Formatted Console Output (Python)

This module practices table-style output, alignment, and precision control.

Learning Metadata

• Difficulty: Beginner.
• Estimated Time: 20-35 minutes.
• Prerequisites: 01-foundations/types-and-io, 01-foundations/operators-and-expressions.
• Cross-Language Lens: Compare stream manipulators, format strings, fmt, and Python formatting for the same reporting task.

Learning Outcomes

• FND-FMT-01: Produce stable human-readable tabular and numeric output.
• FND-FMT-02: Choose precision, alignment, and labels appropriate to the data.

Quick Run

Run from the repository root:

python scripts/automation.py run-module --module-path languages/python/01-foundations/formatted-output-and-iomanip

Topics Covered

• Column alignment for tabular output.
• Fixed precision for monetary and statistical values.
• Building readable reports from structured input.
• Controlling output format based on user precision input.

Common Pitfalls

• Producing unreadable tables with inconsistent widths.
• Not validating precision ranges before formatting.
• Forgetting to maintain numeric precision in totals and averages.

Cross-Language Notes

• In Python, read this module through the native focus ?Formatted Console Output?; the shared folder name remains stable for side-by-side navigation.
• Use dynamic values, collection protocols, and context managers to demonstrate how to produce stable human-readable tabular and numeric output.
• Compare observable behavior with the other tracks when learning to choose precision, alignment, and labels appropriate to the data; equivalent evidence matters more than identical syntax.

Exercise Focus

• exercises/01.py: collect product rows and print an aligned invoice table with totals.
• exercises/02.py: compute summary metrics and print them using user-selected precision.

Exercise Specs

1. exercises/01.py

• Input: product count, then name, price, and quantity for each product.
• Output: formatted table with line totals and grand total.
• Edge cases: non-positive product count; long product names affecting alignment.

2. exercises/02.py

• Input: numeric list plus precision value from 0 to 6.
• Output: count, sum, average, minimum, and maximum with selected precision.
• Edge cases: empty numeric input; precision outside 0..6.

Check Your Work

Run from the repository root after implementing a starter:

python scripts/automation.py check-exercise --language python --level 01-foundations --module formatted-output-and-iomanip --exercise 01

Change --exercise 01 to --exercise 02 for the second task. Consult exercises/solutions/ only after making a complete attempt.

Checkpoint

• I can explain the core ideas of this module.
• I can run and modify example/main.py.
• I completed exercises/01.py.
• I completed exercises/02.py.
• I validated at least one edge case for each exercise.

Content revision 1d0b3f4