Chapter 8: Computation & Data Extraction Workflow

"If it's math, it belongs in a script. Period."

What You'll Build

By the end of this chapter, you'll have a personal toolbox of reusable utilities:

# Your workflow by chapter end:
cat ~/finances/2025/*.csv | tax-prep

# Output:
# MEDICAL: CVS PHARMACY: $456.70
# MEDICAL: WALGREENS: $234.50
# CHARITABLE: RED CROSS: $200.00
# BUSINESS: ZOOM SUBSCRIPTION: $179.88
#
# --- TOTALS ---
# Medical: $1,891.20
# Charitable: $1,550.00
# Business: $774.32
#
# POTENTIAL DEDUCTIONS: $4,215.52

You'll transform from someone who manually categorizes expenses (tedious and error-prone) to someone who builds verified automation tools that work every tax season.

Prerequisites

From Seven Principles Chapter:

• You understand ALL Seven Principles conceptually
• You know why "Bash is the Key" matters (Principle 1)
• You know why "Verification as Core Step" prevents failures (Principle 3)

From File Processing Chapter:

• You can navigate directories (cd, ls, pwd)
• You've run basic Bash commands
• You understand the pipe operator (|) conceptually

Technical Requirements:

• Python 3.x installed (see setup below)
• Unix-like terminal (macOS, Linux, or WSL on Windows)
• Access to Claude Code or similar AI assistant
• A bank statement CSV export (most banks offer this)

Python Setup — verify Python is installed before starting Lesson 1:

# macOS / Linux:
python3 --version

# Windows (Command Prompt or PowerShell):
python --version

If you see a version number (3.x), you're ready. If not, install Python from python.org or use your system's package manager:

• macOS: brew install python
• Ubuntu/Debian: sudo apt install python3
• Windows: Download from python.org and check "Add to PATH" during installation

Chapter Structure

Lesson	Title	Duration	Key Skill
1	From Broken Math to Your First Tool	30 min	Build a Python utility from scratch
2	The Testing Loop	25 min	Verify with exit codes and test data
3	Parsing Real Data	25 min	Parse CSV with Python's csv module
4	Your Permanent Toolkit	20 min	Make scripts into permanent commands
5	Data Wrangling	30 min	Categorize with regex pattern matching
6	Capstone: Tax Season Prep	40 min	Generate tax-ready report

Total Duration: 170 minutes (~3 hours)

Seven Principles in Action

This chapter applies the principles you learned in Chapter 6:

Principle	How You'll Apply It
P1: Bash is the Key	Use cat, find, xargs, pipes as your foundation
P2: Code as Universal Interface	Python scripts as reusable components
P3: Verification as Core Step	Zero-trust debugging with exit codes
P4: Small, Reversible Decomposition	Each lesson builds one composable skill
P5: Persisting State in Files	Aliases and scripts as persistent tools
P6: Constraints and Safety	Test data prevents production errors
P7: Observability	Exit codes make failures visible

The Journey

Lesson 1: From Broken Math to Your First Tool

• Discover why Bash arithmetic fails with decimals
• Build sum.py — a Python script that reads numbers from stdin and calculates sums

Lesson 2: The Testing Loop

• Learn why exit code 0 doesn't mean "correct"
• Create test data with known answers to verify your scripts

Lesson 3: Parsing Real Data

• Understand why simple text tools (like awk) fail on real CSV
• Build a CSV parser with Python's csv module

Lesson 4: Your Permanent Toolkit

• Transform scripts into permanent commands via chmod, aliases, and shell config
• Close your terminal, open a new one, and your tools still work

Lesson 5: Data Wrangling

• Use pattern matching to categorize transactions (Medical, Charitable, Business)
• Handle false positives (Dr. Pepper is not a doctor)

Lesson 6: Capstone

• Orchestrate everything into a real-world tax preparation workflow
• Generate a report your accountant can use
• Process a full year of bank statements with one command

Quick Start for Previous Chapter Graduates

Already comfortable with terminal basics? Here's what's new:

# Bash math FAILS with decimals (you'll discover why)
echo $((14.50 + 23.75))  # Error!

# Simple text tools FAIL on quoted CSV fields
echo '"Amazon, Inc.",-23.99' | awk -F',' '{print $2}'
# Output: Inc."  -- WRONG! Broke on comma inside quotes

# Python handles both correctly (you'll build this)
cat bank-statement.csv | python sum-expenses.py
# Output: Total: $2,456.78

# Pattern matching categorizes for taxes (you'll learn this)
cat bank-statement.csv | python tax-categorize.py
# Output: Medical: $1,891.20, Charitable: $1,550.00

The Real-World Payoff

This isn't academic. By chapter end, you'll solve a real problem:

Before this chapter: Tax season means hours of manual work - opening each bank statement, hunting for medical expenses, trying to remember which "SQ *LOCALSTORE" was business vs personal.

After this chapter: Download your bank CSVs, run one command, get a categorized report. Every year. Forever.

The same pattern applies to any data extraction problem - expense reports, invoice processing, log analysis. You're learning to build tools, not just use them.