I want to know how much time an import takes for both built-in as well as user defined modules.
问题:
回答1:
One way to profile imports is to use the profile_imports module used in bzr source code:
# put those two lines at the top of your script
import profile_imports
profile_imports.install()
# display the results
profile_imports.log_stack_info(sys.stderr)
Besides giving you timing for imports, this also estimates time to compile regex, which is often a significant cause for slowdown in imports.
回答2:
You can test this runnning
$ time python -c "import math"
However, what would this help you? Importing only happens once and will almost never be a bottle neck. Importing the same module over and over will not run significantly slower than importing it once, since Python tracks which modules have already been imported.
What are you actually trying to achieve?
回答3:
To find out how long an import takes, the simplest way is probably using the timeit module..
>>> import timeit
>>> t = timeit.Timer('import urllib')
>>> t.timeit(number = 1000000)
0.98621106147766113
So to import urllib 1 million times, it took just under a second (on a Macbook Pro)..
i have a master script that imports other modules.I need to calculate how much time it takes
If you mean the total script execution time, on Linux/OS X/Cygwin, you can run the script using the time
command, for example:
$ time python myscript.py
real 0m0.046s
user 0m0.024s
sys 0m0.020s
(remember that includes all the Python interpreter startup time, as well as the actual code execution time, although it's pretty trivial amount)
Another, possibly more useful way is to profile the script:
Instead of running your code with
$ python myscript.py
..you use..
$ python -m cProfile myscript.py
1059 function calls in 0.015 CPU seconds
Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 0.000 0.000 <string>:1(<module>)
1 0.002 0.002 0.015 0.015 myscript.py:1(<module>)
[...]
I don't find the command line output very easy to read, so I almost always use gprof2dot, which turns the profiling information into a pretty graphviz graph:
$ python -m cProfile -o myscript.prof myscript.py
$ python gprof2dot.py -o myscript.dot -f pstats myscript.prof
$ dot -Tpng -o profile.png prof_runtest.dot -Gbgcolor=black
Example output (1429x1896px PNG)
回答4:
Starting from Python3.7 releaese, new -X importtime
option is available.
To measure import time, just simply execute your script with that option, e.g. python -X importtime my_script.py
.
For reference:
- https://docs.python.org/3.7/using/cmdline.html#id5
回答5:
Use cProfile:
python -m cProfile yourscript.py
回答6:
Tested on Windows in Python 2.4 - you can try it yourself.
>>> import time
>>> ## Built-in module
>>> def testTime():
now = time.clock() # use time.time() on unix-based systems
import math
print time.clock() - now
>>> testTime()
7.54285810167e-006
>>> ## My own module
>>> def testTime():
now = time.clock()
import myBuiltInModule # Not its actual name ;-)
print time.clock() - now
>>> testTime()
0.00253174635324
>>> testTime()
3.70158777141e-006
So there is a big difference between cached modules and those being brought in from scratch. To illustrate, we can reload the module:
>>> def testTime():
now = time.clock()
reload(myBuiltInModule )
print time.clock() - now
>>> testTime()
0.00250017809526
回答7:
I ran into this issue profiling a large legacy application with a multi-second startup time. It's relatively simple to replace the builtin importer with something that does some profiling. Below is a hacky way of showing approximately how long each module takes to execute:
import os
import sys
import time
class ImportEventNode(object):
def __init__(self, name, start_time, children=None, end_time=None):
self.name = name
self.start_time = start_time
self.children = [] if children is None else children
self.end_time = end_time
def __repr__(self):
return 'ImportEventNode({self.name}, {self.start_time}, children={self.children}, end_time={self.end_time})'.format(self=self)
@property
def total_time(self):
return self.end_time - self.start_time
@property
def net_time(self):
return self.total_time - sum(child.total_time for child in self.children)
root_node = cur_node = None
all_nodes = []
old_import = __import__
def __import__(*args, **kwargs):
global root_node, cur_node
name = args[0]
if name not in sys.modules:
t0 = time.time()
if root_node is None:
root_node = prev_node = cur_node = lcur_node = ImportEventNode(args[0], t0)
else:
prev_node = cur_node
cur_node = lcur_node = ImportEventNode(name, t0)
prev_node.children.append(cur_node)
try:
ret = old_import(*args, **kwargs)
finally:
lcur_node.end_time = time.time()
all_nodes.append(lcur_node)
cur_node = prev_node
return ret
else:
return old_import(*args, **kwargs)
__builtins__.__import__ = __import__
Running on a simple example, here's how it looks on importing scipy.stats:
:import scipy.stats
:
:nodes = sorted(all_nodes, key=(lambda x: x.net_time), reverse=True)
:for node in nodes[:10]:
: print(node.name, node.net_time)
:
:<EOF>
('pkg_resources', 0.08431100845336914)
('', 0.05861020088195801)
('decomp_schur', 0.016885995864868164)
('PIL', 0.0143890380859375)
('scipy.stats', 0.010602712631225586)
('pkg_resources._vendor.packaging.specifiers', 0.007072925567626953)
('add_newdocs', 0.00637507438659668)
('mtrand', 0.005497932434082031)
('scipy.sparse.linalg', 0.005171060562133789)
('scipy.linalg', 0.004471778869628906)