Here's a sample code in Python that turns Linux terminal code from the clipboard into beautified HTML with a black background. The script makes use of the pygments module to syntax highlight the text and clipboard module to get the text from the clipboard.

Python:

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import pygments
import pygments.lexers
import pygments.formatters
import clipboard

# Get text from clipboard
text = clipboard.paste()

# Set the lexer and formatter for the code highlight
lexer = pygments.lexers.TerminalLexer()
formatter = pygments.formatters.HtmlFormatter(style='monokai', full=True)

# Add a black background to the HTML output
formatter.style.background_color = "#000000"

# Highlight the text and create the HTML file
highlighted_text = pygments.highlight(text, lexer, formatter)

# Save the HTML file
with open('beautified.html', 'w') as f:
    f.write(highlighted_text)

To run this script on Wayland, you will need to have the wl-clipboard package installed, which provides clipboard integration for Wayland. You can install it using the command sudo apt-get install wl-clipboard. After installing wl-clipboard, you can replace the clipboard module with the wlclipboard module in the code, as shown below:

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import pygments
import pygments.lexers
import pygments.formatters
import wlclipboard

# Get text from clipboard
text = wlclipboard.get_text()

# Set the lexer and formatter for the code highlight
lexer = pygments.lexers.TerminalLexer()
formatter = pygments.formatters.HtmlFormatter(style='monokai', full=True)

# Add a black background to the HTML output
formatter.style.background_color = "#000000"

# Highlight the text and create the HTML file
highlighted_text = pygments.highlight(text, lexer, formatter)

# Save the HTML file
with open('beautified.html', 'w') as f:
    f.write(highlighted_text)

Note: This code is just a sample and might need to be adapted for your specific use-case.

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def format_text(text):
    if len(text) < 11:
        return "Input text must be at least 11 characters long."

    formatted_text = []
    for i, char in enumerate(text):
        formatted_text.append(char)
        if i in [3, 5, 7, 10]:  # add dash after 4th, 6th, 8th, and 11th digits (0-indexed)
            formatted_text.append('-')

    return ''.join(formatted_text)

# Example usage:
input_text = "12345678901"
output_text = format_text(input_text)
print(output_text)  # Output will be: "1234-56-78-901"

You can round up a float number in Python using the math.ceil() function. This function will round a number up to the nearest integer.

Here’s an example:

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import math

number = 3.14
rounded_number = math.ceil(number)

print(rounded_number)  # Output: 4

In this example, math.ceil(3.14) will round it up to 4. You can use any float number with this function! For more details, you can check the official documentation here: https://docs.python.org/3/library/math.html#math.ceil

In Python, def is a keyword used to define a function. A function is a reusable block of code that can perform a specific task. Here's a simple example:

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def greet(name):
    return f"Hello, {name}!"

In this example, greet is the name of the function, and it takes one parameter, name. When you call greet("Alice"), it will return the string "Hello, Alice!". Functions help organize code and can be called multiple times with different arguments.

In Python, you can add comments by using the # symbol. Anything following the # on that line will be treated as a comment and will not be executed by the program.

Here's an example:

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# This is a single-line comment
print("Hello, World!")  # This prints a message

For multi-line comments, you can use triple quotes (''' or """):

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"""
This is a
multi-line comment
"""
print("Hello again!")

You can read more about comments in Python in the official Python documentation.

SheCodes Athena AI only answers technical questions.

To print a CSV dictionary in Python line by line in a sentence, you can use the csv module to read the CSV file and then iterate over the dictionary values. Here's an example code snippet:

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import csv

# Open the CSV file
with open('your_file.csv') as file:
    # Create a CSV reader object
    reader = csv.DictReader(file)

    # Iterate over each row in the CSV file
    for row in reader:
        # Print each row's values in a sentence
        print(f"Name: {row['Name']}, Age: {row['Age']}, Email: {row['Email']}")

In this code, replace 'your_file.csv' with the path to your actual CSV file. Make sure your CSV file has a header row, so that each column can be accessed by a key in the dictionary. You can specify the appropriate column names in the print statement to access the values from the dictionary.

Note that the csv.DictReader class allows us to work with the CSV data as a dictionary, where the keys are the column names and the values are the corresponding row values.

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word = input("Enter a word: ")
count = 0

for char in word:
    if char == "z":
        count += 1

print("The word contains", count, "lowercase z's.")

Python:

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word = input("Enter a word: ")
new_word = word.replace('a', '@').replace('o', '0')
print(new_word)

Python

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text = input("Enter some text: ")

if text.islower():
    print(True)
else:
    print(False)

The pow() function in Python is used to calculate the exponential value of a number. It takes in two arguments: the base number and the exponent. Here is an example:

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result = pow(2, 3)
print(result)

Output: 8

In this example, the pow() function calculates 2 to the power of 3, which is 8. So, result will store the value 8.

In Python, you can convert a string to an integer using the int() function. This function takes a string as input and returns the equivalent integer value. Here's an example:

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num_str = "123"
num_int = int(num_str)
print(num_int)  # Output: 123

In this example, the string "123" is converted to the integer 123 using the int() function.

The % symbol in Python is called the modulo operator. It is used to find the remainder when one number is divided by another.

Example:

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a = 10
b = 3
result = a % b
print(result) # Output: 1

In the example above, 10 is divided by 3 and the remainder is 1. The modulo operator % is used to obtain that remainder.

The == operator in Python is used to check if two values are equal. It returns True if the values are equal and False otherwise.

Here is an example:

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x = 5
y = 10
z = 5

print(x == y)  # False
print(x == z)  # True

In the above code, x == y evaluates to False because x and y have different values. On the other hand, x == z evaluates to True because x and z have the same value.

Sure! Here's an example of Flask code that allows an admin account special privileges:

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from flask import Flask, request

app = Flask(__name__)

def is_admin(username):
    # Check if the username is an admin
    admins = ['admin1', 'admin2', 'admin3']
    return username in admins

@app.route('/admin')
def admin_page():
    username = request.args.get('username')

    if is_admin(username):
        # Code to display admin page with special privileges
        return 'Welcome to the admin page!'
    else:
        return 'Sorry, you do not have admin privileges.'

if __name__ == '__main__':
    app.run()

In this example, we define the is_admin function which checks if a given username is an admin. The admins list contains the usernames that have admin privileges.

The /admin route is defined, and when accessed, it checks if the provided username parameter is an admin by calling the is_admin function. If the username is an admin, it displays the admin page with special privileges. Otherwise, it returns a message stating that the user does not have admin privileges.

Please note that this is a basic example and may need modifications based on your specific requirements.

To calculate the total profit in a dataframe, you can use the sum() function in Python.

Assuming you have a dataframe called df with a column named "profit", you can calculate the total profit using the following code:

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total_profit = df['profit'].sum()

This will give you the sum of all the values in the "profit" column of the dataframe.

Here is an example:

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df = pd.DataFrame({
  'year': [2018, 2019, 2020],
  'profit': [1000, 2000, 1500]
})

total_profit = df['profit'].sum()
print(total_profit)

Output:

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4500

This means that the total profit in the dataframe is 4500.

To hide the y-axis in a bar chart created with Plotly, you can set the showticklabels attribute of the y-axis to False. Here's an example:

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import plotly.express as px

data = {'Category': ['A', 'B', 'C'],
        'Value': [10, 20, 15]}

fig = px.bar(data, x='Category', y='Value')

fig.update_yaxes(showticklabels=False)

fig.show()

This code creates a bar chart using px.bar and sets the showticklabels attribute of the y-axis to False using update_yaxes. This will hide the tick labels and effectively hide the y-axis. You can customize other aspects of the chart as needed.

To create an absolute matrix, we need to take the absolute value of each element in the input matrix.

Here's how you can do it in Python:

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n, m = map(int, input().split())

matrix = []
for _ in range(n):
    row = list(map(int, input().split()))
    matrix.append(row)

# Create the absolute matrix
absolute_matrix = []
for i in range(n):
    absolute_row = []
    for j in range(m):
        absolute_element = abs(matrix[i][j])
        absolute_row.append(absolute_element)
    absolute_matrix.append(absolute_row)

# Print the absolute matrix
for row in absolute_matrix:
    for element in row:
        print(element, end=" ")
    print()

Example input:

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3 3
-1 2 -3
4 0 -5
6 -7 8

Output:

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1 2 3
4 0 5
6 7 8

This code reads the dimensions of the matrix, then reads the matrix elements. It creates a new matrix with the absolute values of each element and prints the absolute matrix.