> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wandb.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# How do I page through large API results in W&B?

You can page through API result using the [standard lazy-iterator pattern and `per_page` parameter](/models/track/public-api-guide). Additionally, you can use the following checkpointing and bulk-download tips to more effectively page through the results.

## Checkpoint processed run IDs

For very large projects, record IDs you have already handled and skip them on restart:

```python theme={null}
import json
import pathlib
import wandb

checkpoint_file = pathlib.Path("processed_ids.json")
processed = set(json.loads(checkpoint_file.read_text())) if checkpoint_file.exists() else set()

api = wandb.Api()
for run in api.runs("my-entity/my-project"):
    if run.id in processed:
        continue
    process(run)
    processed.add(run.id)
    checkpoint_file.write_text(json.dumps(list(processed)))
```

Avoid `list(api.runs(...))` on huge projects unless you need random access — it forces every page into memory.

## Rate limits on bulk downloads

If each run triggers extra API calls (for example `run.file("output.log").download()`), add a short delay to avoid `429` errors:

```python theme={null}
import time

for run in api.runs("my-entity/my-project"):
    run.file("output.log").download()
    time.sleep(0.1)
```

***

<Badge stroke shape="pill" color="orange" size="md">[Runs](/support/models/tags/runs)</Badge><Badge stroke shape="pill" color="orange" size="md">[Experiments](/support/models/tags/experiments)</Badge><Badge stroke shape="pill" color="orange" size="md">[API](/support/models/tags/api)</Badge><Badge stroke shape="pill" color="orange" size="md">[Artifacts](/support/models/tags/artifacts)</Badge>