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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 |
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1128466114 | I_kwDOCGYnMM5DQwbC | 406 | Creating tables with custom datatypes | psychemedia 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 From a quick look and a quick play, I didn't spot a way to do this in For example: ```python Via https://stackoverflow.com/a/18622264/454773import 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 insertingsqlite3.register_adapter(np.ndarray, adapt_array) Converts TEXT to np.array when selectingsqlite3.register_converter("array", convert_array) ``` ```python from sqlite_utils import Database db = Database('test.db') Reset the database connection to used the parsed datatypesqlite_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 waybut using the new custom data typevector_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 ```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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