Expense tracker with CSV

Goal

Record a student's expenses, refuse bad amounts, save them to expenses.csv with the csv module, load them back, and print this month's total and a per-category breakdown with the biggest category's share.

Why it matters

Saving and loading data is the step that turns a script into a tool. The csv module handles the cases a string join gets wrong, like a note with a comma in it, and you will see exactly why.

What it proves

You can validate input, write and read a file with the csv module, and summarise rows with a dict.

Steps · 6 checkpoints

Each step is one function in expenses.py. In the workspace, press Check next to a step: it runs your file and tells you exactly what is still wrong.

1. 1Record one expense. Write add_expense(): refuse an amount of 0 or less with ValueError, clean the category (strip + lowercase), store amount as a float, append the row and return it.
2. 2Save to CSV with a header. Write save_csv(rows, path): csv.DictWriter with FIELDS, a header row first, one line per expense.
3. 3Load it back. Write load_csv(path): return [] when the file is missing, otherwise csv.DictReader rows with amount turned back into a float.
4. 4One month's total. Write monthly_total(rows, month): add up the amounts whose date starts with the month, e.g. "2026-09".
5. 5Totals per category, biggest first. Write total_by_category(rows): a dict of category to total, ordered from the biggest total to the smallest.
6. 6Biggest category and the full summary. In main(), print the biggest category and its share of all spending: Biggest category: rent (77.6% of ₹8,379). The check reads everything your program printed.

Requirements · rubric

Build against this exact list — it is the spec your published project is judged on.

• 01add_expense() refuses amounts of 0 or less with ValueError
• 02save_csv() writes a header and quotes fields that contain commas
• 03load_csv() returns [] on a first run and turns amounts back into numbers
• 04monthly_total() and total_by_category() are correct, biggest category first
• 05The summary prints the month's total, each category and the biggest one's share

Starter code

Copy this into a new file — or open it in a workspace as expenses.py. The TODO parts are yours to fill.

"""
Expense tracker with CSV.

Records expenses, saves them to expenses.csv, loads them back and prints
where the money went. Uses only the csv module from the standard library.
Fill in one function per step, press Run, then press "Check step".
"""

import csv
from pathlib import Path

CSV_PATH = Path("expenses.csv")
FIELDS = ["date", "category", "amount", "note"]

SEED = [
    ("2026-08-28", "food", 240, "canteen thali"),
    ("2026-08-30", "travel", 60, "metro card top-up"),
    ("2026-09-01", "rent", 6500, "PG rent share"),
    ("2026-09-02", "food", 180, "chai + samosa x6"),
    ("2026-09-04", "books", 450, "DSA book, second hand"),
    ("2026-09-05", "travel", 120, "auto to college"),
    ("2026-09-07", "food", 320, "birthday treat"),
    ("2026-09-09", "recharge", 299, "Jio monthly"),
    ("2026-09-12", "food", 210, "mess extra"),
]


def add_expense(rows: list[dict], date: str, category: str, amount: float, note: str = "") -> dict:
    # TODO: refuse amount <= 0 with ValueError. Otherwise build
    # {"date", "category" (stripped + lowercase), "amount" (float), "note"},
    # append it to rows and return it.
    raise NotImplementedError("step 1, add_expense(): validate and append one row")


def save_csv(rows: list[dict], path: Path = CSV_PATH) -> None:
    # TODO: open(path, "w", newline="", encoding="utf-8"), then
    # csv.DictWriter(f, fieldnames=FIELDS) -> writeheader() -> writerows(rows)
    raise NotImplementedError("step 2, save_csv(): write rows with a header")


def load_csv(path: Path = CSV_PATH) -> list[dict]:
    # TODO: return [] if the file does not exist. Otherwise read it with
    # csv.DictReader. CSV gives back strings, so turn "amount" into a float.
    raise NotImplementedError("step 3, load_csv(): read the rows back")


def monthly_total(rows: list[dict], month: str) -> float:
    # TODO: sum the amounts whose date starts with month, e.g. "2026-09"
    raise NotImplementedError("step 4, monthly_total(): one month's spending")


def total_by_category(rows: list[dict]) -> dict[str, float]:
    # TODO: {category: total}, biggest total first.
    # Hint: sorted(totals.items(), key=lambda kv: kv[1], reverse=True)
    raise NotImplementedError("step 5, total_by_category(): totals, biggest first")


def main() -> None:
    rows: list[dict] = []
    for date, cat, amount, note in SEED:
        add_expense(rows, date, cat, amount, note)
    save_csv(rows)
    rows = load_csv()
    print(f"Loaded {len(rows)} expenses from {CSV_PATH}")
    print(f"September 2026: ₹{monthly_total(rows, '2026-09'):,.0f}")
    totals = total_by_category(rows)
    for cat, amt in totals.items():
        print(f"  {cat:<10} ₹{amt:>8,.0f}")
    # TODO: print the biggest category and its share of all spending:
    # "Biggest category: rent (77.6% of ₹8,379)"
    raise NotImplementedError("step 6, main(): print the biggest category")


if __name__ == "__main__":
    try:
        main()
    except NotImplementedError as todo:
        # A fresh starter is SUPPOSED to stop here. Say which step is next
        # instead of printing a traceback that looks like a bug.
        print(f"Not built yet: {todo}")
        print("Write that function, then press Run again. Each step you finish moves this message forward.")

Reference solution

"""
Expense tracker with CSV.

Records expenses, saves them to expenses.csv, loads them back and prints
where the money went. Uses only the csv module from the standard library.
"""

import csv
from pathlib import Path

CSV_PATH = Path("expenses.csv")
FIELDS = ["date", "category", "amount", "note"]

SEED = [
    ("2026-08-28", "food", 240, "canteen thali"),
    ("2026-08-30", "travel", 60, "metro card top-up"),
    ("2026-09-01", "rent", 6500, "PG rent share"),
    ("2026-09-02", "food", 180, "chai + samosa x6"),
    ("2026-09-04", "books", 450, "DSA book, second hand"),
    ("2026-09-05", "travel", 120, "auto to college"),
    ("2026-09-07", "food", 320, "birthday treat"),
    ("2026-09-09", "recharge", 299, "Jio monthly"),
    ("2026-09-12", "food", 210, "mess extra"),
]


def add_expense(rows: list[dict], date: str, category: str, amount: float, note: str = "") -> dict:
    if amount <= 0:
        raise ValueError("amount must be more than 0")
    row = {"date": date, "category": category.strip().lower(), "amount": float(amount), "note": note}
    rows.append(row)
    return row


def save_csv(rows: list[dict], path: Path = CSV_PATH) -> None:
    with open(path, "w", newline="", encoding="utf-8") as f:
        writer = csv.DictWriter(f, fieldnames=FIELDS)
        writer.writeheader()
        writer.writerows(rows)


def load_csv(path: Path = CSV_PATH) -> list[dict]:
    if not Path(path).exists():
        return []
    with open(path, newline="", encoding="utf-8") as f:
        return [{**r, "amount": float(r["amount"])} for r in csv.DictReader(f)]


def total_by_category(rows: list[dict]) -> dict[str, float]:
    totals: dict[str, float] = {}
    for r in rows:
        totals[r["category"]] = totals.get(r["category"], 0) + r["amount"]
    return dict(sorted(totals.items(), key=lambda kv: kv[1], reverse=True))


def monthly_total(rows: list[dict], month: str) -> float:
    return sum(r["amount"] for r in rows if r["date"].startswith(month))


def main() -> None:
    rows: list[dict] = []
    for date, cat, amount, note in SEED:
        add_expense(rows, date, cat, amount, note)
    save_csv(rows)
    rows = load_csv()
    print(f"Loaded {len(rows)} expenses from {CSV_PATH}")
    print(f"September 2026: ₹{monthly_total(rows, '2026-09'):,.0f}")
    totals = total_by_category(rows)
    for cat, amt in totals.items():
        print(f"  {cat:<10} ₹{amt:>8,.0f}")
    grand = sum(totals.values())
    top = next(iter(totals))
    print(f"Biggest category: {top} ({totals[top] / grand * 100:.1f}% of ₹{grand:,.0f})")


if __name__ == "__main__":
    main()