03-stream-processor

Exercise 03 - Stream dangerous sightings from CSV

The scenario

Field teams export sighting data as CSV files that can grow to hundreds of megabytes. Loading the entire file into memory with readFile would spike the process and risk an out-of-memory crash. Instead, the park's tooling reads CSV data as a stream — processing one line at a time so memory stays flat regardless of file size.

You'll build a stream-based CSV filter that reads a trackingId,dangerLevel,zone file line by line, skips the header, parses each row, and collects only the rows above a danger threshold.

What you will build

streamFilterDangerous(filePath, minDanger) — in starter/stream-filter.js

• Use fs.createReadStream plus readline.createInterface to read the file line by line.
• Skip the first line (the CSV header).
• For each data row, split on commas, parse dangerLevel as an integer, and keep rows where dangerLevel >= minDanger.
• Return a Promise that resolves to an array of matching objects:

[
  { trackingId: 'TRX-001', dangerLevel: 5, zone: 'Cretaceous Valley' },
  { trackingId: 'VLR-042', dangerLevel: 4, zone: 'Raptor Ridge' },
]

The test fixture CSV looks like:

trackingId,dangerLevel,zone
TRX-001,5,Cretaceous Valley
BNT-003,2,Herbivore Plains
VLR-042,4,Raptor Ridge

Getting started

Open starter/stream-filter.js. Replace the stub. There's a fixture.csv in the starter directory for testing. Then run:

node starter/index.js

Verify

cd starter && pnpm install && pnpm test

The test reads the fixture with minDanger: 4 and expects exactly two rows.

Hints

• readline.createInterface({ input: createReadStream(filePath) }) gives you an async iterable of lines.
• Use for await (const line of rl) to process each line.
• Skip the first line with a boolean flag.
• const [trackingId, dangerRaw, zone] = line.split(',') destructures each CSV row.
• Number(dangerRaw) converts the string; check Number.isFinite() to reject garbage.

Reference solution

solution/stream-filter.js