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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
1128466114 I_kwDOCGYnMM5DQwbC 406 Creating tables with custom datatypes 82988 open 0     5 2022-02-09T12:16:31Z 2022-09-15T18:13:50Z   NONE   Via https://stackoverflow.com/a/18622264/454773 I note the ability to register custom handlers for novel datatypes that can map into and out of things like sqlite `BLOB`s. From a quick look and a quick play, I didn't spot a way to do this in `sqlite_utils`? For example: ```python # Via https://stackoverflow.com/a/18622264/454773 import sqlite3 import numpy as np import io def adapt_array(arr): """ http://stackoverflow.com/a/31312102/190597 (SoulNibbler) """ out = io.BytesIO() np.save(out, arr) out.seek(0) return sqlite3.Binary(out.read()) def convert_array(text): out = io.BytesIO(text) out.seek(0) return np.load(out) # Converts np.array to TEXT when inserting sqlite3.register_adapter(np.ndarray, adapt_array) # Converts TEXT to np.array when selecting sqlite3.register_converter("array", convert_array) ``` ```python from sqlite_utils import Database db = Database('test.db') # Reset the database connection to used the parsed datatype # sqlite_utils doesn't seem to support eg: # Database('test.db', detect_types=sqlite3.PARSE_DECLTYPES) db.conn = sqlite3.connect(db_name, detect_types=sqlite3.PARSE_DECLTYPES) # Create a table the old fashioned way # but using the new custom data type vector_table_create = """ CREATE TABLE dummy (title TEXT, vector array ); """ cur = db.conn.cursor() cur.execute(vector_table_create) # sqlite_utils doesn't appear to support custom types (yet?!) # The following errors on the "array" datatype """ db["dummy"].create({ "title": str, "vector": "array", }) """ ``` We can then add / retrieve records from the database where the datatype of the `vector` field is a custom registered `array` type (which is to say, a `numpy` array): ```python import numpy as np db["dummy"].insert({'title':"test1", 'vector':np.array([1,2,3])}) for row in db.query("SELECT * FROM dummy"): print(row['title'], row['vector'], type(row['vector'])) """ test1 [1 2 3] <class 'numpy.ndarray'> """ ``` It would be handy to be able to do this idiomatically in `sqlite_utils`. 140912432 issue     {"url": "https://api.github.com/repos/simonw/sqlite-utils/issues/406/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}    

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