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3 rows where comments = 4, type = "issue" and user = 82988 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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377155320 | MDU6SXNzdWUzNzcxNTUzMjA= | 370 | Integration with JupyterLab | psychemedia 82988 | open | 0 | 4 | 2018-11-04T13:57:13Z | 2022-09-29T08:17:47Z | CONTRIBUTOR | I just watched a demo video for the JupyterLab Chart Editor which wraps the plotly chart editor app in a JupyterLab panel and lets you open a plotly chart JSON file in that editor. Essentially, it pops an HTML app into a panel in JupyterLab, and I think registers the app as a file viewer for a particular file type. (I'm not completely taken by it, tbh, because it means you can do irreproducible things to the chart definition file, but that's another issue). JupyterLab extensions can also open files from a dialogue as the iframe/html previewer shows: https://github.com/timkpaine/jupyterlab_iframe. This made me wonder about what For example, by right-clicking on a CSV file (for which there is already a CSV table view) in the file browser, offer a View / Run as datasette file viewer option that will:
(? Create a new SQLite db for each CSV file and launch each datasette view on a new port? Or have a JupyterLab (session?) SQLite db that stores all As a freebie, the Related: |
datasette 107914493 | issue | { "url": "https://api.github.com/repos/simonw/datasette/issues/370/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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1063388037 | I_kwDOCGYnMM4_YgOF | 343 | Provide function to generate hash_id from specified columns | psychemedia 82988 | closed | 0 | 4 | 2021-11-25T10:12:12Z | 2022-03-02T04:25:25Z | 2022-03-02T04:25:25Z | NONE | Hi I note that you define It would be useful to be able to call a complementary function to generate a corresponding Or is there a better pattern for doing that? |
sqlite-utils 140912432 | issue | { "url": "https://api.github.com/repos/simonw/sqlite-utils/issues/343/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
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336924199 | MDU6SXNzdWUzMzY5MjQxOTk= | 330 | Limit text display in cells containing large amounts of text | psychemedia 82988 | closed | 0 | 4 | 2018-06-29T09:15:22Z | 2018-07-24T04:53:20Z | 2018-07-10T16:20:48Z | CONTRIBUTOR | The default preview of a database shows all columns (is the row count limited?) which is fine in many cases but can take a long time to load / offer a large overhead if the table is a SpatiaLite table containing geometry columns that include large shapefiles. Would it make sense to have a setting that can limit the amount of text displayed in any given cell in the table preview, or (less useful?) suppress (with notification) the display of overlong columns unless enabled by the user? An issue then arises if a user does want to see all the text in a cell: 1) for a particular cell; 2) for every cell in the table; 3) for all cells in a particular column or columns (I haven't checked but what if a column contains e.g. raw image data? Does this display as raw data? Or can this be rendered in a context aware way as an image preview? I guess a custom template would be one way to do that?) |
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