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Update webservice with cherrypy

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Fix playback issues that was causing Kodi to hang up
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angelblue05 2019-01-30 06:43:14 -06:00
parent b2bc90cb06
commit 158a736360
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from more_itertools.more import * # noqa
from more_itertools.recipes import * # noqa

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"""Imported from the recipes section of the itertools documentation.
All functions taken from the recipes section of the itertools library docs
[1]_.
Some backward-compatible usability improvements have been made.
.. [1] http://docs.python.org/library/itertools.html#recipes
"""
from collections import deque
from itertools import (
chain, combinations, count, cycle, groupby, islice, repeat, starmap, tee
)
import operator
from random import randrange, sample, choice
from six import PY2
from six.moves import filter, filterfalse, map, range, zip, zip_longest
__all__ = [
'accumulate',
'all_equal',
'consume',
'dotproduct',
'first_true',
'flatten',
'grouper',
'iter_except',
'ncycles',
'nth',
'nth_combination',
'padnone',
'pairwise',
'partition',
'powerset',
'prepend',
'quantify',
'random_combination_with_replacement',
'random_combination',
'random_permutation',
'random_product',
'repeatfunc',
'roundrobin',
'tabulate',
'tail',
'take',
'unique_everseen',
'unique_justseen',
]
def accumulate(iterable, func=operator.add):
"""
Return an iterator whose items are the accumulated results of a function
(specified by the optional *func* argument) that takes two arguments.
By default, returns accumulated sums with :func:`operator.add`.
>>> list(accumulate([1, 2, 3, 4, 5])) # Running sum
[1, 3, 6, 10, 15]
>>> list(accumulate([1, 2, 3], func=operator.mul)) # Running product
[1, 2, 6]
>>> list(accumulate([0, 1, -1, 2, 3, 2], func=max)) # Running maximum
[0, 1, 1, 2, 3, 3]
This function is available in the ``itertools`` module for Python 3.2 and
greater.
"""
it = iter(iterable)
try:
total = next(it)
except StopIteration:
return
else:
yield total
for element in it:
total = func(total, element)
yield total
def take(n, iterable):
"""Return first *n* items of the iterable as a list.
>>> take(3, range(10))
[0, 1, 2]
>>> take(5, range(3))
[0, 1, 2]
Effectively a short replacement for ``next`` based iterator consumption
when you want more than one item, but less than the whole iterator.
"""
return list(islice(iterable, n))
def tabulate(function, start=0):
"""Return an iterator over the results of ``func(start)``,
``func(start + 1)``, ``func(start + 2)``...
*func* should be a function that accepts one integer argument.
If *start* is not specified it defaults to 0. It will be incremented each
time the iterator is advanced.
>>> square = lambda x: x ** 2
>>> iterator = tabulate(square, -3)
>>> take(4, iterator)
[9, 4, 1, 0]
"""
return map(function, count(start))
def tail(n, iterable):
"""Return an iterator over the last *n* items of *iterable*.
>>> t = tail(3, 'ABCDEFG')
>>> list(t)
['E', 'F', 'G']
"""
return iter(deque(iterable, maxlen=n))
def consume(iterator, n=None):
"""Advance *iterable* by *n* steps. If *n* is ``None``, consume it
entirely.
Efficiently exhausts an iterator without returning values. Defaults to
consuming the whole iterator, but an optional second argument may be
provided to limit consumption.
>>> i = (x for x in range(10))
>>> next(i)
0
>>> consume(i, 3)
>>> next(i)
4
>>> consume(i)
>>> next(i)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
StopIteration
If the iterator has fewer items remaining than the provided limit, the
whole iterator will be consumed.
>>> i = (x for x in range(3))
>>> consume(i, 5)
>>> next(i)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
StopIteration
"""
# Use functions that consume iterators at C speed.
if n is None:
# feed the entire iterator into a zero-length deque
deque(iterator, maxlen=0)
else:
# advance to the empty slice starting at position n
next(islice(iterator, n, n), None)
def nth(iterable, n, default=None):
"""Returns the nth item or a default value.
>>> l = range(10)
>>> nth(l, 3)
3
>>> nth(l, 20, "zebra")
'zebra'
"""
return next(islice(iterable, n, None), default)
def all_equal(iterable):
"""
Returns ``True`` if all the elements are equal to each other.
>>> all_equal('aaaa')
True
>>> all_equal('aaab')
False
"""
g = groupby(iterable)
return next(g, True) and not next(g, False)
def quantify(iterable, pred=bool):
"""Return the how many times the predicate is true.
>>> quantify([True, False, True])
2
"""
return sum(map(pred, iterable))
def padnone(iterable):
"""Returns the sequence of elements and then returns ``None`` indefinitely.
>>> take(5, padnone(range(3)))
[0, 1, 2, None, None]
Useful for emulating the behavior of the built-in :func:`map` function.
See also :func:`padded`.
"""
return chain(iterable, repeat(None))
def ncycles(iterable, n):
"""Returns the sequence elements *n* times
>>> list(ncycles(["a", "b"], 3))
['a', 'b', 'a', 'b', 'a', 'b']
"""
return chain.from_iterable(repeat(tuple(iterable), n))
def dotproduct(vec1, vec2):
"""Returns the dot product of the two iterables.
>>> dotproduct([10, 10], [20, 20])
400
"""
return sum(map(operator.mul, vec1, vec2))
def flatten(listOfLists):
"""Return an iterator flattening one level of nesting in a list of lists.
>>> list(flatten([[0, 1], [2, 3]]))
[0, 1, 2, 3]
See also :func:`collapse`, which can flatten multiple levels of nesting.
"""
return chain.from_iterable(listOfLists)
def repeatfunc(func, times=None, *args):
"""Call *func* with *args* repeatedly, returning an iterable over the
results.
If *times* is specified, the iterable will terminate after that many
repetitions:
>>> from operator import add
>>> times = 4
>>> args = 3, 5
>>> list(repeatfunc(add, times, *args))
[8, 8, 8, 8]
If *times* is ``None`` the iterable will not terminate:
>>> from random import randrange
>>> times = None
>>> args = 1, 11
>>> take(6, repeatfunc(randrange, times, *args)) # doctest:+SKIP
[2, 4, 8, 1, 8, 4]
"""
if times is None:
return starmap(func, repeat(args))
return starmap(func, repeat(args, times))
def pairwise(iterable):
"""Returns an iterator of paired items, overlapping, from the original
>>> take(4, pairwise(count()))
[(0, 1), (1, 2), (2, 3), (3, 4)]
"""
a, b = tee(iterable)
next(b, None)
return zip(a, b)
def grouper(n, iterable, fillvalue=None):
"""Collect data into fixed-length chunks or blocks.
>>> list(grouper(3, 'ABCDEFG', 'x'))
[('A', 'B', 'C'), ('D', 'E', 'F'), ('G', 'x', 'x')]
"""
args = [iter(iterable)] * n
return zip_longest(fillvalue=fillvalue, *args)
def roundrobin(*iterables):
"""Yields an item from each iterable, alternating between them.
>>> list(roundrobin('ABC', 'D', 'EF'))
['A', 'D', 'E', 'B', 'F', 'C']
This function produces the same output as :func:`interleave_longest`, but
may perform better for some inputs (in particular when the number of
iterables is small).
"""
# Recipe credited to George Sakkis
pending = len(iterables)
if PY2:
nexts = cycle(iter(it).next for it in iterables)
else:
nexts = cycle(iter(it).__next__ for it in iterables)
while pending:
try:
for next in nexts:
yield next()
except StopIteration:
pending -= 1
nexts = cycle(islice(nexts, pending))
def partition(pred, iterable):
"""
Returns a 2-tuple of iterables derived from the input iterable.
The first yields the items that have ``pred(item) == False``.
The second yields the items that have ``pred(item) == True``.
>>> is_odd = lambda x: x % 2 != 0
>>> iterable = range(10)
>>> even_items, odd_items = partition(is_odd, iterable)
>>> list(even_items), list(odd_items)
([0, 2, 4, 6, 8], [1, 3, 5, 7, 9])
"""
# partition(is_odd, range(10)) --> 0 2 4 6 8 and 1 3 5 7 9
t1, t2 = tee(iterable)
return filterfalse(pred, t1), filter(pred, t2)
def powerset(iterable):
"""Yields all possible subsets of the iterable.
>>> list(powerset([1,2,3]))
[(), (1,), (2,), (3,), (1, 2), (1, 3), (2, 3), (1, 2, 3)]
"""
s = list(iterable)
return chain.from_iterable(combinations(s, r) for r in range(len(s) + 1))
def unique_everseen(iterable, key=None):
"""
Yield unique elements, preserving order.
>>> list(unique_everseen('AAAABBBCCDAABBB'))
['A', 'B', 'C', 'D']
>>> list(unique_everseen('ABBCcAD', str.lower))
['A', 'B', 'C', 'D']
Sequences with a mix of hashable and unhashable items can be used.
The function will be slower (i.e., `O(n^2)`) for unhashable items.
"""
seenset = set()
seenset_add = seenset.add
seenlist = []
seenlist_add = seenlist.append
if key is None:
for element in iterable:
try:
if element not in seenset:
seenset_add(element)
yield element
except TypeError:
if element not in seenlist:
seenlist_add(element)
yield element
else:
for element in iterable:
k = key(element)
try:
if k not in seenset:
seenset_add(k)
yield element
except TypeError:
if k not in seenlist:
seenlist_add(k)
yield element
def unique_justseen(iterable, key=None):
"""Yields elements in order, ignoring serial duplicates
>>> list(unique_justseen('AAAABBBCCDAABBB'))
['A', 'B', 'C', 'D', 'A', 'B']
>>> list(unique_justseen('ABBCcAD', str.lower))
['A', 'B', 'C', 'A', 'D']
"""
return map(next, map(operator.itemgetter(1), groupby(iterable, key)))
def iter_except(func, exception, first=None):
"""Yields results from a function repeatedly until an exception is raised.
Converts a call-until-exception interface to an iterator interface.
Like ``iter(func, sentinel)``, but uses an exception instead of a sentinel
to end the loop.
>>> l = [0, 1, 2]
>>> list(iter_except(l.pop, IndexError))
[2, 1, 0]
"""
try:
if first is not None:
yield first()
while 1:
yield func()
except exception:
pass
def first_true(iterable, default=False, pred=None):
"""
Returns the first true value in the iterable.
If no true value is found, returns *default*
If *pred* is not None, returns the first item for which
``pred(item) == True`` .
>>> first_true(range(10))
1
>>> first_true(range(10), pred=lambda x: x > 5)
6
>>> first_true(range(10), default='missing', pred=lambda x: x > 9)
'missing'
"""
return next(filter(pred, iterable), default)
def random_product(*args, **kwds):
"""Draw an item at random from each of the input iterables.
>>> random_product('abc', range(4), 'XYZ') # doctest:+SKIP
('c', 3, 'Z')
If *repeat* is provided as a keyword argument, that many items will be
drawn from each iterable.
>>> random_product('abcd', range(4), repeat=2) # doctest:+SKIP
('a', 2, 'd', 3)
This equivalent to taking a random selection from
``itertools.product(*args, **kwarg)``.
"""
pools = [tuple(pool) for pool in args] * kwds.get('repeat', 1)
return tuple(choice(pool) for pool in pools)
def random_permutation(iterable, r=None):
"""Return a random *r* length permutation of the elements in *iterable*.
If *r* is not specified or is ``None``, then *r* defaults to the length of
*iterable*.
>>> random_permutation(range(5)) # doctest:+SKIP
(3, 4, 0, 1, 2)
This equivalent to taking a random selection from
``itertools.permutations(iterable, r)``.
"""
pool = tuple(iterable)
r = len(pool) if r is None else r
return tuple(sample(pool, r))
def random_combination(iterable, r):
"""Return a random *r* length subsequence of the elements in *iterable*.
>>> random_combination(range(5), 3) # doctest:+SKIP
(2, 3, 4)
This equivalent to taking a random selection from
``itertools.combinations(iterable, r)``.
"""
pool = tuple(iterable)
n = len(pool)
indices = sorted(sample(range(n), r))
return tuple(pool[i] for i in indices)
def random_combination_with_replacement(iterable, r):
"""Return a random *r* length subsequence of elements in *iterable*,
allowing individual elements to be repeated.
>>> random_combination_with_replacement(range(3), 5) # doctest:+SKIP
(0, 0, 1, 2, 2)
This equivalent to taking a random selection from
``itertools.combinations_with_replacement(iterable, r)``.
"""
pool = tuple(iterable)
n = len(pool)
indices = sorted(randrange(n) for i in range(r))
return tuple(pool[i] for i in indices)
def nth_combination(iterable, r, index):
"""Equivalent to ``list(combinations(iterable, r))[index]``.
The subsequences of *iterable* that are of length *r* can be ordered
lexicographically. :func:`nth_combination` computes the subsequence at
sort position *index* directly, without computing the previous
subsequences.
"""
pool = tuple(iterable)
n = len(pool)
if (r < 0) or (r > n):
raise ValueError
c = 1
k = min(r, n - r)
for i in range(1, k + 1):
c = c * (n - k + i) // i
if index < 0:
index += c
if (index < 0) or (index >= c):
raise IndexError
result = []
while r:
c, n, r = c * r // n, n - 1, r - 1
while index >= c:
index -= c
c, n = c * (n - r) // n, n - 1
result.append(pool[-1 - n])
return tuple(result)
def prepend(value, iterator):
"""Yield *value*, followed by the elements in *iterator*.
>>> value = '0'
>>> iterator = ['1', '2', '3']
>>> list(prepend(value, iterator))
['0', '1', '2', '3']
To prepend multiple values, see :func:`itertools.chain`.
"""
return chain([value], iterator)

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from doctest import DocTestSuite
from unittest import TestCase
from itertools import combinations
from six.moves import range
import more_itertools as mi
def load_tests(loader, tests, ignore):
# Add the doctests
tests.addTests(DocTestSuite('more_itertools.recipes'))
return tests
class AccumulateTests(TestCase):
"""Tests for ``accumulate()``"""
def test_empty(self):
"""Test that an empty input returns an empty output"""
self.assertEqual(list(mi.accumulate([])), [])
def test_default(self):
"""Test accumulate with the default function (addition)"""
self.assertEqual(list(mi.accumulate([1, 2, 3])), [1, 3, 6])
def test_bogus_function(self):
"""Test accumulate with an invalid function"""
with self.assertRaises(TypeError):
list(mi.accumulate([1, 2, 3], func=lambda x: x))
def test_custom_function(self):
"""Test accumulate with a custom function"""
self.assertEqual(
list(mi.accumulate((1, 2, 3, 2, 1), func=max)), [1, 2, 3, 3, 3]
)
class TakeTests(TestCase):
"""Tests for ``take()``"""
def test_simple_take(self):
"""Test basic usage"""
t = mi.take(5, range(10))
self.assertEqual(t, [0, 1, 2, 3, 4])
def test_null_take(self):
"""Check the null case"""
t = mi.take(0, range(10))
self.assertEqual(t, [])
def test_negative_take(self):
"""Make sure taking negative items results in a ValueError"""
self.assertRaises(ValueError, lambda: mi.take(-3, range(10)))
def test_take_too_much(self):
"""Taking more than an iterator has remaining should return what the
iterator has remaining.
"""
t = mi.take(10, range(5))
self.assertEqual(t, [0, 1, 2, 3, 4])
class TabulateTests(TestCase):
"""Tests for ``tabulate()``"""
def test_simple_tabulate(self):
"""Test the happy path"""
t = mi.tabulate(lambda x: x)
f = tuple([next(t) for _ in range(3)])
self.assertEqual(f, (0, 1, 2))
def test_count(self):
"""Ensure tabulate accepts specific count"""
t = mi.tabulate(lambda x: 2 * x, -1)
f = (next(t), next(t), next(t))
self.assertEqual(f, (-2, 0, 2))
class TailTests(TestCase):
"""Tests for ``tail()``"""
def test_greater(self):
"""Length of iterable is greather than requested tail"""
self.assertEqual(list(mi.tail(3, 'ABCDEFG')), ['E', 'F', 'G'])
def test_equal(self):
"""Length of iterable is equal to the requested tail"""
self.assertEqual(
list(mi.tail(7, 'ABCDEFG')), ['A', 'B', 'C', 'D', 'E', 'F', 'G']
)
def test_less(self):
"""Length of iterable is less than requested tail"""
self.assertEqual(
list(mi.tail(8, 'ABCDEFG')), ['A', 'B', 'C', 'D', 'E', 'F', 'G']
)
class ConsumeTests(TestCase):
"""Tests for ``consume()``"""
def test_sanity(self):
"""Test basic functionality"""
r = (x for x in range(10))
mi.consume(r, 3)
self.assertEqual(3, next(r))
def test_null_consume(self):
"""Check the null case"""
r = (x for x in range(10))
mi.consume(r, 0)
self.assertEqual(0, next(r))
def test_negative_consume(self):
"""Check that negative consumsion throws an error"""
r = (x for x in range(10))
self.assertRaises(ValueError, lambda: mi.consume(r, -1))
def test_total_consume(self):
"""Check that iterator is totally consumed by default"""
r = (x for x in range(10))
mi.consume(r)
self.assertRaises(StopIteration, lambda: next(r))
class NthTests(TestCase):
"""Tests for ``nth()``"""
def test_basic(self):
"""Make sure the nth item is returned"""
l = range(10)
for i, v in enumerate(l):
self.assertEqual(mi.nth(l, i), v)
def test_default(self):
"""Ensure a default value is returned when nth item not found"""
l = range(3)
self.assertEqual(mi.nth(l, 100, "zebra"), "zebra")
def test_negative_item_raises(self):
"""Ensure asking for a negative item raises an exception"""
self.assertRaises(ValueError, lambda: mi.nth(range(10), -3))
class AllEqualTests(TestCase):
"""Tests for ``all_equal()``"""
def test_true(self):
"""Everything is equal"""
self.assertTrue(mi.all_equal('aaaaaa'))
self.assertTrue(mi.all_equal([0, 0, 0, 0]))
def test_false(self):
"""Not everything is equal"""
self.assertFalse(mi.all_equal('aaaaab'))
self.assertFalse(mi.all_equal([0, 0, 0, 1]))
def test_tricky(self):
"""Not everything is identical, but everything is equal"""
items = [1, complex(1, 0), 1.0]
self.assertTrue(mi.all_equal(items))
def test_empty(self):
"""Return True if the iterable is empty"""
self.assertTrue(mi.all_equal(''))
self.assertTrue(mi.all_equal([]))
def test_one(self):
"""Return True if the iterable is singular"""
self.assertTrue(mi.all_equal('0'))
self.assertTrue(mi.all_equal([0]))
class QuantifyTests(TestCase):
"""Tests for ``quantify()``"""
def test_happy_path(self):
"""Make sure True count is returned"""
q = [True, False, True]
self.assertEqual(mi.quantify(q), 2)
def test_custom_predicate(self):
"""Ensure non-default predicates return as expected"""
q = range(10)
self.assertEqual(mi.quantify(q, lambda x: x % 2 == 0), 5)
class PadnoneTests(TestCase):
"""Tests for ``padnone()``"""
def test_happy_path(self):
"""wrapper iterator should return None indefinitely"""
r = range(2)
p = mi.padnone(r)
self.assertEqual([0, 1, None, None], [next(p) for _ in range(4)])
class NcyclesTests(TestCase):
"""Tests for ``nyclces()``"""
def test_happy_path(self):
"""cycle a sequence three times"""
r = ["a", "b", "c"]
n = mi.ncycles(r, 3)
self.assertEqual(
["a", "b", "c", "a", "b", "c", "a", "b", "c"],
list(n)
)
def test_null_case(self):
"""asking for 0 cycles should return an empty iterator"""
n = mi.ncycles(range(100), 0)
self.assertRaises(StopIteration, lambda: next(n))
def test_pathalogical_case(self):
"""asking for negative cycles should return an empty iterator"""
n = mi.ncycles(range(100), -10)
self.assertRaises(StopIteration, lambda: next(n))
class DotproductTests(TestCase):
"""Tests for ``dotproduct()``'"""
def test_happy_path(self):
"""simple dotproduct example"""
self.assertEqual(400, mi.dotproduct([10, 10], [20, 20]))
class FlattenTests(TestCase):
"""Tests for ``flatten()``"""
def test_basic_usage(self):
"""ensure list of lists is flattened one level"""
f = [[0, 1, 2], [3, 4, 5]]
self.assertEqual(list(range(6)), list(mi.flatten(f)))
def test_single_level(self):
"""ensure list of lists is flattened only one level"""
f = [[0, [1, 2]], [[3, 4], 5]]
self.assertEqual([0, [1, 2], [3, 4], 5], list(mi.flatten(f)))
class RepeatfuncTests(TestCase):
"""Tests for ``repeatfunc()``"""
def test_simple_repeat(self):
"""test simple repeated functions"""
r = mi.repeatfunc(lambda: 5)
self.assertEqual([5, 5, 5, 5, 5], [next(r) for _ in range(5)])
def test_finite_repeat(self):
"""ensure limited repeat when times is provided"""
r = mi.repeatfunc(lambda: 5, times=5)
self.assertEqual([5, 5, 5, 5, 5], list(r))
def test_added_arguments(self):
"""ensure arguments are applied to the function"""
r = mi.repeatfunc(lambda x: x, 2, 3)
self.assertEqual([3, 3], list(r))
def test_null_times(self):
"""repeat 0 should return an empty iterator"""
r = mi.repeatfunc(range, 0, 3)
self.assertRaises(StopIteration, lambda: next(r))
class PairwiseTests(TestCase):
"""Tests for ``pairwise()``"""
def test_base_case(self):
"""ensure an iterable will return pairwise"""
p = mi.pairwise([1, 2, 3])
self.assertEqual([(1, 2), (2, 3)], list(p))
def test_short_case(self):
"""ensure an empty iterator if there's not enough values to pair"""
p = mi.pairwise("a")
self.assertRaises(StopIteration, lambda: next(p))
class GrouperTests(TestCase):
"""Tests for ``grouper()``"""
def test_even(self):
"""Test when group size divides evenly into the length of
the iterable.
"""
self.assertEqual(
list(mi.grouper(3, 'ABCDEF')), [('A', 'B', 'C'), ('D', 'E', 'F')]
)
def test_odd(self):
"""Test when group size does not divide evenly into the length of the
iterable.
"""
self.assertEqual(
list(mi.grouper(3, 'ABCDE')), [('A', 'B', 'C'), ('D', 'E', None)]
)
def test_fill_value(self):
"""Test that the fill value is used to pad the final group"""
self.assertEqual(
list(mi.grouper(3, 'ABCDE', 'x')),
[('A', 'B', 'C'), ('D', 'E', 'x')]
)
class RoundrobinTests(TestCase):
"""Tests for ``roundrobin()``"""
def test_even_groups(self):
"""Ensure ordered output from evenly populated iterables"""
self.assertEqual(
list(mi.roundrobin('ABC', [1, 2, 3], range(3))),
['A', 1, 0, 'B', 2, 1, 'C', 3, 2]
)
def test_uneven_groups(self):
"""Ensure ordered output from unevenly populated iterables"""
self.assertEqual(
list(mi.roundrobin('ABCD', [1, 2], range(0))),
['A', 1, 'B', 2, 'C', 'D']
)
class PartitionTests(TestCase):
"""Tests for ``partition()``"""
def test_bool(self):
"""Test when pred() returns a boolean"""
lesser, greater = mi.partition(lambda x: x > 5, range(10))
self.assertEqual(list(lesser), [0, 1, 2, 3, 4, 5])
self.assertEqual(list(greater), [6, 7, 8, 9])
def test_arbitrary(self):
"""Test when pred() returns an integer"""
divisibles, remainders = mi.partition(lambda x: x % 3, range(10))
self.assertEqual(list(divisibles), [0, 3, 6, 9])
self.assertEqual(list(remainders), [1, 2, 4, 5, 7, 8])
class PowersetTests(TestCase):
"""Tests for ``powerset()``"""
def test_combinatorics(self):
"""Ensure a proper enumeration"""
p = mi.powerset([1, 2, 3])
self.assertEqual(
list(p),
[(), (1,), (2,), (3,), (1, 2), (1, 3), (2, 3), (1, 2, 3)]
)
class UniqueEverseenTests(TestCase):
"""Tests for ``unique_everseen()``"""
def test_everseen(self):
"""ensure duplicate elements are ignored"""
u = mi.unique_everseen('AAAABBBBCCDAABBB')
self.assertEqual(
['A', 'B', 'C', 'D'],
list(u)
)
def test_custom_key(self):
"""ensure the custom key comparison works"""
u = mi.unique_everseen('aAbACCc', key=str.lower)
self.assertEqual(list('abC'), list(u))
def test_unhashable(self):
"""ensure things work for unhashable items"""
iterable = ['a', [1, 2, 3], [1, 2, 3], 'a']
u = mi.unique_everseen(iterable)
self.assertEqual(list(u), ['a', [1, 2, 3]])
def test_unhashable_key(self):
"""ensure things work for unhashable items with a custom key"""
iterable = ['a', [1, 2, 3], [1, 2, 3], 'a']
u = mi.unique_everseen(iterable, key=lambda x: x)
self.assertEqual(list(u), ['a', [1, 2, 3]])
class UniqueJustseenTests(TestCase):
"""Tests for ``unique_justseen()``"""
def test_justseen(self):
"""ensure only last item is remembered"""
u = mi.unique_justseen('AAAABBBCCDABB')
self.assertEqual(list('ABCDAB'), list(u))
def test_custom_key(self):
"""ensure the custom key comparison works"""
u = mi.unique_justseen('AABCcAD', str.lower)
self.assertEqual(list('ABCAD'), list(u))
class IterExceptTests(TestCase):
"""Tests for ``iter_except()``"""
def test_exact_exception(self):
"""ensure the exact specified exception is caught"""
l = [1, 2, 3]
i = mi.iter_except(l.pop, IndexError)
self.assertEqual(list(i), [3, 2, 1])
def test_generic_exception(self):
"""ensure the generic exception can be caught"""
l = [1, 2]
i = mi.iter_except(l.pop, Exception)
self.assertEqual(list(i), [2, 1])
def test_uncaught_exception_is_raised(self):
"""ensure a non-specified exception is raised"""
l = [1, 2, 3]
i = mi.iter_except(l.pop, KeyError)
self.assertRaises(IndexError, lambda: list(i))
def test_first(self):
"""ensure first is run before the function"""
l = [1, 2, 3]
f = lambda: 25
i = mi.iter_except(l.pop, IndexError, f)
self.assertEqual(list(i), [25, 3, 2, 1])
class FirstTrueTests(TestCase):
"""Tests for ``first_true()``"""
def test_something_true(self):
"""Test with no keywords"""
self.assertEqual(mi.first_true(range(10)), 1)
def test_nothing_true(self):
"""Test default return value."""
self.assertEqual(mi.first_true([0, 0, 0]), False)
def test_default(self):
"""Test with a default keyword"""
self.assertEqual(mi.first_true([0, 0, 0], default='!'), '!')
def test_pred(self):
"""Test with a custom predicate"""
self.assertEqual(
mi.first_true([2, 4, 6], pred=lambda x: x % 3 == 0), 6
)
class RandomProductTests(TestCase):
"""Tests for ``random_product()``
Since random.choice() has different results with the same seed across
python versions 2.x and 3.x, these tests use highly probably events to
create predictable outcomes across platforms.
"""
def test_simple_lists(self):
"""Ensure that one item is chosen from each list in each pair.
Also ensure that each item from each list eventually appears in
the chosen combinations.
Odds are roughly 1 in 7.1 * 10e16 that one item from either list will
not be chosen after 100 samplings of one item from each list. Just to
be safe, better use a known random seed, too.
"""
nums = [1, 2, 3]
lets = ['a', 'b', 'c']
n, m = zip(*[mi.random_product(nums, lets) for _ in range(100)])
n, m = set(n), set(m)
self.assertEqual(n, set(nums))
self.assertEqual(m, set(lets))
self.assertEqual(len(n), len(nums))
self.assertEqual(len(m), len(lets))
def test_list_with_repeat(self):
"""ensure multiple items are chosen, and that they appear to be chosen
from one list then the next, in proper order.
"""
nums = [1, 2, 3]
lets = ['a', 'b', 'c']
r = list(mi.random_product(nums, lets, repeat=100))
self.assertEqual(2 * 100, len(r))
n, m = set(r[::2]), set(r[1::2])
self.assertEqual(n, set(nums))
self.assertEqual(m, set(lets))
self.assertEqual(len(n), len(nums))
self.assertEqual(len(m), len(lets))
class RandomPermutationTests(TestCase):
"""Tests for ``random_permutation()``"""
def test_full_permutation(self):
"""ensure every item from the iterable is returned in a new ordering
15 elements have a 1 in 1.3 * 10e12 of appearing in sorted order, so
we fix a seed value just to be sure.
"""
i = range(15)
r = mi.random_permutation(i)
self.assertEqual(set(i), set(r))
if i == r:
raise AssertionError("Values were not permuted")
def test_partial_permutation(self):
"""ensure all returned items are from the iterable, that the returned
permutation is of the desired length, and that all items eventually
get returned.
Sampling 100 permutations of length 5 from a set of 15 leaves a
(2/3)^100 chance that an item will not be chosen. Multiplied by 15
items, there is a 1 in 2.6e16 chance that at least 1 item will not
show up in the resulting output. Using a random seed will fix that.
"""
items = range(15)
item_set = set(items)
all_items = set()
for _ in range(100):
permutation = mi.random_permutation(items, 5)
self.assertEqual(len(permutation), 5)
permutation_set = set(permutation)
self.assertLessEqual(permutation_set, item_set)
all_items |= permutation_set
self.assertEqual(all_items, item_set)
class RandomCombinationTests(TestCase):
"""Tests for ``random_combination()``"""
def test_psuedorandomness(self):
"""ensure different subsets of the iterable get returned over many
samplings of random combinations"""
items = range(15)
all_items = set()
for _ in range(50):
combination = mi.random_combination(items, 5)
all_items |= set(combination)
self.assertEqual(all_items, set(items))
def test_no_replacement(self):
"""ensure that elements are sampled without replacement"""
items = range(15)
for _ in range(50):
combination = mi.random_combination(items, len(items))
self.assertEqual(len(combination), len(set(combination)))
self.assertRaises(
ValueError, lambda: mi.random_combination(items, len(items) + 1)
)
class RandomCombinationWithReplacementTests(TestCase):
"""Tests for ``random_combination_with_replacement()``"""
def test_replacement(self):
"""ensure that elements are sampled with replacement"""
items = range(5)
combo = mi.random_combination_with_replacement(items, len(items) * 2)
self.assertEqual(2 * len(items), len(combo))
if len(set(combo)) == len(combo):
raise AssertionError("Combination contained no duplicates")
def test_pseudorandomness(self):
"""ensure different subsets of the iterable get returned over many
samplings of random combinations"""
items = range(15)
all_items = set()
for _ in range(50):
combination = mi.random_combination_with_replacement(items, 5)
all_items |= set(combination)
self.assertEqual(all_items, set(items))
class NthCombinationTests(TestCase):
def test_basic(self):
iterable = 'abcdefg'
r = 4
for index, expected in enumerate(combinations(iterable, r)):
actual = mi.nth_combination(iterable, r, index)
self.assertEqual(actual, expected)
def test_long(self):
actual = mi.nth_combination(range(180), 4, 2000000)
expected = (2, 12, 35, 126)
self.assertEqual(actual, expected)
def test_invalid_r(self):
for r in (-1, 3):
with self.assertRaises(ValueError):
mi.nth_combination([], r, 0)
def test_invalid_index(self):
with self.assertRaises(IndexError):
mi.nth_combination('abcdefg', 3, -36)
class PrependTests(TestCase):
def test_basic(self):
value = 'a'
iterator = iter('bcdefg')
actual = list(mi.prepend(value, iterator))
expected = list('abcdefg')
self.assertEqual(actual, expected)
def test_multiple(self):
value = 'ab'
iterator = iter('cdefg')
actual = tuple(mi.prepend(value, iterator))
expected = ('ab',) + tuple('cdefg')
self.assertEqual(actual, expected)