Reproducible Notebook Habits

Unit ID: M01-U07 Estimated active time: 18-25 minutes

A result is stronger when it can be repeated

A notebook is not complete merely because the final output looks right. It should work again from a fresh state and make its assumptions visible.

Reproducible means that the documented steps can be run again under the stated conditions to produce the expected result.

For this beginner module, reproducibility has five parts:

1. Inputs appear before calculations.
2. Every used name is created in the notebook.
3. Cells run in top-to-bottom order.
4. Important assumptions and units are written down.
5. Restart-and-run-all finishes without an error.

Organise a notebook into sections

A short notebook can use this order:

1. Title and purpose in a Markdown cell.
2. Inputs in a code cell.
3. Calculations in a code cell.
4. Results in a code cell.
5. Checks and notes in Markdown or code cells.

Example:

# Inputs: fictional amounts in Indian rupees
breakfast_cost = 120
travel_cost = 250
lunch_cost = 180

# Calculations
total_cost = breakfast_cost + travel_cost + lunch_cost
average_cost = total_cost / 3

# Results
print("Total cost:", total_cost)
print("Average cost:", average_cost)

Check expected facts

Before trusting the result, identify a simple fact you can verify independently.

For the example:

• All three costs are positive.
• The total should be larger than each individual cost.
• The average should lie between the smallest and largest cost.

We will later turn such expectations into automated tests. Today, write them as a short review note and inspect the output.

Restart and run all

Use this final routine:

1. Save the notebook.
2. Restart the kernel and clear old outputs if the interface supports it.
3. Run all cells from top to bottom.
4. Confirm that no cell depends on a value from an earlier experiment.
5. Read the final output and compare it with your expected facts.
6. Save the clean result.

If the notebook fails, do not hide the failed cell. Find the first failure, repair its cause, and repeat the clean-state test.

A reproducibility challenge

The following notebook was edited during an experiment:

distance_km = 12

travel_time_hours = distance_km / speed_km_per_hour

speed_km_per_hour = 24
print("Travel time:", travel_time_hours)

Repair it so it runs from top to bottom. Then add a purpose comment and a unit to the output label.

One clear version is:

# Estimate travel time for a fictional journey
distance_km = 12
speed_km_per_hour = 24
travel_time_hours = distance_km / speed_km_per_hour
print("Travel time in hours:", travel_time_hours)

Expected output:

Travel time in hours: 0.5

Prepare for the checkpoint

Before moving on, confirm that you can:

• distinguish a Markdown cell from a code cell;
• explain what the kernel remembers;
• restart and run all;
• identify a name used before creation;
• predict simple arithmetic and printed output; and
• label inputs, calculations, and results clearly.

Takeaway

Reproducibility is a working habit, not a final decoration. Keep the required state visible, organise steps in dependency order, state assumptions, and test from a clean kernel. You are now ready to build the Module 1 checkpoint.