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 BLOBs.

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.