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5 rows where number = 3, state = "open" and type = "issue" sorted by updated_at descending
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id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | pull_request | body | repo | type | active_lock_reason | performed_via_github_app | reactions | draft | state_reason |
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602533481 | MDU6SXNzdWU2MDI1MzM0ODE= | 3 | Import EXIF data into SQLite - lens used, ISO, aperture etc | simonw 9599 | open | 0 | Apple Photos online and securely browsable 5324096 | 2 | 2020-04-18T19:24:31Z | 2021-10-05T12:38:24Z | MEMBER | dogsheep-photos 256834907 | issue | { "url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/3/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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952189173 | MDU6SXNzdWU5NTIxODkxNzM= | 3 | Use HN algolia endpoint to retrieve trees | simonw 9599 | open | 0 | 3 | 2021-07-25T03:35:27Z | 2021-07-25T18:41:17Z | MEMBER | The
Here's an example that loads quickly, with about 50 comments: https://hn.algolia.com/api/v1/items/27941108 It doesn't appear to use pagination at all - if a thread is big then the response is big. I ran this search to find some stories with more than 1000 comments: https://hn.algolia.com/api/v1/search?tags=story&numericFilters=num_comments%3E=1000 Here's one: https://news.ycombinator.com/item?id=25015967 with 4759 comments. Hitting the API takes 41s and returns 3.7 MB of JSON!
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hacker-news-to-sqlite 248903544 | issue | { "url": "https://api.github.com/repos/dogsheep/hacker-news-to-sqlite/issues/3/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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769397742 | MDU6SXNzdWU3NjkzOTc3NDI= | 3 | sqlite-utils error on takeout import | khimaros 231498 | open | 0 | 0 | 2020-12-17T01:18:48Z | 2020-12-17T01:19:04Z | NONE |
there is no table create in additionally, this package and hackernews-to-sqlite have conflicting |
google-takeout-to-sqlite 206649770 | issue | { "url": "https://api.github.com/repos/dogsheep/google-takeout-to-sqlite/issues/3/reactions", "total_count": 2, "+1": 2, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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503243784 | MDU6SXNzdWU1MDMyNDM3ODQ= | 3 | Extract images into separate tables | simonw 9599 | open | 0 | 1 | 2019-10-07T05:43:01Z | 2020-09-01T06:17:45Z | MEMBER | As already done with authors. Slightly harder because images do not have a universally unique ID. Also need to figure out what to do about there being columns for both |
pocket-to-sqlite 213286752 | issue | { "url": "https://api.github.com/repos/dogsheep/pocket-to-sqlite/issues/3/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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267515678 | MDU6SXNzdWUyNjc1MTU2Nzg= | 3 | Make individual column valuables addressable, with smart content types | simonw 9599 | open | 0 | 1 | 2017-10-23T01:11:32Z | 2017-12-10T03:11:58Z | OWNER | Some SQLite databases embed images in columns. It would be cool if these had URLs.
The one without an explicit file extension auto-detects the correct extension. |
datasette 107914493 | issue | { "url": "https://api.github.com/repos/simonw/datasette/issues/3/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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CREATE TABLE [issues] ( [id] INTEGER PRIMARY KEY, [node_id] TEXT, [number] INTEGER, [title] TEXT, [user] INTEGER REFERENCES [users]([id]), [state] TEXT, [locked] INTEGER, [assignee] INTEGER REFERENCES [users]([id]), [milestone] INTEGER REFERENCES [milestones]([id]), [comments] INTEGER, [created_at] TEXT, [updated_at] TEXT, [closed_at] TEXT, [author_association] TEXT, [pull_request] TEXT, [body] TEXT, [repo] INTEGER REFERENCES [repos]([id]), [type] TEXT , [active_lock_reason] TEXT, [performed_via_github_app] TEXT, [reactions] TEXT, [draft] INTEGER, [state_reason] TEXT); CREATE INDEX [idx_issues_repo] ON [issues] ([repo]); CREATE INDEX [idx_issues_milestone] ON [issues] ([milestone]); CREATE INDEX [idx_issues_assignee] ON [issues] ([assignee]); CREATE INDEX [idx_issues_user] ON [issues] ([user]);