# Trending December 2023 # Learn How To Use Boolean Operators In Matlab # Suggested January 2024 # Top 17 Popular

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Introduction to Matlab boolean

MATLAB Boolean operators are used to return logical values (True for 1 and False for 0) in case we want to check if a condition is met or not. Boolean operators are very useful in codes where we need to execute code lines based on certain conditions.

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For example, we can compare 2 numbers using logical operators and get True in the output if the numbers are equal else False.

Syntax:

How to use Matlab boolean with Examples?

Let us now understand how to use logical or Boolean operators in MATLAB. We will discuss 2 scenarios:

The use of Boolean operators in arrays

The use of Boolean operators in circuits

Example #1

In this example, we will use an ‘&’ operator between 2 matrices. An ‘&’ operator will give ‘1’ as the output if the corresponding elements in both the matrices are non-zero, else it will give ‘0’ as the output. The steps to be followed for this example are:

Initialize the input matrices

Use the ‘&’ operator between the matrices

Code:

A = [5 4 1; 5 2 0; 1 0 1] [Initializing the 1st matrix] B = [0 1 1; 0 0 0; 1 9 3] [Initializing the 2nd matrix] [Using the Boolean operator ‘&’ between the matrices. The output will be a matrix of 0s and 1s]

This is how our input and output will look like in MATLAB:

Input:

A = [5 4 1; 5 2 0; 1 0 1] B = [0 1 1; 0 0 0; 1 9 3] A & B

Output:

As we can see in the output, the Boolean operator ‘&’ gives ‘1’ as the output if the corresponding elements in both the matrices are non-zero, else it gives ‘0’ as the output

Next, we will see the use of the ‘&’ operator in the circuits

Example #2

When used in circuits, the ‘&’ operator will give ‘1’ as the output if both the variables are non-zero, else it will give ‘0’ as the output. The steps to be followed for this example are:

Initialize the input variables

Use the if-else loop along with the Boolean ‘&’ operator

Code:

[Initializing the 1st variable] [Initializing the 2nd variable] [Initializing the 3rd variable] [This loop with Boolean ‘&’ operator will check if both the variables are non-zero; In this example we have taken both ‘a’ and ‘b’ as non-zero] [This loop will check if both the variables ‘a’ and ‘c’ are non-zero]

This is how our input and output will look like in MATLAB:

Input:

Output:

In the 1st loop, both the variables ‘a’ and ‘b’ are non-zero, so the output after using Boolean ‘&’ operator is “Both the numbers are non-zero”

In the 2nd loop, the variables ‘a’ is non-zero, whereas the variable ‘c’ is zero, so the output after using Boolean ‘&’ operator is “Both the numbers are not non-zero”

Example #3

Initialize the input matrices

Code:

A = [2 4 6; 2 2 0; 3 0 7] [Initializing the 1st matrix] B = [0 4 1; 1 0 0; 2 0 3] [Initializing the 2nd matrix]

This is how our input and output will look like in MATLAB:

Input:

A = [2 4 6; 2 2 0; 3 0 7] B = [0 4 1; 1 0 0; 2 0 3]

Output:

Example #4

Initialize the input variables

Code:

[Initializing the 1st variable] [Initializing the 2nd variable] [Initializing the 3rd variable] [Initializing the 4th variable] [This loop will check if one of the variables ‘c’ and ‘d’ is non-zero]

This is how our input and output will look like in MATLAB:

Input:

end

Output:

Conclusion

Boolean operators are useful in cases where we want to check if a condition is met or not.

Boolean operators are also used in circuit codes where we need to execute code lines based on certain conditions.

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This is a guide to Matlab boolean. Here we discuss how to use logical or Boolean operators in MATLAB along with the Examples and outputs. You may also look at the following article to learn more –

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## Learn How To Use Stabilizer In Krita?

Introduction to Krita Stabilizer

Krita Stabilizer is the most important feature of this software, and by enabling this feature, we can provide smoothing to our brush stroke. There are some parameters also with this feature that are adjustable, and by adjusting them, we can make a variation in the smoothing quality of brush stroke. You have noticed many times that when you start to draw your raster artwork in Krita, you faced a smoothing problem in brush strokes. There is a couple of things for this issue, and you can short out these things by following some designing technique in this software.

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How to Use Stabilizer in Krita?

A stabilizer actually works as a smoothing agent for brush stroke. Now let me tell you why you need to smooth brush stroke and what happens when we do it?

Now go to the tool panel, which is on the left side of the working screen and select Freehand Brush Tool or press the B button of the keyboard as the shortcut key of it.

Choose your desired brush preset from here. I will take a basic brush preset to explain to you about the stabilizer feature.

Set size of the brush as 10 pixels from this Size option.

You can also set the size of the brush tip from Edit Brush presets dialog box. Just give your desired value in the Diameter option of the chosen brush.

Now draw a line with this brush.

And zoom it at 100%. You can see there is jazziness in this line, and it is not smooth. Due to this issue, your artwork may look blurry, which is not good for you.

Now the canvas size is very big. Draw a line with the same brush preset parameters, which we used last time in an 800 x 800 pixels document.

When you zoom in, you can see only 100% zoom; it is much smoother than the previous one. So I will suggest you take a bigger size of document for your artwork in Krita software. Document size below 1000 x 1000 pixels will act as a baby size for your artwork, and you will not get your desired result.

And draw a line you can see it is lots of jazziness in it.

For having more smoothness in line, we can do a couple of things, such as we can use smoothing settings in the brush. Here on the right side of the working screen, you will have the Tool options tab, and in this tab, we have Brush Smoothing options.

Let me tell you about these options one by one. First is will select a Basic option and draw a line next to the previous line, which I have drawn with the None option of Brush Smoothing.

One more time, draw a line, but this time select the Stabilizer option of this list, and you can find a difference between each option. With the Stabilizer option, you will have a smoother line than all of the options. Here when you select the stabilizer option, the mouse cursor will change into two circles; tip like that and out circle represents delay time during drawing with it.

Delay can be understood as controlling the speed of drawing any stroke that means when the value of delay is less, then the stabilizer will provide less stoppage in drawing any stroke, or if delay value is more, then there will be more stoppage during drawing and speed of drawing that stroke becomes slow. Due to slow speed, there will be good smoothness on any stroke.

For example, if I draw this curve with less value of delay, it will be less smooth.

And if I increased the delay value, then you can see it is smoother than the last one.

Conclusion

Now you can understand how important a Stabilizer is in Krita? You can use this feature of Krita to have a good quality of the result of your art work. It is easy to handle it because it offers adjustable parameters for dealing with our different requirements. I am sure it will be a very helpful feature to your art work in Krita.

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This is a guide to Krita Stabilizer. Here we discuss How to use Stabilizer in Krita, and by enabling this feature, we can provide smoothing to our brush stroke. You may also have a look at the following articles to learn more –

## How Exist Function Work In Matlab With Examples?

Introduction to Matlab exist

In Matlab, the ‘exist’ stands for existence. ‘exist’ function checks the existence of variables, functions, classes, folders, etc. this function helps us to know about the available checklist in the Matlab workspace. If the given file or folder is already present in Matlab, it will create an error while creating a new file with the same name and use the same folder instead of the new folder so that space will be optimized. This function gives integer values as output; This output return value varies from 0 to 8.

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Syntax

exist input

exist (‘max’)

exist (‘inbuilt function name’)

exist gui file

exist Matlab file name file

exist until dir

exist folder name dir

How exist function work in Matlab?

‘Exist’ function returns values in the form of integers. If a given quantity is present in Matlab, then it gives an output from 1 to 8 depending upon the type of quantity. And if the given quantity is not present in Matlab, then it gives the output as ‘0’. We can check the existence of variables, files with extension ‘.m’, ‘.mlx’, ‘.mlapp’, ‘.mat’, ‘.fig’,’.txt’ ), folders as dir, inbuilt functions, classes, etc. if the given variable is present in Matlab workspace then it returns number ‘1’, for files it returns ‘2’ or ‘3’. If it is a simulation model, then it returns chúng tôi we are checking the existence of the inbuilt function, then it will show presence by ‘5’, and for folders, it will return ‘7’.

Examples

Here are the following examples mention below

Example #1 ( Variables )

In this example, first, we need to create one variable, then we can check the existence of the variable; here, one variable is created, which is ‘input ‘. After variable creation, we have used the existing function on the variable; therefore, the output is 1 that means the ‘input’ variable is present in Matlab workspace, which is illustrated in example 1(a). in example 1(b), without creating any variable, we directly applied the function on the ‘output’ variable, and it returns the result as 0, which means the ‘output ‘ variable is not present in the Matlab workspace.

Matlab code for Example 1(a) –

exist input

Output:

Matlab code for Example 1( b ):

exist output

Example #2

In this example, we will check the existence of inbuilt functions from Matlab. There are various functions available in Matlab like max, mean, min, avg, import, disp, use, and so on. Here we have used the max’ function to check existence obviously as we know it is present in Matlab so that it will return output value as ‘5’. And we will use one random name, ‘abc’, it will return output as ‘0’, which means there no such function available in Matlab, which is illustrated in example 2.

Matlab code for Example 2:

exist(‘abc’)

Output:

Example #3

This example will check the existence of files in Matlab. To check the present first, we need to create one file, here we have created a Matlab file with the name ‘gui.m’. There is a limitation on extensions to check the existence of files; only a few extensions are allowed like ‘.m’, ‘.mlx’, ‘.mlapp’, ‘.mat’, ‘.fig’,’.txt’. As we have already created a Matlab file with extension .m, then we will get the output as ‘2’. Numbers ‘2’ represent the existence of files. On another side, we have checked the existence of file gui10; it returns the value 0, which means there is no such file with the name gui 10 in the workspace.

Matlab code for Example 3:

Output:

Example #4

In this example, we will check the existence of a folder. To check existence in the directory, first, we need to create one folder, here we have created one folder in the directory ‘util’, and after checking existence, it returns the value ‘7’. That means the given folder is present in the directory, and the number ‘7’ represents the folder’s existence in the Matlab workspace. Then we checked the existence of another folder, ‘util10’, which is not present in the directory so that it will return the result as ‘0’.

Matlab code for Example 4:

exist util10 dir

Output:

Conclusion

In this article, we have seen various uses of the ‘exist’ function. It checks the existence of almost every factor which is required in stands implementation of any model. There is some alternative to existing a function like ‘is file’ and ‘is the folder’, but instead of using different syntax for each term (variable, files, folders, function, class), it’s good practice to use the same function for all the terms.

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## Learn How To Use A Kreg Jig To Make Pocket Holes

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Make pocket holes with ease using a kreg jig! This simple tool makes building furniture and woodworking projects so easy!

Whether you’re making a wood countertop or a mirror frame, the kreg jig is such a handy tool to have around.

When I bought my kreg jig, I had no idea how much I would love it. Sure, DIY bloggers everywhere sing it’s praises, but would I find it useful? After over 2 years of using it, I’ve found that I love it.

We used it to build our farmhouse table, the bar in our sunroom, a cabinet in our kitchen (that still needs to be finished) and countless other projects.

Over the weekend, we built a bathroom countertop, and as I worked on it, I felt it would be helpful to write a guide on using a kreg jig to make pocket holes.

This post contains affiliate links. By purchasing an item through an affiliate link, I earn a small commission at no extra cost to you. As an Amazon Associate I earn from qualifying purchases.

Using a Kreg Jig FAQs About the Kreg R3 System

We bought ours without knowing how useful it would be, so we bought a smaller kit and a clamp. Even though it’s not the large kit, it gets the job done.

The kit comes with a sample pack of screws. So far, I haven’t found that other screws work with the kreg jig. I’m partial to deck screws when building, so this bums me out a lot.

What is a kreg jig?

A kreg jig is a pocket hole jig. It allows you to make pocket holes without much thought or fuss.

Pocket holes are holes that drilled at at angle and can be filled. The pocket holes turn out perfect every time with a kreg jig.

What are pocket holes?

Pocket holes are used to join 2 pieces of wood without visible screws. They can be used to join 2 pieces to make a flat surface (like a table top), or to join 2 pieces to form a perpendicular angle (like an L or a cube).

Pocket holes are the best way to join wood, in my opinion. You get a strong surface without using glue.

Why would you want pocket holes?

A kreg jig is also very useful for joining smaller pieces of wood together to create one large piece (like a tabletop or countertop.) It creates a very strong joint, which is really important for furniture.

It’s also useful for joining corners, particularly when you’re using thinner or weaker wood that you wouldn’t want to screw straight into, like plywood.

Can you use regular screws with a Kreg Jig?

Unfortunately, no. You have to use the kreg jig brand screws because other screws don’t fit.

Luckily, the screws are good quality!

They remind me of my favorite deck screws because they have a smooth shaft that creates tighter joints.

How to Use a Kreg Jig R3 to Make Pocket Holes

Measure the thickness of your wood. My wood was 3/4″ thick. Don’t make assumptions here. If you buy a 1×4, it’s not a true 1″ x 4″. It’s typically about 3/4″ x 3 1/2″.

Cross reference the handy chart that comes in the book with your kit. It tells you the setting that you need for your kreg jig and the length of screws needed. You will use this chart every time you use it, so don’t lose it!

Adjust the drill bit to the correct depth based on the wood thickness. Use the allen wrench to loosen the depth collar and move it to the correct spot as indicated by the case. Then tighten it with the allen wrench. Mine needed to be 3/4″, so I moved it until the edge lined up with the 3/4″ mark.

Adjust the jig to the correct depth. Be sure to use the arrow and not the top line like I did by mistake! You will have to redrill all the holes. Push each side up or down until it’s in the right place. (This part took me forever to figure out.)

Clamp the jig in the right spot. For the countertop we were building, we placed it about 3″ from where we were going to cut it, and about every 6″ after that.

Attach the drill bit to your drill.

Drill the pocket holes using the jig. The jig has 2 holes, but I normally just choose one.

Repeat for all of your holes.

Screw the wood together. When you are finished drilling all of the holes, change the drill bit to the driver and screw in the right length of screws. The guide will tell you the right length. Be sure not to over-tighten because wood needs a little breathing room to expand. We used clamps to keep the wood nice and tight.

Repeat for the rest of your holes.

You can see where I messed up and set the kreg jig using the top as the guide instead of the arrow. The correct length of screws would have been too short at this setting. Longer screws would poke through the beautiful top. Luckily, it doesn’t matter what the underneath of a countertop looks like!

Using a kreg jig is much easier than I ever imagined and it makes DIY projects look more professional. Now that you know how to use a kreg jig, you’ll be making beautiful projects in no time!

Have you ever used a kreg jig?

Kreg Jig Projects Using Pocket Holes

Emy is a vintage obsessed mama of 2 DIYer who loves sharing affordable solutions for common home problems. You don’t need a giant budget to create a lovely home. Read more…

## 7 Different Types Of Operators In Python

Introduction to Python Operators

Python operators are special symbols or reserved keywords that execute operations on one or more operands (values or variables). Operators are essential to programming, allowing developers to manipulate data and control program flow. Python has many operators that perform various operations such as arithmetic, comparison, logic, assignment, identity, membership, and bitwise operations.

Operators can operate on different types of data, such as numbers, strings, lists, tuples, and dictionaries, depending on the operator type and the operands’ data type. For example, the addition operator (+) can add two numbers, concatenate two strings, or merge two lists.

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Key Highlights

Python operators are the symbols that perform specific operations in between the operands. These operators are usually involved in performing the operations such as logical, arithmetic, comparison, etc.

The Python interpreter follows a particular order while executing these operators. The operator precedence in Python determines how operators are evaluated in an expression.

Understanding Python operators is critical for developing Python programs. Using operators, developers can write code that performs complex operations quickly and efficiently, allowing them to create more powerful and effective programs.

Types of Python Operators

Python Operators are a fundamental programming part that allows developers to manipulate data and control program flow. Python has several types of operators that can be used to perform different operations.

Python’s most common types of operators include

Arithmetic operators

Assignment operators

Comparison operators

Logical operators

Identity operators

Membership operators

Bitwise operators.

Understanding the different types of Python operators and how to use them effectively is critical for developing Python programs that can perform complex operations on data.

Python offers a diverse set of operators that serve various purposes.

1. Arithmetic Operator

Arithmetic operators are used to perform mathematical operations.

Operator Description Syntax Output

+ Addition a+b Returns the sum of the operands

– Subtraction a-b Returns Difference of the operands

/ Division a/b Returns Quotient of the operands

* Multiplication a*b Returns product of the operands

** Exponentiation a**b returns exponent of a raised to the power b

% Modulus a%b returns the remainder of the division

// Floor division a//b returns a real value and ignores the decimal part

Consider an example program for carrying out the arithmetic operations explained above.

Adds two values to obtain the sum.

Example:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) add = Xa + Xb print('Sum of the numbers is',Xa ,'and' ,Xb ,'is :',add)

Output:

2. Subtraction (–)

This operator subtracts or provides the difference between two operands.

Example:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) diff = Xa - Xb print('Difference of the numbers is ',Xa ,'and' ,Xb ,'is :',diff)

Output:

3. Multiplication (*)

This operator multiplies two operands and provides the results.

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) mul = Xa * Xb print('Product of the numbers is ' ,Xa ,'and' ,Xb ,'is :',mul)

Output:

4. Division (/)

This operator involves dividing two operands.

Example:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) div = Xa / Xb print('Division of the numbers is ',Xa ,'and' ,Xb ,'is :',div)

Output:

5. Exponentiation (**)

The exponentiation operator is nothing but the power, where the representation of the operands is in the form of ab or Xa ** Xb. It performs the multiplication operation.

Example:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) power = Xa ** Xb print('Exponent of the numbers is ',Xa ,'and' ,Xb ,'is :',power)

Output:

6. Floor division (//)

This operator rounds off the decimals obtained in the division operation.

Example:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) floor_div = Xa print('Floor Division of the numbers is ',Xa ,'and' ,Xb ,'is :',floor_div)

Output:

7. Modulus (%)

The modulus operator obtains the remainder after dividing the operands.

Example:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) modulus = Xa % Xb print('Modulus of the numbers is ',Xa ,'and' ,Xb ,'is :',modulus)

Output:

Overall Example:

Code:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) add = Xa + Xb diff = Xa - Xb mul = Xa * Xb div = Xa / Xb floor_div = Xa power = Xa ** Xb modulus = Xa % Xb print('Sum of the numbers is',Xa ,'and' ,Xb ,'is :',add) print('Difference of the numbers is ',Xa ,'and' ,Xb ,'is :',diff) print('Product of the numbers is ' ,Xa ,'and' ,Xb ,'is :',mul) print('Division of the numbers is ',Xa ,'and' ,Xb ,'is :',div) print('Floor Division of the numbers is ',Xa ,'and' ,Xb ,'is :',floor_div) print('Exponent of the numbers is ',Xa ,'and' ,Xb ,'is :',power) print('Modulus of the numbers is ',Xa ,'and' ,Xb ,'is :',modulus)

Output:

2. Bitwise Operators

In Python bitwise operator is usually used to perform operations on the binary representation for the integer values. The bitwise operator works on bits and conducts the operations bit by bit. Refers to the operators working on a bit, i.e., they treat the operand as a string of bits; for example, in bitwise operations, 5 will be considered 0101.

The box below provides the bitwise operators in Python

Operator

Description Syntax

Output

& Binary AND a&b The bit is copied to the result only if present in both operands.

| Binary OR This function copies a bit if present in either of the operands.

^ Binary XOR a^b Copies the bit if it is set in one operand but not both.

~ Binary One’s Complement a~b Unary operation of flipping bits.

<< Binary Left Shift a<<b The left operand value is moved left by the number of bits specified by the right operand.

>> Binary Right Shift The value of the left operand is shifted to the right by the number of bits indicated by the right operand.

The below example shows the bitwise operator as follows. In the below example, we have defined all the bitwise operators as follows.

1. Bitwise AND (&)

The bitwise AND operator performs the logical AND operation on the values given and returns the value.

Example:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) res = Xa & Xb print ("Xa & Xb : ", res)

Output:

The bitwise OR operator performs logical OR operation on the given input values.

Example:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: '))

Output:

3. Bitwise xor (^)

The bitwise xor operator performs the logical XOR operation on the corresponding bits on the input values.

Example:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) res = Xa ^ Xb print ("Xa ^ Xb : ", res)

Output:

4. Bitwise 1’s complement (~)

The bitwise 1’s complement operator returns the result of the bitwise negation of a value where each bit is inverted.

Example:

X = int(input('Enter number: ')) res = ~X print ("X : ", res)

Output:

5. Bitwise left-shift (<<)

The bitwise left-shift operator shifts the bits for a value by a given number of places to the left-hand side by adding 0s to new positions.

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) res = Xa << Xb print ("Xa << Xb : ", res)

Output:

The bitwise right-shift operator involves shifting the bits for an input value by a given number of places right; during this, some bits usually get lost.

Example:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: '))

Output:

Overall Example

Code:

first_operand = 10 second_operand = 15 res = first_operand & second_operand print ("first_operand & second_operand : ", res) res = first_operand ^ second_operand print ("first_operand ^ second_operand : ", res) res = ~first_operand; print ("~first_operand : ", res) res = first_operand << 5; print ("first_operand << 5 : ", res)

Output:

3. Membership Operators

Refers to the operators used in the validation of membership of operand test in a sequence, such as strings, lists, or tuples. There are two types of membership operators in Python.

Operator

Syntax

Output

in if (a in x): This statement is considered true if it locates a variable in the designated sequence and false if it does not. not in If ( b not in x ): This statement will be true if it fails to locate a variable in the designated sequence and false if it does locate it.

The below example shows the membership operator as follows.

Code:

first_operand = 29 second_operand = 23 list = [11, 15, 19, 23, 27] if (first_operand not in list): print("first_operand is NOT present in given list") else: print("first_operand is present in given list") if (second_operand in list): print("second_operand is present in given list") else: print("second_operand is NOT present in given list")

Output:

4. Identity Operators

In Python, the identity operator is used to compare the memory locations of two objects and to return the Boolean value that depends on whether they refer to the same object. There are two types of identity operators in Python.

Operator Syntax Output

is x is y returns True if the type of the value in y points to the same type in the x.

is not x is not y returns True if the type of the value in y points to a different type than the value in the x

The below example shows the identity operator as follows.

Code:

first_operand = 10 second_operand = 20 third_operand = first_operand print(first_operand is not second_operand) print(first_operand is third_operand)

Output:

5. Comparison Operators

A comparison operator is used to compare the values of two operands, and after comparing the value, it will return a true or false Boolean value. It is also known as Relational operators.

Operator Syntax Output

== (a == b) If the values of a and b are equal, then the condition becomes true.

!= (a != b) If the values of a and b are not equal, then the condition becomes true.

If the values of a and b are not equal, then the condition becomes true.

> If the value of a is greater than that of b, then the condition becomes true.

< (a < b) If the value of a is less than that of b, then the condition becomes true.

>= If the value of a is greater than or equal to that of b, then the condition becomes true.

<= (a <= b) If the value of b is less than or equal to that of b, then the condition becomes true.

The below example shows the comparison operator as follows.

Code:

x = 30 y = 35

Output:

2. Less than (<)

Code:

x = 30 y = 35 print('x < y is', x<y)

Output:

3. Equal to (==)

Code:

Xa = int(input('Enter First number: ')) Xb = int(input('Enter Second number: ')) print("Xa == Xb : ", Xa == Xb)

Output:

4. Not equal to (!=)

Code:

x = 30 y = 35 print('x != y is', x!=y)

Output:

Code:

x = 30 y = 35

Output:

6. Less than or equal to (<=):

Code:

x = 30 y = 35 print('x <= y is', x<=y)

Output:

Overall Code

Code:

first_operand = 15 second_operand = 25 print("first_operand == second_operand : ", first_operand == second_operand) print("first_operand != second_operand : ", first_operand != second_operand) print("first_operand < second_operand : ", first_operand < second_operand) print("first_operand <= second_operand : ", first_operand <= second_operand)

Output:

6. Assignment Operators

When working with Python, you can use assignment operators to assign variable values. Following are the types of assignment operators in Python.

Operator Description Syntax Output

= Equal to c = a + b assigns a value of a + b into c

+= Add AND c += a is equivalent to c = c + a

-= Subtract AND c -= a is equivalent to c = c – a

*= Multiply AND c *= a is equivalent to c = c * a

/= Divide AND c /= a is equivalent to c = c / ac /= a is equivalent to c = c / a

%= Modulus AND c %= a is equivalent to c = c % a

**= Exponent AND c **= a is equivalent to c = c ** a

//= Floor Division c is equivalent to c = c

The below example shows the assignment operator as follows.

Code:

first_operand = 10 first_operand += 5 print ("first_operand += 5 : ", first_operand) first_operand -= 5 print ("first_operand -= 5 : ", first_operand) first_operand *= 5 print ("first_operand *= 5 : ", first_operand) first_operand /= 5 print ("first_operand /= 5 : ",first_operand) first_operand %= 3 print ("first_operand %= 3 : ", first_operand) first_operand **= 2 print ("first_operand **= 2 : ", first_operand) first_operand print ("first_operand

Output:

7. Logical Operators

These operators are used to perform similar operations as logical gates; there are 3 types of logical operators in Python.

Operator Description Syntax Output

and Logical AND a and b a condition is true if both a and b are true

or Logical OR a or b a condition is true if either a and b are true

not Logical NOT not a Complement the operand

The below example shows the logical operator as follows.

Code:

first_operand = True second_operand = False print(first_operand and second_operand) print(first_operand or second_operand) print(not first_operand)

Output:

Python Operators Precedence

In Python, operators are evaluated in a specific order of precedence when used in an expression. This order determines their sequence of evaluation. The order of precedence ensures that expressions are evaluated correctly, following the standard mathematical rules. In cases where multiple operators have the same precedence, the order of evaluation follows the associativity of the operator. For example, some operators, such as addition and multiplication, are left-associative, meaning they are evaluated from left to right. Others, such as exponentiation, are right-associative, meaning they are evaluated from right to left. The below table shows operator precedence as follows.

Operator Description

** Exponentiation

‘~ + -’ Bitwise NOT, Unary Plus and Minus

<‘* / % Multiplication, division, modulus, and floor division

Bitwise shift right and left

& Bitwise AND

^ Bitwise XOR

and Logical and

not Logical not

or Logical or

Comparison Operators

= %= /= Assignment Operators

Is, is not Identity Operators

in not in Membership Operators

not or and Logical Operators

Q2. What is operator precedence? Which operator has the highest precedence?

Ans: Operator precedence is an order which is predefined and followed by the interpreter while executing multiple operations at the same time. Among all the operators (), parentheses have the highest precedence.

Q3. Is the boolean value true if null?

Ans: The null value represents that the specified variable doesn’t have anything in it. Hence it is neither true nor false.

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We hope that this EDUCBA information on “Python Operators” was beneficial to you. You can view EDUCBA’s recommended articles for more information.

## How To Use Pprint In Python?

Introduction

Improve your Python output with the power of pprint! Properly formatted and visually appealing output can greatly enhance your code debugging experience. This article introduces pprint, a Python library that serves as a Data Pretty Printer. Whether you’re dealing with JSON files or working with dictionaries, pprint can help you handle large amounts of data more effectively. Say goodbye to messy outputs and confusing structures. Best of all, pprint is an inbuilt Python library, so no separate installation is required. Let’s dive in and make your outputs shine!

This article was published as a part of the Data Science Blogathon.

What is pprint()?

It stands for “Pretty Print”, and is one of the native Python libraries that allows you to customize your outputs with its numerous parameters and flags for its single class pprint(). Here is the official documentation to list all of its properties and usage.

pprint() Parameters

The library contains just a single class, called pprint(). There are in total six parameters that can be used with this class. Here is a short description of the parameters along with their default values:

indent: The number of spaces to indent each line, this value can help when specific formatting is needed. Default value = 1

width: Maximum characters that can be in a single line. If the number of words exceeds this limit, the remaining text will be wrapped on the lines below. Default value = 80

depth: The number of depth levels to be shown while using nested data types. By default, it shows all the data, but if specified, the data beyond the depth level is shown as a series of dots ( . . . ). Default value = None

stream: This is used to specify an output stream and is mainly used to pretty print a file. Its default behavior is to use sys.stdout. Default value = None

compact: This is a boolean argument. If set to True, it will consolidate complex data structures into single lines, within the specified width. If the value is the default (ie. False) all the items will be formatted on separate lines. Default value = False

sort_dicts: This is also a boolean argument. While printing dictionaries with pprint(), it prints the key-value pair sorted according to the key name alphabetically. When set to false, the key, value pairs will be displayed according to their order of insertion. Default value = True

Now enough with the technical stuff, let’s jump into the programming part!

Basics of pprint()

First, we import the pprint module at the beginning of our notebook.

import pprint

Now you can either use the pprint() method or instantiate your pprint object with PrettyPrinter().

﻿

Now let us create a sample dictionary to demonstrate some of the arguments of the class pprint().

sample_dict = { 'name': 'Sion', 'age': 21, 'message': 'Thank you for reading this article!', 'topic':'Python Libraries' }

If we simply print out this dictionary using print, what we get is:

Now that doesn’t look much appealing, does it? But still one might argue that this output format is okay since you can clearly see which value belongs to which key, but what happens if these values are extremely long, and nested. Or if the volume of our key-value pairs is much much more? That’s when it all goes downhill. It will become very very difficult to read, but worry not, print to the rescue:

pprint.pprint(sample_dict)

Firstly, all the pairs have their separate row, which increases the readability tenfold. Also if you look closely, all the elements are automatically sorted according to the keys.

The pprintpp Module

Also Read: How to Read Common File Formats in Python – CSV, Excel, JSON, and more!

Text Wrapping

Image Source: Elle

Most people might know the basics that I showed above. Now let’s use some of the other parameters to further customize our outputs.

Another basic usage is text wrapping. Suppose you are not satisfied by just printing the key-value pairs on separate lines, but want to have the text wrapped when the length of the line exceeds a certain amount. For this, we can use the width parameter.

pprint.pprint(sample_dict, width = 30)

Apart from this, we can use the indent parameter to add indentation in front of each row for better readability.

pprint.pprint(sample_dict, width = 30, indent = 10)

Here is an example for the usage of compact and width parameters:

import pprint stuff = ['spam', 'eggs', 'lumberjack', 'knights', 'ni'] stuff.insert(0, stuff[:]) pp = pprint.PrettyPrinter(indent=4) pp.pprint(stuff) pp = pprint.PrettyPrinter(width=41, compact=True) pp.pprint(stuff) Deep Nested Objects

Image Source: Missouri Dept. of Conservation

Sometimes while working with highly nested objects, we just want to view just the outer values and are not interested in the deeper levels. For example, if we have a nested tuple like this:

sample_tuple = ('spam', ('eggs', ('lumberjack', ('knights', ('ni', ('dead', ('parrot', ('fresh fruit',))))))))

Now if we use print or print, the outputs will be almost similar:

print(sample_tuple) > ('spam', ('eggs', ('lumberjack', ('knights', ('ni', ('dead', ('parrot', ('fresh fruit',)))))))) pp.pprint(sample_tuple)

However, if the depth parameter is specified, anything deeper than that will be truncated:

pprint.pprint(sample_tuple, depth=2) pprint.pprint(sample_tuple, depth=1) p = pprint.PrettyPrinter(depth=6) p.pprint(sample_tuple) pprint() vs PrettyPrinter()

The difference between these two is that the pprint() method uses the default arguments and settings of the libraries, which you can change like we previously saw, but these changes are temporary.

With PrettyPrinter(), you can create a class, with your own specifications and override the default settings to create permanent class objects which retain their forms and values all over your project.

import pprint coordinates = [ { "name": "Location 1", "gps": (29.008966, 111.573724) }, { "name": "Location 2", "gps": (40.1632626, 44.2935926) }, { "name": "Location 3", "gps": (29.476705, 121.869339) } ] pprint.pprint(coordinates, depth=1) > [{...}, {...}, {...}] pprint.pprint(coordinates)

As you can see, the arguments supplied were just temporary. Conversely, these settings are stored with PrettyPrinter(), and you can use them wherever in the code you want, without any change in functionality:

import pprint my_printer = pprint.PrettyPrinter(depth=1) coordinates = [ { "name": "Location 1", "gps": (29.008966, 111.573724) }, { "name": "Location 2", "gps": (40.1632626, 44.2935926) }, { "name": "Location 3", "gps": (29.476705, 121.869339) } ] my_printer.pprint(coordinates) > [{...}, {...}, {...}] Conclusion Frequently Asked Questions

Q1. What is Pprint used for?

A. Pprint (pretty print) is a Python module used for formatting complex data structures more readably and organized, especially when printing them to the console or writing to a file.

Q2. What is the difference between print and Pprint?

A. The main difference between print and Pprint is that Pprint is designed to format complex data structures such as dictionaries and lists, preserving their structure and providing indentation. In contrast, print is used for simple output of values or strings.

Q3. Is Pprint standard in Python?

A. Pprint is not a standard built-in module in Python, but it is included in the Python Standard Library, meaning it is available by default in most Python installations.

Q4. Is Pprint native to Python?

A. Yes, Pprint is native to Python as it is included in the Python Standard Library, allowing developers to utilize its functionality without needing external dependencies or installations.

References

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