Price-drop alert

Goal

Analyse a month of a product's prices: the lowest day, how often it fell, a one-line chart, the days it hit your target and whether to buy today.

Why it matters

Every list problem you will meet (min, index, comparing neighbours, filtering) shows up here, on data you actually care about before a sale.

What it proves

You can analyse a list of numbers with loops and comprehensions and turn it into a decision.

Steps · 6 checkpoints

Each step is one function in price_alert.py. In the workspace, press Check next to a step: it runs your file and tells you exactly what is still wrong. Step 1 is free; the rest are part of Pro or your 7-day free trial.

1. 1The lowest price and its day. Write lowest(prices): return a (price, day) tuple for the lowest price, with days counted from 1. Here that is (20999, 26).
2. 2Days the price fell. Write drop_days(prices): the days (from 1) when the price was lower than the day before. Day 1 can never be a drop. For [5, 4, 4, 6, 3] that is [2, 5].
3. 3A chart in one line. Write sparkline(prices): one character from ▁▂▃▄▅▆▇█ per price, lowest ▁ and highest █. The level is round((price - low) / (high - low) * 7). If every price is the same, use ▁ for all of them.
4. 4Days you could have bought. Write days_at_or_below(prices, target): the days (from 1) when the price was at or below target. With a target of 21,500 that is [22, 26, 27].
5. 5Buy or wait. Write verdict(prices, target) using today's price, the last one. At or below target: BUY: ₹21,999 is at or below your ₹22,000. Otherwise: WAIT: ₹499 above your ₹21,500.
6. 6The full alert. In main(), print the verdict for TARGET as the last line. The check reads everything your program printed.

Requirements · rubric

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

• 01lowest() returns the price and its day, counting days from 1
• 02drop_days() compares each day with the day before
• 03sparkline() scales prices to eight levels and handles equal prices
• 04days_at_or_below() and verdict() treat a price equal to the target as a buy
• 05The program prints the full alert

Starter code

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

"""
Price-drop alert.

Reads 30 days of a phone's price, draws a sparkline, finds the best day
and says whether to buy today. Fill in one function per step, press Run,
then press "Check" on that step.
"""

TARGET = 21500  # buy when the price is at or below this (₹)

# One price per day for the last 30 days (sample data)
PRICES = [24999, 24999, 24499, 24999, 23999, 23999, 24499, 22999, 22999, 23499,
          23999, 23999, 22499, 22999, 23499, 21999, 21999, 22999, 23499, 23999,
          22999, 21499, 21999, 22499, 22999, 20999, 21499, 21999, 22499, 21999]


def lowest(prices: list[int]) -> tuple[int, int]:
    # TODO: return (lowest price, the day it happened). Days count from 1,
    # so the first price is day 1. Hint: min() and list.index().
    raise NotImplementedError("step 1, lowest(): the lowest price and its day")


def drop_days(prices: list[int]) -> list[int]:
    # TODO: the days (counting from 1) when the price was lower than the
    # day before. Day 1 has no day before it, so it is never a drop.
    raise NotImplementedError("step 2, drop_days(): days the price fell")


def sparkline(prices: list[int]) -> str:
    # TODO: one character per price from "▁▂▃▄▅▆▇█": the lowest price gets
    # ▁, the highest █, the rest in between.
    # level = round((price - low) / (high - low) * 7)
    raise NotImplementedError("step 3, sparkline(): a chart in one line of text")


def days_at_or_below(prices: list[int], target: int) -> list[int]:
    # TODO: the days (from 1) when the price was at or below target.
    raise NotImplementedError("step 4, days_at_or_below(): days you could have bought")


def verdict(prices: list[int], target: int) -> str:
    # TODO: look at today's price (the last one).
    # At or below target: "BUY: ₹21,999 is at or below your ₹22,000"
    # Otherwise:          "WAIT: ₹499 above your ₹21,500"
    raise NotImplementedError("step 5, verdict(): buy today or wait")


def main() -> None:
    low, day = lowest(PRICES)
    print(f"Lowest ₹{low:,} on day {day}")
    print(f"Fell on {len(drop_days(PRICES))} of 30 days")
    print(f"30 days  {sparkline(PRICES)}")
    hits = days_at_or_below(PRICES, TARGET)
    print(f"At or below ₹{TARGET:,} on days {hits}")
    result = verdict(PRICES, TARGET)
    # TODO: print result as the last line.
    raise NotImplementedError("step 6, main(): print the verdict")


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.")