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2 rows where issue = 732674148 and "updated_at" is on date 2022-09-28
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id ▼ | html_url | issue_url | node_id | user | created_at | updated_at | author_association | body | reactions | issue | performed_via_github_app |
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1260829829 | https://github.com/simonw/datasette/issues/1062#issuecomment-1260829829 | https://api.github.com/repos/simonw/datasette/issues/1062 | IC_kwDOBm6k_c5LJryF | fgregg 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} | Refactor .csv to be an output renderer - and teach register_output_renderer to stream all rows 732674148 | |
1260909128 | https://github.com/simonw/datasette/issues/1062#issuecomment-1260909128 | https://api.github.com/repos/simonw/datasette/issues/1062 | IC_kwDOBm6k_c5LJ_JI | fgregg 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} | Refactor .csv to be an output renderer - and teach register_output_renderer to stream all rows 732674148 |
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