issue_comments: 543273540
This data as json
| 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/3#issuecomment-543273540 | https://api.github.com/repos/dogsheep/twitter-to-sqlite/issues/3 | 543273540 | MDEyOklzc3VlQ29tbWVudDU0MzI3MzU0MA== | 9599 | 2019-10-17T17:12:51Z | 2019-10-17T17:12:51Z | MEMBER | Just importing tweets here isn't enough - how are we supposed to know which tweets were imported by which search? So I think the right thing to do here is to also create a `search_runs` table, which records each individual run of this tool (with a timestamp and the search terms used). Then have a `search_runs_tweets` m2m table which shows which Tweets were found by that search. | {"total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} | 488833975 |