github
html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | issue | performed_via_github_app |
---|---|---|---|---|---|---|---|---|---|---|---|
https://github.com/dogsheep/twitter-to-sqlite/issues/39#issuecomment-606843224 | https://api.github.com/repos/dogsheep/twitter-to-sqlite/issues/39 | 606843224 | MDEyOklzc3VlQ29tbWVudDYwNjg0MzIyNA== | 9599 | 2020-03-31T19:59:11Z | 2020-03-31T20:06:32Z | MEMBER | Or... have a single `since_ids` table to track since values, and have its primary key be a string that looks something like this: `user:123145` `home:23441` `mentions:23425` `search:99ff9cefff5cbfd804f7cd43e2b27ced8addbe8d` That last example would use the hash generated here: https://github.com/dogsheep/twitter-to-sqlite/blob/810cb2af5a175837204389fd7f4b5721f8b325ab/twitter_to_sqlite/cli.py#L792-L808 | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
590666760 | |
https://github.com/dogsheep/twitter-to-sqlite/issues/39#issuecomment-606844521 | https://api.github.com/repos/dogsheep/twitter-to-sqlite/issues/39 | 606844521 | MDEyOklzc3VlQ29tbWVudDYwNjg0NDUyMQ== | 9599 | 2020-03-31T20:01:39Z | 2020-03-31T20:01:39Z | MEMBER | I think `utils.fetch_timeline()` grows a new argument, `since_key`. | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
590666760 | |
https://github.com/dogsheep/twitter-to-sqlite/issues/39#issuecomment-606824992 | https://api.github.com/repos/dogsheep/twitter-to-sqlite/issues/39 | 606824992 | MDEyOklzc3VlQ29tbWVudDYwNjgyNDk5Mg== | 9599 | 2020-03-31T19:24:23Z | 2020-03-31T19:24:23Z | MEMBER | The `--since` option is actually used by four commands: * `user-timeline` * `home-timeline` * `mentions-timeline` * `search` All of them use the same `fetch_timeline()` utility function under the hood. I should move the logic that looks up the last `since_id` into that shared function. Question: should I have a table for each of those four methods or a single table that is used by them all? I'm leaning towards four separate tables. | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
590666760 | |
https://github.com/simonw/sqlite-utils/pull/96#issuecomment-606394619 | https://api.github.com/repos/simonw/sqlite-utils/issues/96 | 606394619 | MDEyOklzc3VlQ29tbWVudDYwNjM5NDYxOQ== | 9599 | 2020-03-31T04:38:17Z | 2020-03-31T04:40:23Z | OWNER | I wonder if there are any other Pandas conversions we should be doing? https://pandas.pydata.org/pandas-docs/stable/getting_started/basics.html#dtypes | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
589801352 | |
https://github.com/simonw/sqlite-utils/pull/96#issuecomment-606394349 | https://api.github.com/repos/simonw/sqlite-utils/issues/96 | 606394349 | MDEyOklzc3VlQ29tbWVudDYwNjM5NDM0OQ== | 9599 | 2020-03-31T04:37:16Z | 2020-03-31T04:37:16Z | OWNER | Test failure was just a Black formatting issue. | { "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
589801352 |