Coding5s / Pillar 1 / Stage 04

Refactor

Stage 4 starts with something that already works and asks the learner to make it better. The task shifts from achieving basic functionality to evaluating quality, identifying weaknesses, and improving the solution according to the conventions and constraints of the target technical ecosystem.

INSPECT → EVALUATE → IDENTIFY WEAKNESSES → REFACTOR → VERIFY

Reference output: Below is a complete example of a Stage 4 lesson generated through the Coding5s prompt architecture. The review criteria, technical constraints, quality targets, and required improvements vary according to the technology, topic, learner level, and configured ecosystem rules.

🔹 Topic #23 | Stage 4 🧹 Refactor | Python Core & Scripting | 📊 Level: Intermediate | 🌐 Coding5s.com

Concept: Conditional Branching (if, elif, else)

Dataset detected: NO. Generating dummy data.

📥 From: Tech Lead

📤 To: Python Core & Scripting Dev

Subject: Please save my sanity before the deployment

Hi, the Junior sent this over. Incredibly, it actually works and produces the correct output, but my eyes are bleeding reading it. Please refactor it before it hits production.

🚨 Your objective in this lesson: You must copy the code blocks from each Challenge exactly as they are and paste them into your IDE, then refactor the code by rewriting it professionally until you achieve the exact Program Output when running the refactored program.

Challenge 1️⃣: Tax Bracket Calculator

This script iterates through a list of income values and calculates the required tax amount based on predefined brackets, but uses terrible nested logic and redundant type casting instead of a clean if/elif/else chain.

💩 Dirty Code:

Python

lst = [15000.0, 45000.0, 95000.0, 200000.0]
for val in lst:
    v = float(val)
    res = 0.0
    if v < 20000.0:
        res = v * 0.05
    else:
        if v >= 20000.0 and v < 50000.0:
            res = v * 0.10
        elif v >= 50000.0 and v < 100000.0:
            res = v * 0.15
        else:
            if v >= 100000.0:
                res = v * 0.25
    print(f"Income: ${v:,.2f} -> Tax: ${res:,.2f}")

💻 Program Output:

Plaintext

Income: $15,000.00 -> Tax: $750.00
Income: $45,000.00 -> Tax: $4,500.00
Income: $95,000.00 -> Tax: $14,250.00
Income: $200,000.00 -> Tax: $50,000.00

Challenge 2️⃣: Subscription Tier Benefits

This code assigns features and monthly costs based on string names of subscription tiers. It suffers from duplicate condition checks, unnecessary intermediate variables, and inconsistent string normalization.

💩 Dirty Code:

Python

usR_liST = ["basic", "PREMIUM", "vip", "None"]
for u in usR_liST:
    a1 = str(u).lower()
    b2 = ""
    if a1 == "basic":
        b2 = "Standard Ads"
    elif a1 == "premium":
        b2 = "No Ads + HD"
    elif a1 == "vip":
        b2 = "No Ads + 4K + Downloads"
    elif a1 == "none":
        b2 = "Guest Mode"
    else:
        b2 = "Guest Mode"
    
    c3 = float(0)
    if a1 == "vip":
        c3 = 19.99
    elif a1 == "premium":
        c3 = 9.99
    else:
        c3 = 0.00
    print(f"User: {u} | Benefits: {b2} | Cost: ${c3:,.2f}")

💻 Program Output:

Plaintext

User: basic | Benefits: Standard Ads | Cost: $0.00
User: PREMIUM | Benefits: No Ads + HD | Cost: $9.99
User: vip | Benefits: No Ads + 4K + Downloads | Cost: $19.99
User: None | Benefits: Guest Mode | Cost: $0.00

Challenge 3️⃣: Sensor Priority Router

This script evaluates sensor temperature data to trigger hardware alerts and assign potential maintenance costs. It uses over-complicated boolean checks (== True), deep nesting, and confusing abbreviations.

💩 Dirty Code:

Python

s_d = [{"t": 95, "m": True}, {"t": 40, "m": False}, {"t": 110, "m": True}, {"t": 10, "m": False}]
for tmp_dict in s_d:
    t_val = int(tmp_dict["t"])
    m_val = bool(tmp_dict["m"])
    stat = ""
    p = 0.0
    
    if t_val > 100 and m_val == True:
        stat = "CRITICAL SHUTDOWN"
        p = 5000.00
    elif t_val > 100 and m_val == False:
        stat = "OVERHEAT WARNING"
        p = 1000.00
    else:
        if t_val > 80:
            stat = "MAINTENANCE CHECK"
            p = 250.00
        else:
            stat = "SYSTEM OPTIMAL"
            p = 0.00
            
    print(f"Sensor Temp: {t_val} -> Status: {stat} | Cost: ${p:,.2f}")

💻 Program Output:

Plaintext

Sensor Temp: 95 -> Status: MAINTENANCE CHECK | Cost: $250.00
Sensor Temp: 40 -> Status: SYSTEM OPTIMAL | Cost: $0.00
Sensor Temp: 110 -> Status: CRITICAL SHUTDOWN | Cost: $5,000.00
Sensor Temp: 10 -> Status: SYSTEM OPTIMAL | Cost: $0.00

Challenge 4️⃣: E-Commerce Discount Calculator

This program applies dynamic pricing rules based on the cart total and user membership level. The code is highly verbose, repeats mathematical operations, and features erratic casing for variable names.

💩 Dirty Code:

Python

carTs = [ {"v": "150.50", "mem": "GOLD"}, {"v": "45.00", "mem": "SILVER"}, {"v": "250.00", "mem": "NONE"}, {"v": "5.00", "mem": "GOLD"} ]
for c_i in carTs:
    amT = float(str(c_i["v"]))
    tYpE = str(c_i["mem"])
    f_aMt = 0.0
    
    if amT >= 100.00:
        if tYpE == "GOLD":
            f_aMt = amT - (amT * 0.20)
        elif tYpE == "SILVER":
            f_aMt = amT - (amT * 0.10)
        else:
            f_aMt = amT - (amT * 0.05)
    elif amT >= 50.00:
        if tYpE == "GOLD":
            f_aMt = amT - (amT * 0.10)
        else:
            f_aMt = amT
    else:
        f_aMt = amT
    
    s = f_aMt
    print(f"Original: ${amT:,.2f} | Member: {tYpE} | Final Price: ${s:,.2f}")

💻 Program Output:

Plaintext

Original: $150.50 | Member: GOLD | Final Price: $120.40
Original: $45.00 | Member: SILVER | Final Price: $45.00
Original: $250.00 | Member: NONE | Final Price: $237.50
Original: $5.00 | Member: GOLD | Final Price: $5.00

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