PY-L2-13 · Challenge — Inventory Inspector

Challenge — Inventory Inspector

One dataset. Six questions. Each one harder than the last. Today you put twelve lessons' worth of collection skills to work on a single warehouse inventory — and earn the right to move on to strings, files and modules.

⏱ 1 hour🧩 Challenge lesson📚 After PY-L2-12💻 VS Code or online-python.com

What This Challenge Tests

3 min

By the end of this lesson you should be comfortable with:

Reading nested data — a list of dictionaries where one field is itself a list.
Filtering records by a field value, and projecting a single field out.
Summing, counting and finding maxima across a list of dicts.
Reshaping a list of dicts into a dict of lists (group-by).
Using set operations to answer membership questions.

The Dataset

5 min

Save this dataset in a new file inventory.py. Every challenge below uses it — don't change the data, just write the queries underneath.

# inventory.py — Adva Warehouse stock list

products = [
    {"sku": "P001", "name": "pencil",     "stall": "stationery", "price": 0.50, "qty": 120, "tags": ["writing", "wood"]},
    {"sku": "P002", "name": "eraser",     "stall": "stationery", "price": 0.80, "qty":  60, "tags": ["writing"]},
    {"sku": "P003", "name": "ruler 30cm", "stall": "stationery", "price": 1.20, "qty":  18, "tags": ["measuring", "plastic"]},
    {"sku": "P004", "name": "sharpener",  "stall": "stationery", "price": 1.50, "qty":   8, "tags": ["writing", "metal"]},
    {"sku": "F101", "name": "apple",      "stall": "fruit",      "price": 1.00, "qty":  40, "tags": ["fresh", "snack"]},
    {"sku": "F102", "name": "banana",     "stall": "fruit",      "price": 0.40, "qty":  90, "tags": ["fresh", "snack"]},
    {"sku": "F103", "name": "durian",     "stall": "fruit",      "price": 8.50, "qty":   5, "tags": ["fresh"]},
    {"sku": "D201", "name": "milo",       "stall": "drinks",     "price": 4.50, "qty":  25, "tags": ["chocolate", "hot"]},
    {"sku": "D202", "name": "kopi",       "stall": "drinks",     "price": 3.00, "qty":  35, "tags": ["caffeine", "hot"]},
    {"sku": "D203", "name": "teh tarik",  "stall": "drinks",     "price": 3.50, "qty":  22, "tags": ["caffeine", "hot", "milk"]},
    {"sku": "D204", "name": "cendol",     "stall": "drinks",     "price": 5.00, "qty":   0, "tags": ["sweet", "cold"]},
]

Eleven products, four fields each plus a nested list of tags. Skim it once, then crack on with the six tasks below.

How to use this lesson

For each task, try first without opening the hint. Compare with the hint only after a real attempt. Tasks 4-6 are stretch goals — finish 1-3 first, then come back if there's time.

Task 1 · The Headline Numbers

8 min

Print four headline numbers about the warehouse:

Total number of distinct products (= len(products)).
Total units in stock — sum of every qty.
Total stock value — sum of qty * price for every product.
How many distinct stalls there are. Hint: use set().

Hint

print("Products :", len(products))
print("Units    :", sum([p["qty"] for p in products]))

value = 0
for p in products:
    value += p["qty"] * p["price"]
print("Value RM :", value)

stalls = set([p["stall"] for p in products])
print("Stalls   :", len(stalls), stalls)

Three list comprehensions and one set — exactly the patterns from PY-L2-02, L2-06 and L2-08.

Task 2 · Out-of-Stock & Low-Stock Alerts

8 min

Two filters in one go:

Print every product whose qty is exactly 0, in this format: OUT — D204 cendol.
Print every product with 0 < qty <= 10 as LOW — F103 durian (5).
At the end, print {ALERTS: n, OUT: x, LOW: y} — the three totals.

Hint

out  = [p for p in products if p["qty"] == 0]
low  = [p for p in products if 0 < p["qty"] <= 10]

for p in out:
    print("OUT —", p["sku"], p["name"])

for p in low:
    print("LOW —", p["sku"], p["name"], "(", p["qty"], ")")

print({"ALERTS": len(out) + len(low), "OUT": len(out), "LOW": len(low)})

Python supports the maths-chain 0 < x <= 10 directly — same as x > 0 and x <= 10, but neater.

Task 3 · The Most Valuable Single Product

8 min

For every product, the value-in-stock is qty * price. Find the product with the highest such value, and print:

Top single line: F102 banana — RM 36.0  ( 90 units × 0.4 )

Scan the list and track the whole record.

Hint

top   = products[0]
top_v = top["qty"] * top["price"]

for p in products:
    v = p["qty"] * p["price"]
    if v > top_v:
        top   = p
        top_v = v

print("Top single line:", top["sku"], top["name"],
      "— RM", top_v,
      " (", top["qty"], "units ×", top["price"], ")")

The trick from PY-L2-11: tracking the whole record instead of just the number lets you print every detail at the end.

Task 4 · Group Totals by Stall

8 min

Build a by_stall dict where the key is the stall name and the value is the total stock value for that stall. Print the dict, then the stall with the highest combined value.

Hint

by_stall = {}
for p in products:
    stall = p["stall"]
    value = p["qty"] * p["price"]
    if stall not in by_stall:
        by_stall[stall] = 0
    by_stall[stall] += value

print(by_stall)

top_stall = ""
top_value = 0
for stall, v in by_stall.items():
    if v > top_value:
        top_value = v
        top_stall = stall
print("Top stall:", top_stall, "(RM", top_value, ")")

This is a tweak of the group-by recipe — instead of appending to a list per group, we're summing into a number per group. Same shape, different operation.

Task 5 · The Tag Index (Stretch)

8 min

Every product has a list of tags. Build by_tag — a dict mapping each tag to a list of product names that wear it. Then:

Print the dict.
Print the tag with the most products attached.
Print all products that are tagged both "writing" AND "metal" — use a set intersection on set(by_tag["writing"]) & set(by_tag["metal"]).

Hint

by_tag = {}
for p in products:
    for tag in p["tags"]:
        if tag not in by_tag:
            by_tag[tag] = []
        by_tag[tag].append(p["name"])

print(by_tag)

top_tag = ""
top_n   = 0
for tag, names in by_tag.items():
    if len(names) > top_n:
        top_n   = len(names)
        top_tag = tag
print("Top tag:", top_tag, "(", top_n, ")")

both = set(by_tag["writing"]) & set(by_tag["metal"])
print("Writing AND metal:", both)

The inner for tag in p["tags"] walks the nested list — that's the moment a list-of-dicts-with-list becomes a real test of your loop muscle. Set intersection from PY-L2-09 then turns the "tagged with both" question into one line.

Task 6 · The Promo Generator (Stretch)

7 min

Build a function make_promo(min_qty=20) that returns a new list-of-dicts containing only the products with qty >= min_qty, each with their price discounted by 10%. The function shouldn't change the original products list.

Test it: call make_promo(), then make_promo(50). Print both.

Hint

def make_promo(min_qty=20):
    promo = []
    for p in products:
        if p["qty"] >= min_qty:
            promo.append({
                "sku":   p["sku"],
                "name":  p["name"],
                "price": round(p["price"] * 0.9, 2),
                "was":   p["price"],
                "qty":   p["qty"],
            })
    return promo

print(make_promo())
print()
print(make_promo(50))

The function takes a default argument (from PY-L1-28). Each loop iteration builds a brand-new dict — that's how we avoid mutating the original products. round(x, 2) tidies the discounted price to 2 decimal places.

Putting It All Together · Inventory Inspector CLI

8 min

Save inspector.py. Wrap every task above into a menu-driven program that the user can drive.

Inside a while True: loop, offer:

1 Headlines (Task 1)
2 Stock alerts (Task 2)
3 Top single line (Task 3)
4 Group totals (Task 4)
5 Tag index (Task 5)
6 Promo (Task 6) — ask the user for the min_qty threshold
7 Quit

Show one possible solution

# inspector.py — menu-driven inventory inspector

products = [
    # ... paste your inventory.py products list here ...
]

def headlines():
    print("Products :", len(products))
    print("Units    :", sum([p["qty"] for p in products]))
    value = sum([p["qty"] * p["price"] for p in products])
    print("Value RM :", value)
    stalls = set([p["stall"] for p in products])
    print("Stalls   :", len(stalls), stalls)

def alerts():
    out = [p for p in products if p["qty"] == 0]
    low = [p for p in products if 0 < p["qty"] <= 10]
    for p in out:
        print("OUT —", p["sku"], p["name"])
    for p in low:
        print("LOW —", p["sku"], p["name"], "(", p["qty"], ")")
    print({"ALERTS": len(out) + len(low), "OUT": len(out), "LOW": len(low)})

def top_line():
    top = products[0]
    top_v = top["qty"] * top["price"]
    for p in products:
        v = p["qty"] * p["price"]
        if v > top_v:
            top, top_v = p, v
    print("Top single line:", top["sku"], top["name"], "— RM", top_v)

def group_totals():
    by_stall = {}
    for p in products:
        by_stall[p["stall"]] = by_stall.get(p["stall"], 0) + p["qty"] * p["price"]
    print(by_stall)

def tag_index():
    by_tag = {}
    for p in products:
        for tag in p["tags"]:
            if tag not in by_tag:
                by_tag[tag] = []
            by_tag[tag].append(p["name"])
    print(by_tag)

def promo(min_qty):
    out = []
    for p in products:
        if p["qty"] >= min_qty:
            out.append({"sku": p["sku"], "name": p["name"],
                        "price": round(p["price"] * 0.9, 2),
                        "was": p["price"]})
    print(out)

while True:
    print()
    print("1 headlines  2 alerts  3 top  4 stalls  5 tags  6 promo  7 quit")
    pick = input("Choose: ")
    if   pick == "1": headlines()
    elif pick == "2": alerts()
    elif pick == "3": top_line()
    elif pick == "4": group_totals()
    elif pick == "5": tag_index()
    elif pick == "6":
        n = int(input("min_qty: "))
        promo(n)
    elif pick == "7":
        print("Bye!")
        break
    else:
        print("Pick 1-7.")

Non-negotiables: every task wrapped in a named function, a menu loop, and at least one user-typed argument feeding into the promo function. Once it works, this file is a working CLI you could ship.

Recap

3 min

Twelve lessons of collections, all on one page. Filter with a comprehension. Sum a field with sum([p["f"] for p in data]). Find the best record by tracking the whole dict. Group by a category with the if-key-not-in recipe — for lists, or for running totals. Reach for a set whenever you need membership or unique items, and lean on set operators (&, |, -, ^) to answer combination questions in one line. Wrap each query in a function and you've got a working report tool.

What's next

You've mastered the four core collection shapes. Tomorrow we step sideways: split, join, strip, find — the string methods that turn messy text into clean data. Real-world data hardly ever arrives pre-bucketed; you usually have to slice it out of a string first.

Homework

4 min

Re-skin inspector.py for a topic you actually care about. Pick one of:

A list of your favourite games — fields: name, platform, hours-played, genres (list).
A list of movies — name, year, runtime, tags (list).
A list of football players — name, club, goals, positions (list).

Re-run all six tasks against your new dataset. Don't change the queries — only the data. Bring your re-skinned file to class.

Sample · games_inspector.py (top half)

# games_inspector.py — same six tasks, different dataset

games = [
    {"sku": "G01", "name": "Stardew Valley", "platform": "PC",     "price": 14.99, "qty": 1, "tags": ["farm", "indie", "cozy"]},
    {"sku": "G02", "name": "Celeste",        "platform": "Switch", "price": 19.99, "qty": 1, "tags": ["platformer", "indie"]},
    {"sku": "G03", "name": "Hades",          "platform": "PC",     "price": 24.99, "qty": 1, "tags": ["roguelike", "indie"]},
    {"sku": "G04", "name": "Hollow Knight",  "platform": "Switch", "price": 14.99, "qty": 1, "tags": ["metroidvania", "indie"]},
    # ...
]

# Task 1
print("Games on shelf :", len(games))
print("Distinct platforms:", set([g["platform"] for g in games]))

# Task 4 — group total spend by platform
by_platform = {}
for g in games:
    by_platform[g["platform"]] = by_platform.get(g["platform"], 0) + g["price"]
print(by_platform)

Same shape — different topic. The point is that the query logic is reusable; only the field names and dataset change. Bring your file and we'll combine it with classmates' in the next class.

Challenge — Inventory Inspector

⏱ 1 hour🧩 Challenge lesson📚 After PY-L2-12💻 VS Code or online-python.com

# inventory.py — Adva Warehouse stock list products = [ {"sku": "P001", "name": "pencil", "stall": "stationery", "price": 0.50, "qty": 120, "tags": ["writing", "wood"]}, {"sku": "P002", "name": "eraser", "stall": "stationery", "price": 0.80, "qty": 60, "tags": ["writing"]}, {"sku": "P003", "name": "ruler 30cm", "stall": "stationery", "price": 1.20, "qty": 18, "tags": ["measuring", "plastic"]}, {"sku": "P004", "name": "sharpener", "stall": "stationery", "price": 1.50, "qty": 8, "tags": ["writing", "metal"]}, {"sku": "F101", "name": "apple", "stall": "fruit", "price": 1.00, "qty": 40, "tags": ["fresh", "snack"]}, {"sku": "F102", "name": "banana", "stall": "fruit", "price": 0.40, "qty": 90, "tags": ["fresh", "snack"]}, {"sku": "F103", "name": "durian", "stall": "fruit", "price": 8.50, "qty": 5, "tags": ["fresh"]}, {"sku": "D201", "name": "milo", "stall": "drinks", "price": 4.50, "qty": 25, "tags": ["chocolate", "hot"]}, {"sku": "D202", "name": "kopi", "stall": "drinks", "price": 3.00, "qty": 35, "tags": ["caffeine", "hot"]}, {"sku": "D203", "name": "teh tarik", "stall": "drinks", "price": 3.50, "qty": 22, "tags": ["caffeine", "hot", "milk"]}, {"sku": "D204", "name": "cendol", "stall": "drinks", "price": 5.00, "qty": 0, "tags": ["sweet", "cold"]}, ]

print("Products :", len(products)) print("Units :", sum([p["qty"] for p in products])) value = 0 for p in products: value += p["qty"] * p["price"] print("Value RM :", value) stalls = set([p["stall"] for p in products]) print("Stalls :", len(stalls), stalls)

out = [p for p in products if p["qty"] == 0] low = [p for p in products if 0 < p["qty"] <= 10] for p in out: print("OUT —", p["sku"], p["name"]) for p in low: print("LOW —", p["sku"], p["name"], "(", p["qty"], ")") print({"ALERTS": len(out) + len(low), "OUT": len(out), "LOW": len(low)})

top = products[0] top_v = top["qty"] * top["price"] for p in products: v = p["qty"] * p["price"] if v > top_v: top = p top_v = v print("Top single line:", top["sku"], top["name"], "— RM", top_v, " (", top["qty"], "units ×", top["price"], ")")

by_stall = {} for p in products: stall = p["stall"] value = p["qty"] * p["price"] if stall not in by_stall: by_stall[stall] = 0 by_stall[stall] += value print(by_stall) top_stall = "" top_value = 0 for stall, v in by_stall.items(): if v > top_value: top_value = v top_stall = stall print("Top stall:", top_stall, "(RM", top_value, ")")

by_tag = {} for p in products: for tag in p["tags"]: if tag not in by_tag: by_tag[tag] = [] by_tag[tag].append(p["name"]) print(by_tag) top_tag = "" top_n = 0 for tag, names in by_tag.items(): if len(names) > top_n: top_n = len(names) top_tag = tag print("Top tag:", top_tag, "(", top_n, ")") both = set(by_tag["writing"]) & set(by_tag["metal"]) print("Writing AND metal:", both)

def make_promo(min_qty=20): promo = [] for p in products: if p["qty"] >= min_qty: promo.append({ "sku": p["sku"], "name": p["name"], "price": round(p["price"] * 0.9, 2), "was": p["price"], "qty": p["qty"], }) return promo print(make_promo()) print() print(make_promo(50))

# inspector.py — menu-driven inventory inspector products = [ # ... paste your inventory.py products list here ... ] def headlines(): print("Products :", len(products)) print("Units :", sum([p["qty"] for p in products])) value = sum([p["qty"] * p["price"] for p in products]) print("Value RM :", value) stalls = set([p["stall"] for p in products]) print("Stalls :", len(stalls), stalls) def alerts(): out = [p for p in products if p["qty"] == 0] low = [p for p in products if 0 < p["qty"] <= 10] for p in out: print("OUT —", p["sku"], p["name"]) for p in low: print("LOW —", p["sku"], p["name"], "(", p["qty"], ")") print({"ALERTS": len(out) + len(low), "OUT": len(out), "LOW": len(low)}) def top_line(): top = products[0] top_v = top["qty"] * top["price"] for p in products: v = p["qty"] * p["price"] if v > top_v: top, top_v = p, v print("Top single line:", top["sku"], top["name"], "— RM", top_v) def group_totals(): by_stall = {} for p in products: by_stall[p["stall"]] = by_stall.get(p["stall"], 0) + p["qty"] * p["price"] print(by_stall) def tag_index(): by_tag = {} for p in products: for tag in p["tags"]: if tag not in by_tag: by_tag[tag] = [] by_tag[tag].append(p["name"]) print(by_tag) def promo(min_qty): out = [] for p in products: if p["qty"] >= min_qty: out.append({"sku": p["sku"], "name": p["name"], "price": round(p["price"] * 0.9, 2), "was": p["price"]}) print(out) while True: print() print("1 headlines 2 alerts 3 top 4 stalls 5 tags 6 promo 7 quit") pick = input("Choose: ") if pick == "1": headlines() elif pick == "2": alerts() elif pick == "3": top_line() elif pick == "4": group_totals() elif pick == "5": tag_index() elif pick == "6": n = int(input("min_qty: ")) promo(n) elif pick == "7": print("Bye!") break else: print("Pick 1-7.")