python性能对比之items
#1
#-*- coding:utf8-*-
import datetime
road_nodes = {}
for i in range(5000000):
road_nodes[i] = {'id':i}
beg_time = datetime.datetime.now()
for key, val in road_nodes.items():
pass
end_time = datetime.datetime.now()
print "time_scan:", end_time - beg_time
耗时
$python com_1.py
time_scan: 0:00:17.126098
#2
#-*- coding:utf8-*- import datetime road_nodes = []
for i in range(5000000):
road_nodes.append(i) beg_time = datetime.datetime.now()
for key in road_nodes:
pass
end_time = datetime.datetime.now() print "time_scan:", end_time - beg_time
耗时
$python com_2.py
time_scan: 0:00:00.325304
#3
#-*- coding:utf8-*-
import datetime
road_nodes = {}
for i in range(5000000):
road_nodes[i] = {'id':i}
beg_time = datetime.datetime.now()
for key in road_nodes:
pass
end_time = datetime.datetime.now()
print "time_scan:", end_time - beg_time
耗时
$python com_3.py
time_scan: 0:00:00.359197
总结
只对于字典key的遍历，用for key in dic方式
python性能对比之in list/dict
#1
from datetime import datetime
a = []
for i in range(50000):
a.append(i) aim_list = []
for i in range(1000000):
aim_list.append(i) beg_time = datetime.now()
for key in a:
if key in aim_list:
pass
end_time = datetime.now()
print "scan:", end_time - beg_time
运行
$python draw.py
scan: 0:00:38.624985
#2
from datetime import datetime
a = []
for i in range(50000):
a.append(i) aim_list = {}
for i in range(1000000):
aim_list[i] = None beg_time = datetime.now()
for key in a:
if key in aim_list:
pass
end_time = datetime.now()
print "scan:", end_time - beg_time
运行
$python draw2.py
scan: 0:00:00.014031
分析
巨大的差异由 aim_list类型导致，一个是list，一个是dict
for i in ***时，list是一个个遍历，效率是O(n);dict是直接找到，效率是O(1)。