Empty cache #491
Empty cache #491
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Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (1)
executorlib/interactive/shared.py (1)
635-647: Consider implementing a cache expiration mechanism.The current implementation lacks a way to handle cache expiration. Consider adding timestamp-based or version-based cache invalidation.
Example implementation:
def is_cache_valid(file_name: str, max_age: int = 3600) -> bool: """ Check if cache file is valid based on age. Args: file_name (str): Cache file path max_age (int): Maximum age in seconds Returns: bool: True if cache is valid """ try: stats = os.stat(file_name) return (time.time() - stats.st_mtime) < max_age except OSError: return False
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executorlib/interactive/shared.py(1 hunks)
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executorlib/interactive/shared.py (1)
635-647: Verify cache directory permissions and cleanup strategy.
The cache implementation should consider:
- Proper permissions for the cache directory
- Cache cleanup strategy (size/age limits)
- Handling of concurrent access to cache files
Let's verify the cache directory setup and permissions:
| exe_flag, result = get_output(file_name=file_name) | ||
| if exe_flag: | ||
| future = task_dict["future"] | ||
| future.set_result(result) | ||
| future_queue.task_done() | ||
| else: | ||
| _execute_task( | ||
| interface=interface, | ||
| task_dict=task_dict, | ||
| future_queue=future_queue, | ||
| ) | ||
| data_dict["output"] = future.result() | ||
| dump(file_name=file_name, data_dict=data_dict) |
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Add error handling for cache operations and implement atomic file operations.
The cache validation logic needs improvement in several areas:
- File operations (
dump,get_output) should have proper error handling - Cache file creation/updates should be atomic to prevent race conditions
- Invalid cache files should be cleaned up to prevent disk space issues
Consider implementing these improvements:
- exe_flag, result = get_output(file_name=file_name)
- if exe_flag:
- future = task_dict["future"]
- future.set_result(result)
- future_queue.task_done()
- else:
- _execute_task(
- interface=interface,
- task_dict=task_dict,
- future_queue=future_queue,
- )
- data_dict["output"] = future.result()
- dump(file_name=file_name, data_dict=data_dict)
+ try:
+ exe_flag, result = get_output(file_name=file_name)
+ if exe_flag:
+ future = task_dict["future"]
+ future.set_result(result)
+ future_queue.task_done()
+ else:
+ # Remove invalid cache file
+ os.remove(file_name)
+ _execute_task(
+ interface=interface,
+ task_dict=task_dict,
+ future_queue=future_queue,
+ )
+ data_dict["output"] = future.result()
+ # Use temporary file for atomic write
+ temp_file = file_name + '.tmp'
+ dump(file_name=temp_file, data_dict=data_dict)
+ os.replace(temp_file, file_name)
+ except Exception as e:
+ future.set_exception(e)
+ future_queue.task_done()
+ raise📝 Committable suggestion
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| exe_flag, result = get_output(file_name=file_name) | |
| if exe_flag: | |
| future = task_dict["future"] | |
| future.set_result(result) | |
| future_queue.task_done() | |
| else: | |
| _execute_task( | |
| interface=interface, | |
| task_dict=task_dict, | |
| future_queue=future_queue, | |
| ) | |
| data_dict["output"] = future.result() | |
| dump(file_name=file_name, data_dict=data_dict) | |
| try: | |
| exe_flag, result = get_output(file_name=file_name) | |
| if exe_flag: | |
| future = task_dict["future"] | |
| future.set_result(result) | |
| future_queue.task_done() | |
| else: | |
| # Remove invalid cache file | |
| os.remove(file_name) | |
| _execute_task( | |
| interface=interface, | |
| task_dict=task_dict, | |
| future_queue=future_queue, | |
| ) | |
| data_dict["output"] = future.result() | |
| # Use temporary file for atomic write | |
| temp_file = file_name + '.tmp' | |
| dump(file_name=temp_file, data_dict=data_dict) | |
| os.replace(temp_file, file_name) | |
| except Exception as e: | |
| future.set_exception(e) | |
| future_queue.task_done() | |
| raise |
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Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (3)
executorlib/standalone/hdf.py (1)
25-31: Use contextlib.suppress for cleaner error handling.The current try-except block can be simplified using
contextlib.suppressfor better readability.+from contextlib import suppress + def dump(file_name: str, data_dict: dict) -> None: """ Dump data dictionary into HDF5 file ... """ group_dict = { "fn": "function", "args": "input_args", "kwargs": "input_kwargs", "output": "output", } with h5py.File(file_name, "a") as fname: for data_key, data_value in data_dict.items(): if data_key in group_dict.keys(): - try: - fname.create_dataset( - name="/" + group_dict[data_key], - data=np.void(cloudpickle.dumps(data_value)), - ) - except ValueError: - pass + with suppress(ValueError): + fname.create_dataset( + name="/" + group_dict[data_key], + data=np.void(cloudpickle.dumps(data_value)), + )🧰 Tools
🪛 Ruff
25-31: Use
contextlib.suppress(ValueError)instead oftry-except-passReplace with
contextlib.suppress(ValueError)(SIM105)
tests/test_executor_backend_mpi.py (2)
100-129: Consider making timing assertions more robust.While the test logic is sound, the hard-coded timing thresholds might make the test flaky on slower CI systems or under heavy system load.
Consider these improvements:
def test_executor_cache_bypass(self): + SLEEP_DURATION = 1 + TIMING_BUFFER = 0.1 # Buffer for slower systems with Executor( max_workers=2, backend="local", block_allocation=True, cache_directory="./cache", ) as exe: cloudpickle_register(ind=1) time_1 = time.time() - fs_1 = exe.submit(calc_sleep, 1) - fs_2 = exe.submit(calc_sleep, 1) + fs_1 = exe.submit(calc_sleep, SLEEP_DURATION) + fs_2 = exe.submit(calc_sleep, SLEEP_DURATION) self.assertEqual(fs_1.result(), 1) self.assertTrue(fs_1.done()) time_2 = time.time() self.assertEqual(fs_2.result(), 1) self.assertTrue(fs_2.done()) time_3 = time.time() - self.assertTrue(time_2 - time_1 > 1) - self.assertTrue(time_3 - time_1 > 1) + self.assertTrue(time_2 - time_1 >= SLEEP_DURATION - TIMING_BUFFER) + self.assertTrue(time_3 - time_1 >= SLEEP_DURATION - TIMING_BUFFER) time_4 = time.time() - fs_3 = exe.submit(calc_sleep, 1) - fs_4 = exe.submit(calc_sleep, 1) + fs_3 = exe.submit(calc_sleep, SLEEP_DURATION) + fs_4 = exe.submit(calc_sleep, SLEEP_DURATION) self.assertEqual(fs_3.result(), 1) self.assertTrue(fs_3.done()) time_5 = time.time() self.assertEqual(fs_4.result(), 1) self.assertTrue(fs_4.done()) time_6 = time.time() - self.assertTrue(time_5 - time_4 < 1) - self.assertTrue(time_6 - time_4 < 1) + # For cached results, expect near-instant completion + self.assertTrue(time_5 - time_4 < TIMING_BUFFER) + self.assertTrue(time_6 - time_4 < TIMING_BUFFER)
Line range hint
143-154: Fix timing comparison and improve robustness.There's a bug in the timing assertion and similar timing threshold issues as the previous test.
Apply these fixes:
@unittest.skipIf( skip_mpi4py_test, "mpi4py is not installed, so the mpi4py tests are skipped." ) def test_meta_executor_parallel_cache(self): + SLEEP_DURATION = 1 + TIMING_BUFFER = 0.1 # Buffer for slower systems with Executor( max_cores=2, resource_dict={"cores": 2}, backend="local", block_allocation=True, cache_directory="./cache", ) as exe: cloudpickle_register(ind=1) time_1 = time.time() - fs_1 = exe.submit(mpi_funct_sleep, 1) + fs_1 = exe.submit(mpi_funct_sleep, SLEEP_DURATION) self.assertEqual(fs_1.result(), [(1, 2, 0), (1, 2, 1)]) self.assertTrue(fs_1.done()) time_2 = time.time() - self.assertTrue(time_2 - time_1 > 1) + self.assertTrue(time_2 - time_1 >= SLEEP_DURATION - TIMING_BUFFER) time_3 = time.time() - fs_2 = exe.submit(mpi_funct_sleep, 1) + fs_2 = exe.submit(mpi_funct_sleep, SLEEP_DURATION) self.assertEqual(fs_2.result(), [(1, 2, 0), (1, 2, 1)]) self.assertTrue(fs_2.done()) time_4 = time.time() - self.assertTrue(time_3 - time_4 < 1) # Bug: Incorrect time comparison + # For cached results, expect near-instant completion + self.assertTrue(time_4 - time_3 < TIMING_BUFFER)
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📒 Files selected for processing (2)
executorlib/standalone/hdf.py(1 hunks)tests/test_executor_backend_mpi.py(2 hunks)
🧰 Additional context used
🪛 Ruff
executorlib/standalone/hdf.py
25-31: Use contextlib.suppress(ValueError) instead of try-except-pass
Replace with contextlib.suppress(ValueError)
(SIM105)
🔇 Additional comments (2)
executorlib/standalone/hdf.py (1)
25-31: Verify the error handling strategy.
Silently ignoring ValueError during dataset creation could mask important errors. While this might be intentional for handling race conditions in concurrent access, it could also hide legitimate issues.
Let's verify the concurrent access scenario:
Consider adding debug logging before the try block to help with troubleshooting:
import logging
logging.debug(f"Attempting to create dataset {group_dict[data_key]} in {file_name}")✅ Verification successful
Let me check the test files to understand the error handling context better.
Let me check one more thing to understand the full context of this HDF5 file handling.
Silent ValueError handling is appropriate in this context
The error handling strategy is correct. The dump() function in hdf.py is used to store serialized Python objects in an HDF5 file, and the silent handling of ValueError serves a specific purpose:
- The function uses
h5py.Filein append mode ("a") - The ValueError would occur if the dataset already exists, which is an expected scenario in concurrent or repeated access patterns
- Silently continuing is the right behavior as it prevents duplicate writes while maintaining idempotency
The code is part of a caching mechanism, as evidenced by the module's location and usage patterns in test files. In this context, attempting to create a dataset that already exists is not an error condition that needs handling or logging.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for concurrent HDF5 access patterns in the codebase
# Expected: Find evidence of multiple processes/threads accessing the same HDF5 file
# Look for HDF5 file access in concurrent contexts
echo "Searching for concurrent HDF5 access patterns..."
rg -l "h5py.File.*[\"']a[\"']" | xargs rg -l "multiprocessing|threading|concurrent|parallel|mpi"
# Look for related test cases
echo "Searching for related test cases..."
fd -g "test_*.py" | xargs rg -l "h5py.*concurrent|parallel|race"
Length of output: 581
Script:
#!/bin/bash
# Check the test files for HDF5 related tests and error handling patterns
echo "Checking test files for HDF5 error handling..."
rg -A 5 -B 5 "h5py" tests/test_*.py
# Look for the actual usage context in the codebase
echo "Checking HDF5 usage context..."
rg -A 5 -B 5 "create_dataset" executorlib/
Length of output: 6348
Script:
#!/bin/bash
# Check for the complete implementation of the HDF5 handling module
echo "Checking complete HDF5 module implementation..."
cat executorlib/standalone/hdf.py
# Look for any related error handling patterns
echo "Checking for error handling patterns..."
rg -A 5 -B 5 "ValueError" executorlib/standalone/
Length of output: 16825
🧰 Tools
🪛 Ruff
25-31: Use contextlib.suppress(ValueError) instead of try-except-pass
Replace with contextlib.suppress(ValueError)
(SIM105)
tests/test_executor_backend_mpi.py (1)
17-20: LGTM! Well-structured helper function.
The calc_sleep function is appropriately implemented for testing cache timing behavior.
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Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (3)
tests/test_executor_backend_mpi.py (3)
9-14: Consider using importlib.util for consistency.While the current h5py import check is valid, consider using
importlib.util.find_specfor consistency with the mpi4py check below:-try: - import h5py - skip_h5py_test = False -except ImportError: - skip_h5py_test = True +skip_h5py_test = importlib.util.find_spec("h5py") is None🧰 Tools
🪛 Ruff
10-10:
h5pyimported but unused; consider usingimportlib.util.find_specto test for availability(F401)
106-139: Consider improving test reliability.While the test logic is sound, time-based assertions can be flaky in CI environments. Consider these improvements:
- Extract the sleep duration and timing thresholds as constants
- Add a small buffer to timing comparisons to reduce flakiness
+ SLEEP_DURATION = 1.0 + TIMING_BUFFER = 0.1 # 10% buffer for timing assertions def test_executor_cache_bypass(self): with Executor(...) as exe: cloudpickle_register(ind=1) time_1 = time.time() - fs_1 = exe.submit(calc_sleep, 1) - fs_2 = exe.submit(calc_sleep, 1) + fs_1 = exe.submit(calc_sleep, self.SLEEP_DURATION) + fs_2 = exe.submit(calc_sleep, self.SLEEP_DURATION) # ... rest of the test ... - self.assertTrue(time_2 - time_1 > 1) - self.assertTrue(time_3 - time_1 > 1) + self.assertTrue(time_2 - time_1 > self.SLEEP_DURATION * (1 - self.TIMING_BUFFER)) + self.assertTrue(time_3 - time_1 > self.SLEEP_DURATION * (1 - self.TIMING_BUFFER))
Line range hint
141-165: Apply consistent timing improvements.For consistency with the previous test, consider applying the same timing constant and buffer improvements here.
Additionally, verify that the timing assertion on line 165 has the correct order of operands:
- self.assertTrue(time_3 - time_4 < 1) + self.assertTrue(time_4 - time_3 < self.SLEEP_DURATION * self.TIMING_BUFFER)
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tests/test_executor_backend_mpi.py(3 hunks)
🧰 Additional context used
🪛 Ruff
tests/test_executor_backend_mpi.py
10-10: h5py imported but unused; consider using importlib.util.find_spec to test for availability
(F401)
🔇 Additional comments (1)
tests/test_executor_backend_mpi.py (1)
23-26: LGTM! Well-structured test helper.
The function provides a good way to test caching behavior by introducing a measurable delay.
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