issues
5 rows where author_association = "NONE", comments = 1, repo = 140912432 and state = "open" sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1988525411 | I_kwDOCGYnMM52hn1j | 603 | Pyhton 3.12 Bug report | constantinedev 1324252 | open | 0 | 1 | 2023-11-10T22:57:48Z | 2023-12-08T05:10:31Z | NONE | I start with new python3 verison 3.12.0 Also have the error where connect DataBase
As well now of the resolved plan just keep the sqlite-utils version in python3.12 with v3.32.1 [tested] but where are the sqlite3.Connection problem.... This won't happen on python version down to 3.11[tested]
Just the python3.12.0, I have test this error are come from the sqlite3 connection
The error say from Let fix together. |
sqlite-utils 140912432 | issue | { "url": "https://api.github.com/repos/simonw/sqlite-utils/issues/603/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
||||||||
1733198948 | I_kwDOCGYnMM5nToRk | 555 | Filter table by a large bunch of ids | redraw 10843208 | open | 0 | 1 | 2023-05-31T00:29:51Z | 2023-06-14T22:01:57Z | NONE | Hi! this might be a question related to both SQLite & sqlite-utils, and you might be more experienced with them. I have a large bunch of ids, and I'm wondering which is the best way to query them in terms of performance, and simplicity if possible. The naive approach would be something like Another approach might be creating a temp table, or in-memory db table, insert all ids in that table and then join with the target one. I failed to attach an in-memory db both using sqlite-utils, and plain sql's execute(), so my closest approach is something like,
That kinda worked, I couldn't find an option in sqlite-utils's |
sqlite-utils 140912432 | issue | { "url": "https://api.github.com/repos/simonw/sqlite-utils/issues/555/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
||||||||
1720096994 | I_kwDOCGYnMM5mhpji | 554 | `IndexError` when doing `.insert(..., pk='id')` after `insert_all` | xavdid 1231935 | open | 0 | 1 | 2023-05-22T17:13:02Z | 2023-05-22T17:18:33Z | NONE | I believe this is related to https://github.com/simonw/sqlite-utils/issues/98. When ```py from sqlite_utils import Database def test_pk_for_insert(fresh_db): user = {"id": "abc", "name": "david"}
if name == "main": db = Database("bug.db") if db["users"].exists(): raise ValueError( "bug only shows on a new database - remove bug.db before running the script" ) test_pk_for_insert(db) ``` The error is:
The issue is in this block: relevant locals are:
What's most interesting is the comment |
sqlite-utils 140912432 | issue | { "url": "https://api.github.com/repos/simonw/sqlite-utils/issues/554/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
||||||||
907795562 | MDU6SXNzdWU5MDc3OTU1NjI= | 265 | Using enable_fts before search term | prabhur 36287 | open | 0 | 1 | 2021-06-01T01:43:34Z | 2023-04-01T17:27:18Z | NONE | Many thanks for the sqlite-utils suite of utilities. Has made my life much much easier. I used this to create a table and enable FTS. All works fine. The datasette utility detects FTS and shows a text box. Searching for a term using that interface works well. However, when I start to use features by following https://www.sqlite.org/fts5.html section "3. Full-text Query Syntax" I seem to run into issues that I suspect is due to As an example, if i search for the term Similarly, when I try to restrict the search to a single column in FTS using a spec like
Any ideas why? How can I get the benefits of both escaping as well as utilizing different facets of providing / controlling search terms? Thanks. |
sqlite-utils 140912432 | issue | { "url": "https://api.github.com/repos/simonw/sqlite-utils/issues/265/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
||||||||
836829560 | MDU6SXNzdWU4MzY4Mjk1NjA= | 248 | support for Apache Arrow / parquet files I/O | mhalle 649467 | open | 0 | 1 | 2021-03-20T14:59:30Z | 2021-10-28T23:46:48Z | NONE | I just started looking at Apache Arrow using pyarrow for import and export of tabular datasets, and it looks quite compelling. It might be worth looking at for sqlite-utils and/or datasette. As a test, I took a random jsonl data dump of a dataset I have with floats, strings, and ints and converted it to arrow's parquet format using the naive The only hangup is the automatic type inference of the naive reader. It's great for general laziness and for parsing JSON columns (it correctly interpreted a table of mine with a JSON array). However, I did get an exception for a string column where most entries looked integer-like but had a couple values that weren't -- the reader tried to coerce all of them for some reason, even though the JSON type is string. Since the writer optionally takes a schema, it shouldn't be too hard to grab the sqlite header types. With some additional hinting, you might get datetime columns and JSON, which are native Arrow types. Somewhat tangentially, someone even wrote an sqlite vfs extension for Parquet: https://cldellow.com/2018/06/22/sqlite-parquet-vtable.html |
sqlite-utils 140912432 | issue | { "url": "https://api.github.com/repos/simonw/sqlite-utils/issues/248/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Advanced export
JSON shape: default, array, newline-delimited, object
CREATE TABLE [issues] ( [id] INTEGER PRIMARY KEY, [node_id] TEXT, [number] INTEGER, [title] TEXT, [user] INTEGER REFERENCES [users]([id]), [state] TEXT, [locked] INTEGER, [assignee] INTEGER REFERENCES [users]([id]), [milestone] INTEGER REFERENCES [milestones]([id]), [comments] INTEGER, [created_at] TEXT, [updated_at] TEXT, [closed_at] TEXT, [author_association] TEXT, [pull_request] TEXT, [body] TEXT, [repo] INTEGER REFERENCES [repos]([id]), [type] TEXT , [active_lock_reason] TEXT, [performed_via_github_app] TEXT, [reactions] TEXT, [draft] INTEGER, [state_reason] TEXT); CREATE INDEX [idx_issues_repo] ON [issues] ([repo]); CREATE INDEX [idx_issues_milestone] ON [issues] ([milestone]); CREATE INDEX [idx_issues_assignee] ON [issues] ([assignee]); CREATE INDEX [idx_issues_user] ON [issues] ([user]);