#!/data/data/com.termux/files/usr/bin/env python

"""Tool for measuring execution time of small code snippets.

This module avoids a number of common traps for measuring execution
times.  See also Tim Peters' introduction to the Algorithms chapter in
the Python Cookbook, published by O'Reilly.

Library usage: see the Timer class.

Command line usage:
    python timeit.py [-n N] [-r N] [-s S] [-t] [-c] [-h] [--] [statement]

Options:
  -n/--number N: how many times to execute 'statement' (default: see below)
  -r/--repeat N: how many times to repeat the timer (default 7)
  -s/--setup S: statement to be executed once initially (default 'pass')
  -t/--time: use time.time() (default on Unix)
  -c/--clock: use time.clock() (default on Windows)
  -v/--verbose: print raw timing results; repeat for more digits precision
  -h/--help: print this usage message and exit
  --: separate options from statement, use when statement starts with -
  statement: statement to be timed (default 'pass')

A multi-line statement may be given by specifying each line as a
separate argument; indented lines are possible by enclosing an
argument in quotes and using leading spaces.  Multiple -s options are
treated similarly.

If -n is not given, a suitable number of loops is calculated by trying
successive powers of 10 until the total time is at least 0.2 seconds.

The difference in default timer function is because on Windows,
clock() has microsecond granularity but time()'s granularity is 1/60th
of a second; on Unix, clock() has 1/100th of a second granularity and
time() is much more precise.  On either platform, the default timer
functions measure wall clock time, not the CPU time.  This means that
other processes running on the same computer may interfere with the
timing.  The best thing to do when accurate timing is necessary is to
repeat the timing a few times and use the best time.  The -r option is
good for this; the default of 3 repetitions is probably enough in most
cases.  On Unix, you can use clock() to measure CPU time.

Note: there is a certain baseline overhead associated with executing a
pass statement.  The code here doesn't try to hide it, but you should
be aware of it.  The baseline overhead can be measured by invoking the
program without arguments.

The baseline overhead differs between Python versions!  Also, to
fairly compare older Python versions to Python 2.3, you may want to
use python -O for the older versions to avoid timing SET_LINENO
instructions.
"""

import gc
import math
import os
import sys
import time

__all__ = ["Timer"]

dummy_src_name = "<timeit-src>"
default_number = 1000000
default_repeat = 7

if sys.platform == "win32":
    # On Windows, the best timer is time.clock()
    default_timer = time.clock
else:
    # On most other platforms the best timer is time.time()
    default_timer = time.time

# Don't change the indentation of the template; the reindent() calls
# in Timer.__init__() depend on setup being indented 4 spaces and stmt
# being indented 8 spaces.
template = """
def inner(_it, _timer%(init)s):
    %(setup)s
    _t0 = _timer()
    while _it > 0:
        _it -= 1
        %(stmt)s
    _t1 = _timer()
    return _t1 - _t0
"""

def reindent(src, indent):
    """Helper to reindent a multi-line statement."""
    return src.replace("\n", "\n" + " "*indent)

def _template_func(setup, func):
    """Create a timer function. Used if the "statement" is a callable."""
    def inner(_it, _timer, _func=func):
        setup()
        _t0 = _timer()
        while _it > 0:
            _it -= 1
            _func()
        _t1 = _timer()
        return _t1 - _t0
    return inner

class Timer:
    """Class for timing execution speed of small code snippets.

    The constructor takes a statement to be timed, an additional
    statement used for setup, and a timer function.  Both statements
    default to 'pass'; the timer function is platform-dependent (see
    module doc string).

    To measure the execution time of the first statement, use the
    timeit() method.  The repeat() method is a convenience to call
    timeit() multiple times and return a list of results.

    The statements may contain newlines, as long as they don't contain
    multi-line string literals.
    """

    def __init__(self, stmt="pass", setup="pass", timer=default_timer):
        """Constructor.  See class doc string."""
        self.timer = timer
        ns = {}
        if isinstance(stmt, basestring):
            # Check that the code can be compiled outside a function
            if isinstance(setup, basestring):
                compile(setup, dummy_src_name, "exec")
                compile(setup + '\n' + stmt, dummy_src_name, "exec")
            else:
                compile(stmt, dummy_src_name, "exec")
            stmt = reindent(stmt, 8)
            if isinstance(setup, basestring):
                setup = reindent(setup, 4)
                src = template % {'stmt': stmt, 'setup': setup, 'init': ''}
            elif hasattr(setup, '__call__'):
                src = template % {'stmt': stmt, 'setup': '_setup()',
                                  'init': ', _setup=_setup'}
                ns['_setup'] = setup
            else:
                raise ValueError("setup is neither a string nor callable")
            self.src = src # Save for traceback display
            def make_inner():
                # PyPy tweak: recompile the source code each time before
                # calling inner(). There are situations like Issue #1776
                # where PyPy tries to reuse the JIT code from before,
                # but that's not going to work: the first thing the
                # function does is the "-s" statement, which may declare
                # new classes (here a namedtuple). We end up with
                # bridges from the inner loop; more and more of them
                # every time we call inner().
                code = compile(src, dummy_src_name, "exec")
                exec code in globals(), ns
                return ns["inner"]
            self.make_inner = make_inner
        elif hasattr(stmt, '__call__'):
            self.src = None
            if isinstance(setup, basestring):
                _setup = setup
                def setup():
                    exec _setup in globals(), ns
            elif not hasattr(setup, '__call__'):
                raise ValueError("setup is neither a string nor callable")
            inner = _template_func(setup, stmt)
            self.make_inner = lambda: inner
        else:
            raise ValueError("stmt is neither a string nor callable")

    def print_exc(self, file=None):
        """Helper to print a traceback from the timed code.

        Typical use:

            t = Timer(...)       # outside the try/except
            try:
                t.timeit(...)    # or t.repeat(...)
            except:
                t.print_exc()

        The advantage over the standard traceback is that source lines
        in the compiled template will be displayed.

        The optional file argument directs where the traceback is
        sent; it defaults to sys.stderr.
        """
        import linecache, traceback
        if self.src is not None:
            linecache.cache[dummy_src_name] = (len(self.src),
                                               None,
                                               self.src.split("\n"),
                                               dummy_src_name)
        # else the source is already stored somewhere else

        traceback.print_exc(file=file)

    def timeit(self, number=default_number):
        """Time 'number' executions of the main statement.

        To be precise, this executes the setup statement once, and
        then returns the time it takes to execute the main statement
        a number of times, as a float measured in seconds.  The
        argument is the number of times through the loop, defaulting
        to one million.  The main statement, the setup statement and
        the timer function to be used are passed to the constructor.
        """
        inner = self.make_inner()
        gcold = gc.isenabled()
        if '__pypy__' not in sys.builtin_module_names:
            gc.disable()    # only do that on CPython
        try:
            timing = inner(number, self.timer)
        finally:
            if gcold:
                gc.enable()
        return timing

    def repeat(self, repeat=default_repeat, number=default_number):
        """Call timeit() a few times.

        This is a convenience function that calls the timeit()
        repeatedly, returning a list of results.  The first argument
        specifies how many times to call timeit(), defaulting to 3;
        the second argument specifies the timer argument, defaulting
        to one million.

        Note: it's tempting to calculate mean and standard deviation
        from the result vector and report these.  However, this is not
        very useful.  In a typical case, the lowest value gives a
        lower bound for how fast your machine can run the given code
        snippet; higher values in the result vector are typically not
        caused by variability in Python's speed, but by other
        processes interfering with your timing accuracy.  So the min()
        of the result is probably the only number you should be
        interested in.  After that, you should look at the entire
        vector and apply common sense rather than statistics.
        """
        r = []
        for i in range(repeat):
            t = self.timeit(number)
            r.append(t)
        return r

def timeit(stmt="pass", setup="pass", timer=default_timer,
           number=default_number):
    """Convenience function to create Timer object and call timeit method."""
    return Timer(stmt, setup, timer).timeit(number)

def repeat(stmt="pass", setup="pass", timer=default_timer,
           repeat=default_repeat, number=default_number):
    """Convenience function to create Timer object and call repeat method."""
    return Timer(stmt, setup, timer).repeat(repeat, number)

def main(args=None, _wrap_timer=None):
    """Main program, used when run as a script.

    The optional 'args' argument specifies the command line to be parsed,
    defaulting to sys.argv[1:].

    The return value is an exit code to be passed to sys.exit(); it
    may be None to indicate success.

    When an exception happens during timing, a traceback is printed to
    stderr and the return value is 1.  Exceptions at other times
    (including the template compilation) are not caught.

    '_wrap_timer' is an internal interface used for unit testing.  If it
    is not None, it must be a callable that accepts a timer function
    and returns another timer function (used for unit testing).
    """
    if args is None:
        args = sys.argv[1:]
    origargs = args
    import getopt
    try:
        opts, args = getopt.getopt(args, "n:s:r:tcvh",
                                   ["number=", "setup=", "repeat=",
                                    "time", "clock", "verbose", "help"])
    except getopt.error, err:
        print err
        print "use -h/--help for command line help"
        return 2
    timer = default_timer
    stmt = "\n".join(args) or "pass"
    number = 0 # auto-determine
    setup = []
    repeat = default_repeat
    verbose = 0
    precision = 3
    units = {"sec": 1, "msec": 1e3, "usec": 1e6, "ns": 1e9}
    for o, a in opts:
        if o in ("-n", "--number"):
            number = int(a)
        if o in ("-s", "--setup"):
            setup.append(a)
        if o in ("-r", "--repeat"):
            repeat = int(a)
            if repeat <= 0:
                repeat = 1
        if o in ("-t", "--time"):
            timer = time.time
        if o in ("-c", "--clock"):
            timer = time.clock
        if o in ("-v", "--verbose"):
            if verbose:
                precision += 1
            verbose += 1
        if o in ("-h", "--help"):
            print __doc__,
            return 0
    setup = "\n".join(setup) or "pass"

    print "WARNING: timeit is a very unreliable tool. use pyperf or something else for real measurements"
    executable = os.path.basename(sys.executable)
    print "%s -m pip install pyperf" % executable
    print "%s -m pyperf timeit %s" % (
        executable,
        " ".join([(arg if arg.startswith("-") else repr(arg))
                        for arg in origargs]), )
    print "-" * 60
    # Include the current directory, so that local imports work (sys.path
    # contains the directory of this script, rather than the current
    # directory)
    sys.path.insert(0, os.curdir)
    if _wrap_timer is not None:
        timer = _wrap_timer(timer)
    t = Timer(stmt, setup, timer)
    if number == 0:
        # determine number so that 0.2 <= total time < 2.0
        for i in range(0, 10):
            number = 10**i
            try:
                x = t.timeit(number)
            except:
                t.print_exc()
                return 1
            if verbose:
                print "%d loops -> %.*g secs" % (number, precision, x)
            if x >= 0.2:
                break
    try:
        timings = t.repeat(repeat, number)
    except:
        t.print_exc()
        return 1
    if verbose:
        print "raw times:", " ".join(["%.*g" % (precision, x) for x in timings])

    timings = [dt / number for dt in timings]

    def _avg(l):
        return math.fsum(l) / len(l)
    def _stdev(l):
        avg = _avg(l)
        return (math.fsum([(x - avg) ** 2 for x in l]) / len(l)) ** 0.5

    average = _avg(timings)

    scales = [(scale, unit) for unit, scale in units.items()]
    scales.sort()
    for scale, time_unit in scales:
        if average * scale >= 1.0:
             break

    stdev = _stdev(timings)
    print("%s loops, average of %d: %.*g +- %.*g %s per loop (using standard deviation)"
          % (number, repeat,
             precision, average * scale,
             precision, stdev * scale, time_unit))
    return None

if __name__ == "__main__":
    sys.exit(main())
