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[[FrontPage/Python]]
アプリのデータ永続化のためにSQLite3を使う
** ndarrayの格納方法 [#ca61ac23]
データ解析ではndarrayで多次元配列を操作するのがほとんど.毎回呼び出していると時間がかかるのでDBに突っ込みたい.
- 方法1
-- http://stackoverflow.com/questions/18621513/python-insert-numpy-array-into-sqlite3-database
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'>
** pandasでSQLiteを使う [#ff88333e]
http://www.mwsoft.jp/programming/numpy/rdb_to_pandas.html
** pandasでRDBの読み書きをする [#p2a1c03e]
http://www.mwsoft.jp/programming/numpy/rdb_to_pandas.html
def create_db():
# PandasのDataFrameを生成
df = loadDataFrame(WAVDIR_ABSPATH)
# PandasのDataFrameをSQLiteに保存
with sqlite3.connect('ExpData2.db') as conn:
# conn.execute("DROP TABLE IF EXISTS tbl_golf")
psql.to_sql(df, 'tbl_golf', con=conn, index=True, if_exists='replace')
cur = conn.execute('SELECT * FROM tbl_golf')
print cur.fetchall()
def load_db():
# dbからデータを呼び出しpandasへ保存
with sqlite3.connect('ExpData2.db') as conn:
sql = "SELECT * FROM tbl_golf"
df = psql.read_sql(sql,conn)
print df