You could register a new array
data type with sqlite3
:
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)
x = np.arange(12).reshape(2,6)
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_DECLTYPES)
cur = con.cursor()
cur.execute("create table test (arr array)")
With this setup, you can simply insert the NumPy array with no change in syntax:
cur.execute("insert into test (arr) values (?)", (x, ))
And retrieve the array directly from sqlite as a NumPy array:
cur.execute("select arr from test")
data = cur.fetchone()[0]
print(data)
# [[ 0 1 2 3 4 5]
# [ 6 7 8 9 10 11]]
print(type(data))
# <type 'numpy.ndarray'>
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