添加宽松判题的client
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163
judge/judger/loose_client.py
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163
judge/judger/loose_client.py
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# coding=utf-8
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import json
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import commands
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import hashlib
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from multiprocessing import Pool
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from settings import max_running_number, lrun_gid, lrun_uid, judger_workspace
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from language import languages
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from result import result
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from compiler import compile_
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from judge_exceptions import JudgeClientError, CompileError
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from utils import parse_lrun_output
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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,
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max_real_time, max_memory, test_case_dir):
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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_real_time: 最大执行时间,单位ms
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:param max_memory: 最大内存,单位MB
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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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self._max_real_time = max_real_time
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self._max_memory = max_memory
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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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def _generate_command(self, test_case_id):
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"""
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设置相关运行限制 进制访问网络 如果启用tmpfs 就把代码输出写入tmpfs,否则写入硬盘
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"""
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# todo 系统调用白名单 chroot等参数
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command = "lrun" + \
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" --max-cpu-time " + str(self._max_cpu_time / 1000.0) + \
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" --max-real-time " + str(self._max_real_time / 1000.0 * 2) + \
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" --max-memory " + str(self._max_memory * 1000 * 1000) + \
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" --network false" + \
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" --uid " + str(lrun_uid) + \
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" --gid " + str(lrun_gid)
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execute_command = self._language["execute_command"].format(exe_path=self._exe_path)
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command += (" " +
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execute_command +
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# 0就是stdin
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" 0<" + self._test_case_dir + str(test_case_id) + ".in" +
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# 1就是stdout
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" 1>" + judger_workspace + str(test_case_id) + ".out" +
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# 3是stderr,包含lrun的输出和程序的异常输出
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" 3>&2")
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return command
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def _parse_lrun_output(self, output):
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# 要注意的是 lrun把结果输出到了stderr,所以有些情况下lrun的输出可能与程序的一些错误输出的混合的,要先分离一下
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error = None
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# 倒序找到MEMORY的位置
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output_start = output.rfind("MEMORY")
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if output_start == -1:
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raise JudgeClientError("Lrun result parse error")
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# 如果不是0,说明lrun输出前面有输出,也就是程序的stderr有内容
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if output_start != 0:
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error = output[0:output_start]
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# 分离出lrun的输出
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output = output[output_start:]
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return error, parse_lrun_output(output)
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def _compare_output(self, test_case_id):
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output_path = judger_workspace + str(test_case_id) + ".out"
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try:
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f = open(output_path, "r")
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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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try:
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std = open(self._test_case_dir+test_case_id+".out", "r")
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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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lines=std.readline()
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line_conut = len(lines)
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for i in range(0, line_conut-2):
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if lines[i]
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def _judge_one(self, test_case_id):
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# 运行lrun程序 接收返回值
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command = self._generate_command(test_case_id)
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status_code, output = commands.getstatusoutput(command)
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if status_code:
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raise JudgeClientError(output)
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error, run_result = self._parse_lrun_output(output)
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run_result["test_case_id"] = test_case_id
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# 如果返回值非0 或者信号量不是0 或者程序的stderr有输出 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"] or error:
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run_result["result"] = result["runtime_error"]
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return run_result
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# 代表内存或者时间超过限制了
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if run_result["exceed"]:
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if run_result["exceed"] == "memory":
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run_result["result"] = result["memory_limit_exceeded"]
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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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raise JudgeClientError("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 需要判断代码的输出是否正确
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if self._compare_output(test_case_id):
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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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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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# todo logging
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print 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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@@ -2,8 +2,15 @@
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import sys
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import sys
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import json
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import json
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import MySQLdb
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import MySQLdb
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import os
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# 判断判题模式
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judge_model = os.environ.get("judge_model", "default")
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if judge_model == "default":
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from client import JudgeClient
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elif judge_model == "loose":
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from loose_client import JudgeClient
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from client import JudgeClient
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from language import languages
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from language import languages
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from compiler import compile_
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from compiler import compile_
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from result import result
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from result import result
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