1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
|
import sqlite3
import numpy as np
import pandas.util.testing as tm
from pandas import DataFrame, date_range, read_sql_query, read_sql_table
from sqlalchemy import create_engine
from ..pandas_vb_common import setup # noqa
class SQL(object):
goal_time = 0.2
params = ['sqlalchemy', 'sqlite']
param_names = ['connection']
def setup(self, connection):
N = 10000
con = {'sqlalchemy': create_engine('sqlite:///:memory:'),
'sqlite': sqlite3.connect(':memory:')}
self.table_name = 'test_type'
self.query_all = 'SELECT * FROM {}'.format(self.table_name)
self.con = con[connection]
self.df = DataFrame({'float': np.random.randn(N),
'float_with_nan': np.random.randn(N),
'string': ['foo'] * N,
'bool': [True] * N,
'int': np.random.randint(0, N, size=N),
'datetime': date_range('2000-01-01',
periods=N,
freq='s')},
index=tm.makeStringIndex(N))
self.df.loc[1000:3000, 'float_with_nan'] = np.nan
self.df['datetime_string'] = self.df['datetime'].astype(str)
self.df.to_sql(self.table_name, self.con, if_exists='replace')
def time_to_sql_dataframe(self, connection):
self.df.to_sql('test1', self.con, if_exists='replace')
def time_read_sql_query(self, connection):
read_sql_query(self.query_all, self.con)
class WriteSQLDtypes(object):
goal_time = 0.2
params = (['sqlalchemy', 'sqlite'],
['float', 'float_with_nan', 'string', 'bool', 'int', 'datetime'])
param_names = ['connection', 'dtype']
def setup(self, connection, dtype):
N = 10000
con = {'sqlalchemy': create_engine('sqlite:///:memory:'),
'sqlite': sqlite3.connect(':memory:')}
self.table_name = 'test_type'
self.query_col = 'SELECT {} FROM {}'.format(dtype, self.table_name)
self.con = con[connection]
self.df = DataFrame({'float': np.random.randn(N),
'float_with_nan': np.random.randn(N),
'string': ['foo'] * N,
'bool': [True] * N,
'int': np.random.randint(0, N, size=N),
'datetime': date_range('2000-01-01',
periods=N,
freq='s')},
index=tm.makeStringIndex(N))
self.df.loc[1000:3000, 'float_with_nan'] = np.nan
self.df['datetime_string'] = self.df['datetime'].astype(str)
self.df.to_sql(self.table_name, self.con, if_exists='replace')
def time_to_sql_dataframe_column(self, connection, dtype):
self.df[[dtype]].to_sql('test1', self.con, if_exists='replace')
def time_read_sql_query_select_column(self, connection, dtype):
read_sql_query(self.query_col, self.con)
class ReadSQLTable(object):
goal_time = 0.2
def setup(self):
N = 10000
self.table_name = 'test'
self.con = create_engine('sqlite:///:memory:')
self.df = DataFrame({'float': np.random.randn(N),
'float_with_nan': np.random.randn(N),
'string': ['foo'] * N,
'bool': [True] * N,
'int': np.random.randint(0, N, size=N),
'datetime': date_range('2000-01-01',
periods=N,
freq='s')},
index=tm.makeStringIndex(N))
self.df.loc[1000:3000, 'float_with_nan'] = np.nan
self.df['datetime_string'] = self.df['datetime'].astype(str)
self.df.to_sql(self.table_name, self.con, if_exists='replace')
def time_read_sql_table_all(self):
read_sql_table(self.table_name, self.con)
def time_read_sql_table_parse_dates(self):
read_sql_table(self.table_name, self.con, columns=['datetime_string'],
parse_dates=['datetime_string'])
class ReadSQLTableDtypes(object):
goal_time = 0.2
params = ['float', 'float_with_nan', 'string', 'bool', 'int', 'datetime']
param_names = ['dtype']
def setup(self, dtype):
N = 10000
self.table_name = 'test'
self.con = create_engine('sqlite:///:memory:')
self.df = DataFrame({'float': np.random.randn(N),
'float_with_nan': np.random.randn(N),
'string': ['foo'] * N,
'bool': [True] * N,
'int': np.random.randint(0, N, size=N),
'datetime': date_range('2000-01-01',
periods=N,
freq='s')},
index=tm.makeStringIndex(N))
self.df.loc[1000:3000, 'float_with_nan'] = np.nan
self.df['datetime_string'] = self.df['datetime'].astype(str)
self.df.to_sql(self.table_name, self.con, if_exists='replace')
def time_read_sql_table_column(self, dtype):
read_sql_table(self.table_name, self.con, columns=[dtype])
|
