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test_cacheutils.py
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# -*- coding: utf-8 -*-
import string
import sys
from abc import abstractmethod, ABCMeta
import pytest
from boltons.cacheutils import LRU, LRI, cached, cachedmethod, cachedproperty, MinIDMap, ThresholdCounter
class CountingCallable(object):
def __init__(self):
self.call_count = 0
def __call__(self, *a, **kw):
self.call_count += 1
return self.call_count
def test_lru_add():
cache = LRU(max_size=3)
for i in range(4):
cache[i] = i
assert len(cache) == 3
assert 0 not in cache
def test_lri():
cache_size = 10
bc = LRI(cache_size, on_miss=lambda k: k.upper())
for idx, char in enumerate(string.ascii_letters):
x = bc[char]
assert x == char.upper()
least_recent_insert_index = idx - cache_size
if least_recent_insert_index >= 0:
# least recently inserted object evicted
assert len(bc) == cache_size
for char in string.ascii_letters[least_recent_insert_index+1:idx]:
assert char in bc
# test that reinserting an existing key changes eviction behavior
bc[string.ascii_letters[-cache_size+1]] = "new value"
least_recently_inserted_key = string.ascii_letters[-cache_size+2]
bc["unreferenced_key"] = "value"
keys_in_cache = [
string.ascii_letters[i]
for i in range(-cache_size + 1, 0)
if string.ascii_letters[i] != least_recently_inserted_key
]
keys_in_cache.append("unreferenced_key")
assert len(bc) == cache_size
for k in keys_in_cache:
assert k in bc
def test_lri_cache_eviction():
"""
Regression test
Original LRI implementation had a bug where the specified cache
size only supported `max_size` number of inserts to the cache,
rather than support `max_size` number of keys in the cache. This
would result in some unintuitive behavior, where a key is evicted
recently inserted value would be evicted from the cache if the key
inserted was inserted `max_size` keys earlier.
"""
test_cache = LRI(2)
# dequeue: (key1); dict keys: (key1)
test_cache["key1"] = "value1"
# dequeue: (key1, key1); dict keys: (key1)
test_cache["key1"] = "value1"
# dequeue: (key1, key1, key2); dict keys: (key1, key2)
test_cache["key2"] = "value2"
# dequeue: (key1, key2, key3); dict keys: (key2, key3)
test_cache["key3"] = "value3"
# will error here since we evict key1 from the cache and it doesn't
# exist in the dict anymore
test_cache["key3"] = "value3"
def test_cache_sizes_on_repeat_insertions():
"""
Regression test
Original LRI implementation had an unbounded size of memory
regardless of the value for its `max_size` parameter due to a naive
insertion algorithm onto an underlying deque data structure. To
prevent memory leaks, this test will assert that a cache does not
grow past its max size given values of a uniform memory footprint
"""
caches_to_test = (LRU, LRI)
for cache_type in caches_to_test:
test_cache = cache_type(2)
# note strings are used to force allocation of memory
test_cache["key1"] = "1"
test_cache["key2"] = "1"
initial_list_size = len(test_cache._get_flattened_ll())
for k in test_cache:
for __ in range(100):
test_cache[k] = "1"
list_size_after_inserts = len(test_cache._get_flattened_ll())
assert initial_list_size == list_size_after_inserts
def test_lru_basic():
lru = LRU(max_size=1)
repr(lru) # sanity
lru['hi'] = 0
lru['bye'] = 1
assert len(lru) == 1
lru['bye']
assert lru.get('hi') is None
del lru['bye']
assert 'bye' not in lru
assert len(lru) == 0
assert not lru
try:
lru.pop('bye')
except KeyError:
pass
else:
assert False
default = object()
assert lru.pop('bye', default) is default
try:
lru.popitem()
except KeyError:
pass
else:
assert False
lru['another'] = 1
assert lru.popitem() == ('another', 1)
lru['yet_another'] = 2
assert lru.pop('yet_another') == 2
lru['yet_another'] = 3
assert lru.pop('yet_another', default) == 3
lru['yet_another'] = 4
lru.clear()
assert not lru
lru['yet_another'] = 5
second_lru = LRU(max_size=1)
assert lru.copy() == lru
second_lru['yet_another'] = 5
assert second_lru == lru
assert lru == second_lru
lru.update(LRU(max_size=2, values=[('a', 1),
('b', 2)]))
assert len(lru) == 1
assert 'yet_another' not in lru
lru.setdefault('x', 2)
assert dict(lru) == {'x': 2}
lru.setdefault('x', 3)
assert dict(lru) == {'x': 2}
assert lru != second_lru
assert second_lru != lru
def test_lru_with_dupes():
SIZE = 2
lru = LRU(max_size=SIZE)
for i in [0, 0, 1, 1, 2, 2]:
lru[i] = i
assert _test_linkage(lru._anchor, SIZE + 1), 'linked list invalid'
def test_lru_with_dupes_2():
"From Issue #55, h/t github.com/mt"
SIZE = 3
lru = LRU(max_size=SIZE)
keys = ['A', 'A', 'B', 'A', 'C', 'B', 'D', 'E']
for i, k in enumerate(keys):
lru[k] = 'HIT'
assert _test_linkage(lru._anchor, SIZE + 1), 'linked list invalid'
return
def _test_linkage(dll, max_count=10000, prev_idx=0, next_idx=1):
"""A function to test basic invariants of doubly-linked lists (with
links made of Python lists).
1. Test that the list is not longer than a certain length
2. That the forward links (indicated by `next_idx`) correspond to
the backward links (indicated by `prev_idx`).
The `dll` parameter is the root/anchor link of the list.
"""
start = cur = dll
i = 0
prev = None
while 1:
if i > max_count:
raise Exception("did not return to anchor link after %r rounds"
% max_count)
if prev is not None and cur is start:
break
prev = cur
cur = cur[next_idx]
if cur[prev_idx] is not prev:
raise Exception('prev_idx does not point to prev at i = %r' % i)
i += 1
return True
def test_cached_dec():
lru = LRU()
inner_func = CountingCallable()
func = cached(lru)(inner_func)
assert inner_func.call_count == 0
func()
assert inner_func.call_count == 1
func()
assert inner_func.call_count == 1
func('man door hand hook car door')
assert inner_func.call_count == 2
return
def test_unscoped_cached_dec():
lru = LRU()
inner_func = CountingCallable()
func = cached(lru)(inner_func)
other_inner_func = CountingCallable()
other_func = cached(lru)(other_inner_func)
assert inner_func.call_count == 0
func('a')
assert inner_func.call_count == 1
func('a')
other_func('a')
assert other_inner_func.call_count == 0
return
def test_callable_cached_dec():
lru = LRU()
get_lru = lambda: lru
inner_func = CountingCallable()
func = cached(get_lru)(inner_func)
assert inner_func.call_count == 0
func()
assert inner_func.call_count == 1
func()
assert inner_func.call_count == 1
lru.clear()
func()
assert inner_func.call_count == 2
func()
assert inner_func.call_count == 2
print(repr(func))
return
def test_cachedmethod():
class Car(object):
def __init__(self, cache=None):
self.h_cache = LRI() if cache is None else cache
self.door_count = 0
self.hook_count = 0
self.hand_count = 0
@cachedmethod('h_cache')
def hand(self, *a, **kw):
self.hand_count += 1
@cachedmethod(lambda obj: obj.h_cache)
def hook(self, *a, **kw):
self.hook_count += 1
@cachedmethod('h_cache', scoped=False)
def door(self, *a, **kw):
self.door_count += 1
car = Car()
# attribute name-style
assert car.hand_count == 0
car.hand('h', a='nd')
assert car.hand_count == 1
car.hand('h', a='nd')
assert car.hand_count == 1
# callable-style
assert car.hook_count == 0
car.hook()
assert car.hook_count == 1
car.hook()
assert car.hook_count == 1
# Ensure that non-selfish caches share the cache nicely
lru = LRU()
car_one = Car(cache=lru)
assert car_one.door_count == 0
car_one.door('bob')
assert car_one.door_count == 1
car_one.door('bob')
assert car_one.door_count == 1
car_two = Car(cache=lru)
assert car_two.door_count == 0
car_two.door('bob')
assert car_two.door_count == 0
# try unbound for kicks
Car.door(Car(), 'bob')
# always check the repr
print(repr(car_two.door))
print(repr(Car.door))
return
def test_cachedmethod_maintains_func_abstraction():
ABC = ABCMeta('ABC', (object,), {})
class Car(ABC):
def __init__(self, cache=None):
self.h_cache = LRI() if cache is None else cache
self.hand_count = 0
@cachedmethod('h_cache')
@abstractmethod
def hand(self, *a, **kw):
self.hand_count += 1
with pytest.raises(TypeError):
Car()
def test_cachedproperty():
class Proper(object):
def __init__(self):
self.expensive_func = CountingCallable()
@cachedproperty
def useful_attr(self):
"""Useful DocString"""
return self.expensive_func()
prop = Proper()
assert prop.expensive_func.call_count == 0
assert prop.useful_attr == 1
assert prop.expensive_func.call_count == 1
assert prop.useful_attr == 1
assert prop.expensive_func.call_count == 1
# Make sure original DocString is accessible
assert Proper.useful_attr.__doc__ == "Useful DocString"
prop.useful_attr += 1 # would not be possible with normal properties
assert prop.useful_attr == 2
delattr(prop, 'useful_attr')
assert prop.expensive_func.call_count == 1
assert prop.useful_attr
assert prop.expensive_func.call_count == 2
repr(Proper.useful_attr)
def test_cachedproperty_maintains_func_abstraction():
ABC = ABCMeta('ABC', (object,), {})
class AbstractExpensiveCalculator(ABC):
@cachedproperty
@abstractmethod
def calculate(self):
pass
with pytest.raises(TypeError):
AbstractExpensiveCalculator()
def test_min_id_map():
import sys
if '__pypy__' in sys.builtin_module_names:
return # TODO: pypy still needs some work
midm = MinIDMap()
class Foo(object):
def __init__(self, val):
self.val = val
# use this circular array to have them periodically collected
ref_wheel = [None, None, None]
for i in range(1000):
nxt = Foo(i)
ref_wheel[i % len(ref_wheel)] = nxt
assert midm.get(nxt) <= len(ref_wheel)
if i % 10 == 0:
midm.drop(nxt)
# test __iter__
assert sorted([f.val for f in list(midm)[:10]]) == list(range(1000 - len(ref_wheel), 1000))
items = list(midm.iteritems())
assert isinstance(items[0][0], Foo)
assert sorted(item[1] for item in items) == list(range(0, len(ref_wheel)))
def test_threshold_counter():
tc = ThresholdCounter(threshold=0.1)
tc.add(1)
assert tc.items() == [(1, 1)]
tc.update([2] * 10)
assert tc.get(1) == 0
tc.add(5)
assert 5 in tc
assert len(list(tc.elements())) == 11
assert tc.threshold == 0.1
assert tc.get_common_count() == 11
assert tc.get_uncommon_count() == 1 # bc the initial 1 was dropped
assert round(tc.get_commonality(), 2) == 0.92
assert tc.most_common(2) == [(2, 10), (5, 1)]
assert list(tc.elements()) == ([2] * 10) + [5]
assert tc[2] == 10
assert len(tc) == 2
assert sorted(tc.keys()) == [2, 5]
assert sorted(tc.values()) == [1, 10]
assert sorted(tc.items()) == [(2, 10), (5, 1)]