Pull product data over an API
Search volume for "<retailer> API documentation" is enormous and the documentation mostly does not exist. Amazon, Walmart, Target, Home Depot — developers keep looking for a product endpoint that was never published, or that was published and then locked behind a partner agreement. So you end up calling a web data API instead: something that takes a URL and gives you back the fields. This course is about doing that properly, from the first authenticated request to a feed your warehouse can depend on.
What you will be able to do
- Decide between an official retailer API, a web data API and writing your own scraper, with reasons you can defend in review
- Make an authenticated request and read the response without guessing what the fields mean
- Declare a schema so the extractor returns the fields you need rather than the ones it felt like returning
- Work with asynchronous runs: start, poll, and handle a job that finishes half-done
- Retry a failed request without being billed twice for the same page
- Land the result in a warehouse table that does not quietly drift out of date
The six lessons
Lessons one and two are short and assume nothing but curl. From three onwards you will get more out of it with a key in your hand.
- 01When an API beats writing your own scraperThree ways to get product data, the honest cost of each, and the specific question that decides between them.10 min read Read lesson 1 →
- 02Authentication, keys, and your first real requestBearer tokens versus query-string keys, where to keep the secret, and how to read the first response you get back.10 min read Read lesson 2 →
- 03Declaring a schema, and why your fields came back emptyNeeds an accountAn extractor returns what you asked for, and most people ask badly. How to declare fields, why types matter, and the one mistake that silently drops a column.12 min read Read lesson 3 →
- 04Asynchronous runs, polling, and partial resultsWhy collection APIs hand back a job rather than data, how to poll without hammering, and what to do with a run that finished eighty per cent done.11 min read Read lesson 4 →
- 05Errors, retries, and not paying twiceWhich failures are worth retrying, how idempotency keys stop a retry becoming a second invoice, and the error class that means stop rather than try harder.11 min read Read lesson 5 →
- 06Putting the feed into your stack without it driftingNeeds an accountScheduling, loading, and the schema decisions that determine whether a price feed is still trustworthy in six months.12 min read Read lesson 6 →
Who this is for
Written for
- Developers who have been told to "get the competitor prices" and have discovered the retailer has no public API
- Data engineers deciding whether to own the collection layer or buy it
- Backend teams wiring a third-party feed into an existing pipeline and wanting to know where it will break
Not written for
- Readers looking for a no-code setup — course one covers the same ground without a terminal
- Anyone wanting a specific vendor's endpoint reference. This is the shape of the problem; the reference lives in that vendor's docs.
Before you start
The questions developers ask in the first ten minutes.
No, deliberately. Endpoint names change and a course that hardcodes them rots. What does not change is the shape: authenticate, declare what you want, start a run, poll it, handle partial results, retry safely. Learn the shape and any vendor's reference becomes a lookup rather than a tutorial.
Start at lesson one
Three ways to get product data, the honest cost of each, and the specific question that decides between them.