What is Jupyter Notebook?

Jupyter Notebook is an open-source web application that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It is widely used for data analysis, scientific research, and machine learning projects.

Why Automate Jupyter Notebook Execution?

Running Jupyter Notebooks manually can be time-consuming, especially if you have multiple notebooks to process or if you’re generating reports on a regular basis. Automating the execution of these notebooks in a loop allows for efficient batch processing and ensures consistent results every time.

Steps to Create the Python Script

Below is a simple Python script that runs a Jupyter Notebook in a loop and saves the results to HTML files:

import time
import os
import subprocess

def run_notebook(notebook_path, output_path):
    try:
        # Convert Jupyter notebook to HTML after executing it
        subprocess.run([
            "jupyter", "nbconvert", "--to", "html", "--execute", 
            "--output", output_path, notebook_path
        ], check=True)
        print(f"Notebook executed and saved to {output_path}")
    except subprocess.CalledProcessError as e:
        print(f"Error executing notebook: {e}")

def run_notebook_in_loop(notebook_path, output_dir, loop_count=5, delay_seconds=60):
    if not os.path.exists(output_dir):
        os.makedirs(output_dir)
    
    for i in range(loop_count):
        output_path = os.path.join(output_dir, f"output_{i+1}.html")
        run_notebook(notebook_path, output_path)
        print(f"Sleeping for {delay_seconds} seconds...")
        time.sleep(delay_seconds)  # Delay between runs

if __name__ == "__main__":
    notebook_path = "your_notebook.ipynb"  # Replace with your notebook path
    output_dir = "notebook_outputs"  # Output directory to save HTML files
    run_notebook_in_loop(notebook_path, output_dir)

        

How the Script Works

This script consists of two main functions:

• run_notebook: This function executes the Jupyter notebook and saves the output as an HTML file. It uses the subprocess.run() method to call Jupyter’s nbconvert tool.
• run_notebook_in_loop: This function runs the notebook multiple times in a loop, saving each result to a different HTML file. You can specify the number of iterations with the loop_count parameter and set a delay between each run with the delay_seconds parameter.

Why You Should Use This Automation

Automating Jupyter Notebook execution and saving the results to HTML has several advantages:

• Consistency: Ensures that each notebook is executed with the same parameters and processes.
• Efficiency: Saves time by running notebooks automatically, especially when working with large datasets or generating reports.
• Batch Processing: Helps in processing multiple notebooks in a single workflow without manual intervention.

Conclusion

By using this Python script, you can automate the process of running Jupyter Notebooks in a loop and save the output to HTML. This is useful for automating data analysis tasks or generating reports without manual intervention. You can adjust the script to suit your specific needs, such as modifying the output format or frequency of execution.