mirror of
https://github.com/QingdaoU/OnlineJudge.git
synced 2025-01-17 01:54:52 +00:00
177 lines
7.8 KiB
Python
177 lines
7.8 KiB
Python
# coding=utf-8
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import os
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import json
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import hashlib
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import judger
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import spj_client
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from multiprocessing import Pool
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from settings import max_running_number
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from language import languages
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from result import result
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from judge_exceptions import JudgeClientError
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from logger import logger
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# 下面这个函数作为代理访问实例变量，否则Python2会报错，是Python2的已知问题
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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 _run(instance, test_case_id):
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return instance._judge_one(test_case_id)
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class JudgeClient(object):
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def __init__(self, language_code, exe_path, max_cpu_time, max_memory, test_case_dir, judge_base_path, spj_path):
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"""
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:param language_code: 语言编号
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:param exe_path: 可执行文件路径
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:param max_cpu_time: 最大cpu时间，单位ms
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:param max_memory: 最大内存，单位字节，直接传给judger.run方法
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:param test_case_dir: 测试用例文件夹路径
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:return:返回结果list
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"""
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self._language = languages[language_code]
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self._exe_path = exe_path
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self._max_cpu_time = max_cpu_time
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# 如果是Java, 就不在judger中限制内存分配了, 而是转移到Java运行参数中,
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# 参见 https://github.com/QingdaoU/OnlineJudge/issues/23
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# 这里给出3倍的限制, 是为了防止出现OutOfMemory异常导致误判为Runtime Error,
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# 如果实际使用超过了3倍, 就只能得到Runtime Error的结果了
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# 而最后会比较Java实际使用的内存和1.5倍的设定内存的大小
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self._real_max_memory = max_memory
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if self._language["name"] == "java":
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self._max_memory = judger.MEMORY_UNLIMITED
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self.execute_command = self._language["execute_command"].\
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format(exe_path=self._exe_path, max_memory=max_memory * 3).split(" ")
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else:
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self._max_memory = self._real_max_memory
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self.execute_command = self._language["execute_command"].format(exe_path=self._exe_path).split(" ")
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self._test_case_dir = test_case_dir
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# 进程池
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self._pool = Pool(processes=max_running_number)
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# 测试用例配置项
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self._test_case_info = self._load_test_case_info()
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self._judge_base_path = judge_base_path
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self._spj_path = spj_path
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def _load_test_case_info(self):
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# 读取测试用例信息 转换为dict
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try:
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f = open(os.path.join(self._test_case_dir, "info"))
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return json.loads(f.read())
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except IOError:
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raise JudgeClientError("Test case config file not found")
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except ValueError:
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raise JudgeClientError("Test case config file format error")
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def _compare_output(self, test_case_id):
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test_case_config = self._test_case_info["test_cases"][str(test_case_id)]
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output_path = os.path.join(self._judge_base_path, str(test_case_id) + ".out")
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try:
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f = open(output_path, "rb")
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except IOError:
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# 文件不存在等引发的异常 返回结果错误
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return "", False
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if "striped_output_md5" not in test_case_config:
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# 计算输出文件的md5 和之前测试用例文件的md5进行比较
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# 兼容之前没有striped_output_md5的测试用例
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# 现在比较的是完整的文件
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md5 = hashlib.md5()
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while True:
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data = f.read(2 ** 8)
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if not data:
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break
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md5.update(data)
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output_md5 = md5.hexdigest()
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return output_md5, output_md5 == test_case_config["output_md5"]
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else:
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# 这时候需要去除用户输出最后的空格和换行 再去比较md5
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md5 = hashlib.md5()
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# 比较和返回去除空格后的md5比较结果
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md5.update(f.read().rstrip())
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output_md5 = md5.hexdigest()
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return output_md5, output_md5 == test_case_config["striped_output_md5"]
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def _judge_one(self, test_case_id):
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in_file = os.path.join(self._test_case_dir, str(test_case_id) + ".in")
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out_file = os.path.join(self._judge_base_path, str(test_case_id) + ".out")
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run_result = judger.run(path=self.execute_command[0],
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max_cpu_time=self._max_cpu_time,
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max_memory=self._max_memory,
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in_file=in_file,
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out_file=out_file,
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args=self.execute_command[1:],
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env=["PATH=" + os.environ["PATH"]],
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use_sandbox=self._language["use_sandbox"],
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use_nobody=True)
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run_result["test_case"] = test_case_id
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# 对Java的特殊处理, 详见__init__函数中注释
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if self._language["name"] == "java" and run_result["memory"] > self._real_max_memory * 1.5:
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run_result["flag"] = 3
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# 将judger返回的结果标志转换为本系统中使用的
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if run_result["flag"] == 0:
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if self._spj_path is None:
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output_md5, r = self._compare_output(test_case_id)
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if r:
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run_result["result"] = result["accepted"]
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else:
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run_result["result"] = result["wrong_answer"]
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run_result["output_md5"] = output_md5
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else:
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spj_result = spj_client.spj(path=self._spj_path,
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max_cpu_time=3 * self._max_cpu_time,
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max_memory=3 * self._real_max_memory,
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in_path=in_file,
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user_out_path=out_file)
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if spj_result["spj_result"] == spj_client.AC:
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run_result["result"] = result["accepted"]
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elif spj_result["spj_result"] == spj_client.WA:
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run_result["result"] = result["wrong_answer"]
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else:
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run_result["result"] = result["system_error"]
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run_result["error"] = "SPJ Crashed, return: %d, signal: %d" % \
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(spj_result["spj_result"], spj_result["signal"])
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elif run_result["flag"] in [1, 2]:
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run_result["result"] = result["time_limit_exceeded"]
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elif run_result["flag"] == 3:
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run_result["result"] = result["memory_limit_exceeded"]
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elif run_result["flag"] == 4:
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run_result["result"] = result["runtime_error"]
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elif run_result["flag"] == 5:
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run_result["result"] = result["system_error"]
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return run_result
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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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_results.append(self._pool.apply_async(_run, (self, i + 1)))
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self._pool.close()
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self._pool.join()
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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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logger.error("system error")
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logger.error(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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