from timeit import Timer
from random import randrange, seed, sample
from collections import defaultdict
from itertools import repeat

class Counter(dict):
    def __missing__(self, key):
        return 0

def c1(data):
    c = Counter()
    for elem in data:
        c[elem] += 1
    return c

def c2(data):
    c = Counter()
    c_get = c.get
    for elem in data:
        c[elem] = c_get(elem, 0) + 1
    return c

def c2a(data):
    c = Counter()
    c_get = c.get
    zero = 0
    for elem in data:
        c[elem] = c_get(elem, zero) + 1
    return c

def c3(data):
    c = Counter()
    for elem in data:
        if elem in c:
            c[elem] += 1
        else:
            c[elem] = 1
    return c

def c4(data, KeyError=KeyError):
    c = Counter()
    for elem in data:
        try:
            c[elem] += 1
        except KeyError:
            c[elem] = 1
    return c

def c5(data):
    c = defaultdict(repeat(0).__next__)
    for elem in data:
        c[elem] += 1
    return c


N = 10000
data_even = [randrange(N) for i in range(N)]
data_set = sample(range(N*6), N)                    # no collisions
data_sparse = [randrange(N*6) for i in range(N)]    # rare collisions
data_dense = [randrange(N//6) for i in range(N)]    # many duplicates (collisions)

setup = 'from __main__ import c1, c2, c2a, c3, c4, c5, ' \
        'data_set, data_dense, data_sparse, data_even'
for func in 'dict.fromkeys c1 c2 c2a c3 c4 c5'.split():
    for data in 'data_set data_sparse data_even data_dense'.split():
        stmt = '%s(%s)' % (func, data)
        time = min(Timer(stmt, setup).repeat(7, 30))
        print('%-25s\t%6.3f' % (stmt, time))
    print()