Using Functions Across Jupyter Notebooks in Python

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What will you learn?

Discover how to efficiently reuse functions defined in one Jupyter notebook within another, promoting code reusability and organization.

Introduction to the Problem and Solution

When working with multiple Jupyter notebooks, it’s common to encounter shared functions that need to be reused across these notebooks. To address this, creating a module from the notebook containing the function and importing it into another notebook where its functionality is required proves to be an effective solution. This approach not only fosters code reusability but also helps in maintaining clean and organized notebooks.

To utilize a function from one Jupyter notebook in another, follow these steps: 1. Define the function in one notebook. 2. Export the function as a module. 3. Import the module into another notebook. 4. Utilize the function within the second notebook.

Code

# Save this code snippet as 'my_functions.py' or any desired filename
def my_function():
    return "Hello from another Jupyter Notebook!"

# Copyright PHD

In your new Jupyter Notebook where you want to use my_function:

# Importing our custom module containing the function
import my_functions

# Using the imported function
result = my_functions.my_function()
print(result)  # Output: Hello from another Jupyter Notebook!

# Copyright PHD

Ensure both files (‘my_functions.py’ and your new Jupyter Notebook) are saved in the same directory.

Explanation

  • Defining a Function: Begin by defining a simple function my_function() within one of your notebooks.
  • Exporting as Module: Saving this code snippet with your function as ‘my_functions.py’ transforms it into an importable module.
  • Importing Modules: In your new notebook, import ‘my_functions’, making all functions defined within ‘my_functions.py’ accessible for use.
  • Utilizing Imported Function: Call my_function() using dot notation (e.g., module_name.function_name()) after importing.
    How do I save a specific cell or set of cells as a Python script or .py file?

    To save individual cells as a Python script or .py file in your Jupyter Notebook, prepend those cells with “%%writefile filename.py”.

    Can I import multiple functions from different modules into one Python script?

    Yes, you can import multiple functions from different modules by listing them after importing like so: from module_name import func1, func2.

    Do I need internet connectivity while importing custom modules?

    No, internet connectivity is not required when importing custom modules stored locally on your machine or server.

    Can I modify my custom module without restarting my current kernel session?

    To update changes made in your custom module without restarting kernel sessions each time, consider using %load_ext autoreload and %autoreload 2.

    How can I organize multiple related functions within a single module?

    Group related functions together within one Python script (module) for better code organization and maintenance.

    Conclusion

    In conclusion, leveraging functions across various Jupyter Notebooks enhances code reusability and promotes cleaner project structures. By encapsulating related functionalities into separate modules that can be effortlessly imported wherever necessary, developers experience streamlined workflows.

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