【Python】处理 joblib.externals.loky.process_executor._RemoteTraceback:PermissionError:[WinError 5] 拒绝访问

knn = KNeighborsClassifier(n_neighbors=5, n_jobs=-1)

这么一坨异常栈：
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joblib.externals.loky.process_executor._RemoteTraceback:
“””
Traceback (most recent call last):
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib\externals\loky\process_executor.py”, line 404, in _process_worker
call_item = call_queue.get(block=True, timeout=timeout)
File “C:\Users\yk\AppData\Local\Programs\Python\Python37\lib\multiprocessing\queues.py”, line 99, in get
if not self._rlock.acquire(block, timeout):
PermissionError: [WinError 5] 拒绝访问。
“””

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File “D:/PyCharm/xxxxxxxxxxxxxxxxxxxxx.py”, line 28, in <module>
classifier = GridSearchCV(pipe, search_space, cv=5, verbose=0).fit(features_standardized, target)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\utils\validation.py”, line 73, in inner_f
return f(**kwargs)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\model_selection_search.py”, line 736, in fit
self._run_search(evaluate_candidates)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\model_selection_search.py”, line 1188, in _run_search
evaluate_candidates(ParameterGrid(self.param_grid))
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\model_selection_search.py”, line 715, in evaluate_candidates
cv.split(X, y, groups)))
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib\parallel.py”, line 1029, in __call__
if self.dispatch_one_batch(iterator):
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib\parallel.py”, line 847, in dispatch_one_batch
self._dispatch(tasks)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib\parallel.py”, line 765, in _dispatch
job = self._backend.apply_async(batch, callback=cb)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib_parallel_backends.py”, line 206, in apply_async
result = ImmediateResult(func)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib_parallel_backends.py”, line 570, in __init__
self.results = batch()
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib\parallel.py”, line 253, in __call__
for func, args, kwargs in self.items]
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib\parallel.py”, line 253, in <listcomp>
for func, args, kwargs in self.items]
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\model_selection_validation.py”, line 560, in _fit_and_score
test_scores = _score(estimator, X_test, y_test, scorer)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\model_selection_validation.py”, line 607, in _score
scores = scorer(estimator, X_test, y_test)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\metrics_scorer.py”, line 90, in __call__
score = scorer(estimator, *args, **kwargs)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\metrics_scorer.py”, line 372, in _passthrough_scorer
return estimator.score(*args, **kwargs)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\utils\metaestimators.py”, line 119, in <lambda>
out = lambda *args, **kwargs: self.fn(obj, *args, **kwargs)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\pipeline.py”, line 611, in score
return self.steps[-1][-1].score(Xt, y, **score_params)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\base.py”, line 499, in score
return accuracy_score(y, self.predict(X), sample_weight=sample_weight)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\neighbors_classification.py”, line 175, in predict
neigh_dist, neigh_ind = self.kneighbors(X)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\sklearn\neighbors_base.py”, line 665, in kneighbors
for s in gen_even_slices(X.shape[0], n_jobs)
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib\parallel.py”, line 1042, in __call__
self.retrieve()
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib\parallel.py”, line 921, in retrieve
self._output.extend(job.get(timeout=self.timeout))
File “D:\PyCharm\machine_learning_py_codes\venv\lib\site-packages\joblib_parallel_backends.py”, line 540, in wrap_future_result
return future.result(timeout=timeout)
File “C:\Users\yk\AppData\Local\Programs\Python\Python37\lib\concurrent\futures_base.py”, line 432, in result
return self.__get_result()
File “C:\Users\yk\AppData\Local\Programs\Python\Python37\lib\concurrent\futures_base.py”, line 384, in __get_result
raise self._exception
joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable.

我先去查了 joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable. 这个问题，没有任何有意义的建议。

然后找到问题开始的地方：PermissionError: [WinError 5] 拒绝访问，发现网上的说法更是扯远了，然后就很自闭。
照着网上的说法，修改了users权限，然后就报错[WinError6]，是在没办法。

但在写另一篇code的时候，遇到类似的问题，报错基本一致，我就思考了一下为什么会报这个错：结合之前网上查的资料，我觉得多集中在多线程和多核上，再看着WinError，我还得去改users权限，那就说明问题在OS上。
这个问题我现在也没有一个成熟的结论，但我的判断是：Python代码无权访问WindowsOS的一些核心信息？？？

那怎么处理呢？反正也只是本机的简单test，去掉多核相关n_jobs=-1，使用默认的n_jobs即可：

knn = KNeighborsClassifier(n_neighbors=5)

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【Python】处理 joblib.externals.loky.process_executor._RemoteTraceback:PermissionError:[WinError 5] 拒绝访问

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