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 1181236173,I_kwDOCGYnMM5GaDvN,422,Reconsider not running convert functions against null values,9599,open,0,,,1,2022-03-25T20:22:40Z,2022-03-25T20:23:21Z,,OWNER,,"I just got caught out by the fact that `None` values are not processed by the `.convert()` mechanism https://github.com/simonw/sqlite-utils/blob/0b7b80bd40fe86e4d66a04c9f607d94991c45c0b/sqlite_utils/db.py#L2504-L2510 I had run this code while working on #420 and I wasn't sure why it didn't work: ``` $ sqlite-utils add-column content.db articles score float $ sqlite-utils convert content.db articles score ' import random random.seed(10) def convert(value): global random return random.random() ' ``` The reason it didn't work is that the newly added `score` column was full of `null` values. I fixed it by doing this instead: $ sqlite-utils add-column content.db articles score float --not-null-default 1.0 But this indicates to me that the design of `convert()` here may be incorrect.",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/422/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 688351054,MDU6SXNzdWU2ODgzNTEwNTQ=,140,Idea: insert-files mechanism for adding extra columns with fixed values,9599,open,0,,,1,2020-08-28T20:57:36Z,2022-03-20T19:45:45Z,,OWNER,,"Say for example you want to populate a `file_type` column with the value `gif`. That could work like this: ``` sqlite-utils insert-files gifs.db images *.gif \ -c path -c md5 -c last_modified:mtime \ -c file_type:text:gif --pk=path ``` So a column defined as a `text` column with a value that follows a second colon.",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/140/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 675753042,MDU6SXNzdWU2NzU3NTMwNDI=,131,sqlite-utils insert: options for column types,9599,open,0,,,5,2020-08-09T18:59:11Z,2022-03-15T13:21:42Z,,OWNER,,"The `insert` command currently results in string types for every column - at least when used against CSV or TSV inputs. It would be useful if you could do the following: - automatically detects the column types based on eg the first 1000 records - explicitly state the rule for specific columns `--detect-types` could work for the former - or it could do that by default and allow opt-out using `--no-detect-types` For specific columns maybe this: sqlite-utils insert db.db images images.tsv \ --tsv \ -c id int \ -c score float",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/131/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 1160034488,I_kwDOCGYnMM5FJLi4,411,Support for generated columns,25778,open,0,,,8,2022-03-04T20:41:33Z,2022-03-11T22:32:43Z,,CONTRIBUTOR,,"This is a fairly new feature -- SQLite version 3.31.0 (2020-01-22) -- that I, admittedly, haven't gotten to work yet. But it looks _incredibly_ useful: https://dgl.cx/2020/06/sqlite-json-support I'm not sure if this is an option on `add-column` or a separate command like `add-generated-column`. Either way, it needs an argument to populate it. It could be something like this: ```sh sqlite-utils add-column data.db table-name generated --as 'json_extract(data, ""$.field"")' --virtual ``` More here: https://www.sqlite.org/gencol.html",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/411/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 1125297737,I_kwDOCGYnMM5DEq5J,402,Advanced class-based `conversions=` mechanism,9599,open,0,,,14,2022-02-06T19:47:41Z,2022-02-16T10:18:55Z,,OWNER,,"The `conversions=` parameter works like this at the moment: https://sqlite-utils.datasette.io/en/3.23/python-api.html#converting-column-values-using-sql-functions ```python db[""places""].insert( {""name"": ""Wales"", ""geometry"": wkt}, conversions={""geometry"": ""GeomFromText(?, 4326)""}, ) ``` This proposal is to support values in that dictionary that are objects, not strings, which can represent more complex conversions - spun out from #399. New proposed mechanism: ```python from sqlite_utils.utils import LongitudeLatitude db[""places""].insert( { ""name"": ""London"", ""point"": (-0.118092, 51.509865) }, conversions={""point"": LongitudeLatitude}, ) ``` Here `LongitudeLatitude` is a magical value which does TWO things: it sets up the `GeomFromText(?, 4326)` SQL function, and it handles converting the `(51.509865, -0.118092)` tuple into a `POINT({} {})` string. This would involve a change to the `conversions=` contract - where it usually expects a SQL string fragment, but it can also take an object which combines that SQL string fragment with a Python conversion function. Best of all... this resolves the `lat, lon` v.s. `lon, lat` dilemma because you can use `from sqlite_utils.utils import LongitudeLatitude` OR `from sqlite_utils.utils import LatitudeLongitude` depending on which you prefer! _Originally posted by @simonw in https://github.com/simonw/sqlite-utils/issues/399#issuecomment-1030739566_",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/402/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 1072792507,I_kwDOCGYnMM4_8YO7,352,`sqlite-utils insert --extract colname`,9599,open,0,,,4,2021-12-07T00:55:44Z,2022-02-03T22:59:36Z,,OWNER,,"Is there a reason I've not added `--extract` as an option for `sqlite-utils insert` next? There's a `extracts=` option for the various `table.insert()` etc methods - last line in this code block: https://github.com/simonw/sqlite-utils/blob/213a0ff177f23a35f3b235386366ff132eb879f1/sqlite_utils/db.py#L2483-L2495",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/352/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 1122446693,I_kwDOCGYnMM5C5y1l,394,Test against Python 3.11-dev,9599,open,0,,,1,2022-02-02T22:21:03Z,2022-02-03T21:06:35Z,,OWNER,,"Same as: - https://github.com/simonw/datasette/issues/1621",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/394/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 1090798237,I_kwDOCGYnMM5BBEKd,359,Use RETURNING if available to populate last_pk,9599,open,0,,,0,2021-12-29T23:43:23Z,2021-12-29T23:43:23Z,,OWNER,,"Inspired by this: https://news.ycombinator.com/item?id=29729283 > Because SQLite is effectively serializing all the writes for us, we have zero locking in our code. We used to have to lock when inserting new items (to get the LastInsertRowId), but the newer version of SQLite supports the RETURNING keyword, so we don't even have to lock on inserts now.",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/359/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 706001517,MDU6SXNzdWU3MDYwMDE1MTc=,163,Idea: conversions= could take Python functions,9599,open,0,,,4,2020-09-22T00:37:12Z,2021-12-20T00:56:52Z,,OWNER,,"Right now you use `conversions=` like this: ```python db[""example""].insert({ ""name"": ""The Bigfoot Discovery Museum"" }, conversions={""name"": ""upper(?)""}) ``` How about if you could optionally provide a Python function (or a lambda) like this? ```python db[""example""].insert({ ""name"": ""The Bigfoot Discovery Museum"" }, conversions={""name"": lambda s: s.upper()}) ``` This would work by creating a random name for that function, registering it (similar to #162), executing the SQL and then un-registering the custom function at the end.",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/163/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 1066603133,PR_kwDOCGYnMM4vKAzW,347,Test against pysqlite3 running SQLite 3.37,9599,open,0,,,9,2021-11-29T23:17:57Z,2021-12-11T01:02:19Z,,OWNER,simonw/sqlite-utils/pulls/347,Refs #346 and #344.,140912432,pull,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/347/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",0, 1071531082,I_kwDOCGYnMM4_3kRK,349,A way of creating indexes on newly created tables,9599,open,0,,,3,2021-12-05T18:56:12Z,2021-12-07T01:04:37Z,,OWNER,,"I'm writing code for https://github.com/simonw/git-history/issues/33 that creates a table inside a loop: ```python item_pk = db[item_table].lookup( {""_item_id"": item_id}, item_to_insert, column_order=(""_id"", ""_item_id""), pk=""_id"", ) ``` I need to look things up by `_item_id` on this table, which means I need an index on that column (the table can get very big). But there's no mechanism in SQLite utils to detect if the table was created for the first time and add an index to it. And I don't want to run `CREATE INDEX IF NOT EXISTS` every time through the loop. This should work like the `foreign_keys=` mechanism. ",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/349/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 1072435124,I_kwDOCGYnMM4_7A-0,350,Optional caching mechanism for table.lookup(),9599,open,0,,,3,2021-12-06T17:54:25Z,2021-12-06T17:56:57Z,,OWNER,,"Inspired by work on `git-history` where I used this pattern: ```python column_name_to_id = {} def column_id(column): if column not in column_name_to_id: id = db[""columns""].lookup( {""namespace"": namespace_id, ""name"": column}, foreign_keys=((""namespace"", ""namespaces"", ""id""),), ) column_name_to_id[column] = id return column_name_to_id[column] ``` If you're going to be doing a large number of `table.lookup(...)` calls and you know that no other script will be modifying the database at the same time you can presumably get a big speedup using a Python in-memory cache - maybe even a LRU one to avoid memory bloat.",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/350/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 1066563554,I_kwDOCGYnMM4_knfi,346,Way to test SQLite 3.37 (and potentially other versions) in CI,9599,open,0,,,5,2021-11-29T22:21:06Z,2021-11-29T23:12:49Z,,OWNER,,"> Need to figure out a good pattern for testing this in CI too - it will currently skip the new tests if it doesn't have SQLite 3.37 or higher. _Originally posted by @simonw in https://github.com/simonw/sqlite-utils/issues/344#issuecomment-982076924_",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/346/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,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 `pyarrow.parquet.write_file()` command, which has automatic type inferrence. It compressed down to 7% of the original size. Conversion of a 26MB JSON file and serializing it to parquet was eyeblink instantaneous. Parquet files are portable and can be directly imported into pandas and other analytics software. 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 ",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}",, 817989436,MDU6SXNzdWU4MTc5ODk0MzY=,242,Async support,25778,open,0,,,13,2021-02-27T18:29:38Z,2021-10-28T14:37:56Z,,CONTRIBUTOR,,"Following our conversation last week, want to note this here before I forget. I've had a couple situations where I'd like to do a bunch of updates in an async event loop, but I run into SQLite's issues with concurrent writes. This feels like something sqlite-utils could help with. PeeWee ORM has a [SQLite write queue](http://docs.peewee-orm.com/en/latest/peewee/playhouse.html#sqliteq) that might be a good model. It's using threads or gevent, but I _think_ that approach would translate well enough to asyncio. Happy to help with this, too.",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/242/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 974067156,MDU6SXNzdWU5NzQwNjcxNTY=,318,Research: handle gzipped CSV directly,9599,open,0,,,2,2021-08-18T21:23:04Z,2021-08-18T21:25:30Z,,OWNER,,"Would it be worthwhile for the `sqlite-utils` command-line tool to grow features to efficiently directly interact with gzipped CSV data? Maybe add `--gz` options to both `insert` and to the various commands that output query results.",140912432,issue,,,"{""url"": ""https://api.github.com/repos/simonw/sqlite-utils/issues/318/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",, 722816436,MDU6SXNzdWU3MjI4MTY0MzY=,186,.extract() shouldn't extract null values,9599,open,0,,,7,2020-10-16T02:41:08Z,2021-08-12T12:32:14Z,,OWNER,,"This almost works, but it creates a rogue `type` record with a value of None. ``` In [1]: import sqlite_utils In [2]: db = sqlite_utils.Database(memory=True) In [5]: db[""creatures""].insert_all([ {""id"": 1, ""name"": ""Simon"", ""type"": None}, {""id"": 2, ""name"": ""Natalie"", ""type"": None}, {""id"": 3, ""name"": ""Cleo"", ""type"": ""dog""}], pk=""id"") Out[5]: