issue_comments
3 rows where author_association = "NONE" and reactions = "{"total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 1, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}" sorted by node_id
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 3
id | html_url | issue_url | node_id ▼ | user | created_at | updated_at | author_association | body | reactions | issue | performed_via_github_app |
---|---|---|---|---|---|---|---|---|---|---|---|
967801997 | https://github.com/simonw/datasette/issues/1380#issuecomment-967801997 | https://api.github.com/repos/simonw/datasette/issues/1380 | IC_kwDOBm6k_c45r3yN | Segerberg 7094907 | 2021-11-13T08:05:37Z | 2021-11-13T08:09:11Z | NONE | @glasnt yeah I guess that could be an option. I run datasette on large databases > 75gb and the startup time is a bit slow for me even with -i --inspect-file options. Here's a quick sketch for a plugin that will reload db's in a folder that you set for the plugin in metadata.json. If you request /-reload-db new db's will be added. (You probably want to implement some authentication for this =) ) https://gist.github.com/Segerberg/b96a0e0a5389dce2396497323cda7042 |
{ "total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 1, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Serve all db files in a folder 924748955 | |
1312898318 | https://github.com/simonw/datasette/issues/1886#issuecomment-1312898318 | https://api.github.com/repos/simonw/datasette/issues/1886 | IC_kwDOBm6k_c5OQT0O | eigenfoo 19851673 | 2022-11-14T00:52:16Z | 2022-11-14T00:52:16Z | NONE | I'm a cryptic crossword enthusiast and have spent a lot of time scraping and parsing cryptic crossword clues from various blogs, forums and publications. The result is over half a million clues from cryptic crosswords over the past twelve years, including the clue, answer, puzzle date, puzzle name and a link to the original source. This is all hosted using Datasette, which has been a delight to use: https://cryptics.georgeho.org/ This dataset is a significant work of crossword archivism and scholarship, as acquiring historical crosswords and structuring their contents require focused effort and tedious cleaning that few are willing to do for such trivial data - for example, according to this 2004 selection guide, the Library of Congress explicitly does not collect crossword puzzles. Anecdotally, I know that many constructors/setters of cryptic crosswords use this dataset as a resource, and some even simply call it "the database" - this is probably one of the most impactful data projects I've worked on! |
{ "total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 1, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Call for birthday presents: if you're using Datasette, let us know how you're using it here 1447050738 | |
829885904 | https://github.com/simonw/datasette/issues/1310#issuecomment-829885904 | https://api.github.com/repos/simonw/datasette/issues/1310 | MDEyOklzc3VlQ29tbWVudDgyOTg4NTkwNA== | ColinMaudry 3747136 | 2021-04-30T06:58:46Z | 2021-04-30T07:26:11Z | NONE | I made it work with openpyxl. I'm not sure all the code under ```python from datasette import hookimpl from datasette.utils.asgi import Response from openpyxl import Workbook from openpyxl.writer.excel import save_virtual_workbook from openpyxl.cell import WriteOnlyCell from openpyxl.styles import Alignment, Font, PatternFill from tempfile import NamedTemporaryFile def render_spreadsheet(rows): wb = Workbook(write_only=True) ws = wb.create_sheet() ws = wb.active ws.title = "decp"
@hookimpl def register_output_renderer(): return {"extension": "xlsx", "render": render_spreadsheet, "can_render": lambda: False} ``` The key part was to find the right function to wrap the spreadsheet object I'll update this issue when the plugin is packaged and ready for broader use. |
{ "total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 1, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
I'm creating a plugin to export a spreadsheet file (.ods or .xlsx) 870125126 |
Advanced export
JSON shape: default, array, newline-delimited, object
CREATE TABLE [issue_comments] ( [html_url] TEXT, [issue_url] TEXT, [id] INTEGER PRIMARY KEY, [node_id] TEXT, [user] INTEGER REFERENCES [users]([id]), [created_at] TEXT, [updated_at] TEXT, [author_association] TEXT, [body] TEXT, [reactions] TEXT, [issue] INTEGER REFERENCES [issues]([id]) , [performed_via_github_app] TEXT); CREATE INDEX [idx_issue_comments_issue] ON [issue_comments] ([issue]); CREATE INDEX [idx_issue_comments_user] ON [issue_comments] ([user]);
user 3