Exporting data from sqlite to numpy array

Question

I'm not a programmer, I do this purely as a hobby..

I found a way to save numpy array in to sqlite database

import sqlite3
import numpy

# Array of 4 columns and 100 rows
data = numpy.random.rand(100, 4)

# Create a sample database
conn = sqlite3.connect('sample.db')
cursor = conn.cursor()

# Create a new table with four columns
cursor.execute('''create table data (field1 real, field2 real, field3 real,    field4 real)''')
conn.commit()

# Insert the data array into the 'data' table
cursor.executemany('''insert into data values (?, ?, ?, ?)''', map(tuple,    data.tolist()))
conn.commit()
cursor.close()
conn.close()

But I have a problem about finding a way to reverse the process.. I want to load data from database in numpy array.. Some suggestion where to find a simple example?

hpaulj · Accepted Answer · 2017-03-20 22:28:34Z

7

Just fetch all the values. That gives you a list of tuples. np.array() takes you back to the original array:

In [12]: cursor.execute('SELECT * from data')
Out[12]: <sqlite3.Cursor at 0xaf8e9d60>
In [13]: alist = cursor.fetchall()
In [14]: len(alist)
Out[14]: 100
In [15]: alist[0]
Out[15]: 
(0.3327498114993416,
 0.6164620040846208,
 0.5099007559772143,
 0.7808234554641948)
In [16]: data1 = np.array(alist)
In [17]: np.allclose(data, data1)
Out[17]: True

The fact that it's a list of tuples doesn't matter. It's just as good as a list of lists.

answered Mar 20, 2017 at 22:28

hpaulj

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