"""Tests to show that the benchmarks we based our speed optimizations on are still valid"""

from functools import partial
from timeit import timeit

from nose.tools import ok_


timeit = partial(timeit, number=10000)


def test_lists_vs_dicts():
    """See what's faster at int key lookup: dicts or lists."""
    list_time = timeit('item = l[9000]', 'l = [0] * 10000')
    dict_time = timeit('item = d[9000]', 'd = dict((x, 0) for x in xrange(10000))')

    # Dicts take about 1.6x as long as lists in Python 2.6 and 2.7.
    print '%s < %s' % (list_time, dict_time)
    ok_(list_time < dict_time)


def test_call_vs_inline():
    """How bad is the calling penalty?"""
    no_call = timeit('l[0] += 1', 'l = [0]')
    call = timeit('add(); l[0] += 1', 'l = [0]\n'
                                      'def add():\n'
                                      '    pass')

    # Calling a function is pretty fast; it takes just 1.2x as long as the
    # global var access and addition in l[0] += 1.
    print '%s (no call) < %s (call)' % (no_call, call)
    ok_(no_call < call)


def test_startswith_vs_regex():
    """Can I beat the speed of regexes by special-casing literals?"""
    re_time = timeit(
        'r.match(t, 19)',
        'import re\n'
        "r = re.compile('hello')\n"
        "t = 'this is the finest hello ever'")
    startswith_time = timeit("t.startswith('hello', 19)",
                             "t = 'this is the finest hello ever'")

    # Regexes take 2.24x as long as simple string matching.
    print '%s (startswith) < %s (re)' % (startswith_time, re_time)
    ok_(startswith_time < re_time)

"""Tests to show that the benchmarks we based our speed optimizations on are still valid"""

from functools import partial
from timeit import timeit

from nose.tools import ok_


timeit = partial(timeit, number=100000)


def test_lists_vs_dicts():
    """See what's faster at int key lookup: dicts or lists."""
    list_time = timeit('item = l[9000]', 'l = [0] * 10000')
    dict_time = timeit('item = d[9000]', 'd = dict((x, 0) for x in xrange(10000))')

    # Dicts take about 1.6x as long as lists in Python 2.6 and 2.7.
    print '%s < %s' % (list_time, dict_time)
    ok_(list_time < dict_time)


def test_call_vs_inline():
    """How bad is the calling penalty?"""
    no_call = timeit('l[0] += 1', 'l = [0]')
    call = timeit('add(); l[0] += 1', 'l = [0]\n'
                                      'def add():\n'
                                      '    pass')

    # Calling a function is pretty fast; it takes just 1.2x as long as the
    # global var access and addition in l[0] += 1.
    print '%s (no call) < %s (call)' % (no_call, call)
    ok_(no_call < call)


def test_startswith_vs_regex():
    """Can I beat the speed of regexes by special-casing literals?"""
    re_time = timeit(
        'r.match(t, 19)',
        'import re\n'
        "r = re.compile('hello')\n"
        "t = 'this is the finest hello ever'")
    startswith_time = timeit("t.startswith('hello', 19)",
                             "t = 'this is the finest hello ever'")

    # Regexes take 2.24x as long as simple string matching.
    print '%s (startswith) < %s (re)' % (startswith_time, re_time)
    ok_(startswith_time < re_time)

Increase number of timeit loops for benchmarks. They were spuriously failing sometimes.