mirror of
https://github.com/wassname/cachier.git
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working on memory core locking + tests
Memory core is now thread safe extend memory core tests added checkdocs
This commit is contained in:
+48
-11
@@ -7,27 +7,29 @@ from datetime import timedelta
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from random import random
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from time import sleep, time
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import pytest
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import pandas as pd
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from cachier import cachier
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@cachier(backend='memory', next_time=False)
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def _takes_5_seconds(arg_1, arg_2):
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def _takes_2_seconds(arg_1, arg_2):
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"""Some function."""
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sleep(5)
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sleep(2)
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return 'arg_1:{}, arg_2:{}'.format(arg_1, arg_2)
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@pytest.mark.memory
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def test_memory_core():
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"""Basic memory core functionality."""
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_takes_5_seconds.clear_cache()
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_takes_5_seconds('a', 'b')
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_takes_2_seconds.clear_cache()
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_takes_2_seconds('a', 'b')
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start = time()
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_takes_5_seconds('a', 'b', verbose_cache=True)
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_takes_2_seconds('a', 'b', verbose_cache=True)
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end = time()
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assert end - start < 1
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_takes_5_seconds.clear_cache()
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_takes_2_seconds.clear_cache()
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SECONDS_IN_DELTA = 3
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@@ -40,6 +42,7 @@ def _stale_after_seconds(arg_1, arg_2):
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return random()
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@pytest.mark.memory
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def test_stale_after():
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"""Testing the stale_after functionality."""
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_stale_after_seconds.clear_cache()
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@@ -60,6 +63,7 @@ def _stale_after_next_time(arg_1, arg_2):
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return random()
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@pytest.mark.memory
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def test_stale_after_next_time():
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"""Testing the stale_after with next_time functionality."""
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_stale_after_next_time.clear_cache()
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@@ -88,6 +92,7 @@ def _random_num_with_arg(a):
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return random()
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@pytest.mark.memory
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def test_overwrite_cache():
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"""Tests that the overwrite feature works correctly."""
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_random_num.clear_cache()
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@@ -111,6 +116,7 @@ def test_overwrite_cache():
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_random_num_with_arg.clear_cache()
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@pytest.mark.memory
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def test_ignore_cache():
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"""Tests that the ignore_cache feature works correctly."""
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_random_num.clear_cache()
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@@ -148,12 +154,15 @@ def _calls_takes_time(res_queue):
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res_queue.put(res)
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@pytest.mark.memory
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def test_memory_being_calculated():
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"""Testing memory core handling of being calculated scenarios."""
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_takes_time.clear_cache()
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res_queue = queue.Queue()
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thread1 = threading.Thread(target=_calls_takes_time, kwargs={'res_queue': res_queue})
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thread2 = threading.Thread(target=_calls_takes_time, kwargs={'res_queue': res_queue})
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thread1 = threading.Thread(
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target=_calls_takes_time, kwargs={'res_queue': res_queue})
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thread2 = threading.Thread(
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target=_calls_takes_time, kwargs={'res_queue': res_queue})
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thread1.start()
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sleep(0.5)
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thread2.start()
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@@ -177,6 +186,7 @@ def _calls_being_calc_next_time(res_queue):
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res_queue.put(res)
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@pytest.mark.memory
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def test_being_calc_next_time():
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"""Testing memory core handling of being calculated scenarios."""
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_takes_time.clear_cache()
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@@ -212,8 +222,31 @@ def _delete_cache(arg_1, arg_2):
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return random() + arg_1 + arg_2
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@pytest.mark.memory
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def test_clear_being_calculated():
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"""Test memory core clear `being calculated` functionality."""
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_takes_time.clear_cache()
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res_queue = queue.Queue()
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thread1 = threading.Thread(
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target=_calls_takes_time, kwargs={'res_queue': res_queue})
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thread2 = threading.Thread(
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target=_calls_takes_time, kwargs={'res_queue': res_queue})
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thread1.start()
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_takes_time.clear_being_calculated()
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sleep(0.5)
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thread2.start()
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thread1.join()
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thread2.join()
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assert res_queue.qsize() == 2
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res1 = res_queue.get()
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res2 = res_queue.get()
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assert res1 != res2
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@pytest.mark.memory
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def test_clear_being_calculated_with_empty_cache():
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"""Test memory core clear `being calculated` functionality."""
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_takes_time.clear_cache()
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_takes_time.clear_being_calculated()
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@@ -227,6 +260,7 @@ def _error_throwing_func(arg1):
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return 7
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@pytest.mark.memory
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def test_error_throwing_func():
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# with
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res1 = _error_throwing_func(4)
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@@ -235,15 +269,18 @@ def test_error_throwing_func():
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assert res1 == res2
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@pytest.mark.memory
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def test_callable_hash_param():
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def _hash_params(args, kwargs):
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def _hash(obj):
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if isinstance(obj, pd.core.frame.DataFrame):
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return hashlib.sha256(pd.util.hash_pandas_object(obj).values.tobytes()).hexdigest()
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return hashlib.sha256(
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pd.util.hash_pandas_object(obj).values.tobytes()
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).hexdigest()
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return obj
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k_args = tuple(map(_hash, args))
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k_kwargs = tuple(sorted({k: _hash(v) for k, v in kwargs.items()}.items()))
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k_kwargs = tuple(sorted(
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{k: _hash(v) for k, v in kwargs.items()}.items()))
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return k_args + k_kwargs
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@cachier(backend='memory', hash_params=_hash_params)
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