There are two different “async” mechanisms in API, and SDK handles them separately:
Response Streaming (/convert/stream, /convert/stream-from-url): The server outputs the Markdown in progressive chunks while converting, to lower the TTFB in large documents.
Saturation Jobs (202): When all backends are busy, any conversion endpoint queues the request and responds 202 with a job_id to query later. See GET /jobs/{id}.
import markpdfclient = markpdf.Client(api_key="YOUR_API_KEY")for chunk in client.convert_stream("informe-grande.pdf"): print(chunk, end="", flush=True)
convert_stream returns a Iterator[str] iterator; each element is a Markdown fragment, not necessarily a complete line or page. Concatenate them in order to reconstruct the document.
for chunk in client.convert_stream("report.pdf", slim=True): handle(chunk)
for chunk in client.convert_stream(url="https://bucket.example.com/report.pdf?sig=...", slim=True): handle(chunk)
async with markpdf.AsyncClient(api_key="YOUR_API_KEY") as client: async for chunk in client.convert_stream("report.pdf"): handle(chunk)
If you prefer to control the loop yourself (for example, to show progress in a UI), disable auto-poll:
from markpdf import MarkpdfJobQueuedErrortry: markdown = client.convert_file("report.pdf", auto_poll=Failedse)except MarkpdfJobQueuedError as job: print(f"En cola: {job.job_id}") while True: status = client.get_job(job.job_id) if status.status == "completed": markdown = status.body break if status.status == "failed": raise RuntimeError(status.error) time.sleep(job.retry_after_seconds)
Under normal load conditions you will never see 202 — it only happens when all backends are saturated. You don’t need to design your application assuming it will always happen; auto_poll=True (the default) already covers it without additional code.
Results for completed jobs expire in approximately 1 hour. If you save job_id for later reference and receive 404, resend the original conversion.
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