def time(self,line='', cell=None, local_ns=None):
expr = self.shell.input_transformer_manager.transform_cell(cell)
## parse ast
tp_min = 0.1
t0 = clock()
expr_ast = self.shell.compile.ast_parse(expr)
tp = clock()-t0
## compile
tc_min = 0.1
t0 = clock()
code = self.shell.compile(expr_ast, source, mode)
tc = clock()-t0
## execute
st = clock2()
try:
exec(code, glob, local_ns)
except:
self.shell.showtraceback()
return
end = clock2()
# Compute actual times and report
cpu_user = end[0]-st[0]
cpu_sys = end[1]-st[1]
cpu_tot = cpu_user+cpu_sys
print("CPU times: user %s, sys: %s, total: %s" % (_format_time(cpu_user),_format_time(cpu_sys),_format_time(cpu_tot)))
if tc > tc_min:
print("Compiler : %s" % _format_time(tc))
if tp > tp_min:
print("Parser : %s" % _format_time(tp))
def _run_with_timing(run, nruns):
"""
Run function `run` and print timing information.
Parameters
----------
run : callable
Any callable object which takes no argument.
nruns : int
Number of times to execute `run`.
"""
twall0 = time.time()
if nruns == 1:
t0 = clock2()
run()
t1 = clock2()
t_usr = t1[0] - t0[0]
t_sys = t1[1] - t0[1]
print "\nIPython CPU timings (estimated):"
print " User : %10.2f s." % t_usr
print " System : %10.2f s." % t_sys
else:
runs = range(nruns)
t0 = clock2()
for nr in runs:
run()
t1 = clock2()
t_usr = t1[0] - t0[0]
t_sys = t1[1] - t0[1]
print "\nIPython CPU timings (estimated):"
print "Total runs performed:", nruns
print " Times : %10s %10s" % ('Total', 'Per run')
print " User : %10.2f s, %10.2f s." % (t_usr, t_usr / nruns)
print " System : %10.2f s, %10.2f s." % (t_sys, t_sys / nruns)
twall1 = time.time()
print "Wall time: %10.2f s." % (twall1 - twall0)
def _run_with_timing(run, nruns):
"""
Run function `run` and print timing information.
Parameters
----------
run : callable
Any callable object which takes no argument.
nruns : int
Number of times to execute `run`.
"""
twall0 = time.time()
if nruns == 1:
t0 = clock2()
run()
t1 = clock2()
t_usr = t1[0] - t0[0]
t_sys = t1[1] - t0[1]
print "\nIPython CPU timings (estimated):"
print " User : %10.2f s." % t_usr
print " System : %10.2f s." % t_sys
else:
runs = range(nruns)
t0 = clock2()
for nr in runs:
run()
t1 = clock2()
t_usr = t1[0] - t0[0]
t_sys = t1[1] - t0[1]
print "\nIPython CPU timings (estimated):"
print "Total runs performed:", nruns
print " Times : %10s %10s" % ('Total', 'Per run')
print " User : %10.2f s, %10.2f s." % (t_usr, t_usr / nruns)
print " System : %10.2f s, %10.2f s." % (t_sys, t_sys / nruns)
twall1 = time.time()
print "Wall time: %10.2f s." % (twall1 - twall0)
def time(self,parameter_s, local_ns=None):
"""Time execution of a Python statement or expression.
The CPU and wall clock times are printed, and the value of the
expression (if any) is returned. Note that under Win32, system time
is always reported as 0, since it can not be measured.
This function provides very basic timing functionality. In Python
2.3, the timeit module offers more control and sophistication, so this
could be rewritten to use it (patches welcome).
Examples
--------
::
In [1]: time 2**128
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00
Out[1]: 340282366920938463463374607431768211456L
In [2]: n = 1000000
In [3]: time sum(range(n))
CPU times: user 1.20 s, sys: 0.05 s, total: 1.25 s
Wall time: 1.37
Out[3]: 499999500000L
In [4]: time print 'hello world'
hello world
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00
Note that the time needed by Python to compile the given expression
will be reported if it is more than 0.1s. In this example, the
actual exponentiation is done by Python at compilation time, so while
the expression can take a noticeable amount of time to compute, that
time is purely due to the compilation:
In [5]: time 3**9999;
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00 s
In [6]: time 3**999999;
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00 s
Compiler : 0.78 s
"""
# fail immediately if the given expression can't be compiled
expr = self.shell.prefilter(parameter_s,False)
# Minimum time above which parse time will be reported
tp_min = 0.1
t0 = clock()
expr_ast = ast.parse(expr)
tp = clock()-t0
# Apply AST transformations
expr_ast = self.shell.transform_ast(expr_ast)
# Minimum time above which compilation time will be reported
tc_min = 0.1
if len(expr_ast.body)==1 and isinstance(expr_ast.body[0], ast.Expr):
mode = 'eval'
source = '<timed eval>'
expr_ast = ast.Expression(expr_ast.body[0].value)
else:
mode = 'exec'
source = '<timed exec>'
t0 = clock()
code = compile(expr_ast, source, mode)
tc = clock()-t0
# skew measurement as little as possible
glob = self.shell.user_ns
wtime = time.time
# time execution
wall_st = wtime()
if mode=='eval':
st = clock2()
out = eval(code, glob, local_ns)
end = clock2()
else:
st = clock2()
exec code in glob, local_ns
end = clock2()
out = None
wall_end = wtime()
# Compute actual times and report
wall_time = wall_end-wall_st
cpu_user = end[0]-st[0]
cpu_sys = end[1]-st[1]
cpu_tot = cpu_user+cpu_sys
print "CPU times: user %.2f s, sys: %.2f s, total: %.2f s" % \
(cpu_user,cpu_sys,cpu_tot)
print "Wall time: %.2f s" % wall_time
if tc > tc_min:
print "Compiler : %.2f s" % tc
if tp > tp_min:
print "Parser : %.2f s" % tp
return out
def run(self, parameter_s='', runner=None,
file_finder=get_py_filename):
"""Run the named file inside IPython as a program.
Usage:\\
%run [-n -i -t [-N<N>] -d [-b<N>] -p [profile options] -G] file [args]
Parameters after the filename are passed as command-line arguments to
the program (put in sys.argv). Then, control returns to IPython's
prompt.
This is similar to running at a system prompt:\\
$ python file args\\
but with the advantage of giving you IPython's tracebacks, and of
loading all variables into your interactive namespace for further use
(unless -p is used, see below).
The file is executed in a namespace initially consisting only of
__name__=='__main__' and sys.argv constructed as indicated. It thus
sees its environment as if it were being run as a stand-alone program
(except for sharing global objects such as previously imported
modules). But after execution, the IPython interactive namespace gets
updated with all variables defined in the program (except for __name__
and sys.argv). This allows for very convenient loading of code for
interactive work, while giving each program a 'clean sheet' to run in.
Arguments are expanded using shell-like glob match. Patterns
'*', '?', '[seq]' and '[!seq]' can be used. Additionally,
tilde '~' will be expanded into user's home directory. Unlike
real shells, quotation does not suppress expansions. Use
*two* back slashes (e.g., '\\\\*') to suppress expansions.
To completely disable these expansions, you can use -G flag.
Options:
-n: __name__ is NOT set to '__main__', but to the running file's name
without extension (as python does under import). This allows running
scripts and reloading the definitions in them without calling code
protected by an ' if __name__ == "__main__" ' clause.
-i: run the file in IPython's namespace instead of an empty one. This
is useful if you are experimenting with code written in a text editor
which depends on variables defined interactively.
-e: ignore sys.exit() calls or SystemExit exceptions in the script
being run. This is particularly useful if IPython is being used to
run unittests, which always exit with a sys.exit() call. In such
cases you are interested in the output of the test results, not in
seeing a traceback of the unittest module.
-t: print timing information at the end of the run. IPython will give
you an estimated CPU time consumption for your script, which under
Unix uses the resource module to avoid the wraparound problems of
time.clock(). Under Unix, an estimate of time spent on system tasks
is also given (for Windows platforms this is reported as 0.0).
If -t is given, an additional -N<N> option can be given, where <N>
must be an integer indicating how many times you want the script to
run. The final timing report will include total and per run results.
For example (testing the script uniq_stable.py)::
In [1]: run -t uniq_stable
IPython CPU timings (estimated):\\
User : 0.19597 s.\\
System: 0.0 s.\\
In [2]: run -t -N5 uniq_stable
IPython CPU timings (estimated):\\
Total runs performed: 5\\
Times : Total Per run\\
User : 0.910862 s, 0.1821724 s.\\
System: 0.0 s, 0.0 s.
-d: run your program under the control of pdb, the Python debugger.
This allows you to execute your program step by step, watch variables,
etc. Internally, what IPython does is similar to calling:
pdb.run('execfile("YOURFILENAME")')
with a breakpoint set on line 1 of your file. You can change the line
number for this automatic breakpoint to be <N> by using the -bN option
(where N must be an integer). For example::
%run -d -b40 myscript
will set the first breakpoint at line 40 in myscript.py. Note that
the first breakpoint must be set on a line which actually does
something (not a comment or docstring) for it to stop execution.
Or you can specify a breakpoint in a different file::
%run -d -b myotherfile.py:20 myscript
When the pdb debugger starts, you will see a (Pdb) prompt. You must
first enter 'c' (without quotes) to start execution up to the first
breakpoint.
Entering 'help' gives information about the use of the debugger. You
can easily see pdb's full documentation with "import pdb;pdb.help()"
at a prompt.
-p: run program under the control of the Python profiler module (which
prints a detailed report of execution times, function calls, etc).
You can pass other options after -p which affect the behavior of the
profiler itself. See the docs for %prun for details.
In this mode, the program's variables do NOT propagate back to the
IPython interactive namespace (because they remain in the namespace
where the profiler executes them).
Internally this triggers a call to %prun, see its documentation for
details on the options available specifically for profiling.
There is one special usage for which the text above doesn't apply:
if the filename ends with .ipy, the file is run as ipython script,
just as if the commands were written on IPython prompt.
-m: specify module name to load instead of script path. Similar to
the -m option for the python interpreter. Use this option last if you
want to combine with other %run options. Unlike the python interpreter
only source modules are allowed no .pyc or .pyo files.
For example::
%run -m example
will run the example module.
-G: disable shell-like glob expansion of arguments.
"""
# get arguments and set sys.argv for program to be run.
opts, arg_lst = self.parse_options(parameter_s,
'nidtN:b:pD:l:rs:T:em:G',
mode='list', list_all=1)
if "m" in opts:
modulename = opts["m"][0]
modpath = find_mod(modulename)
if modpath is None:
warn('%r is not a valid modulename on sys.path'%modulename)
return
arg_lst = [modpath] + arg_lst
try:
filename = file_finder(arg_lst[0])
except IndexError:
warn('you must provide at least a filename.')
print '\n%run:\n', oinspect.getdoc(self.run)
return
except IOError as e:
try:
msg = str(e)
except UnicodeError:
msg = e.message
error(msg)
return
if filename.lower().endswith('.ipy'):
with preserve_keys(self.shell.user_ns, '__file__'):
self.shell.user_ns['__file__'] = filename
self.shell.safe_execfile_ipy(filename)
return
# Control the response to exit() calls made by the script being run
exit_ignore = 'e' in opts
# Make sure that the running script gets a proper sys.argv as if it
# were run from a system shell.
save_argv = sys.argv # save it for later restoring
if 'G' in opts:
args = arg_lst[1:]
else:
# tilde and glob expansion
args = shellglob(map(os.path.expanduser, arg_lst[1:]))
sys.argv = [filename] + args # put in the proper filename
# protect sys.argv from potential unicode strings on Python 2:
if not py3compat.PY3:
sys.argv = [ py3compat.cast_bytes(a) for a in sys.argv ]
if 'i' in opts:
# Run in user's interactive namespace
prog_ns = self.shell.user_ns
__name__save = self.shell.user_ns['__name__']
prog_ns['__name__'] = '__main__'
main_mod = self.shell.new_main_mod(prog_ns)
else:
# Run in a fresh, empty namespace
if 'n' in opts:
name = os.path.splitext(os.path.basename(filename))[0]
else:
name = '__main__'
main_mod = self.shell.new_main_mod()
prog_ns = main_mod.__dict__
prog_ns['__name__'] = name
# Since '%run foo' emulates 'python foo.py' at the cmd line, we must
# set the __file__ global in the script's namespace
prog_ns['__file__'] = filename
# pickle fix. See interactiveshell for an explanation. But we need to
# make sure that, if we overwrite __main__, we replace it at the end
main_mod_name = prog_ns['__name__']
if main_mod_name == '__main__':
restore_main = sys.modules['__main__']
else:
restore_main = False
# This needs to be undone at the end to prevent holding references to
# every single object ever created.
sys.modules[main_mod_name] = main_mod
try:
stats = None
with self.shell.readline_no_record:
if 'p' in opts:
stats = self.prun('', None, False, opts, arg_lst, prog_ns)
else:
if 'd' in opts:
deb = debugger.Pdb(self.shell.colors)
# reset Breakpoint state, which is moronically kept
# in a class
bdb.Breakpoint.next = 1
bdb.Breakpoint.bplist = {}
bdb.Breakpoint.bpbynumber = [None]
# Set an initial breakpoint to stop execution
maxtries = 10
bp_file, bp_line = parse_breakpoint(opts.get('b', [1])[0], filename)
checkline = deb.checkline(bp_file, bp_line)
if not checkline:
for bp in range(bp_line + 1, bp_line + maxtries + 1):
if deb.checkline(bp_file, bp):
break
else:
msg = ("\nI failed to find a valid line to set "
"a breakpoint\n"
"after trying up to line: %s.\n"
"Please set a valid breakpoint manually "
"with the -b option." % bp)
error(msg)
return
# if we find a good linenumber, set the breakpoint
deb.do_break('%s:%s' % (bp_file, bp_line))
# Mimic Pdb._runscript(...)
deb._wait_for_mainpyfile = True
deb.mainpyfile = deb.canonic(filename)
# Start file run
print "NOTE: Enter 'c' at the",
print "%s prompt to start your script." % deb.prompt
ns = {'execfile': py3compat.execfile, 'prog_ns': prog_ns}
try:
#save filename so it can be used by methods on the deb object
deb._exec_filename = filename
deb.run('execfile("%s", prog_ns)' % filename, ns)
except:
etype, value, tb = sys.exc_info()
# Skip three frames in the traceback: the %run one,
# one inside bdb.py, and the command-line typed by the
# user (run by exec in pdb itself).
self.shell.InteractiveTB(etype, value, tb, tb_offset=3)
else:
if runner is None:
runner = self.default_runner
if runner is None:
runner = self.shell.safe_execfile
if 't' in opts:
# timed execution
try:
nruns = int(opts['N'][0])
if nruns < 1:
error('Number of runs must be >=1')
return
except (KeyError):
nruns = 1
twall0 = time.time()
if nruns == 1:
t0 = clock2()
runner(filename, prog_ns, prog_ns,
exit_ignore=exit_ignore)
t1 = clock2()
t_usr = t1[0] - t0[0]
t_sys = t1[1] - t0[1]
print "\nIPython CPU timings (estimated):"
print " User : %10.2f s." % t_usr
print " System : %10.2f s." % t_sys
else:
runs = range(nruns)
t0 = clock2()
for nr in runs:
runner(filename, prog_ns, prog_ns,
exit_ignore=exit_ignore)
t1 = clock2()
t_usr = t1[0] - t0[0]
t_sys = t1[1] - t0[1]
print "\nIPython CPU timings (estimated):"
print "Total runs performed:", nruns
print " Times : %10.2f %10.2f" % ('Total', 'Per run')
print " User : %10.2f s, %10.2f s." % (t_usr, t_usr / nruns)
print " System : %10.2f s, %10.2f s." % (t_sys, t_sys / nruns)
twall1 = time.time()
print "Wall time: %10.2f s." % (twall1 - twall0)
else:
# regular execution
runner(filename, prog_ns, prog_ns, exit_ignore=exit_ignore)
if 'i' in opts:
self.shell.user_ns['__name__'] = __name__save
else:
# The shell MUST hold a reference to prog_ns so after %run
# exits, the python deletion mechanism doesn't zero it out
# (leaving dangling references).
self.shell.cache_main_mod(prog_ns, filename)
# update IPython interactive namespace
# Some forms of read errors on the file may mean the
# __name__ key was never set; using pop we don't have to
# worry about a possible KeyError.
prog_ns.pop('__name__', None)
with preserve_keys(self.shell.user_ns, '__file__'):
self.shell.user_ns.update(prog_ns)
finally:
# It's a bit of a mystery why, but __builtins__ can change from
# being a module to becoming a dict missing some key data after
# %run. As best I can see, this is NOT something IPython is doing
# at all, and similar problems have been reported before:
# http://coding.derkeiler.com/Archive/Python/comp.lang.python/2004-10/0188.html
# Since this seems to be done by the interpreter itself, the best
# we can do is to at least restore __builtins__ for the user on
# exit.
self.shell.user_ns['__builtins__'] = builtin_mod
# Ensure key global structures are restored
sys.argv = save_argv
if restore_main:
sys.modules['__main__'] = restore_main
else:
# Remove from sys.modules the reference to main_mod we'd
# added. Otherwise it will trap references to objects
# contained therein.
del sys.modules[main_mod_name]
return stats
def time(self,line='', cell=None, local_ns=None):
"""Time execution of a Python statement or expression.
The CPU and wall clock times are printed, and the value of the
expression (if any) is returned. Note that under Win32, system time
is always reported as 0, since it can not be measured.
This function can be used both as a line and cell magic:
- In line mode you can time a single-line statement (though multiple
ones can be chained with using semicolons).
- In cell mode, you can time the cell body (a directly
following statement raises an error).
This function provides very basic timing functionality. Use the timeit
magic for more controll over the measurement.
Examples
--------
::
In [1]: %time 2**128
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00
Out[1]: 340282366920938463463374607431768211456L
In [2]: n = 1000000
In [3]: %time sum(range(n))
CPU times: user 1.20 s, sys: 0.05 s, total: 1.25 s
Wall time: 1.37
Out[3]: 499999500000L
In [4]: %time print 'hello world'
hello world
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00
Note that the time needed by Python to compile the given expression
will be reported if it is more than 0.1s. In this example, the
actual exponentiation is done by Python at compilation time, so while
the expression can take a noticeable amount of time to compute, that
time is purely due to the compilation:
In [5]: %time 3**9999;
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00 s
In [6]: %time 3**999999;
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00 s
Compiler : 0.78 s
"""
# fail immediately if the given expression can't be compiled
if line and cell:
raise UsageError("Can't use statement directly after '%%time'!")
if cell:
expr = self.shell.input_transformer_manager.transform_cell(cell)
else:
expr = self.shell.input_transformer_manager.transform_cell(line)
# Minimum time above which parse time will be reported
tp_min = 0.1
t0 = clock()
expr_ast = ast.parse(expr)
tp = clock()-t0
# Apply AST transformations
expr_ast = self.shell.transform_ast(expr_ast)
# Minimum time above which compilation time will be reported
tc_min = 0.1
if len(expr_ast.body)==1 and isinstance(expr_ast.body[0], ast.Expr):
mode = 'eval'
source = '<timed eval>'
expr_ast = ast.Expression(expr_ast.body[0].value)
else:
mode = 'exec'
source = '<timed exec>'
t0 = clock()
code = compile(expr_ast, source, mode)
tc = clock()-t0
# skew measurement as little as possible
glob = self.shell.user_ns
wtime = time.time
# time execution
wall_st = wtime()
if mode=='eval':
st = clock2()
out = eval(code, glob, local_ns)
end = clock2()
else:
st = clock2()
exec code in glob, local_ns
end = clock2()
out = None
wall_end = wtime()
# Compute actual times and report
wall_time = wall_end-wall_st
cpu_user = end[0]-st[0]
cpu_sys = end[1]-st[1]
cpu_tot = cpu_user+cpu_sys
# On windows cpu_sys is always zero, so no new information to the next print
if sys.platform != 'win32':
print "CPU times: user %s, sys: %s, total: %s" % \
(_format_time(cpu_user),_format_time(cpu_sys),_format_time(cpu_tot))
print "Wall time: %s" % _format_time(wall_time)
if tc > tc_min:
print "Compiler : %s" % _format_time(tc)
if tp > tp_min:
print "Parser : %s" % _format_time(tp)
return out
def time(self, line='', cell=None, local_ns=None):
"""Time execution of a Python statement or expression.
The CPU and wall clock times are printed, and the value of the
expression (if any) is returned. Note that under Win32, system time
is always reported as 0, since it can not be measured.
This function can be used both as a line and cell magic:
- In line mode you can time a single-line statement (though multiple
ones can be chained with using semicolons).
- In cell mode, you can time the cell body (a directly
following statement raises an error).
This function provides very basic timing functionality. Use the timeit
magic for more controll over the measurement.
Examples
--------
::
In [1]: %time 2**128
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00
Out[1]: 340282366920938463463374607431768211456L
In [2]: n = 1000000
In [3]: %time sum(range(n))
CPU times: user 1.20 s, sys: 0.05 s, total: 1.25 s
Wall time: 1.37
Out[3]: 499999500000L
In [4]: %time print 'hello world'
hello world
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00
Note that the time needed by Python to compile the given expression
will be reported if it is more than 0.1s. In this example, the
actual exponentiation is done by Python at compilation time, so while
the expression can take a noticeable amount of time to compute, that
time is purely due to the compilation:
In [5]: %time 3**9999;
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00 s
In [6]: %time 3**999999;
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00 s
Compiler : 0.78 s
"""
# fail immediately if the given expression can't be compiled
if line and cell:
raise UsageError("Can't use statement directly after '%%time'!")
if cell:
expr = self.shell.input_transformer_manager.transform_cell(cell)
else:
expr = self.shell.input_transformer_manager.transform_cell(line)
# Minimum time above which parse time will be reported
tp_min = 0.1
t0 = clock()
expr_ast = ast.parse(expr)
tp = clock() - t0
# Apply AST transformations
expr_ast = self.shell.transform_ast(expr_ast)
# Minimum time above which compilation time will be reported
tc_min = 0.1
if len(expr_ast.body) == 1 and isinstance(expr_ast.body[0], ast.Expr):
mode = 'eval'
source = '<timed eval>'
expr_ast = ast.Expression(expr_ast.body[0].value)
else:
mode = 'exec'
source = '<timed exec>'
t0 = clock()
code = compile(expr_ast, source, mode)
tc = clock() - t0
# skew measurement as little as possible
glob = self.shell.user_ns
wtime = time.time
# time execution
wall_st = wtime()
if mode == 'eval':
st = clock2()
out = eval(code, glob, local_ns)
end = clock2()
else:
st = clock2()
exec code in glob, local_ns
end = clock2()
out = None
wall_end = wtime()
# Compute actual times and report
wall_time = wall_end - wall_st
cpu_user = end[0] - st[0]
cpu_sys = end[1] - st[1]
cpu_tot = cpu_user + cpu_sys
# On windows cpu_sys is always zero, so no new information to the next print
if sys.platform != 'win32':
print "CPU times: user %s, sys: %s, total: %s" % \
(_format_time(cpu_user),_format_time(cpu_sys),_format_time(cpu_tot))
print "Wall time: %s" % _format_time(wall_time)
if tc > tc_min:
print "Compiler : %s" % _format_time(tc)
if tp > tp_min:
print "Parser : %s" % _format_time(tp)
return out
def time(self, parameter_s, local_ns=None):
"""Time execution of a Python statement or expression.
The CPU and wall clock times are printed, and the value of the
expression (if any) is returned. Note that under Win32, system time
is always reported as 0, since it can not be measured.
This function provides very basic timing functionality. In Python
2.3, the timeit module offers more control and sophistication, so this
could be rewritten to use it (patches welcome).
Examples
--------
::
In [1]: time 2**128
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00
Out[1]: 340282366920938463463374607431768211456L
In [2]: n = 1000000
In [3]: time sum(range(n))
CPU times: user 1.20 s, sys: 0.05 s, total: 1.25 s
Wall time: 1.37
Out[3]: 499999500000L
In [4]: time print 'hello world'
hello world
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00
Note that the time needed by Python to compile the given expression
will be reported if it is more than 0.1s. In this example, the
actual exponentiation is done by Python at compilation time, so while
the expression can take a noticeable amount of time to compute, that
time is purely due to the compilation:
In [5]: time 3**9999;
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00 s
In [6]: time 3**999999;
CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
Wall time: 0.00 s
Compiler : 0.78 s
"""
# fail immediately if the given expression can't be compiled
expr = self.shell.prefilter(parameter_s, False)
# Minimum time above which compilation time will be reported
tc_min = 0.1
try:
mode = 'eval'
t0 = clock()
code = compile(expr, '<timed eval>', mode)
tc = clock() - t0
except SyntaxError:
mode = 'exec'
t0 = clock()
code = compile(expr, '<timed exec>', mode)
tc = clock() - t0
# skew measurement as little as possible
glob = self.shell.user_ns
wtime = time.time
# time execution
wall_st = wtime()
if mode == 'eval':
st = clock2()
out = eval(code, glob, local_ns)
end = clock2()
else:
st = clock2()
exec code in glob, local_ns
end = clock2()
out = None
wall_end = wtime()
# Compute actual times and report
wall_time = wall_end - wall_st
cpu_user = end[0] - st[0]
cpu_sys = end[1] - st[1]
cpu_tot = cpu_user + cpu_sys
print "CPU times: user %.2f s, sys: %.2f s, total: %.2f s" % \
(cpu_user,cpu_sys,cpu_tot)
print "Wall time: %.2f s" % wall_time
if tc > tc_min:
print "Compiler : %.2f s" % tc
return out
def run(self, parameter_s='', runner=None, file_finder=get_py_filename):
"""Run the named file inside IPython as a program.
Usage:\\
%run [-n -i -t [-N<N>] -d [-b<N>] -p [profile options]] file [args]
Parameters after the filename are passed as command-line arguments to
the program (put in sys.argv). Then, control returns to IPython's
prompt.
This is similar to running at a system prompt:\\
$ python file args\\
but with the advantage of giving you IPython's tracebacks, and of
loading all variables into your interactive namespace for further use
(unless -p is used, see below).
The file is executed in a namespace initially consisting only of
__name__=='__main__' and sys.argv constructed as indicated. It thus
sees its environment as if it were being run as a stand-alone program
(except for sharing global objects such as previously imported
modules). But after execution, the IPython interactive namespace gets
updated with all variables defined in the program (except for __name__
and sys.argv). This allows for very convenient loading of code for
interactive work, while giving each program a 'clean sheet' to run in.
Options:
-n: __name__ is NOT set to '__main__', but to the running file's name
without extension (as python does under import). This allows running
scripts and reloading the definitions in them without calling code
protected by an ' if __name__ == "__main__" ' clause.
-i: run the file in IPython's namespace instead of an empty one. This
is useful if you are experimenting with code written in a text editor
which depends on variables defined interactively.
-e: ignore sys.exit() calls or SystemExit exceptions in the script
being run. This is particularly useful if IPython is being used to
run unittests, which always exit with a sys.exit() call. In such
cases you are interested in the output of the test results, not in
seeing a traceback of the unittest module.
-t: print timing information at the end of the run. IPython will give
you an estimated CPU time consumption for your script, which under
Unix uses the resource module to avoid the wraparound problems of
time.clock(). Under Unix, an estimate of time spent on system tasks
is also given (for Windows platforms this is reported as 0.0).
If -t is given, an additional -N<N> option can be given, where <N>
must be an integer indicating how many times you want the script to
run. The final timing report will include total and per run results.
For example (testing the script uniq_stable.py)::
In [1]: run -t uniq_stable
IPython CPU timings (estimated):\\
User : 0.19597 s.\\
System: 0.0 s.\\
In [2]: run -t -N5 uniq_stable
IPython CPU timings (estimated):\\
Total runs performed: 5\\
Times : Total Per run\\
User : 0.910862 s, 0.1821724 s.\\
System: 0.0 s, 0.0 s.
-d: run your program under the control of pdb, the Python debugger.
This allows you to execute your program step by step, watch variables,
etc. Internally, what IPython does is similar to calling:
pdb.run('execfile("YOURFILENAME")')
with a breakpoint set on line 1 of your file. You can change the line
number for this automatic breakpoint to be <N> by using the -bN option
(where N must be an integer). For example::
%run -d -b40 myscript
will set the first breakpoint at line 40 in myscript.py. Note that
the first breakpoint must be set on a line which actually does
something (not a comment or docstring) for it to stop execution.
When the pdb debugger starts, you will see a (Pdb) prompt. You must
first enter 'c' (without quotes) to start execution up to the first
breakpoint.
Entering 'help' gives information about the use of the debugger. You
can easily see pdb's full documentation with "import pdb;pdb.help()"
at a prompt.
-p: run program under the control of the Python profiler module (which
prints a detailed report of execution times, function calls, etc).
You can pass other options after -p which affect the behavior of the
profiler itself. See the docs for %prun for details.
In this mode, the program's variables do NOT propagate back to the
IPython interactive namespace (because they remain in the namespace
where the profiler executes them).
Internally this triggers a call to %prun, see its documentation for
details on the options available specifically for profiling.
There is one special usage for which the text above doesn't apply:
if the filename ends with .ipy, the file is run as ipython script,
just as if the commands were written on IPython prompt.
-m: specify module name to load instead of script path. Similar to
the -m option for the python interpreter. Use this option last if you
want to combine with other %run options. Unlike the python interpreter
only source modules are allowed no .pyc or .pyo files.
For example::
%run -m example
will run the example module.
"""
# get arguments and set sys.argv for program to be run.
opts, arg_lst = self.parse_options(parameter_s,
'nidtN:b:pD:l:rs:T:em:',
mode='list',
list_all=1)
if "m" in opts:
modulename = opts["m"][0]
modpath = find_mod(modulename)
if modpath is None:
warn('%r is not a valid modulename on sys.path' % modulename)
return
arg_lst = [modpath] + arg_lst
try:
filename = file_finder(arg_lst[0])
except IndexError:
warn('you must provide at least a filename.')
print '\n%run:\n', oinspect.getdoc(self.run)
return
except IOError as e:
try:
msg = str(e)
except UnicodeError:
msg = e.message
error(msg)
return
if filename.lower().endswith('.ipy'):
self.shell.safe_execfile_ipy(filename)
return
# Control the response to exit() calls made by the script being run
exit_ignore = 'e' in opts
# Make sure that the running script gets a proper sys.argv as if it
# were run from a system shell.
save_argv = sys.argv # save it for later restoring
# simulate shell expansion on arguments, at least tilde expansion
args = [os.path.expanduser(a) for a in arg_lst[1:]]
sys.argv = [filename] + args # put in the proper filename
# protect sys.argv from potential unicode strings on Python 2:
if not py3compat.PY3:
sys.argv = [py3compat.cast_bytes(a) for a in sys.argv]
if 'i' in opts:
# Run in user's interactive namespace
prog_ns = self.shell.user_ns
__name__save = self.shell.user_ns['__name__']
prog_ns['__name__'] = '__main__'
main_mod = self.shell.new_main_mod(prog_ns)
else:
# Run in a fresh, empty namespace
if 'n' in opts:
name = os.path.splitext(os.path.basename(filename))[0]
else:
name = '__main__'
main_mod = self.shell.new_main_mod()
prog_ns = main_mod.__dict__
prog_ns['__name__'] = name
# Since '%run foo' emulates 'python foo.py' at the cmd line, we must
# set the __file__ global in the script's namespace
prog_ns['__file__'] = filename
# pickle fix. See interactiveshell for an explanation. But we need to
# make sure that, if we overwrite __main__, we replace it at the end
main_mod_name = prog_ns['__name__']
if main_mod_name == '__main__':
restore_main = sys.modules['__main__']
else:
restore_main = False
# This needs to be undone at the end to prevent holding references to
# every single object ever created.
sys.modules[main_mod_name] = main_mod
try:
stats = None
with self.shell.readline_no_record:
if 'p' in opts:
stats = self.prun('', None, False, opts, arg_lst, prog_ns)
else:
if 'd' in opts:
deb = debugger.Pdb(self.shell.colors)
# reset Breakpoint state, which is moronically kept
# in a class
bdb.Breakpoint.next = 1
bdb.Breakpoint.bplist = {}
bdb.Breakpoint.bpbynumber = [None]
# Set an initial breakpoint to stop execution
maxtries = 10
bp = int(opts.get('b', [1])[0])
checkline = deb.checkline(filename, bp)
if not checkline:
for bp in range(bp + 1, bp + maxtries + 1):
if deb.checkline(filename, bp):
break
else:
msg = (
"\nI failed to find a valid line to set "
"a breakpoint\n"
"after trying up to line: %s.\n"
"Please set a valid breakpoint manually "
"with the -b option." % bp)
error(msg)
return
# if we find a good linenumber, set the breakpoint
deb.do_break('%s:%s' % (filename, bp))
# Start file run
print "NOTE: Enter 'c' at the",
print "%s prompt to start your script." % deb.prompt
ns = {
'execfile': py3compat.execfile,
'prog_ns': prog_ns
}
try:
#save filename so it can be used by methods on the deb object
deb._exec_filename = filename
deb.run('execfile("%s", prog_ns)' % filename, ns)
except:
etype, value, tb = sys.exc_info()
# Skip three frames in the traceback: the %run one,
# one inside bdb.py, and the command-line typed by the
# user (run by exec in pdb itself).
self.shell.InteractiveTB(etype,
value,
tb,
tb_offset=3)
else:
if runner is None:
runner = self.default_runner
if runner is None:
runner = self.shell.safe_execfile
if 't' in opts:
# timed execution
try:
nruns = int(opts['N'][0])
if nruns < 1:
error('Number of runs must be >=1')
return
except (KeyError):
nruns = 1
twall0 = time.time()
if nruns == 1:
t0 = clock2()
runner(filename,
prog_ns,
prog_ns,
exit_ignore=exit_ignore)
t1 = clock2()
t_usr = t1[0] - t0[0]
t_sys = t1[1] - t0[1]
print "\nIPython CPU timings (estimated):"
print " User : %10.2f s." % t_usr
print " System : %10.2f s." % t_sys
else:
runs = range(nruns)
t0 = clock2()
for nr in runs:
runner(filename,
prog_ns,
prog_ns,
exit_ignore=exit_ignore)
t1 = clock2()
t_usr = t1[0] - t0[0]
t_sys = t1[1] - t0[1]
print "\nIPython CPU timings (estimated):"
print "Total runs performed:", nruns
print " Times : %10.2f %10.2f" % (
'Total', 'Per run')
print " User : %10.2f s, %10.2f s." % (
t_usr, t_usr / nruns)
print " System : %10.2f s, %10.2f s." % (
t_sys, t_sys / nruns)
twall1 = time.time()
print "Wall time: %10.2f s." % (twall1 - twall0)
else:
# regular execution
runner(filename,
prog_ns,
prog_ns,
exit_ignore=exit_ignore)
if 'i' in opts:
self.shell.user_ns['__name__'] = __name__save
else:
# The shell MUST hold a reference to prog_ns so after %run
# exits, the python deletion mechanism doesn't zero it out
# (leaving dangling references).
self.shell.cache_main_mod(prog_ns, filename)
# update IPython interactive namespace
# Some forms of read errors on the file may mean the
# __name__ key was never set; using pop we don't have to
# worry about a possible KeyError.
prog_ns.pop('__name__', None)
self.shell.user_ns.update(prog_ns)
finally:
# It's a bit of a mystery why, but __builtins__ can change from
# being a module to becoming a dict missing some key data after
# %run. As best I can see, this is NOT something IPython is doing
# at all, and similar problems have been reported before:
# http://coding.derkeiler.com/Archive/Python/comp.lang.python/2004-10/0188.html
# Since this seems to be done by the interpreter itself, the best
# we can do is to at least restore __builtins__ for the user on
# exit.
self.shell.user_ns['__builtins__'] = builtin_mod
# Ensure key global structures are restored
sys.argv = save_argv
if restore_main:
sys.modules['__main__'] = restore_main
else:
# Remove from sys.modules the reference to main_mod we'd
# added. Otherwise it will trap references to objects
# contained therein.
del sys.modules[main_mod_name]
return stats