{"html_url": "https://github.com/simonw/datasette/issues/1886#issuecomment-1312898318", "issue_url": "https://api.github.com/repos/simonw/datasette/issues/1886", "id": 1312898318, "node_id": "IC_kwDOBm6k_c5OQT0O", "user": {"value": 19851673, "label": "eigenfoo"}, "created_at": "2022-11-14T00:52:16Z", "updated_at": "2022-11-14T00:52:16Z", "author_association": "NONE", "body": "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/\r\n\r\nThis 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](https://cryptics.georgeho.org/static/documents/Selection_AppendixE_v2.pdf), 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!", "reactions": "{\"total_count\": 1, \"+1\": 0, \"-1\": 0, \"laugh\": 0, \"hooray\": 1, \"confused\": 0, \"heart\": 0, \"rocket\": 0, \"eyes\": 0}", "issue": {"value": 1447050738, "label": "Call for birthday presents: if you're using Datasette, let us know how you're using it here"}, "performed_via_github_app": null}
{"html_url": "https://github.com/simonw/datasette/issues/1380#issuecomment-967801997", "issue_url": "https://api.github.com/repos/simonw/datasette/issues/1380", "id": 967801997, "node_id": "IC_kwDOBm6k_c45r3yN", "user": {"value": 7094907, "label": "Segerberg"}, "created_at": "2021-11-13T08:05:37Z", "updated_at": "2021-11-13T08:09:11Z", "author_association": "NONE", "body": "@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 =) ) \r\n\r\nhttps://gist.github.com/Segerberg/b96a0e0a5389dce2396497323cda7042\r\n", "reactions": "{\"total_count\": 1, \"+1\": 0, \"-1\": 0, \"laugh\": 0, \"hooray\": 1, \"confused\": 0, \"heart\": 0, \"rocket\": 0, \"eyes\": 0}", "issue": {"value": 924748955, "label": "Serve all db files in a folder"}, "performed_via_github_app": null}
{"html_url": "https://github.com/simonw/datasette/issues/1310#issuecomment-829885904", "issue_url": "https://api.github.com/repos/simonw/datasette/issues/1310", "id": 829885904, "node_id": "MDEyOklzc3VlQ29tbWVudDgyOTg4NTkwNA==", "user": {"value": 3747136, "label": "ColinMaudry"}, "created_at": "2021-04-30T06:58:46Z", "updated_at": "2021-04-30T07:26:11Z", "author_association": "NONE", "body": "I made it work with openpyxl. I'm not sure all the code under `@hookimpl` is necessary... but it works :)\r\n\r\n```python\r\nfrom datasette import hookimpl\r\nfrom datasette.utils.asgi import Response\r\nfrom openpyxl import Workbook\r\nfrom openpyxl.writer.excel import save_virtual_workbook\r\nfrom openpyxl.cell import WriteOnlyCell\r\nfrom openpyxl.styles import Alignment, Font, PatternFill\r\nfrom tempfile import NamedTemporaryFile\r\n\r\ndef render_spreadsheet(rows):\r\n    wb = Workbook(write_only=True)\r\n    ws = wb.create_sheet()\r\n    ws = wb.active\r\n    ws.title = \"decp\"\r\n\r\n    columns = rows[0].keys()\r\n    headers = []\r\n    for col in columns :\r\n        c = WriteOnlyCell(ws, col)\r\n        c.fill = PatternFill(\"solid\", fgColor=\"DDEFFF\")\r\n        headers.append(c)\r\n    ws.append(headers)\r\n\r\n    for row in rows:\r\n        wsRow = []\r\n        for col in columns:\r\n            c = WriteOnlyCell(ws, row[col])\r\n            if col == \"objet\" :\r\n                c.alignment = Alignment(wrapText = True)\r\n            wsRow.append(c)\r\n        ws.append(wsRow)\r\n\r\n    with NamedTemporaryFile() as tmp:\r\n        wb.save(tmp.name)\r\n        tmp.seek(0)\r\n        return Response(\r\n            tmp.read(),\r\n            headers={\r\n                'Content-Disposition': 'attachment; filename=decp.xlsx',\r\n                'Content-type': 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'\r\n            }\r\n        )\r\n\r\n@hookimpl\r\ndef register_output_renderer():\r\n    return {\"extension\": \"xlsx\",\r\n    \"render\": render_spreadsheet,\r\n    \"can_render\": lambda: False}\r\n\r\n```\r\n\r\nThe key part was to find the right function to wrap the spreadsheet object `wb`. `NamedTemporaryFile()` did it!\r\n\r\nI'll update this issue when the plugin is packaged and ready for broader use.", "reactions": "{\"total_count\": 1, \"+1\": 0, \"-1\": 0, \"laugh\": 0, \"hooray\": 1, \"confused\": 0, \"heart\": 0, \"rocket\": 0, \"eyes\": 0}", "issue": {"value": 870125126, "label": "I'm creating a plugin to export a spreadsheet file (.ods or .xlsx)"}, "performed_via_github_app": null}