity loop and will never end.

break

It is a control flow statement used to come out of a loop.

Input:

age = 19
if age >= 18:
       print ("You are eligible to vote.")
       break

Output:

You are eligible to vote.

As soon as the condition is satisfied, the break statement ends the loop.

for

The keyword is used to create a for loop.

Input:

num = [1, 2, 3]
cube = []
for number in num:
    cube.append(number ** 3)

print (cube)

Output:

[1, 8, 27]

This loop will run till all the elements in the list are gone through it.

not

It is another logical operator that returns False when the value is True and vice versa.

The truth table for not operator:

A	not A
True	False
False	True

class

The class keyword is udes to define a class in Python.

from

This statement is used when you can to include a specific part of the module.

Input:

from math import sqrt
print(sqrt(9))

Output:

The whole math module is not imported, only a specific function is imported into the project.

or

It is a logical operator that returns True if any one of the statements is True.

Here is the truth table for or operator

A	B	A or B
True	True	True
True	False	True
False	True	True
False	False	False

Input:

stat1 = True
stat2 = False
result = stat1 or stat 2
print (result)

Output:

TRUE

One of the statements is True and according tot the truth table, the or operator will return True.

continue

It is a control flow statement used to continue to the next iteration of a loop. Unlike break, the continue statement does not exit the loop.

Input:

age = [12, 14, 15, 16, 18]
for number in age
print ("Not eligible")
if age >=18:
continue      
print ("You are eligible to vote.")
break

Output:

Not eligible
Not eligible
Not eligible
Not eligible
You are eligible to vote.

The condition in the if statement is not satisfied by the first element. The loop should end there but due tot he continue statement, the loop continues.

global

Accessing a global variable is simple as any other variable but to modify a global variable, you need to use the global keyword.

Input:

age = 18

def check():
       global age
       age = 16

check()
print (age)

Output:

The age variable is a global variable and we cannot change it's value without using the global statement.

pass

It is a null statement in Python that will do nothing.

Input:

def sub(a, b)
  pass
class Student
  pass

It is used as a placeholder for future code. It simply prevents getting errors when an empty code is run.

Display all keywords

We can display the full list of all the keywords in the current version of Python by typing the following command in the Python interpreter.

import keyword
print (keyword.kwlist)

And to find out the number of reserved words in Python.

print (len(kewyord.kwlist))

Check if the name is included in the reserved word list in Python

To check if the name is a part of the list of reserved keywords in Python, we can use the keyword.iskeyword() function.

Input:

import keyword
print (keyword.iskeyword(“global”))
print (keyword.iskeyword(“print”))

Output:

TRUE

FALSE

Closing Thoughts

Python reserved words designate special language functionality. No other variable can have the same name as these keywords. We read about all the reserved keywords and how to check if the name is a keyword or not. One can learn about more Python concepts here.

What are Identifiers in Python?

hrishikesh1990 — Wed, 15 Jun 2022 08:47:39 +0000

In this tutorial, we will answer the question - what are Identifiers in Python. An identifier is a user-defined name given to identities like class, functions, variables, modules, or any other object in Python. Here we will discuss the rules for writing identifiers.

Rules for writing Identifiers
Valid Identifiers Example
Invalid Identifiers Example
Python Keywords
Testing the Validity of Python Identifiers
Python Identifier Naming Best Practices
Closing Thoughts

Rules for writing Identifiers in Python

The identifier is a combination of character digits and underscore and the character includes letters in lowercase (a-z), letters in uppercase (A-Z), digits (0-9), and an underscore (_).
An identifier cannot begin with a digit. If an identifier starts with a digit, it will give a Syntax error.
In Python, keywords are the reserved names that are built-in to Python, so a keyword cannot be used as an identifier - they have a special meaning and we cannot use them as identifier names.
Special symbols like !, @, #, $, %, etc. are not allowed in identifiers.
Python identifiers cannot only contain digits.
There is no restriction on the length of identifiers.
Identifier names are case-sensitive.

Python Valid Identifiers Example

abc123
abc_de
_abc
ABC
abc

Python Invalid Identifiers Example

123abc
abc@
123
for

Python Keywords

Here is the list of some reserved keywords in Python that cannot be used as identifiers.

False	def	if	raise
None	del	import	return
True	elif	in	try
and	else	is	while
as	except	lambda	with
assert	finally	nonlocal	yield
break	for	not	await
class	form	or	async
continue	global	pass

As you can see here all the keywords except 'True', 'False', and 'None' are in lowercase, therefore they must be written as they are.

Testing the Validity of Python Identifiers

The str.isidentifier() function is used to check the validity of an identifier but, this method doesn’t take reserved keywords into consideration. So, we can use this function with keyword.iskeyword() to check if the name is valid or not.

Input:

print ("abc".isidentifier())
print ("123abc".isidentifier())
print ("_abc".isidentifier())
print ("for".isidentifier())

Output:

TRUE
FALSE
TRUE
TRUE

Now, we know “for” is a reserved keyword so, it is an invalid identifier.

Input:

def is_valid_identifier(x):

    Return x.isidentifier() and not keyword.iskeyword(x)

print(is_valid_identifier("for"))

Output:

FALSE

Python Identifier Naming Best Practices

Only class names are started with capital letters (Student, Employee).
Multiple words in a variable are separated by an underscore (is_valid()).
If an identifier begins with an underscore, it means it is a private identifier. This does not make the variable private. It is only for the ease of the programmer to easily distinguish between private variables and public variables.
Python built-in magic methods use double underscores around the names (len). Therefore, double underscores are used only when you are dealing with mangling in Python.
Using longer name than one character is always preferred (index = 1 is better than i = 1).
Camel case are used while naming the variables (studentAddress, studentId). Camel case use a capital letter to begin the second word in a compound name or phrase, when it is not separated from the first word by a space.

Closing Thoughts on Python identifiers

Python Identifiers are user-defined names. We discussed the rules and some best practices while naming identifiers that are good for fellow Python programmers. One can learn about more Python concepts here.

Python remove file - How to delete a file?

hrishikesh1990 — Mon, 30 May 2022 10:35:46 +0000

The files in Python are used for various purposes by the developers. After the developer has worked with the file, it is important to know how to delete it. For example in a large program, the developer would need to create files to store data but would not require them after the execution of the program. This is when deleting the file is a good idea and in this tutorial, we will discuss different ways to delete or remove a file in Python.

In this tutorial, we will discuss various methods to remove a file in Python using the os.remove() and the pathlib module. We will also discuss how to remove an empty and a non-empty directory in Python.

Removing file in Python using os.remove()
Using the pathlib module to remove a file in Python
Removing empty directory
Removing a non-empty directory
Closing thoughts

Removing file in Python using os.remove()

The OS module in Python provides functions for interacting with the operating system. This standard utility module provides a portable way of using operating system-dependent functionality. This module can remove a file or file path but cannot delete a directory. If the specified path is a directory, then the module will raise an OSError.

Syntax:

os.remove(path, *, dir_fd = None)

Case 1: To remove a file

Input:

import os

file = 'file.txt'  
location = "/home/User/Documents"
path = os.path.join(location, file)  
os.remove(path)

print (“The file has been removed")

Output:

The file has been removed

In the above code snippet, we first specify which file we want to delete and where it's located. Then, after joining, we use the os.remove() operation to delete it.

Case 2: The specified path is a directory

Input:

import os

path = "/home/User/Documents/abcdef"

os.remove(path)
print (“The file has been removed")

Output:

Traceback (most recent call last):
  File "osremove.py", line 15, in 
    os.remove(path)
IsADirectoryError: [Errno 21] Is a directory: '/home/User/Documents/acdef'

Here, we do not need to use the 'join' operation as we directly specify the exact location. Make sure to import the OS library before using the os.remove() function.

Using the pathlib module to remove a file in Python

The pathlib module is very useful in removing or deleting a file in Python 3.4 or above. It is similar to the os.remove() and have to create a path object at first.

Input:

import pathlib
p_obj = Path(".")
type(p_obj)
file = pathlib.Path("file_1/file.txt")
file.unlink()

When an instance of the Path class is created, a WindowsPath or PosixPath will be returned according to the machine you’re working on. And the unlink() function is used to remove the file or the symbolic link.

Removing empty directory

The above two approaches cannot be used to remove a folder. The os.rmdir() function in the OS module can delete an empty directory in Python.

Input:

import os
directory = "/home/User/Documents/abcdef"
os.rmdir('directory')

print (“The directory is removed.”)

Output:

The directory is removed.

The os.rmdir() function can only be used to delete an empty directory. If you specify a folder that contains files, the following error will be returned.

Input:

import os

directory = "/home/User/Documents/abcdef/ghi"

os.rmdir('directory')

Output:

Permission denied: '/home/User/Documents/abcdef/ghi' Directory 'ghi' can not be removed

Removing a non-empty directory

You can use the high-level file operation module, shutil to remove a file or collection of files. You can use this module in the same way as the os.rmdir() function but here you can also remove the non-empty directories. All the contents inside the directory are removed as well.

Input:

import shutil
path = /home/User/Documents/abcdef
shutil.rmtree('path')

print (“All the files inside the directory are removed with the directory”)

Output:

All the files inside the directory are removed with the directory

Just remember that you cannot remove a single file with the shutil.rmtree() function. For deleting a single file, you can use the os.remove() function and the pathlib module that's been illustrated above.

Closing thoughts

In Python, removing a file is a very common operation. The os.remove() function and the pathlib module can remove a single file. While the os.rmdir() function removes an empty directory and the shutil module removes the non-empty directory in Python. You can learn other Python concepts here.

How to print a list in Python?

hrishikesh1990 — Fri, 27 May 2022 06:05:19 +0000

Python has many in-built data structures to make programming faster and more efficient than any other language. All these data structures are mutable and sequential in nature and store huge data collection in various formats. Python’s list data structure is built for simplicity and flexibility. In this tutorial, we will discuss various ways to print a list in Python.

Introduction
Using the * symbol to print a list
The join() function to print a list
Using the map() function to print a list in Python
In Python, print list using for loop
Closing thoughts

Introduction to Python print list

A list can contain any number of elements of different data types such as integer, float, string, etc. and in Python, printing a list is a simple task that can be executed using various methods. This tutorial covers some of the methods to print lists in Python.

Using the * symbol to print a list in Python

To print the contents of a list in a single line with space, * or splat operator is one way to go. It passes all of the contents of a list to a function.

We can print all elements in new lines or separated by space and to do that, we use sep=”\n” or sep=”, ” respectively. The below example illustrates this.

Input:

list = [Jon, Ned, 8, 99]
print (*list)

print ("printing lists separated by commas")
print (*list, sep=",")

print ("printing lists in new line")
print (*list, sep="\n")

Output:

Jon Ned 8 99
printing lists separated by commas
Jon, Ned, 8, 99
printing lists in new line
Jon
Ned
8
99

Using join() to print a list in Python

If the list contains strings as elements, then using the join() function is the smart choice. It simply joins the strings and then prints the list. If the list has integers, then this function will join them to a string first and then print the string. This example shows how it's done:

Input:

list = ["Jon", "Ned", "Arya"]
print (' '.join(list))

list_1 = [1, 2, 3, 4, 5]
print str(list_1)[1:-1]

Output:

John Ned Arya
1, 2, 3, 4, 5

Using map() function to print list in Python

The map() function takes two arguments: a function to apply to each element of a list, and a list. It returns a map object (which is an iterator) after applying the given function to each item of a given iterable. Then the join() function joins the elements of the list using a separator as mentioned in the earlier method. Here's how it's done:

Input:

list = [1, 2, 3, 4, 5]
print(' '.join(map(str, list)))

Output:

1 2 3 4 5

In Python, print list using for loop

One of the standard methods to print a list in Python is using the for loop. You can traverse the list from the 0th index to len(list) and print all the elements in the sequence.

Input:

list = ["Jon", "Ned", "Arya"]

for i in range(0, len(list)):
     print(list[i])

Output:

Jon
Ned
Arya

Moreover, you can also print the list using for loop without mentioning the range as shown below:

Input:

list = ["Jon", "Ned", "Arya"]

for item in list:
     print(item)

Output:

Jon

Ned

Arya

Closing thoughts

Printing the list is one of the everyday tasks while coding your program and getting the expected output. Therefore, we discussed different ways in Python to print the list. One can learn about other tasks related to the Python list here.

Python Initialize List - How to do it?

hrishikesh1990 — Thu, 26 May 2022 05:16:14 +0000

Python List is a collection of ordered values and can hold any type of value. It is a container where we can insert, delete or modify the existing values as the list is mutable in Python. Unlike sets, the list can hold the same value multiple times and considers each as a separate item. In this tutorial, we will read how to initialize a list in Python.

Introduction to Python Initialize List
Initialize using the square brackets in Python
Using the list() function to initialize the list
Using comprehensions to initialize the list
Initialize using * operator
Closing thoughts

Introduction to Python Initialize List

In Python, a user can perform a single task using different ways. Similarly, in order to initialize a list in Python, there is more than one way to do that and we will discuss a few in this tutorial.

Initialize lists using the square brackets in Python

If you want to create an empty list with no values in Python, the square bracket is the way to initialize the list with empty values. You just have to declare a non-value list by specifying a set of square brackets without item values.

Input:

list = []
print (list)

list = [1,2,3,4]
print (list)

Output:

[]
[1,2,3,4]

Using the list() function to initialize the list in Python

It is another way to create an empty list without values in Python as the list() function creates the list from the iterable object.

An iterable may be a container, a sequence that supports iteration, or an iterator object. If no parameter is specified, then a new empty list is created.

Input:

list_1 = list()
print (list_1)

res = []
print (data == res)

Output:

[]
TRUE

Since the square bracket approach is more instructive and concise, it is preferred over the list() function approach.

Using comprehensions to initialize the list in Python

In order to initialize the list with default values, we can use the comprehension method. It consists of square brackets containing an expression followed by a for clause and further followed by an optional if clause. The expression can be any type of object that you want to put on the list. Since the user is initializing the list with zeros, the expression will just be 0.

List comprehension is an easy way to define a list based on an iterator because it is elegant, simple, and widely recognized.

Input:

list = [i for i in range(5)]
print (list)

Output:

[0,1,2,3,4]

This method is way faster than using for and while loops to initialize lists in Python.

Initialize lists using the * operator in Python

Another approach to initialize the list with multiple values is the * operator. The syntax is [object]*n where n is the no of elements in the array.

This method allows us to create a list with a specific number of predefined values.

Input:

list = [5]*10
print (list)

Output:

[5,5,5,5,5,5,5,5,5,5]

This is the fastest method among all the methods discussed to initialize the list in Python.

The only drawback of using the * operator to initialize a list in Python is while declaring 2d arrays as it creates shallow lists i.e only one list object would be created and all the indices would refer to this object which can be inconvenient. That is why in the case of 2d arrays, comprehensions are the better way to initialize a list.

Closing thoughts

Initializing the list is one of the basic things to know while working with lists. We have discussed square brackets and the list() function to create empty lists and comprehensions and the * operator to create a list with multiple values. One can learn about other Python concepts here.