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修复子进程中引发的异常无法捕获的bug
多进程中子进程引发异常之后并不会直接显示,而是在get()方法被访问的时候再次引发异常。参考http://stackoverflow.com/questions/22094852/how-to-catch-exceptions-in-workers-in-multiprocessing
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@ -1,16 +1,15 @@
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# coding=utf-8
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import json
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import time
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import commands
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from copy_reg import pickle
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from types import MethodType
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from multiprocessing import Pool
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from settings import max_running_number, lrun_gid, lrun_uid, use_tmpfs
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from consts import Language, Result
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from copy_reg import pickle
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from types import MethodType
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# 下面两个函数告诉Python怎么pickle类实例中的方法,否则Python2会报错,是Python2的已知bug
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# http://stackoverflow.com/questions/1816958/cant-pickle-type-instancemethod-when-using-pythons-multiprocessing-pool-ma/7309686
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def _pickle_method(method):
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func_name = method.im_func.__name__
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obj = method.im_self
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@ -127,7 +126,6 @@ class JudgeClient(object):
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for line in lines:
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name = line[:9].strip(" ")
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value = line[9:]
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print name, value
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if name == "MEMORY":
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result[translate[name]] = int(value)
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elif name == "CPUTIME":
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@ -157,7 +155,7 @@ class JudgeClient(object):
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run_result["test_case_id"] = test_case_id
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# 如果返回值非0,代表非正常结束
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# 如果返回值非0 或者信号量不是0 代表非正常结束
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if run_result["exit_code"] or run_result["term_sig"] or run_result["siginaled"]:
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run_result["result"] = Result.RUNTIME_ERROR
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return run_result
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@ -169,7 +167,7 @@ class JudgeClient(object):
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elif run_result["exceed"] in ["cpu_time", "real_time"]:
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run_result["result"] = Result.TIME_LIMIT_EXCEEDED
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else:
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run_result["result"] = Result.SYSTEM_ERROR
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raise JudgeClientException("Error exceeded type: " + run_result["exceed"])
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return run_result
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# 下面就是代码正常运行了
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@ -181,15 +179,24 @@ class JudgeClient(object):
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def run(self):
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# 添加到任务队列
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_results = []
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results = []
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for i in range(self.test_case_info["test_case_number"]):
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self.pool.apply_async(self.judge_one, args=(i + 1, ),
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callback=self.collect_result)
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_results.append(self.pool.apply_async(self.judge_one, args=(i + 1, )))
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self.pool.close()
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self.pool.join()
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print self.results
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for item in _results:
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# 注意多进程中的异常只有在get()的时候才会被引发
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# http://stackoverflow.com/questions/22094852/how-to-catch-exceptions-in-workers-in-multiprocessing
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try:
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results.append(item.get())
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except Exception as e:
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results.append({"result": Result.SYSTEM_ERROR})
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return results
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def __getstate__(self):
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# 不同的pool之间进行pickle的时候要排除自己,否则报错
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# http://stackoverflow.com/questions/25382455/python-notimplementederror-pool-objects-cannot-be-passed-between-processes
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self_dict = self.__dict__.copy()
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del self_dict['pool']
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return self_dict
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@ -202,4 +209,4 @@ client = JudgeClient(language=Language.C,
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max_real_time=200000,
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max_memory=1,
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test_case_dir="/var/test_case/1/")
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client.run()
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print client.run()
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