 import random
import string

class RobloxAccountGenerator:
    """
    Class to generate random Roblox account usernames and check their availability.

    Attributes:
    - username_length: int
        The length of the generated username.
    """

    def __init__(self, username_length: int = 5):
        """
        Constructor to instantiate the RobloxAccountGenerator class.

        Parameters:
        - username_length: int (optional)
            The length of the generated username. Default is 5.
        """

        self.username_length = username_length

    def generate_username(self):
        """
        Generates a random Roblox account username.

        Returns:
        - str:
            The generated username.
        """

        # Generating a random username using lowercase letters and digits
        username = ''.join(random.choices(string.ascii_lowercase + string.digits, k=self.username_length))

        return username

    def check_username_availability(self, username: str):
        """
        Checks the availability of a given Roblox account username.

        Parameters:
        - username: str
            The username to check availability for.

        Returns:
        - bool:
            True if the username is available, False otherwise.
        """

        # Simulating the availability check by randomly returning True or False
        return random.choice([True, False])

# Example usage of the RobloxAccountGenerator class:

# Creating an instance of the RobloxAccountGenerator class
generator = RobloxAccountGenerator()

# Generating a random username
username = generator.generate_username()
print(f"Generated username: {username}")

# Checking the availability of the generated username
is_available = generator.check_username_availability(username)
print(f"Username availability: {is_available}")

created 1 year ago

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import sys
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print("Hello "+ name)

About Python

Python is a very popular general-purpose programming language which was created by Guido van Rossum, and released in 1991. It is very popular for web development and you can build almost anything like mobile apps, web apps, tools, data analytics, machine learning etc. It is designed to be simple and easy like english language. It's is highly productive and efficient making it a very popular language.

Tutorial & Syntax help

Loops

1. If-Else:

When ever you want to perform a set of operations based on a condition IF-ELSE is used.

if conditional-expression
    #code
elif conditional-expression
    #code
else:
    #code

Note:

Indentation is very important in Python, make sure the indentation is followed correctly

2. For:

For loop is used to iterate over arrays(list, tuple, set, dictionary) or strings.

Example:

mylist=("Iphone","Pixel","Samsung")
for i in mylist:
    print(i)

3. While:

While is also used to iterate a set of statements based on a condition. Usually while is preferred when number of iterations are not known in advance.

while condition  
    #code

Collections

There are four types of collections in Python.

1. List:

List is a collection which is ordered and can be changed. Lists are specified in square brackets.

Example:

mylist=["iPhone","Pixel","Samsung"]
print(mylist)

2. Tuple:

Tuple is a collection which is ordered and can not be changed. Tuples are specified in round brackets.

Example:

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)

Below throws an error if you assign another value to tuple again.

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
myTuple[1]="onePlus"
print(myTuple)

3. Set:

Set is a collection which is unordered and unindexed. Sets are specified in curly brackets.

Example:

myset = {"iPhone","Pixel","Samsung"}
print(myset)

4. Dictionary:

Dictionary is a collection of key value pairs which is unordered, can be changed, and indexed. They are written in curly brackets with key - value pairs.

Example:

mydict = {
    "brand" :"iPhone",
    "model": "iPhone 11"
}
print(mydict)

Supported Libraries

Following are the libraries supported by OneCompiler's Python compiler

Name	Description
NumPy	NumPy python library helps users to work on arrays with ease
SciPy	SciPy is a scientific computation library which depends on NumPy for convenient and fast N-dimensional array manipulation
SKLearn/Scikit-learn	Scikit-learn or Scikit-learn is the most useful library for machine learning in Python
Pandas	Pandas is the most efficient Python library for data manipulation and analysis
DOcplex	DOcplex is IBM Decision Optimization CPLEX Modeling for Python, is a library composed of Mathematical Programming Modeling and Constraint Programming Modeling