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Ready to add another cool tool to your Python toolkit? Today, we’re going to chat about the XOR operation. Now, if you’re thinking, “XOR sounds like something out of a sci-fi movie,” don’t worry! It’s actually a pretty simple and super useful concept in Python
Python XOR, also known as Exclusive OR, is a type of logical operation used primarily with binary numbers. The XOR operation takes two operands and returns a boolean value of True if exactly one of the operands is True, and False otherwise. In Python, the XOR operation is represented by the caret operator (^).
In Python, you can use the XOR operation for various purposes such as error detection, cryptography, and data manipulation. It plays an important role in many algorithms and data-processing techniques. Having a good grasp of XOR operations in Python will help you find new ways of solving problems.
Before you start using XOR operations in your code, it’s important that you understand the basics of it. Let’s look at some important concepts you should know when using XOR operations.
In this section, we’ll look at what XOR is, how you can use it with boolean values, and its syntax in Python. Let’s get into it!
In Python, XOR is a bitwise operation that allows you to compare two binary numbers bit by bit.
If the bits being compared are identical, the XOR operator returns 0 (False), and if the bits are different, it returns 1 (True).
The XOR operator is also known as the “exclusive or” because it returns true exclusively when the two bits being compared are different.
The Python XOR operator is represented by the ^ symbol.
You can apply it directly to integer operands.
The following is an example illustrating how to use the XOR operator in Python:
a = 5 b = 3 result = a ^ bWhen using the XOR operator, Python automatically converts the integer values to their binary formats. It then performs the XOR operation bit by bit in binary form, and then returns the result as an integer.
Thus, in the example above, the binary representation of 5 (0101) and 3 (0011) are XORed together, resulting in the binary string 0110, which is equal to integer 6.
Python offers multiple methods for implementing XOR operations, such as the ^ bitwise XOR operator, logical operators, and the xor function from the operator module.
In this section, we’ll go over the following:
Implementing Bitwise XOR Operator
Implementing Logical XOR Operators
Implementing XOR using Built-in XOR Module
In Python, you can perform the bitwise XOR operation using the ^ operator. The operator takes two integer operands, converts them into binary format, and then performs the XOR operation bit-by-bit.
The result of the bitwise XOR operation is an integer value. The following example demonstrates the usage of the bitwise XOR operator.
a = 5 # Binary representation: 0101 b = 3 # Binary representation: 0011 result = a ^ b # Binary result: 0110, Decimal result: 6 print(result)You can implement a logical XOR in Python using logical operators and and or. Logical XOR evaluates to True if both operand values are different, otherwise, it evaluates to False.
The following is an example of using logical operators to implement a logical XOR function.
def logical_xor(a, b): return (a and not b) or (not a and b) x = True y = False result = logical_xor(x, y) print(result)The output of this script is given below:
Python also provides the xor function in the built-in operator module, which you can use to perform bitwise XOR operations on integers and logical XOR operations on booleans.
The following is an example of using Python’s built-in XOR module:
from operator import xor x = 5 y = 3 z = True w = False bitwise_result = xor(x, y) # Output: 6 logical_result = xor(z, w) # Output: True print(bitwise_result) print(logical_result)The output of this script is given below:
The two boolean values result in a True value, whereas the integer values give 6 as output.
In Python, you can perform bitwise operations on individual bits of binary numbers.
Some common bitwise operators include Bitwise AND, Bitwise OR, Bitwise NOT, Bitwise Left Shift, and Bitwise Right Shift.
The following sections provide a brief overview of each bitwise operation.
In Python, a bitwise AND operator is represented by the symbol &. It is used to compare two integers at the bit level. For each bit in the resulting binary number, if the corresponding bits in both input numbers are 1, then the resulting bit is 1; otherwise, it is 0.
The following example demonstrates Bitwise AND operator in Python:
A = 1100 B = 1010 A & B # Output:1000The output of the code is 1000. The following steps demonstrate how Python computed 1000 as output:
We start from the rightmost bit (also known as the least significant bit):
0 (from B) AND 0 (from A) results in 0
1 (from B) AND 0 (from A) results in 0
0 (from B) AND 1 (from A) results in 0
1 (from B) AND 1 (from A) results in 1
So, when you perform A AND B, the result is 1000.
For each bit in the resulting binary number, if the corresponding bits in at least one of the input numbers are 1, then the resulting bit is 1; otherwise, it is 0.
The following is an example of bitwise OR in Python:
A = 1100 B = 1010 # Output: 1110The output of the operation is 1110. The following steps demonstrate how Python computed 1110 as output:
Starting from the rightmost bit:
0 (from B) OR 0 (from A) results in 0
1 (from B) OR 0 (from A) results in 1
0 (from B) OR 1 (from A) results in 1
1 (from B) OR 1 (from A) results in 1
So, when you perform A OR B, the result is 1110.
The bitwise NOT operator is represented by the symbol ~. It is used to invert the bits (i.e., change ‘0’ to ‘1’ and ‘1’ to ‘0’) of an integer.
In the example below, we invert the bits of A by performing a bitwise NOT operation on it.
A = 1100 ~A = 0011This is because NOT 1 results in 0, and NOT 0 results in 1.
The bitwise left shift operator is represented by the symbol <<.
This operator lets you move all the bits in the binary representation of a number to the left by a specified number of positions. It fills the vacancies with ‘0’.
The following is an example of a bitwise left shift:
A = 1100 # When we shift A two places to the left, we get: A << 2 = 110000The original two rightmost digits (00) get shifted to the left by two places and two zeros are added to the right end, thus the resulting binary number is 110000.
The following is an example of a bitwise right shift:
A = 1100 #When we shift A two places to the right, we get:The original two rightmost digits (00) get dropped, and the resulting binary number is 11.
These bitwise operators are commonly used to perform operations on integers and binary numbers in Python. It allows you to efficiently manipulate binary data.
When working with XOR operations in Python, you can run into errors from time to time. TypeError is a common error that occurs when using XOR operations.
TypeErrors occur when you apply an operation or function to an object of an inappropriate type.
In the context of Python XOR (exclusive or) operations, a common example of a TypeError is when using incompatible types for bitwise operators.
Since bitwise XOR (^) is only defined for specific built-in data types such as int, bool, and a few others, this can lead to TypeErrors if used incorrectly.
The following is an example of TypeError when using XOR operators:
a = 5 b = "string" result = a ^ b # Raises TypeErrorTo handle this error, you may use a try-except block:
try: result = a ^ b except TypeError: print("Incompatible types for XOR operation")Since a and b have different data types, therefore, it will raise a TypeError. The following is the output of the script:
To learn more about handling errors in Python, check the following video out:
Python XOR with NumPy
Using XOR in Mathematical Operations
Sequence and Protocol Implementations
NumPy is a popular Python library for numerical operations. It provides a function called logical_xor() that allows you to perform element-wise logical XOR on input arrays.
The following is an example of using NumPy to perform XOR operations:
import numpy as np x1 = np.array([True, False, True]) x2 = np.array([False, True, True]) result = np.logical_xor(x1, x2) print(result)In this Python script, we have two arrays, x1 and x2. We apply the logical ‘exclusive OR’ (XOR) operation on these arrays using the np.logical_xor function, which results in a new array.
This array, when printed, gives the output: [True True False], which is the result of the XOR operation for each corresponding pair of elements in x1 and x2.
The output is given below:
You can use XOR in various mathematical operations, such as finding the absolute value of a number without using conditionals.
The following is an example of using XOR in mathematical operations:
def xor_abs(x): negative_number = -5 print(xor_abs(negative_number))This Python script computes the bitwise XOR of the input number and its binary representation with the sign bit shifted to the first operand, and then subtracts the shifted value.
You can also use XOR in sequence and protocol-related operations.
The following example demonstrates generating unique keys for a dictionary that holds integers as keys with XOR:
def xor_key(x1, x2): return x1 ^ x2 existing_keys = [2, 4, 5] choice = 3 unique_key = xor_key(existing_keys[-1], choice) print(unique_key)This example demonstrates the use of XOR on the last element of existing_keys and a custom choice to generate a new unique key.
To use XOR to compute the parity of the number of matches in two sequences, you can use the following code:
sequence_1 = [1, 2, 3, 4, 5] sequence_2 = [1, 2, 2, 4, 6] matches = sum(x1 ^ x2 == 0 for x1, x2 in zip(sequence_1, sequence_2)) parity = matches % 2 print(parity)This example iterates through two sequences, evaluates the XOR between their corresponding elements, finds the number of matches in which the XOR is 0, and computes the parity of the matches.
As we close this discussion of Python’s XOR operation, let’s focus on why understanding this logic operator is crucial for you.
XOR operators play a pivotal role in various fields of computer science, such as error detection and correction, cryptography, and logical computations.
When you learn and apply XOR, you’re adding an important tool to your programming toolbox. XOR operations are useful in array manipulations, improving memory efficiency, and even in algorithm-based problem-solving. XOR operation also helps you understand how data is manipulated at the fundamental.
Using XOR and other bitwise operators is a crucial component of your coding journey. They bring you closer to the machine-level understanding of your code, and in doing so, equip you with a more comprehensive programming language fluency.
Happy coding!
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Power Bi Themes: User Guide With Examples
Power BI is a powerful business analytics tool that helps you visualize and analyze data from various sources. One of the most useful features of Power BI is the ability to apply themes to your reports and dashboards.
Power BI themes allow you to customize your reports and dashboards to match your organization’s branding or personal preferences. You can choose from a variety of pre-built themes or create your own custom theme using the built-in theme generator. Once applied the themes, all visuals in your report will use the colors and formatting from your selected theme as their defaults.
In this article, you’ll learn how to apply themes to your entire report or dashboard to maintain consistency and branding across all your visualizations, making them look more professional and polished.
Power BI themes are standardized color schemes and formatting options that can be applied to your entire report, including visuals, text, and shapes.
With Power BI themes, you can easily apply design changes to your entire reports, such as changing the color scheme, font type, and background color.
Themes in Power BI can be created using a JSON file that contains all the color codes and formatting options.
Power BI themes have several benefits that can help you create professional-looking reports quickly and easily. Some of the benefits of using Power BI themes are:
1. Consistency: Applying a theme to your report ensures that all the visuals, text, and shapes have a consistent look and feel. This can help make your report more professional and easier to read.
2. Branding: You can use your company’s branding colors and fonts in the theme to create a report that aligns with your company’s brand guidelines.
3. Time-saving: Creating a theme once and applying it to multiple reports can save you a lot of time. You don’t have to manually change the colors and formatting options for each report.
4. Accessibility: Power BI themes also include accessible color schemes that can help make your report more accessible to people with color vision deficiencies.
Power BI themes are a powerful tool that can help you create professional-looking reports quickly and easily.
Whether you’re creating a report for your company or for personal use, using a theme can save you time and ensure consistency throughout your report. We’ll go over creating custom themes in the next section.
If you want to create a custom theme in Power BI, there are several factors you need to consider such as background, formatting, shapes, color palette, header, contrast, text color, and more.
Here are some sub-sections to guide you through the process:
The background of your report should be consistent with your corporate colors. To set the background color, go to the View ribbon and select the Themes section.
From there, you can choose from a range of predefined color schemes or just select Customize current theme to create your own Power BI theme.
Formatting is an essential part of creating a custom theme. You can change the font family, font size, and font color to match your brand.
Additionally, you can customize tooltips, wallpaper, and filter pane to give your report a cohesive look and feel.
Shapes can be used to highlight specific data points or to add visual interest to your report. You can customize the shapes in your report by using the theme JSON file.
If you want to create a custom theme, you can start by selecting a pre-built default theme that is close to what you are looking for. From there, you can use the “Customize current theme” option to make adjustments to the color palette, foreground, and data colors.
The Power BI community is an excellent resource for finding inspiration and getting help with your custom theme. You can browse the Theme Gallery to find pre-built themes or ask for help in the community forums.
Color is an essential part of any custom theme. You can use a color palette to ensure that all the colors in your report are consistent with your brand. You can also use the color palette to create contrast and highlight specific data points.
The header of your report is an excellent place to showcase your brand. You can customize the header by adding your logo or by changing the font and font color.
The color theme of your report should be consistent with your brand. You can create a color theme by selecting a base color and then using shades of that color to create contrast.
Contrast is an essential part of any custom theme. You can use contrast to highlight specific data points or to draw attention to important information.
Text color is an important part of any custom theme. You can use text color to create contrast and to make sure that your report is easy to read.
If you are new to creating custom themes, you can use a theme generator to help you get started. A theme generator will guide you through the process of creating a custom theme and will provide you with a range of options to choose from.
Creating a custom theme in Power BI can be a daunting task, but it is essential if you want to create a report that is consistent with your brand.
By following the guidelines outlined in this section, you can create a custom theme that is both visually appealing and easy to read. In the next section, we’ll explore using built-in themes.
If you want to quickly change the appearance of your Power BI report or dashboard, using built-in themes is a great option.
Here’s what you need to know about using them:
Built-in report themes come with predefined color schemes and are accessible from the Power BI Desktop menu.
They provide a quick way to change the look and feel of your report or dashboard without having to customize everything from scratch. You can also use built-in dashboard themes to change the appearance of your dashboard.
While built-in themes are a great starting point, they do have some limitations. For example, you can’t customize the background color or fonts of the visualizations in a report. You also can’t change every visual property using a built-in theme.
If you need more granular control over the look and feel of your report or dashboard, you’ll need to create a custom report or dashboard theme.
Power BI provides a variety of built-in themes that are accessible to everyone. These themes are designed to be visually appealing and accessible to a wide range of users. Some of the themes available include Azure, Colorblind, and Purple Rain.
If you need to create a report or dashboard that is accessible to users with visual impairments, you can use the High Contrast theme. This theme uses high-contrast colors to make it easier for users to distinguish between different elements in the report or dashboard.
If you want to create a custom report or dashboard theme, you’ll need to use the JSON format. This format allows you to specify the colors, fonts, and other visual properties of your theme. You can also use a theme generator to create a custom theme without having to write the JSON code yourself.
Using built-in themes is a quick and easy way to change the appearance of your Power BI report or dashboard.
While they do have some limitations, they are a great starting point if you don’t need a lot of customization.
If you need more granular control over the look and feel of your report or dashboard, you’ll need to create a custom theme using the JSON format.
Now that we have covered using the built-in themes, we’ll go over applying themes to Power BI themes.
By applying themes to your Power BI reports, you can maintain consistent branding, align with company styles, or create visually appealing reports that match your preferences.
Here are some things you should know about when applying themes to Power BI reports:
Power BI themes are standardized color schemes and formatting options that can be applied to your entire report, including visuals, text, and shapes.
You can use a theme to maintain consistency throughout your report without having to individually change each element. This section will guide you through the process of applying themes to your Power BI reports.
When you apply a report theme, all visuals in your report use the colors and formatting from your selected theme as their defaults.
This means that you can quickly change the look and feel of your report by selecting a different theme. You can choose from pre-built themes or create your own custom theme using the JSON theme file.
To apply Power BI report themes, simply open your report in Power BI Desktop and select the “Switch Theme” option from the “View” tab.
From here, you can choose from a variety of pre-built themes or import your own custom JSON theme file. You can also customize your theme by changing the color palette, font, and visual styles.
If you have any feedback or suggestions for improving Power BI themes, you can submit them to the Power BI product team through the Power BI Ideas forum. This is a great way to share your ideas with the Power BI community and help shape the future of the product.
For more information on Power BI themes, you can visit the chúng tôi website, which provides a comprehensive guide to using themes in Power BI. You can also refer to the official Power BI documentation for detailed instructions on applying themes to your reports.
In summary, applying themes to your reports in Power BI is a simple and effective way to maintain consistency and improve the overall design of your reports.
By selecting a pre-built theme or creating your own custom theme, you can quickly and easily change the look and feel of your report to match your brand or personal style.
If you want to learn more about Power BI themes, there are several resources available online that can help you. Here are a few that you might find useful:
Microsoft Power BI Community: The Power BI community is a great place to find information about Power BI themes. You can browse through the Themes Gallery to see examples of custom themes created by other users, or you can ask questions in the forums to get help with creating your own custom themes.
Color Themes: If you’re looking for inspiration for your Power BI themes, there are several websites that offer pre-made color schemes that you can use. Some popular options include Adobe Color, Color Hunt, and Coolors.
Theming: Theming is the process of applying a consistent visual style to your Power BI reports. This can include things like color schemes, fonts, and formatting options. By creating a custom theme, you can ensure that your reports have a consistent look and feel.
Color Blindness: When creating Power BI reports, it’s important to consider users who may be color blind. You can use color schemes that are designed to be accessible to people with color blindness, or you can use other visual cues (such as patterns or textures) to convey information.
Consistency: Consistency is key when it comes to creating effective Power BI reports. By using a consistent theme throughout your reports, you can make it easier for users to understand the information you’re presenting.
Custom Themes: If you want to create your own custom theme for Power BI, there are several tools available that can help. The Power BI Theme Generator is a popular option, as it allows you to create a custom theme based on an existing color scheme.
LinkedIn: If you’re looking to connect with other Power BI users, LinkedIn is a great place to start. There are several Power BI groups on LinkedIn where you can ask questions, share tips and tricks, and connect with other users who are passionate about Power BI.
Power BI themes provide a convenient way to customize the visual appearance of your reports. By applying a theme, you can ensure consistency across multiple reports and dashboards by providing a unified visual style.
It saves time and effort as you can easily apply a theme to a report instead of manually adjusting each formatting element. Themes also allow you to quickly switch between different visual styles or apply custom themes for specific projects or clients.
Whether you are a business user creating reports for your organization or a developer building Power BI solutions for clients, leveraging themes can enhance the overall look and feel of your reports, making them more engaging and impactful for the audience.
If you want to learn more about Power BI, you can watch the video below:
Python Class: A Complete Guide (Beginner Friendly)
Python is an object-oriented programming language. It means almost everything is an object. When becoming a Python developer, it’s crucial to learn what is a Python class and how to use it to create those objects.
A Python class is a blueprint for creating objects.
For example, here is a simple class Person, that has an attribute name:
class Person: name = "Sofie"Now you can create a Person object from the class by:
girl = Person()An object is also known as an instance of a class. The process of creating objects from a class is called instantiation.
You can use a class to instantiate different objects that all represent the class. For example, you can create multiple persons with different names.
How to Crete a Class in PythonTo create a new Python class, use the class keyword.
Here is the syntax for defining a class in Python:
class ExampleClass: passNow, every piece of code you write into this block belongs to that class.
For now, we are going to pass the implementation of the class, as we will return to it later on.
How to Use a Python ClassIn the previous section, you learned the syntax for creating a class in Python. But how can you use this class?
The answer is you can create, or more formally, instantiate objects of the class.
Creating an instance of the above ExampleClass looks like this:
obj = ExampleClass()Now obj is a Python object that represents the ExampleClass. It thus has all the behavior described in the class. However, now the ExampleClass is empty, thus you can not do much with its representative objects.
In the next section, we are going to learn how to associate properties and behavior with the class. This way you can put your class into use.
Attributes and Methods in a Python ClassA bare class is not much of use. To benefit from using classes, you need to associate some behavior with them.
For example, a Person class could store info about the person and a method that introduces it.
To associate properties and behavior to a class, you need to create attributes and methods in the class.
Let’s first have a look at how to create class attributes in Python.
Attributes in a ClassAttributes in classes are properties that are present in the class and its objects. For example, a Fruit class could have a color attribute.
To create attributes in a class, declare them as variables in the class.
For example, let’s create a Fruit class with a color attribute:
class Fruit: color = "Yellow"(Keep in mind you can add as many attributes to your class as you want.)
If you now instantiate a Fruit object based on the above Fruit class, you can access its color property using the dot notation.
For example, let’s create a Fruit object called some_fruit and display its color by printing it into the console:
some_fruit = Fruit() print(some_fruit.color)Output:
YellowNow, the color of some_fruit is "Yellow" because that’s what you defined in the class. But you can change it for this particular object if you wish to.
For instance, let’s turn some_fruit to red:
some_fruit.color = "Red" print(some_fruit.color)Output:
RedThis change in color does not affect the Fruit class. Instead, it only changes the object, as you can see.
Now that you understand what class attributes are in Python, let’s take a look at methods in classes.
Methods in a Python ClassA function inside a class is known as a method. A method assigns behavior to the class.
Usually, a method uses the attributes (or the other methods) of the class to perform some useful task. For example, a Weight class could have a kilograms attribute. In addition, it can have a to_pounds() method, that converts the kilograms to pounds.
To create a method for your class in Python, you need to define a function in it.
As mentioned, the method needs to access the attributes of the class. To do it, the method has to accept an argument that represents the class itself.
Let’s put it all together in a form of a simple example:
Let’s create a Person class and define an introduce() method to it. This makes it possible for each Person object to introduce themselves by calling person.introduce():
class Person: name = "Sophie" def introduce(self): print("Hi, I'm", self.name)If you now look at the introduce() method, you can see it takes one argument called self. This is there because as mentioned earlier, the class needs to be able to access its own attributes to use them. In this case, the person needs to know the name of itself.
Now you can create a person objects and make them introduce themselves using the introduce() method.
For instance:
worker = Person() worker.name = "Jack" worker.introduce()Result:
Hi, I'm JackWonderful! You know the basics of defining a class and creating objects that contain attributes and some useful behavior.
But in the above example, the name of a Person is always Sophie to begin with. When you create a person object, you need to separately change its name if you want to. Even though it works, it is not practical.
A better for instantiating objects would be to directly give them a name upon creation:
dude = Person("Jack")Instead of first creating an object and then changing its name on the next line:
dude = Person() dude.name = "Jack"To do this, you need to understand class initialization and instance variables. These give you the power to instantiate objects with unique attributes instead of separately modifying each object.
Class Initialization in PythonAs you saw in the previous section, creating a person object with a unique name is only possible this way:
dude = Person() dude.name = "Jack"But what you actually want is to be able to do this instead:
dude = Person("Jack")This is possible and it is called class initialization.
To enable class initialization, you need to define a special method into your class. This method is known as a constructor or initializer and is defined with def __init__(self):.
Every class can be provided with the __init__() method. This special method runs whenever you create an object.
You can use the __init__() method to assign initial values to the object (or run other useful operations when an object is created).
The __init__() method is also known as the constructor method of the class.
In the Person class example, all the Person objects have the same name “Sophie”.
But our goal is to be able to create persons with unique names like this:
worker = Person("Jack") assistant = Person("Charlie") manager = Person("Sofie")To make it possible, implement the__init__() method in the Person class:
class Person: def __init__(self, person_name): chúng tôi = person_nameNow, let’s test the Person class by instantiating person objects:
worker = Person("Jack") assistant = Person("Charlie") manager = Person("Sofie") print(worker.name, assistant.name, manager.name)Output:
Jack Charlie SofieLet’s inspect the code of the Person class to understand what is going on:
The __init__() method accepts two parameters: self and person_name
self refers to the Person instance itself. This parameter has to be the first argument of any method in the class. Otherwise, the class does not know how to access its properties.
person_name is the name input that represents the name you give to a new person object.
The last line self.name = person_name means “Assign the input person_name as the name of this person object.”
self.name is an example of an instance variable. This means that self.name is an instance-specific (or object-specific) variable. You can create Person objects each with a different name.
To RecapInitialization makes it possible to assign values to an object upon creation. The __init__() method is responsible for the initialization process. The method runs whenever you create a new object to set it up. This way you can for example give a name to your object when creating it.
ConclusionIn Python, a class is an outline for creating objects.
A Python class can store attributes and methods. These define the behavior of the class.
Also, you can initialize objects by implementing the __init__() method in the class. This way you can create objects with unique values, also known as instance variables without having to modify them separately.
Thanks for reading. Happy coding!
Further Reading50 Python Interview Questions
Guide To Implement Python Pygame With Examples
Introduction to Python Pygame
Web development, programming languages, Software testing & others
Syntax and Parameters of Python PygameBelow are the syntax and parameters:
Syntax
import pygame from pygame.locals import * Parameters
importing pygame module followed by accessing key coordinates easily from locals
From there, you write your game code where you want to insert objects movable, sizeable, etc.
Then initialize the pygame module.
Examples to Implement Python PygameBelow are the examples:
1. initializing the pygame pygame.init()This is a function call. Before calling other pygame functions, we always call this first just after importing the pygame module. If you see an error that says font not initialized, go back and check if you forgot pygame.init() insertion at the very start.
2. Surface Object pygame.display.set_mode((500, 500))This function call returns the pygame.Surface object. The tuple within tells the pixel parameters about width and height. This creates an error if not done properly, which says argument 1 must be 2 items sequences, not int.
Code:
import pygame from pygame.locals import * pygame init() display_window = pygame.display.set_mode((400, 300)) pygame.display.set_caption('Hello World!') while True: for event in pygame.event.get(): if chúng tôi == QUIT: pygame.quit() sys.exit() pygame.display.update()Code:
#Let’s make a character move on the screen. import pygame pygame.init() win = pygame.display.set_mode((500, 500)) pygame.display.set_mode = ("First game") x = 50 y = 50 width = 40 height = 60 vel = 5 run = True while run: pygame.time.delay(100) for event in pygame.event.get(): if chúng tôi == pygame.QUIT: run = False keys = pygame.key.get_pressed() if keys[pygame.K_LEFT]: x -= vel if keys[pygame.K_RIGHT]: x += vel if keys[pygame.K_UP]: y -= vel if keys[pygame.K_DOWN]: y += vel chúng tôi ((0,0,0)) pygame.draw.rect(win, (255, 0, 0),(x, y, widty, height)) pygame.display.update() pygame.quit()
First, we initialize the pygame module by importing it.
Now, we give the parameters for the window size of the game we are constructing.
Naming the game to the first game, which is the name of the window.
Now, creating a character, it needs parameters. Let’s say we create a rectangle. A rectangle needs height, width, x and y coordinates to be placed in the window, the velocity with which it should move across the window.
Output: This is how the output seems for creating a character, that is, in this case, a rectangle.
Then we need to start writing out the main loop, which considers the character movement. In this program, the main loop is going to check for its collision, its mouse events; it’s also going to check if you hit something. This is one of the simple ways to do it.
Now we make a run variable. In the loop, we are going to check the collision. Giving the loop a time delay is going to help you by delaying the things that happen real quick in the window. This regards kind od a clock in pygame. You cannot normally import the clock in pygame, but this is the easy way to do it.
For checking an event: Events in pygame are anything that the user causes. Like, moving the mouse in general, accessing the computer to create files. So, to check for the events, we happened to create a loop check for events.
Then we draw a rectangle that is movable, which is a surface on the pygame window. All the colors in pygame are in RGB, so 255 is red and the giving in the defined parameters width, height, x, y coordinates. Then we update the window, which displays us a rectangle at those particular coordinates and parameters.
Output:
With the use of keys on the keyboard, one can move the rectangle. The output is shown like this. stop and play are used to play the sounds. The immediate recognition of play gives immediate hear of beep and stops when recognizes stop. We can even play background music time by uploading it. The file can be of type MP3, MIDI or WAV.
Code:
play_sound = pygame.mixer.Sound(‘beeps.wav’) play_sound.play() import time time.sleep(5)#lets the sound play for 5 seconds. play_sound.stop() ConclusionIf one knows the basics of Python programming, he can learn the gaming modules on his own. Using loops, variables, if-else statements, the code interprets how the program behaves. You can make many such changes by inserting objects like fonts, clock object, pixel objects and coordinates, drawings, transparent colors, game loops and states, and many more.
Recommended ArticlesWe hope that this EDUCBA information on “Python Pygame” was beneficial to you. You can view EDUCBA’s recommended articles for more information.
Python @Staticmethod Vs @Classmethod: A Complete Guide
In Python, the difference between the @staticmethod and @classmethod is that:
@staticmethod is usually a helper method that behaves the same way no matter what instance you call it on. The @staticmethod knows nothing about the class or its instances.
@classmethod is a method that takes the class as an argument. You can use it as an alternative constructor to the class. (E.g. MyClass.from_string())
This is a complete guide to understanding the differences between @staticmethod and @classmethod in Python. You will learn when to use and when not to use these methods. All the theory is backed up with illustrative examples.
What Is a @staticmethod in Python?In Python, a @staticmethod is a method that belongs to a class rather than an instance of the class.
This means that a @staticmethod is a method that is shared among all instances of a class. It is called on the class itself, rather than on an instance of the class.
Here is an example of a class that defines a static method:
class MyClass: @staticmethod def static_method(): # Code for the static method goes here ...To call a static method, you would do the following:
MyClass.static_method()Note that you do not need to create an instance of the class in order to call the static method. This is because the static method belongs to the class itself, rather than to individual instances of the class. You can also see this by looking at the static method’s arguments. It takes neither self nor cls as the first argument.
What Is a @classmethod in Python?In Python, a @classmethod is a method you can call for both the instances of the class as well as the class itself. A class method takes the class itself (cls) as the first argument, instead of an instance of the class (self).
Here is an example of a class that defines a class method:
class MyClass: @classmethod def class_method(cls): # Code for the class method goes here ...To call a class method, you would do the following:
MyClass.class_method()Note that you do not need to create an instance of the class in order to call the class method. This is because the class method belongs to the class itself, rather than to individual instances of the class.
Also note that the first argument to the class method is the class itself, which is passed in automatically. In the example above, this argument is named cls, but it could be named anything else.
@staticmethod vs @classmethod in PythonIn Python, a @staticmethod is a method that belongs to a class rather than an instance of the class. This means that a @staticmethod is a method that is shared among all instances of a class. It is called on the class itself, rather than on an instance of the class. A static method knows nothing about the class or instance you’re calling it on.
On the other hand, a @classmethod is a method that is called on a class, rather than on an instance of the class. It takes the class as the first argument, rather than an instance of it. This behavior is useful if you want to create an alternative constructor method that initializes the class objects from different parameters.
For example, the dict.fromkeys() method is a class method that initializes a dictionary from keys.
Now that you understand the main difference between the class methods and static methods, let’s take a look at why and when you should use these method types.
Why Use @staticmethod?There are several reasons why you might want to use a @staticmethod rather than defining a regular function outside of a class in Python:
A @staticmethod provides a clear indication that the method belongs to the class, rather than to individual instances of the class. This can make the code easier to read and understand since the purpose and behavior of the method are more clearly defined.
A @staticmethod can be used to define helper functions that are related to the class, but that do not depend on any instance-specific state. This can make the code more modular and reusable since the @staticmethod can be called from multiple places within the class, as well as from outside of the class.
A @staticmethod can be overridden in subclasses. This allows subclasses to provide their own implementation of @staticmethod, which can be useful in certain scenarios.
Overall, using a @staticmethod instead of a regular function can make the code more organized, reusable, and readable, especially when dealing with classes and subclasses in Python.
When Use @staticmethod in Python?Use a @staticmethod in Python when you have a method that belongs to a class, rather than to individual instances of the class.
A @staticmethod is typically used to define helper functions that are related to the class, but that does not depend on any instance-specific state. This makes the code modular and reusable as the @staticmethod can be called from multiple places within the class, as well as from outside of the class.
Notice that if you have a function that does not belong to a class, and that does not depend on any class-specific state, just define a regular function outside of the class. A regular function is more flexible and can be called from anywhere, without being tied to classes so unless the behavior is related to a class it’s better to leave it out of the class.
Python @classmethod as an Alternative ConstructorIn Python, a classmethod can be used as an alternative constructor for a class. This means that you can use a classmethod to define a method that can be used to create and return instances of the class, in addition to the regular __init__ method that is used as the default constructor.
Here is an example of how you might use a @classmethod as an alternative constructor for a class:
class MyClass: def __init__(self, param1, param2): # Code for the regular constructor goes here ... @classmethod def from_string(cls, string): # Code for the classmethod constructor goes here ...In the example above, the __init__ method is the regular constructor for the MyClass class, which is called when you create an instance of the class using the MyClass() syntax.
The from_string method is a @classmethod that can be used as an alternative constructor for the class. In other words, if you want to initialize a MyClass object from a string, you can call the from_string method instead of the default initializer.
To use the from_string method as an alternative constructor, you can simply do the following:
my_object = MyClass.from_string('some string')In this example, the from_string method is called on the MyClass class, rather than on an instance of the class. It is passed the string 'some string' as the argument, and it returns an instance of the MyClass class, which is then assigned to the my_object variable.
Overall, using a @classmethod as an alternative constructor can provide a more convenient and flexible way to create instances of a class in Python. It allows you to define multiple ways of creating instances of a class, and to choose the most appropriate method based on the specific needs of your application.
SummaryIn Python, a class method is a method that belongs to a class rather than a particular object. It is marked with the @classmethod decorator. A class method receives the class as an implicit first argument, just like an instance method receives the instance.
A static method is a method that belongs to a class rather than a particular object. It is marked with the @staticmethod decorator. A static method does not receive any additional arguments; it behaves like a regular function but belongs to the class.
Here is an example of how to use these decorators in a Python class:
class MyClass: @classmethod def class_method(cls): # ... @staticmethod def static_method(): # ...The key difference between a class method and a static method is that a class method can access or modify the class state, while a static method cannot.
Thanks for reading. Happy coding!
Read AlsoDecorators in Python
What Is Less Than Operator (
The less than operator is one of the operators that come under the category of binary operators, which means it requires two operands to operate on. It will return true if the operand on the left side of the operator is less than the operand on the right side. Otherwise, it will return false. The less than operator come under the category of comparison operators that compare two values with each other. In this tutorial, we are going to discuss what is less than an operator in JavaScript and how it works in different situations, with help of code examples.
SyntaxThe following syntax will show how we can use the less than operator to check which operand is smaller out of the two operands −
val1 < val2Let us understand the working of the less than operator practically by implementing it inside a code example.
AlgorithmStep 1 − In the first step of the algorithm, we will define two input elements with the number type to get both inputs from the user in the form of numbers.
Step 4 − In the last step, we will grab the inputs entered by the user inside the input bars using the value property and then convert them into the number using the Number() method, after that we will operate the less than operator on these inputs.
Example 1The below example will show you the working of the less than the operator in the case when both the inputs are in the form of numbers −
var
result
=
document
.
getElementById
(
“result”
)
;
function
display
(
)
{
var
inp1
=
document
.
getElementById
(
“inp1”
)
;
var
val1
=
Number
(
inp1
.
value
)
;
var
inp2
=
document
.
getElementById
(
“inp2”
)
;
var
val2
=
Number
(
inp2
.
value
)
;
var
rem
=
val1
<
val2
;
}
In the above example, we have seen that the less than operator works as expected. Because it is returning true if the left operator is smaller than the right operator else it is returning false.
Let us see one more example where a number will be compared with a string.
AlgorithmThe algorithm of this example is almost similar to the previous one. You just need to change the type of any one input element to the text and remove the Number() method on the value of that particular input.
Example 2The example below illustrates the working of the less than operator if the inputs are of different datatypes, i.e. number and string −
var
result
=
document
.
getElementById
(
“result”
)
;
function
display
(
)
{
var
inp1
=
document
.
getElementById
(
“inp1”
)
;
var
val1
=
inp1
.
value
;
var
inp2
=
document
.
getElementById
(
“inp2”
)
;
var
val2
=
Number
(
inp2
.
value
)
;
var
rem
=
val1
<
val2
;
}
In this example, we can clearly see that when a string number is input by the user the less than operator behaves the same as in case of numbers, but if a name of a long string is input by the user, then it returns false.
Let us see one more example, where a string will be compared with a string using the less than operator.
AlgorithmAlgorithms of the previous and this example are similar. You just need to do some minor changes like change the type of both the input elements to text and remove the Number() method on both the input values.
Example 3Below example will explain the behaviour of the less than operator, if both the inputs are in the form of strings −
var
result
=
document
.
getElementById
(
“result”
)
;
function
display
(
)
{
var
inp1
=
document
.
getElementById
(
“inp1”
)
;
var
val1
=
inp1
.
value
;
var
inp2
=
document
.
getElementById
(
“inp2”
)
;
var
val2
=
inp2
.
value
;
var
rem
=
val1
<
val2
;
}
In the above example, the less than operator behaves same as in the case of numbers if the input is a string number. But it behaves unexpectedly, if both the inputs are strings, because it compares the string with the Unicode code values contained by them.
In this tutorial, we have learned about the less than operator in JavaScript and see the behaviour of the less than operator in different scenarios with help of different code examples for each of these situations to understand them better.
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