Your starting snippet is precisely where I began a year ago. Scaling to 1000+ is definitely feasible, but reliability hinges entirely on your error handling and state management, not just adding delays. I'd categorize the failure modes you'll encounter into three tiers:
1. Transient network/rate limit errors (retry with backoff)
2. Permanent API errors (invalid parameters, auth issues - log and skip)
3. Script/process crashes (requires persisting state outside the script's memory)
Your CSV loop needs to evolve into a state machine. I treat each row as a finite state object: `pending` -> `submitted` -> `completed`/`failed`. The critical step is moving a row to `submitted` and logging the attempt with a unique attempt ID *before* the API call is even made. That way, a crash doesn't result in duplicate submissions.
A fixed delay is rarely sufficient. The Rytr API, like many, uses a token bucket algorithm for rate limiting. You need to parse the `Retry-After` header on a 429 response and implement exponential backoff. My production script uses a simple priority queue where failed jobs are re-enqueued with an increasing delay multiplier.
The real bottleneck for me wasn't the API, but managing the output. Generating 1000 HTML product descriptions means you now have 1000 pieces of text to validate, store, and potentially post-process. I'd recommend generating the content into individual files keyed by your row UUID, not just a single monolithic JSON array. It makes partial retries and downstream processing trivial.
Measure twice, cut once.
That's the exact same starting point I used, just with Python! It's encouraging to see the core API call is that straightforward.
I'm also curious about scaling. When you say "in one go," do you mean like, firing off 1000 requests as fast as possible? Because I think that's where the trouble starts. Did the docs give you any hints about rate limits, or did you just have to find out by hitting them?
CloudNewbie
That snippet is the classic starting point, I've written that same call a dozen times. You've nailed the core question. Moving from 50 to 1000+ is less about the API itself and more about treating your script as a production batch job, even if it's a one-off.
The critical flaw in that simple loop is the lack of idempotency. If your script crashes at request 750, you have no clean way to restart without generating duplicates or missing items. The advice here about logging the attempt with a UUID *before* the call is key, but I'd extend that: you need to store the returned `ryteId` (or whatever they call it) from the successful response immediately. That's your only real proof of creation in Rytr's system, and you'll need it for any later audit or reconciliation. Their support will ask for those IDs if you have a billing discrepancy.
Did you check if their API returns any headers about remaining rate limit quota? For truly large batches, you'd want your delay logic to be dynamic, based on that, rather than a fixed sleep timer.
Logs don't lie.
Your point about idempotency is correct, but storing the returned `ryteId` assumes their API provides it in the immediate response for a bulk request. Many services only give you a job ID, and the actual content IDs come later in a separate callback or status check. You might be logging a promise, not a proof.
Dynamic delays based on headers are ideal, but that's expecting a level of API polish that's often not there. Most of these services just give you a 429 and expect you to guess.
Your vendor is not your friend.
> "generate, say, 1000+ pieces in one go"
That's where you'll hit the wall. APIs like this aren't built for bulk dumps. Your loop will crumble without persistent state and retry logic. I've seen Jenkins jobs fail for less.
Skip the hype and write a proper batch script. Process in chunks, log each attempt to a file, and handle failures manually. It's ugly, but it works.
-- old school
Scaling that snippet is a classic "works on my machine" trap. You'll hit rate limits they don't publish, and your script will die somewhere after request 200.
Your biggest problem isn't the API, it's trusting a loop with no state. When it crashes, you'll have zero idea what succeeded. Everyone here is overcomplicating it. Just log each product's raw input and the returned ID to a simple text file *before* you move to the next row. No fancy queues needed. If it fails, you can at least see the last line that worked.
CRM is a necessary evil
No, with only 50 requests I didn't see any noticeable throttling or slowdown. The responses came back at roughly the same speed.
That's precisely why it's a trap, though. At 50 you're operating in the warm-up lane where everything looks fine. You won't see the real throttling behavior until you push into the hundreds in a sustained loop. I never rely on small batch tests to guess the rate limit. You need to implement a proper exponential backoff from the start, based on 429 or 5xx responses, not a pre-set delay.
Your script should assume throttling exists and handle it reactively, not try to guess a safe static delay upfront.
Automate everything. Twice.