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# MIT License
#
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# MIT License # # Copyright (c) MkDocs4 Documentation Team # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. # --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: percent # format_version: '1.3' # jupytext_version: 1.16.1 # kernelspec: # display_name: Python 3 # language: python # name: python3 # ---

Python Script Notebook Example¶

This notebook is written as a Python script using Jupytext format. It demonstrates how .nb.py files can be used with mkdocs-jupyter.

import matplotlib.pyplot as plt

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# Import required libraries
import numpy as np

print("This is a Jupytext notebook!")

# Import required libraries import numpy as np print("This is a Jupytext notebook!")

Creating a Simple Plot¶

Let's create a simple sine wave plot:

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# Generate data
x = np.linspace(0, 2 * np.pi, 100)
y = np.sin(x)

# Create the plot
plt.figure(figsize=(8, 4))
plt.plot(x, y, "b-", linewidth=2)
plt.title("Sine Wave")
plt.xlabel("x")
plt.ylabel("sin(x)")
plt.grid(True, alpha=0.3)
plt.show()

# Generate data x = np.linspace(0, 2 * np.pi, 100) y = np.sin(x) # Create the plot plt.figure(figsize=(8, 4)) plt.plot(x, y, "b-", linewidth=2) plt.title("Sine Wave") plt.xlabel("x") plt.ylabel("sin(x)") plt.grid(True, alpha=0.3) plt.show()

Benefits of Jupytext¶

Using Jupytext format (.nb.py) has several advantages:

1. Version Control: Python scripts are much easier to diff and merge
2. IDE Support: Full Python IDE features (autocomplete, refactoring)
3. Collaboration: Easier for team members to review and edit
4. Lightweight: No binary data or output stored in the file

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# Example of code that would be easier to review in .py format
def fibonacci(n):
    """Generate Fibonacci sequence up to n terms."""
    if n <= 0:
        return []
    elif n == 1:
        return [0]
    elif n == 2:
        return [0, 1]
    else:
        fib = [0, 1]
        for i in range(2, n):
            fib.append(fib[i - 1] + fib[i - 2])
        return fib


# Generate and display first 10 Fibonacci numbers
fib_sequence = fibonacci(10)
print(f"First 10 Fibonacci numbers: {fib_sequence}")

# Example of code that would be easier to review in .py format def fibonacci(n): """Generate Fibonacci sequence up to n terms.""" if n <= 0: return [] elif n == 1: return [0] elif n == 2: return [0, 1] else: fib = [0, 1] for i in range(2, n): fib.append(fib[i - 1] + fib[i - 2]) return fib # Generate and display first 10 Fibonacci numbers fib_sequence = fibonacci(10) print(f"First 10 Fibonacci numbers: {fib_sequence}")