forked from pandas-dev/pandas
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathpackers.py
166 lines (120 loc) · 4.75 KB
/
packers.py
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
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
from vbench.api import Benchmark
from datetime import datetime
start_date = datetime(2013, 5, 1)
common_setup = """from pandas_vb_common import *
import os
import pandas as pd
from pandas.core import common as com
from random import randrange
f = '__test__.msg'
def remove(f):
try:
os.remove(f)
except:
pass
N=100000
C=5
index = date_range('20000101',periods=N,freq='H')
df = DataFrame(dict([ ("float{0}".format(i),randn(N)) for i in range(C) ]),
index=index)
N=100000
C=5
index = date_range('20000101',periods=N,freq='H')
df2 = DataFrame(dict([ ("float{0}".format(i),randn(N)) for i in range(C) ]),
index=index)
df2['object'] = ['%08x'%randrange(16**8) for _ in range(N)]
remove(f)
"""
#----------------------------------------------------------------------
# msgpack
setup = common_setup + """
df2.to_msgpack(f)
"""
packers_read_pack = Benchmark("pd.read_msgpack(f)", setup, start_date=start_date)
setup = common_setup + """
"""
packers_write_pack = Benchmark("df2.to_msgpack(f)", setup, cleanup="remove(f)", start_date=start_date)
#----------------------------------------------------------------------
# pickle
setup = common_setup + """
df2.to_pickle(f)
"""
packers_read_pickle = Benchmark("pd.read_pickle(f)", setup, start_date=start_date)
setup = common_setup + """
"""
packers_write_pickle = Benchmark("df2.to_pickle(f)", setup, cleanup="remove(f)", start_date=start_date)
#----------------------------------------------------------------------
# csv
setup = common_setup + """
df.to_csv(f)
"""
packers_read_csv = Benchmark("pd.read_csv(f)", setup, start_date=start_date)
setup = common_setup + """
"""
packers_write_csv = Benchmark("df.to_csv(f)", setup, cleanup="remove(f)", start_date=start_date)
#----------------------------------------------------------------------
# hdf store
setup = common_setup + """
df2.to_hdf(f,'df')
"""
packers_read_hdf_store = Benchmark("pd.read_hdf(f,'df')", setup, start_date=start_date)
setup = common_setup + """
"""
packers_write_hdf_store = Benchmark("df2.to_hdf(f,'df')", setup, cleanup="remove(f)", start_date=start_date)
#----------------------------------------------------------------------
# hdf table
setup = common_setup + """
df2.to_hdf(f,'df',table=True)
"""
packers_read_hdf_table = Benchmark("pd.read_hdf(f,'df')", setup, start_date=start_date)
setup = common_setup + """
"""
packers_write_hdf_table = Benchmark("df2.to_hdf(f,'df',table=True)", setup, cleanup="remove(f)", start_date=start_date)
#----------------------------------------------------------------------
# sql
setup = common_setup + """
import sqlite3
from sqlalchemy import create_engine
engine = create_engine('sqlite:///:memory:')
df2.to_sql('table', engine, if_exists='replace')
"""
packers_read_sql= Benchmark("pd.read_sql_table('table', engine)", setup, start_date=start_date)
setup = common_setup + """
import sqlite3
from sqlalchemy import create_engine
engine = create_engine('sqlite:///:memory:')
"""
packers_write_sql = Benchmark("df2.to_sql('table', engine, if_exists='replace')", setup, start_date=start_date)
#----------------------------------------------------------------------
# json
setup_int_index = """
import numpy as np
df.index = np.arange(N)
"""
setup = common_setup + """
df.to_json(f,orient='split')
"""
packers_read_json_date_index = Benchmark("pd.read_json(f, orient='split')", setup, start_date=start_date)
setup = setup + setup_int_index
packers_read_json = Benchmark("pd.read_json(f, orient='split')", setup, start_date=start_date)
setup = common_setup + """
"""
packers_write_json_date_index = Benchmark("df.to_json(f,orient='split')", setup, cleanup="remove(f)", start_date=start_date)
setup = setup + setup_int_index
packers_write_json = Benchmark("df.to_json(f,orient='split')", setup, cleanup="remove(f)", start_date=start_date)
#----------------------------------------------------------------------
# stata
setup = common_setup + """
df.to_stata(f, {'index': 'tc'})
"""
packers_read_stata = Benchmark("pd.read_stata(f)", setup, start_date=start_date)
packers_write_stata = Benchmark("df.to_stata(f, {'index': 'tc'})", setup, cleanup="remove(f)", start_date=start_date)
setup = common_setup + """
df['int8_'] = [randint(np.iinfo(np.int8).min, np.iinfo(np.int8).max - 27) for _ in range(N)]
df['int16_'] = [randint(np.iinfo(np.int16).min, np.iinfo(np.int16).max - 27) for _ in range(N)]
df['int32_'] = [randint(np.iinfo(np.int32).min, np.iinfo(np.int32).max - 27) for _ in range(N)]
df['float32_'] = np.array(randn(N), dtype=np.float32)
df.to_stata(f, {'index': 'tc'})
"""
packers_read_stata_with_validation = Benchmark("pd.read_stata(f)", setup, start_date=start_date)
packers_write_stata_with_validation = Benchmark("df.to_stata(f, {'index': 'tc'})", setup, cleanup="remove(f)", start_date=start_date)