File: serialise-speed

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#!/usr/bin/env python
# Copyright 2010-2015  Lars Wirzenius
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.


import sys
import time

import cliapp
import yaml

import obnamlib


def measure(n, func):
    start = time.clock()
    for i in range(n):
        func()
    end = time.clock()
    return end - start


class MicroBenchmark(cliapp.Application):

    def process_args(self, args):
        n = int(args[0])
        if len(args) > 1:
            obj = self.read_object(args[1])
        else:
            obj = self.get_builtin_object()
        encoded = obnamlib.serialise_object(obj)

        calibrate = measure(n, lambda: None)
        encode = measure(n, lambda: obnamlib.serialise_object(obj))
        self.report('encode', n, encode - calibrate)
        decode = measure(n, lambda: obnamlib.deserialise_object(encoded))
        self.report('decode', n, decode - calibrate)

    def read_object(self, filename):
        with open(filename) as f:
            return yaml.safe_load(f)

    def get_builtin_object(self):
        return {
            'foo': 'bar',
            'big': 'x' * 1024**2,
            'dict': {
                'foo': 'yo',
                'long': ['x'] * 1024**2,
            }
        }

    def report(self, what, num_iters, duration):
        self.output.write(
            '%s: %s ms/iter (%.1f/s)\n' %
            (what, 1000.0 * duration/num_iters, num_iters/duration))

if __name__ == '__main__':
    MicroBenchmark().run()