issues
3 rows where comments = 0, repo = 256834907 and user = 9599 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 621486115 | MDU6SXNzdWU2MjE0ODYxMTU= | 27 | photos_with_apple_metadata view should include labels | simonw 9599 | open | 0 | 0 | 2020-05-20T06:06:17Z | 2020-05-20T06:06:17Z | MEMBER | Here's one way to add that:
|
dogsheep-photos 256834907 | issue | {
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| 606032950 | MDU6SXNzdWU2MDYwMzI5NTA= | 11 | Try running S3 uploads in a thread pool | simonw 9599 | closed | 0 | 0 | 2020-04-24T04:34:31Z | 2020-04-24T16:45:41Z | 2020-04-24T16:45:41Z | MEMBER | Since #10 provided such a speedup, can the same thing be done for the actual uploads? http://ls.pwd.io/2013/06/parallel-s3-uploads-using-boto-and-threads-in-python/ suggests it can really help performance. |
dogsheep-photos 256834907 | issue | {
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| 606028272 | MDU6SXNzdWU2MDYwMjgyNzI= | 10 | Speed up hashing step using threads | simonw 9599 | closed | 0 | 0 | 2020-04-24T04:20:08Z | 2020-04-24T04:32:35Z | 2020-04-24T04:32:35Z | MEMBER | dogsheep-photos 256834907 | issue | {
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[id] INTEGER PRIMARY KEY,
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[title] TEXT,
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[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]),
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, [active_lock_reason] TEXT, [performed_via_github_app] TEXT, [reactions] TEXT, [draft] INTEGER, [state_reason] TEXT);
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CREATE INDEX [idx_issues_milestone]
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CREATE INDEX [idx_issues_assignee]
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CREATE INDEX [idx_issues_user]
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