衡量一个函数的时间在Python参数 [英] Measure time of a function with arguments in Python
问题描述
我试图来衡量 raw_queries的时间(...)
,失败为止。我发现,我应该使用timeit模块。问题是,我不能(=我不知道如何)传递参数,从环境的功能。
重要提示:拨打电话之前 raw_queries
,我们必须执行阶段2()
(环境初始化)
边注:code是在Python 3
高清raw_queries(查询,NLP):
提交查询没有得到视觉反应 在查询问:
nlp.query(q)的高清evaluate_queries(查询,NLP):
测量,该查询需要返回结果的时候 T =定时器(raw_queries(查询,NLP),?????)
打印(t.timeit())DEF阶段2():
载入字典存储,并随后提交查询 #prepare语言处理器来提交查询
all_files = get_files()
B = LinguisticProcessor(all_files)
b.loadDictionary() #加载查询
queries_file ='queries.txt
查询= load_queries(queries_file)如果__name__ =='__main__':
阶段2()
感谢您的帮助。
更新:使用定时
的第二个参数我们可以称之为阶段2()
。问题是,我们需要的参数(查询,NLP)
从环境。
更新:到目前为止最好的解决方案,与unutbu的帮助下(仅发生了什么变化):
DEF evaluate_queries():
测量,该查询需要返回结果的时候 T =定时器(main.raw_queries(查询,NLP),进口为主; \\
(查询,NLP)= main.phase2()) SF ='执行时间:{}毫秒
打印(sf.format(t.timeit(数量= 1000)))
DEF阶段2():
... 返回的查询,B
高清的main():
evaluate_queries()如果__name__ =='__main__':
主要()
首先,切勿使用时间模块时间的函数。这很容易导致错误的结论。见<一href=\"http://stackoverflow.com/questions/1622943/timeit-versus-timing-decorator\">http://stackoverflow.com/questions/1622943/timeit-versus-timing-decorator一个例子。
要时间的函数调用是使用IPython的的%timeit命令的最简单方法。
在那里,你只需启动一个交互式会话IPython中,调用阶段2()
,定义查询
,
然后运行
%timeit raw_queries(查询,NLP)
这我知道使用timeit的第二个最简单的方法是在命令行调用它:
蟒蛇-mtimeit -s进口检验;查询= test.phase2(),test.raw_queries(查询)
(在上面的命令中,我假定脚本名为 test.py
)
这里的成语是
蟒蛇-mtimeit -sSETUP_COMMANDSCOMMAND_TO_BE_TIMED
要能够通过查询
到 raw_queries
函数调用,你必须定义查询
变量。在code您发布查询
在定义阶段2()
,但只能在本地。因此,要建立查询
作为一个全局变量,你需要做的事情等已经 2阶段
收益查询
:
DEF阶段2():
...
返回查询
如果你不想弄糟 2阶段
这样,创建一个虚拟功能:
DEF三期():
#做的东西一样阶段2(),但返回的查询
返回查询
I am trying to measure the time of raw_queries(...)
, unsuccessfully so far. I found that I should use the timeit module. The problem is that I can't (= I don't know how) pass the arguments to the function from the environment.
Important note: Before calling raw_queries
, we have to execute phase2()
(environment initialization).
Side note: The code is in Python 3.
def raw_queries(queries, nlp):
""" Submit queries without getting visual response """
for q in queries:
nlp.query(q)
def evaluate_queries(queries, nlp):
""" Measure the time that the queries need to return their results """
t = Timer("raw_queries(queries, nlp)", "?????")
print(t.timeit())
def phase2():
""" Load dictionary to memory and subsequently submit queries """
# prepare Linguistic Processor to submit it the queries
all_files = get_files()
b = LinguisticProcessor(all_files)
b.loadDictionary()
# load the queries
queries_file = 'queries.txt'
queries = load_queries(queries_file)
if __name__ == '__main__':
phase2()
Thanks for any help.
UPDATE: We can call phase2()
using the second argument of Timer
. The problem is that we need the arguments (queries, nlp)
from the environment.
UPDATE: The best solution so far, with unutbu's help (only what has changed):
def evaluate_queries():
""" Measure the time that the queries need to return their results """
t = Timer("main.raw_queries(queries, nlp)", "import main;\
(queries,nlp)=main.phase2()")
sf = 'Execution time: {} ms'
print(sf.format(t.timeit(number=1000)))
def phase2():
...
return queries, b
def main():
evaluate_queries()
if __name__ == '__main__':
main()
First, never use the time module to time functions. It can easily lead to wrong conclusions. See http://stackoverflow.com/questions/1622943/timeit-versus-timing-decorator for an example.
The easiest way to time a function call is to use IPython's %timeit command.
There, you simply start an interactive IPython session, call phase2()
, define queries
,
and then run
%timeit raw_queries(queries,nlp)
The second easiest way that I know to use timeit is to call it from the command-line:
python -mtimeit -s"import test; queries=test.phase2()" "test.raw_queries(queries)"
(In the command above, I assume the script is called test.py
)
The idiom here is
python -mtimeit -s"SETUP_COMMANDS" "COMMAND_TO_BE_TIMED"
To be able to pass queries
to the raw_queries
function call, you have to define the queries
variable. In the code you posted queries
is defined in phase2()
, but only locally. So to setup queries
as a global variable, you need to do something like have phase2
return queries
:
def phase2():
...
return queries
If you don't want to mess up phase2
this way, create a dummy function:
def phase3():
# Do stuff like phase2() but return queries
return queries
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