html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,issue,performed_via_github_app
https://github.com/simonw/datasette/issues/1062#issuecomment-1260909128,https://api.github.com/repos/simonw/datasette/issues/1062,1260909128,IC_kwDOBm6k_c5LJ_JI,536941,2022-09-28T13:22:53Z,2022-09-28T14:09:54Z,CONTRIBUTOR,"if you went this route:

```python
with sqlite_timelimit(conn, time_limit_ms):
     c.execute(query)
     for chunk in c.fetchmany(chunk_size):
         yield from chunk
```

then `time_limit_ms` would probably have to be greatly extended, because the time spent in the loop will depend on the downstream processing.

i wonder if this was why you were thinking this feature would need a dedicated connection?

---

reading more, there's no real limit i can find on the number of active cursors (or more precisely active prepared statements objects, because sqlite doesn't really have cursors). 

maybe something like this would be okay?

```python
with sqlite_timelimit(conn, time_limit_ms):
     c.execute(query)
     # step through at least one to evaluate the statement, not sure if this is necessary
     yield c.execute.fetchone()
for chunk in c.fetchmany(chunk_size):
    yield from chunk
```

this seems quite weird that there's not more of limit of the number of active prepared statements, but i haven't been able to find one.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",732674148,
https://github.com/simonw/datasette/issues/1062#issuecomment-1260829829,https://api.github.com/repos/simonw/datasette/issues/1062,1260829829,IC_kwDOBm6k_c5LJryF,536941,2022-09-28T12:27:19Z,2022-09-28T12:27:19Z,CONTRIBUTOR,"for teaching `register_output_renderer` to stream it seems like the two options are to

1. a [nested query technique ](https://github.com/simonw/datasette/issues/526#issuecomment-505162238)to paginate through
2. a fetching model that looks like something
```python
with sqlite_timelimit(conn, time_limit_ms):
     c.execute(query)
     for chunk in c.fetchmany(chunk_size):
         yield from chunk
```
currently `db.execute` is not a generator, so this would probably need a new method?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",732674148,