benchmark_signac.py

# Copyright 2017 The Regents of the University of Michigan
#
# Permission is hereby granted, free of charge, to any person obtaining a copy of
# this software and associated documentation files (the "Software"), to deal in
# the Software without restriction, including without limitation the rights to
# use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
# of the Software, and to permit persons to whom the Software is furnished to do
# so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
import os
import six
import string
import random
import timeit
import warnings
import logging
from contextlib import contextmanager
from collections import OrderedDict
from multiprocessing import Pool

import signac
from tqdm import tqdm

if six.PY2:
    from tempdir import TemporaryDirectory
else:
    from tempfile import TemporaryDirectory


logger = logging.getLogger(__name__)


class Timer(timeit.Timer):

    def timeit(self, number=10):
        return number, super().timeit(number=number)

    def repeat(self, repeat=3, number=10):
        return super().repeat(repeat=repeat, number=number)


def size(fn):
    try:
        return os.path.getsize(fn)
    except FileNotFoundError:
        return 0


def calc_project_metadata_size(project):
    sp_size = []
    doc_size = []
    for job in tqdm(project, 'determine metadata size'):
        sp_size.append(size(job.fn(job.FN_MANIFEST)))
        doc_size.append(size(job.fn(job.FN_DOCUMENT)))
    return sp_size, doc_size


def fmt_size(size, units=None):
    "Returns a human readable string reprentation of bytes."
    if units is None:
        units = [' bytes', 'KB', 'MB', 'GB', 'TB', 'PB', 'EB']
    return str(size) + units.pop(0) if size < 1024 else fmt_size(size >> 10, units[1:])


def total(benchmarks):
    n = sum((b[0] for b in benchmarks))
    dt = sum((b[1] for b in benchmarks))
    return n, dt


def print_result(n, dt):
    print("Mean time: {:.2}s ({} iterations)".format(dt / n, n))


def determine_project_size(project):
    sp_size, doc_size = calc_project_metadata_size(project)
    meta = {
        'N': len(project),
        'statepoint_metadata_size': sum(sp_size),
        'document_metadata_size': sum(doc_size),
        'total': sum(sp_size) + sum(doc_size),
    }
    return meta


def noop(*args, **kwarg):
    pass


def _random_str(size):
    return ''.join(random.choice(string.ascii_lowercase) for _ in range(size))


def _make_doc(i, num_keys=1, data_size=0):
    assert num_keys >= 1
    assert data_size >= 0

    doc = {'b_{}'.format(j): _random_str(data_size) for j in range(num_keys - 1)}
    doc['a'] = '{}{}'.format(i, _random_str(max(0, data_size - len(str(i)))))
    return doc


def _make_job(project, num_keys, num_doc_keys, data_size, data_std, i):
    size = max(0, int(random.gauss(data_size, data_std)))
    job = project.open_job(_make_doc(i, num_keys, size))
    if num_doc_keys > 0:
        size = max(0, int(random.gauss(data_size, data_std)))
        job.document.update(_make_doc(i, num_doc_keys, size))
    else:
        job.init()


def generate_random_data(project, N_sp, num_keys=1, num_doc_keys=0,
                         data_size=0, data_std=0, parallel=True):
    assert len(project) == 0

    if six.PY2:
        if parallel:
            warnings.warn("Function 'generate_random_data()' not parallelized for Python 2.")
            parallel = False

    if parallel:
        with Pool() as pool:
            p = [(project, num_keys, num_doc_keys, data_size, data_std, i) for i in range(N_sp)]
            list(pool.starmap(_make_job, tqdm(p, desc='init random project data')))
    else:
        from functools import partial
        make = partial(_make_job, project, num_keys, num_doc_keys, data_size, data_std)
        list(map(make, tqdm(range(N_sp), desc='init random project data')))


@contextmanager
def setup_random_project(N, num_keys=1, num_doc_keys=0,
                         data_size=0, data_std=0, seed=0, root=None):
    random.seed(seed)
    if not isinstance(N, int):
        raise TypeError("N must be an integer!")

    with TemporaryDirectory(dir=root) as tmp:
        project = signac.init_project('benchmark-N={}'.format(N), root=tmp)
        generate_random_data(project, N, num_keys, num_doc_keys, data_size, data_std)
        yield project


def benchmark_project(project, keys=None):
    root = project.root_directory()
    setup = "import signac; project = signac.get_project(root='{}'); ".format(root)
    setup += "from itertools import islice, repeat; import random; "
    setup += "from benchmark_signac import noop;"
    #setup_parallel = setup + "from multiprocessing import Pool; pool = Pool();"

    data = OrderedDict()

    def run(key, timer, repeat=3, number=10):
        if keys is None or key in keys:
            logger.info("Run '{}'...".format(key))
            data[key] = timer.repeat(repeat=repeat, number=number)

    run('determine_len', Timer('len(project)', setup=setup))

    run('select_by_id', Timer(
        stmt="project.open_job(id=jobid)",
        setup=setup + "jobid = random.choice(list(islice(project, 100))).get_id()"))

    run('iterate', Timer("list(project)", setup), 3, 10)

    run('iterate_single_pass', Timer("list(project)", setup), number=1)

    #run('N_iterate', Timer("list(map(noop, project))", setup))
    #run('N_iterate_parallel', Timer("list(pool.map(noop, project))", setup_parallel))

    run('search_lean_filter', Timer(
        stmt="len(project.find_jobs(f))",
        setup=setup + "sp = project.open_job(id=random.choice(list(project.find_job_ids()))).sp();"
        "k, v = sp.popitem(); f = {k: v}"))

    run('search_rich_filter', Timer(
        stmt="len(project.find_jobs(f))",
        setup=setup + "f = project.open_job(id=random.choice(list(project.find_job_ids()))).sp()"))

    return data