Python Assessment: Collection Processing & Algorithms

Time Limit: 90 Minutes Topic: Python Lists, Dictionaries, Loops, Functions & Test Driven Development (TDD)

📋 Overview

Welcome to the Data Analytics assessment. You have been tasked with building analytics functions for a Sales Database, implementing statistical calculations, and creating a Smart Inventory System.

This is an invigilated assessment. You are required to demonstrate not just your ability to write code, but your ability to write tests for that code.

📂 File Structure

• analytics.py 📝 (EDIT THIS)
  • This file contains the empty functions you need to complete.
  • Do not rename any functions or the file itself.
• test_inventory.py 🆕 (CREATE THIS)
  • You must create this file from scratch.
  • This file will contain the Unit Tests for Question 6.

🚀 Instructions

Section A: List Processing (Questions 1-3)

Work with lists of numbers and strings. You'll need loops, conditionals, and list methods.

Section B: Dictionary Operations (Questions 4-5)

Process dictionaries representing real-world data. Requires iteration, key-value manipulation, and aggregation.

Section C: The Inventory Manager (Question 6)

This section requires Test Driven Development (TDD).

1. Read the requirements for check_inventory_status in analytics.py.
2. BEFORE you write the logic, create a new file named test_inventory.py.
3. Implement the TestInventory class and write tests for all scenarios.
4. Once your tests are written, go back to analytics.py and write the code to pass them.

🧪 How to Run Your Tests

python test_inventory.py

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📝 Question Details

SECTION A: List Processing

Question 1: filter_sales_above_threshold(sales: list, threshold: int)

• Given a list of sales amounts (integers), return a NEW list containing only values above the threshold
• Do NOT modify the original list
• Example: filter_sales_above_threshold([100, 250, 75, 300], 150) → [250, 300]
• Return empty list if no values qualify

Question 2: count_product_codes(codes: list, prefix: str)

• Given a list of product codes (strings) and a prefix (string)
• Count how many codes START with the given prefix (case-sensitive)
• Example: count_product_codes(["PROD-001", "PROD-002", "SERV-001"], "PROD") → 2
• Return 0 if no matches found

Question 3: calculate_moving_average(numbers: list, window_size: int)

• Calculate the average of the LAST window_size elements in the list
• Example: calculate_moving_average([10, 20, 30, 40, 50], 3) → 40.0 (average of 30, 40, 50)
• If the list has fewer elements than window_size, use all available elements
• Return the average as a float rounded to 2 decimal places
• Return 0.0 for empty list

SECTION B: Dictionary Operations

Question 4: get_top_seller(sales_data: dict)

• Given a dictionary where keys are employee names and values are sales totals
• Example: {"Alice": 5000, "Bob": 7500, "Carol": 6000}
• Return the NAME of the employee with the highest sales
• If dictionary is empty, return "No Data"
• If there's a tie, return the name that appears first alphabetically

Question 5: merge_inventory(warehouse_a: dict, warehouse_b: dict)

• Given two dictionaries representing product quantities in two warehouses
• Keys are product IDs (strings), values are quantities (integers)
• Return a NEW dictionary with combined quantities for each product
• Example:

  warehouse_a = {"PROD-001": 50, "PROD-002": 30}
  warehouse_b = {"PROD-002": 20, "PROD-003": 40}
  # Result: {"PROD-001": 50, "PROD-002": 50, "PROD-003": 40}

• If a product exists in only one warehouse, include it with its quantity
• Return empty dictionary if both inputs are empty

SECTION C: Inventory Management (TDD)

Question 6: check_inventory_status(stock_level: int, reorder_point: int, max_capacity: int, daily_sales: int)

Create test_inventory.py with class TestInventory and implement tests FIRST.

Parameters:

• stock_level: Current units in stock
• reorder_point: Threshold that triggers reorder
• max_capacity: Maximum warehouse capacity
• daily_sales: Average units sold per day

Logic Tree:

1. INPUT VALIDATION:

   • If ANY parameter is negative: return "Invalid Input"
   • If stock_level > max_capacity: return "Invalid Input"

2. OVERSTOCKED:

   • If stock_level > (max_capacity * 0.9): return "OVERSTOCKED"
   • This means stock is above 90% of capacity

3. CRITICAL (Urgent Reorder):

   • If stock_level < (reorder_point * 0.5): return "CRITICAL"
   • This means stock is below 50% of the reorder point

4. REORDER NEEDED:

   • If stock_level <= reorder_point: return "REORDER"

5. LOW STOCK (Warning):

   • If daily_sales > 0 AND stock_level / daily_sales < 7: return "LOW STOCK"
   • This means stock will run out in less than 7 days at current sales rate
   • Handle division by zero (if daily_sales is 0, skip this check)

6. OPTIMAL:

   • All other cases: return "OPTIMAL"

Example Test Cases to Include:

• Negative values
• Stock exactly at reorder point
• Stock at exactly 90% capacity
• Zero daily sales
• Stock level exactly 6.9 days worth
• Stock level exactly 7 days worth

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⚠️ Important Notes

• Use list comprehensions where appropriate (but loops are acceptable)
• Do NOT use external libraries (no numpy, pandas, etc.)
• Dictionary iteration: use .items(), .keys(), .values() as needed
• For Question 6, test ALL edge cases and boundary conditions
• Round floating point results to 2 decimal places where specified
• Do NOT modify input parameters unless explicitly told to

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📊 Grading Breakdown

• Section A (Q1-Q3): 30 points (10 each)
• Section B (Q4-Q5): 30 points (15 each)
• Section C (Q6): 40 points
  • Test file creation: 10 points
  • Test coverage: 15 points
  • Function implementation: 15 points

Total: 100 points

Good luck!