Trending October 2023 # Types And Examples Of Python Validation # Suggested November 2023 # Top 17 Popular | Benhvienthammyvienaau.com

Trending October 2023 # Types And Examples Of Python Validation # Suggested November 2023 # Top 17 Popular

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Introduction to Python Validation

Whenever the user accepts an input, it needs to be checked for validation which checks if the input data is what we are expecting. The validation can be done in two different ways, that is by using a flag variable or by using try or except which the flag variable will be set to false initially and if we can find out that the input data is what we are expecting the flag status can be set to true and find out what can be done next based on the status of the flag whereas while using try or except, a section of code is tried to run. If there is a negative response, then the except block of code is run.

Types of Validation in Python

There are three types of validation in python, they are:

Type Check: This validation technique in python is used to check the given input data type. For example, int, float, etc.

Length Check: This validation technique in python is used to check the given input string’s length.

Range Check: This validation technique in python is used to check if a given number falls in between the two numbers.

The syntax for validation in Python is given below:

Syntax using the flag:

flagName = False while not flagName: if [Do check here]: flagName = True else: print('error message')

The status of the flag is set to false initially, and the same condition is considered for a while loop to make the statement while not true, and the validation is performed setting the flag to true if the validation condition is satisfied; otherwise, the error message is printed.

Syntax using an exception:

while True: try: [run code that might fail here] break except: print('This is the error message if the code fails') print('run the code from here if code is successfully run in the try block of code above')

print(‘run the code from here if code is successfully run in the try block of code above)

We set the condition to be true initially and perform the necessary validation by running a block of code, and if the code fails to perform the validation, an exception is raised displaying the error message and a success message is printed if the try block successfully executes the code.

Examples of Python Validation

Examples of python validation are:

Example #1

Python program using a flag to validate if the input given by the user is an integer.#Datatype check.

#Declare a variable validInt which is also considered as flag and set it to false validInt = False #Consider the while condition to be true and prompt the user to enter the input while not validInt: #The user is prompted to enter the input age1 = input('Please enter your age ') #The input entered by the user is checked to see if it’s a digit or a number if age1.isdigit(): #The flag is set to true if the if condition is true validInt = True else: print('The input is not a valid number') #This statement is printed if the input entered by the user is a number print('The entered input is a number and that is ' + str(age1))

Output:

Example #2

Python program uses flag and exception to validate the type of input given by the user and determine if it lies within a given range. #Range Check.

Code:

#Declare a variable areTeenager which is also considered as flag and set it to false areTeenager = False #Consider the while condition to be true and prompt the user to enter the input while not areTeenager: try: #The user is prompted to enter the input age1 = int(input('Please enter your age ')) #The input entered by the user is checked if it lies between the range specified except: print('The age entered by you is not a valid number between 13 and 19') #This statement is printed if the input entered by the user lies between the range of the number specified print('You are a teenager whose age lies between 13 and 19 and the entered age is ' + str(age1))

Output:

Example #3

Python program using the flag to check the length of the input string. #Length Check.

Code:

#Declare a variable lenstring which is also considered as flag and set it to false lenstring = False #Consider the while condition to be true and prompt the user to enter the input while not lenstring: password1 = input('Please enter a password consisting of five characters ') #The input entered by the user is checked for its length and if it is below five lenstring = True else: print('The number of characters in the entered password is less than five characters') #This statement is printed if the input entered by the user consists of less than five characters print('The entered password is: ' + password1)

Output:

Benefits

Validation in python helps to improve the security of code.

It prevents third-party users from mishandling the code accidentally or intentionally.

It can be used to check if the input data type is correct or not.

It can be used to check if there are no invalid values in the given input.

It can be used to check if the given input lies in the range or is it out of range.

It can be used to check if the given input meets the constraints specified on them.

It can be used to check if the given input is consistent or not.

It can be used to check if the given input is valid.

It can be used to check if the given input is complete or incomplete.

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Working Of Sleep() Function In Python (Examples)

Introduction to Python Sleep Function

In this article, we will see one of the most used functions that are provided by the time module in Python is the sleep() function. The sleep() function of the time module is used to suspend or halt the current code or thread’s execution for the given number of times in seconds. The sleep() function which takes an argument as time in the number of seconds, which can be specified in floating-point for accuracy. This sleep() function is used in applications like dramatic string printing, and this is also used in the multithreading process.

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Working of sleep() Function in Python

In this section, we will see the Python time method sleep(). The sleep() function suspends the code or thread execution for the specified number of times in seconds in a floating-point number, which can be used to specify the accurate sleep time to the argument. Let us syntax and examples of this function in the below sections.

Syntax:

time.sleep(ts)

Parameters:

ts: This parameter is used to specify the time that execution should be suspended in seconds.

sleep(): It will return nothing as it is just used to suspend the function or code or thread for the specified time in seconds.

Examples to Implement sleep() Function in Python

Below are the examples of sleep() Function in Python:

Example #1

Code:

import time print("Simple program to demonstrate sleep function:") print("The Start time is as follows : ") print(time.ctime()) time.sleep( 5 ) print("The End time is as follows:" ) print(time.ctime())

Output:

Explanation: In the above program, we can see that firstly we need to import the time module to used the sleep() function as it is the function of a time module in Python. We can see the first start time is displayed using the ctime() function of the time module, which is displays the current time. Then we saw the end time to display using the sleep() function to stop the execution and then display the current time when the function is stopped executing the thread using the sleep() function.

Example #2

A dramatic way of printing the given message or String.

Code:

import time print("Program to demonstrate sleep() function used for printing words letter by letter:") strn = "Educba" print("The given word is as follows:") print(strn) for i in range(0, len(strn)): print(strn[i], end ="") time.sleep(0.3)

Output:

Explanation: In the above program, we saw that we have a string defined in this program as “Educba”, so we are trying to print the word letter by letter by using the sleep() function. In this, we have the time specified as 0.3 seconds. This means after every 0.3 seconds, each letter is printed using for loop, having the start range as 0 index of the length of the given string up to the end of the length of the given string and sleep function. To see the visual effect, we have to execute the above program in the local Python editor.

Example #3

Code:

import time from threading import Thread class Worker(Thread): def run(self): for x in range(0, 12): print(x) time.sleep(1) class Waiter(Thread): def run(self): for x in range(100, 103): print(x) time.sleep(5) print("Starting Worker Thread will start from :") Worker().start() print("Starting Waiter Thread will stop at:") Waiter().start() print("Done")

Output:

Conclusion

In this article, we conclude that we have seen the syntax and working of Python’s sleep() function with examples. In this article, we saw from which module this sleep() function can be defined. Therefore we saw we need to import a time module that provides various methods, and the sleep() function is the most popular method of time module in Python. In this article, we saw a simple example of demonstrating the sleep() function with the number of seconds specified as an argument. Lastly, we saw the sleep() function applications, which are used in dramatic printing and in multi-threading.

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Types And Levels Of Conflict

We are all accustomed to disagreements. They are a part of our everyday lives. They are built into human interactions. Nevertheless, this does not imply that every social interaction is always entirely or even partially problematic. It also does not imply that every underlying antagonistic relationship would be exhibited with the same level of animosity or violence. Disputes are a part of the totality of social existence; their area is as extensive and varied as life itself.

To fully comprehend the complexities of various forms and levels of conflict, we must draw on viewpoints from various disciplines, including Anthropology, Sociology, History, Political Science, International Relations, and Psychoanalysis. This will provide us with an interdisciplinary perspective on conflicts.

Types and Levels of Conflict

Scholars need to agree on the types and intensities of conflict. Many researchers have identified various sorts of conflict. Social conflicts, intercommunity conflicts, caste conflicts, group conflicts, interpersonal conflicts, intellectual conflicts, economic conflicts, cultural conflicts, religious conflicts, racial or ethnic conflicts, ideological conflicts, hot and cold conflicts, north and south conflicts, regional conflicts, international or intra-national conflicts, and so on are all possible.

According to Dennis Sandole, a typology promotes analysis, and a typology of conflicts could aid in conflict resolution and analysis. Furthermore, studying several conflict typologies may reveal interconnected insights into a given conflict situation. Such insights allow an analyst and prospective third-party intervener to view a problem from multiple perspectives, increasing the possibility of a more effective reaction.

Quincy Wright’s Classification

Quincy Wright was one of the first political scientists to study conflicts and war comprehensively. Conflict can occur between various types of entities, according to him. Physical conflict, political conflict, intellectual conflict, and legal conflict are his four forms of conflict. He contrasts physical conflict, which occurs when two or more things attempt to occupy the same place simultaneously, with political conflict, which occurs when a group attempts to force its policy on others. He further divides these two types of conflict from ideological conflicts, in which opposing systems of thinking or values clash, and legal disputes, in which controversies over claims or demands are resolved through mutually agreed-upon procedures.

He also sees war as the fifth type of conflict. For him, the war in the legal sense has been defined by the combination of all four categories of conflict mentioned above. The physical struggle of armies to occupy the same space, each seeking to annihilate, disarm, or capture the other; the political struggle of nations to achieve policies against the resistance of others; the ideological struggle of people to preserve or extend ways of life and value systems; and the legal struggle of states to acquire titles, vindicate claims, prevent violence, or punish offenses through recognized procedures of regulation are all manifestations of war.

Anatol Rapoport’s Classification

Anatol Rapoport proposed categorizing confrontations into three types: battles, games, and arguments. Their distinguishing factors include the opponent’s perception, the parties’ intent, and the rational content of the circumstance. The opponent is considered a nuisance in a battle, the objective is to injure him, and the situation is devoid of logic. In a game, the opponent is considered an extension of oneself, the goal is to outwit him, and the scenario is entirely rational. Furthermore, in a dispute, the opponent is seen as essential, but differently, the goal is to persuade him, and the situation is considered rational. Rapoport’s three conflict dynamics models can be expanded upon. He identifies three types of conflicts using the four criteria listed below.

Second, the picture of the opponent (kept by each party) differs: in conflicts, the image maintained by each party is primarily a nuisance; ideally, the opponent should vanish or, at the very least, be decreased in size or importance. In games, each party’s vision of the opponent is that of an essential partner, regarded as a mirror image of the self; preferably, a strong opponent who will do everything in his power to win; and a logical entity whose inner thought processes must be considered.

In discussions, each party’s image of the opponent needs to be corrected or misinformed; ideally, the opponent should become a convert to one’s point of view. Finally, the goals of each party differ in the three types of disputes. In fights, each party’s goal is to hurt, destroy, subdue, or drive away the opponent; in games, it is to outwit the opponent; and in arguments, it is to persuade the opponent.

Fourth, the style of interaction varies across all three types. The form of engagement in fights is a non-rational series of acts and reactions to the other’s and one’s actions; use of thrusts, threats, violence, and so on; and the course of interaction is not dependent on the opponent’s goals. In games, the parties cooperate by adhering to the rules and doing their best to give the greatest challenge to the opponent; actions (stratagems) are chosen based on likely outcomes, and the interaction ends when the outcome is evident to both sides.

In debates, the sides engage in verbal interaction of arguments utilizing various persuasion strategies such as brainwashing, explaining away the opponent’s beliefs, and reducing threats connected with adopting one’s outlook in the opponent’s mind.

Singer’s Classification

Singer’s conflict typology is based on conflict parties’ political status. He maintains his original distinction between (a) interstate wars and (b) extra-systemic (primarily colonial) wars but adds two new categories of non-interstate conflict: (c) ‘civil’ conflicts, in which, unlike (b) one protagonist may be ‘an insurgent or revolutionary group within the recognized territorial boundaries of the state,’ and (d) ‘increasingly complex intrastate wars’ in former colonial states,

Holsti’s Classification

K. J. Holsti also modified this typology in his 1996 book, The State, War, and the State of War. Before 1989, he classified international (interstate) conflict into twenty-four concerns, divided into five composite sets: conflict over territory, economics, nation-state formation, ideology, and ‘human sympathy’ (i.e., ethnicity/religion). He found that the incidence of the first two was decreasing while the incidence of the last three was growing. Later, he focuses on non-interstate war and bases his typology on ‘types of actors and objectives,’ resulting in four conflict categories −

Normal state versus wars (e.g., China and India in 1962) and armed interventions involving significant loss of life (the US in Vietnam, the Soviet Union in Afghanistan)

National liberation decolonizing wars

Internal wars based on ideological goals (e.g., Sendero Luminoso in Peru, Montenegro in Uruguay)

State-nation wars including armed resistance by ethnic, language, and religious groups, often with the goal of secession or separation from the state (e.g., Tamils in Sri Lanka, Ibos in Nigeria)

Kenneth Boulding’s Classification

Kenneth Boulding (1962) classifies social conflicts into eight types −

Disputes between or among individuals

Conflicts between groups (spatially separated groups)

The ecological conflict between groups

Homogeneous organizational conflict (i.e., a conflict between organizations of similar type and aim, such as state vs. state, sect vs. sect, union vs. union, and so on)

Heterogeneous organization conflict (i.e., between unlike organizations, such as state vs. church, union vs. corporation, university vs. church/state, etc.)

Conflicts between a person and a group (mainly socialization conflicts, as in child vs. Family, person vs. peer group, person vs. hierarchical superiors or inferiors, etc.)

The conflict between a person and an organization (mainly role conflicts)

Conflicts between a group and an organization

Conclusion

Disputes serve a variety of functions. Not all conflicts are harmful and destructive. Philosophers such as Hegel and Marx viewed the conflict as a vital tool for change and progress. There are as many typologies as analysts, and the criteria used differ and are frequently incompatible. A list of some labels used in well-known analyses from the 1990s quickly approaches a hundred. Some differentiate by conflict parties, others by conflict problems, but the majority by hybrid lists that appear to mix numerous categories. Some have two types, while others have more than twenty. This unit provides an overview of various conflict kinds and levels.

Random Walk In Python (1D, 2D, And 3D With Examples)

In mathematics, random walk is the process in which objects randomly wander away from where they started.

Here is a video that shows how a particle collides with other particles in two dimensions. The path of the yellow particle is described by random walk:

Random walk is easy to visualize using Python. Here are illustrations of random walks in 1D, 2D, and 3D:

1D Random Walk

2D Random Walk

3D Random Walk

Today you learn how to plot these three graphs by implementing the random walk algorithm in Python.

Why Is Random Walk Useful

Randomness is always present in nature.

When you drop a droplet of the colorant into a glass of water it mixes up automatically without you stirring it.

But how and why does this happen?

Water molecules in the glass vibrate rapidly on a microscopic level. When the colorant molecules collide with the rapidly vibrating water molecules, they bump around in random directions. This eventually mixes the water and the colorant and makes it an evenly colored mix.

If you take one colorant molecule under inspection, you can see its path is completely random. This is because it collides with the water molecules that are vibrating in random directions. If you want to simulate a colorant molecule in a glass of water, you would do it with a random walk.

The random walk algorithm is useful as it can be used to simulate common phenomena of nature.

How to Implement Random Walk in Python

The random walk can be easily implemented in Python. A great starting point is to start with the 1D random walk.

To make the one-dimensional random walk work:

Initialize an object at position y.

Randomly move the object up or down. In other words, add or subtract 1 from the y value.

Keep track of all the positions of the object, that is, the y values.

Then, to implement 2D and 3D random walks, expand this idea into 2 and 3 dimensions.

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Prerequisites

The random walk algorithm itself can be implemented natively in Python. But you need to use a library to visualize the results plus some utilities for generating lists of numbers.

In this guide, you are going to use these two external packages:

NumPy for generating lists of numbers.

Matplotlib for plotting the results of each random walk.

To work with these packages, you need to have them installed on your machine. You can install these with Pip by running the following command in your command line window:

pip install numpy pip instal matplotlib

Now you are all set. Let’s get started with the random walks.

1D Random Walk

The most basic random walk is the 1D random walk. In this form of random walk, the moving object is restricted to moving in one dimension only. In our case, up and down.

The idea is that the object takes a step up or down randomly n times and stores the position values into a list.

Because the movement of the object is one-dimensional, the graph that illustrates the path is a line of some height. This is not useful, because it is impossible to tell where the object was at each step. To make the graph more informative, we are going to assign a timestamp for each step. This makes it a 2D graph with the object’s position on the y-axis and the timestamp on the x-axis.

import numpy as np import matplotlib.pyplot as plt import random def randomwalk1D(n): x, y = 0, 0 # Generate the time points [1, 2, 3, ... , n] timepoints = np.arange(n + 1) positions = [y] directions = ["UP", "DOWN"] for i in range(1, n + 1): # Randomly select either UP or DOWN step = random.choice(directions) # Move the object up or down if step == "UP": y += 1 elif step == "DOWN": y -= 1 # Keep track of the positions positions.append(y) return timepoints, positions

Now you can create a random walk and plot the timepoints as the x-axis and the position of the object as y-axis:

time_data, pos_data = randomwalk1D(1000) plt.plot(time_data, pos_data, 'r-') plt.title("1D Random Walk in Python") plt.show()

Output:

The object moves up or down randomly in a 1D random walk.

To make a comparison, you can plot multiple results of 1D random walks into the same graph:

rw1 = randomwalk1D(1000) rw2 = randomwalk1D(1000) rw3 = randomwalk1D(1000) plt.plot(rw1[0], rw1[1], 'r-', label="rw1") plt.plot(rw2[0], rw2[1], 'g-', label="rw2") plt.plot(rw3[0], rw3[1], 'b-', label="rw3") plt.show()

Output:

Multiple 1D random walks produce different graphs because each walk is random.

Full Code import numpy as np import matplotlib.pyplot as plt import random def randomwalk1D(n): x, y = 0, 0 # Generate the time points [1, 2, 3, ... , n] timepoints = np.arange(n + 1) positions = [y] directions = ["UP", "DOWN"] for i in range(1, n + 1): # Randomly select either UP or DOWN step = random.choice(directions) # Move the object up or down if step == "UP": y += 1 elif step == "DOWN": y -= 1 # Keep track of the positions positions.append(y) return timepoints, positions rw1 = randomwalk1D(1000) rw2 = randomwalk1D(1000) rw3 = randomwalk1D(1000) plt.plot(rw1[0], rw1[1], 'r-', label="rw1") plt.plot(rw2[0], rw2[1], 'g-', label="rw2") plt.plot(rw3[0], rw3[1], 'b-', label="rw3") plt.show()

Now that you know how to implement the random walk algorithm in 1 dimension, let’s move on to higher dimensions.

2D Random Walk

The idea behind the random walk in 2D is the exact same as in one dimension. Now the movement of the object is no longer restricted to up/down. Instead, it can move to the left or right too.

In the 2D case, you are not plotting against time anymore. Instead, it is possible to visualize the walk by plotting the x, and y coordinate pairs into the graph. This draws the 2D path the object took with n steps.

Here is how the algorithm looks in the code:

import numpy as np import matplotlib.pyplot as plt import random def randomwalk2D(n): # [0, 0, 0, ... ,0] x = np.zeros(n) y = np.zeros(n) directions = ["UP", "DOWN", "LEFT", "RIGHT"] for i in range(1, n): # Pick a direction at random step = random.choice(directions) # Move the object according to the direction if step == "RIGHT": x[i] = x[i - 1] + 1 y[i] = y[i - 1] elif step == "LEFT": x[i] = x[i - 1] - 1 y[i] = y[i - 1] elif step == "UP": x[i] = x[i - 1] y[i] = y[i - 1] + 1 elif step == "DOWN": x[i] = x[i - 1] y[i] = y[i - 1] - 1 # Return all the x and y positions of the object return x, y

Here is an example run of a 2D random walk with 1000 steps.

x_data, y_data = randomwalk2D(1000) plt.title("2D Random Walk in Python") plt.plot(x_data, y_data) plt.show()

Here is a path that the above code produces:

2D Random walk with 1000 steps.

Full Code import numpy as np import matplotlib.pyplot as plt import random def randomwalk2D(n): # [0, 0, 0, ... ,0] x = np.zeros(n) y = np.zeros(n) directions = ["UP", "DOWN", "LEFT", "RIGHT"] for i in range(1, n): # Pick a direction at random step = random.choice(directions) # Move the object according to the direction if step == "RIGHT": x[i] = x[i - 1] + 1 y[i] = y[i - 1] elif step == "LEFT": x[i] = x[i - 1] - 1 y[i] = y[i - 1] elif step == "UP": x[i] = x[i - 1] y[i] = y[i - 1] + 1 elif step == "DOWN": x[i] = x[i - 1] y[i] = y[i - 1] - 1 # Return all the x and y positions of the object return x, y x_data, y_data = randomwalk2D(1000) plt.title("2D Random Walk in Python") plt.plot(x_data, y_data) plt.show() 3D Random Walk

Now that you have the 1D and 2D random walks working, let’s finally implement the 3D one.

The idea is exactly the same as in 2D, but now you can move up/down, left/right, and also inward/outward.

Here is how the algorithm looks in the code:

import matplotlib.pyplot as plt import numpy as np import random def randomwalk3D(n): x, y, z = np.zeros(n), np.zeros(n), np.zeros(n) directions = ["UP", "DOWN", "LEFT", "RIGHT", "IN", "OUT"] for i in range(1, n): step = random.choice(directions) if step == "RIGHT": x[i] = x[i - 1] + 1 y[i] = y[i - 1] z[i] = z[i - 1] elif step == "LEFT": x[i] = x[i - 1] - 1 y[i] = y[i - 1] z[i] = z[i - 1] elif step == "UP": x[i] = x[i - 1] y[i] = y[i - 1] + 1 z[i] = z[i - 1] elif step == "DOWN": x[i] = x[i - 1] y[i] = y[i - 1] - 1 z[i] = z[i - 1] elif step == "IN": x[i] = x[i - 1] y[i] = y[i - 1] z[i] = z[i - 1] - 1 elif step == "OUT": x[i] = x[i - 1] y[i] = y[i - 1] z[i] = z[i - 1] + 1 return x, y, z

And here is an example of a 3D random walk with 1000 steps plotted in a 3D interactive graph:

x_data, y_data, z_data = randomwalk3D(1000) ax = plt.subplot(1, 1, 1, projection='3d') ax.plot(x_data, y_data, z_data, alpha=0.9) ax.scatter(x_data[-1], y_data[-1], z_data[-1]) plt.show()

Output:

A 3D random walk in Python with 1000 steps.

If you run this code on your machine, you can freely rotate the resulting graph to inspect it in other directions.

Full Code import matplotlib.pyplot as plt import numpy as np import random def randomwalk3D(n): x, y, z = np.zeros(n), np.zeros(n), np.zeros(n) directions = ["UP", "DOWN", "LEFT", "RIGHT", "IN", "OUT"] for i in range(1, n): step = random.choice(directions) if step == "RIGHT": x[i] = x[i - 1] + 1 y[i] = y[i - 1] z[i] = z[i - 1] elif step == "LEFT": x[i] = x[i - 1] - 1 y[i] = y[i - 1] z[i] = z[i - 1] elif step == "UP": x[i] = x[i - 1] y[i] = y[i - 1] + 1 z[i] = z[i - 1] elif step == "DOWN": x[i] = x[i - 1] y[i] = y[i - 1] - 1 z[i] = z[i - 1] elif step == "IN": x[i] = x[i - 1] y[i] = y[i - 1] z[i] = z[i - 1] - 1 elif step == "OUT": x[i] = x[i - 1] y[i] = y[i - 1] z[i] = z[i - 1] + 1 return x, y, z x_data, y_data, z_data = randomwalk3D(1000) ax = plt.subplot(1, 1, 1, projection='3d') ax.plot(x_data, y_data, z_data, alpha=0.9) ax.scatter(x_data[-1], y_data[-1], z_data[-1]) plt.show() Conclusion

Today you learned how to implement random walk in Python in 1D, 2D, and 3D.

To recap, a random walk is a process where an object starts wandering by taking steps in random directions. This process is present in nature in many ways.

To implement a random walk algorithm in Python, initialize an object at a starting point and start moving it around in random directions n times.

To then visualize random walks with Python, store each location into a list and plot the locations.

With a 1D random walk, you plot the 1D locations with respect to time to better visualize the 1D path.

With 2D and 3D random walks, you plot all the (x, y) or (x, y, z) pairs into the graph to get the path of the object.

Thanks for reading.

Happy coding!

Further Reading

50 Python Interview Questions

Key Concept And Types Of Selenium Testing

What is Selenium Testing?

Web development, programming languages, Software testing & others

This open-source automated testing suite is quite like the HPE Unified Functional Testing software (UFT), but its knack of focusing on automating web-based applications makes it distinctive. Selenium Testing enables automating tests for web applications across diversified platforms as well as browsers. This type of testing is well-versed with a curated set of software, which can be used to quench various needs of an organization with respect to testing. It can boost the business growth of an organization and give it a secured online environment in the long run.

Selenium Testing consists of four key components as follows:

Integrated Development Environment (IDE): It is a Firefox extension mechanism, which is used to effectively automate the browser with its in-built feature of record-and-playback.

Remote Control (RC): It is a server that helps in ‘tricking’ the browser to believe that the web application and Selenium Core, which are being tested, actually belong to a similar domain by acting as an HTTP proxy.

WebDriver: It was first of all the cross-platform testing frameworks, which was an easy-to-use component helping control the browser from the OS level.

Selenium Grid: This mechanism has a remarkable capability of capturing screenshots of the browser at significant stages. It also has the ability to simultaneously rolling out Selenium commands to various machines.

Selenium Testing

A curated set of various software tools, each striving with a distinct approach of assisting test automation, is known as Selenium Testing. This comprehensive suite of tools showcases the capabilities to satisfy the needs of testing of all types of web applications. Selenium Testing perfectly resembles flexibility. It plays a pivotal role in comparing expected test results against the actual behavior of an application. It allows various options in order to locate UI elements. In short, Selenium Testing is an important support system for the execution of tests on multiple browser platforms.

Understanding Selenium Testing

Most of the QA Engineers focus on limited tools which meet the needs of the project. However, gaining expertise about all the tools would put forth various options for approaching and solving diversified problems related to test automation. There are numerous ways by which functionality can be added to both, Selenium test scripts as well as Selenium’s framework. This enables high-end customization of your automation tests. As such, this is one of the greatest strengths of Selenium Testing as compared to other tools used for automation tests. Also, being open-source enables its users to download and modify it in an easy and sustainable manner.

What Type of Testing can be done Using Selenium?

As a suite of open-source software automation tools that include – Selenium IDE, Selenium RC, WebDriver, and Grid, it provides a plethora of solutions related to the testing of software applications. Before discussing the different types of testing procedures, this post highlights a few of the key features that have promoted Selenium testing a preferred choice of testers and developers across the globe.

Quick access to reports

Supports Agile methodology

Simplifies the documentation process

1. Functional testing: It is designed to test every function that lies within the scope of testing in the application and ensures that it works as per the requirement document.

2. Regression testing: Regression testing includes two distinctive components – firstly, it ensures that if new functionality is added to an existing application, the new feature doesn’t disturb the normal functionality. Secondly, when known bugs are fixed, this testing checks that the fixing hasn’t disturbed the other functionalities that were working earlier.

3. UI (black box) testing: Also referred to as black-box testing, where the application is tested only as per the requirement document, and if any issues are bugs come up, they are reported accordingly.

How is Selenium Testing Performed?

Now let’s see the basic elements of this testing process.

There are seven basic steps while creating a selenium test script that complies with every test case and application.

Creating a WebDriver instance

Web page navigation

Finding the HTML element on the web page

Performing action on the HTML element

Evaluating the browser’s response

Running and recording the tests

Conclude

Conclusion

Since testing is one of the most critical components that define the success or failure of any project, selecting the best according to the needs is also a major task. Analyzing today’s competitive IT business environment, selenium testing is undoubtedly one of the best choices for performing automation testing. Easy-to-use functionality and a regular rise in demand is making it popular among testers, developers, and IT organizations. Alongside using it for the testing of the GUI and the functionality of the web-based applications, it is widely used as a unit testing kit for JavaScript.

The fact that it supports multiple browsers like Safari, Mozilla, IE, Chrome, Firefox and can execute multiple tests at a single time makes it an ideal choice for the testers. While comparing with other automation tools, selenium gives multiple options to add functionality to test scripts along with the framework. By minimizing the frequency of manual testing along with finding the bugs that are missed by the manual testing procedure, selenium testing has proved to be a clear winner in the testing arena.

Recommended Articles

This has been a guide to Selenium Testing. Here we discuss the introduction, types of selenium testing and how it is performed. You may also look at the following articles to learn more –

Different Types Of Pollution And Its Effects

About Pollution

The introduction of toxic wastes into the environment is pollution. These toxic wastes are called pollutants. The pollutants are capable of damaging the quality of air, water, and land. Contamination can occur naturally through volcanic dust, sea salt particles, photochemically formed ozone, etc., and by humans.

Valuation, Hadoop, Excel, Mobile Apps, Web Development & many more.

There are mainly three types of pollution. These are Air, Water, and Land pollution.

Air pollution

It can be both apparent and non-apparent.

The effect of pollution can be slower, yet it has the power to impact living things immediately. One such example is the Bhopal gas tragedy.

A natural disaster can also cause air pollution. Gases emitted from a volcano, such as sulfur dioxide, can kill people nearby and leave the soil unfit for a long time.

When nitrogen oxide and sulfur dioxide mix with moisture, they turn into acid and fall back as acid rain. The pale texture of the Taj Mahal in Agra, which once used to be white, results from acid rain.

The World Health Organization(WHO) has issued air quality guidelines to reduce pollutions level in all countries.

Water pollution

Water contamination, while mostly visible, is also invisible and contains dangerous odorless pollutants, just like air pollution.

As per the estimates of the United Nations, 4,000 children die daily from dirty water.

Organisms can also get sick through water pollution indirectly by eating contaminated fish.

The pollutants released by factories into the waterways and the fertilizers used in farms can make a fertile environment for cyanobacteria to grow. It is also called blue-green algae. These cyanobacteria reproduce rapidly and prevent other aquatic organisms, including plants and fish, from surviving in the ocean.

The heat generated through power plants can often pollute the water since aquatic organisms are sensitive to temperature changes.

Land pollution

These days, humans are being affected by pesticides and fertilizers in their food. It can result in cancer and other harmful diseases.

Garbage, like paper, plastic products, junked cars, etc., is also a harmful pollutant that consists of oils, chemicals, and inks.

There is even a shortage of land to dump this garbage. Heavy rains caused a trash landslide in Quezon City, Philippines, killing 218 people.

The earth’s vegetation, herbivores, and predators that depend on each other for food may be contaminated. This process, where a chemical builds up at each food web level, is called bioaccumulation.

Although trash incinerators can aid in the reduction of land pollution, they can make air pollution even worse.

Reduction

The government and people are promoting the 3 R’s, i.e., Reduce, Reuse, and Recycle.

Governments worldwide have been passing specific laws to limit and reduce the number of chemical factories.

International agreements can also help in the reduction of pollution. For example, 191 countries signed the United Nation’s Kyoto Protocol to limit the emission of greenhouse gasses.

Reducing pollutions require the collective effort of political, economic, and environmental leadership.

Both developed and developing countries should work together to strengthen their economies without harming the environment.

Fact

The excessive amount of light in the night sky is known as “light pollution.” Urban areas are generally the source of light pollution. It can harm the ecosystem because it makes it harder to distinguish between night and day.

People must reduce their energy usage at night so the ecosystem can function more naturally. It helps nocturnal and diurnal animals distinguish between day and night easily.

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