更改项目结构

judger/client.py

@@ -0,0 +1,173 @@
+# coding=utf-8
+import json
+import commands
+import hashlib
+from multiprocessing import Pool
+
+from settings import max_running_number, lrun_gid, lrun_uid, judger_workspace
+from language import languages
+from result import result
+from compiler import compile_
+from judge_exceptions import JudgeClientError, CompileError
+from utils import parse_lrun_output
+
+
+# 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
+# http://stackoverflow.com/questions/1816958/cant-pickle-type-instancemethod-when-using-pythons-multiprocessing-pool-ma/7309686
+def _run(instance, test_case_id):
+    return instance._judge_one(test_case_id)
+
+
+class JudgeClient(object):
+    def __init__(self, language_code, exe_path, max_cpu_time,
+                 max_real_time, max_memory, test_case_dir):
+        """
+        :param language_code: 语言编号
+        :param exe_path: 可执行文件路径
+        :param max_cpu_time: 最大cpu时间，单位ms
+        :param max_real_time: 最大执行时间，单位ms
+        :param max_memory: 最大内存，单位MB
+        :param test_case_dir: 测试用例文件夹路径
+        :return:返回结果list
+        """
+        self._language = languages[str(language_code)]
+        self._exe_path = exe_path
+        self._max_cpu_time = max_cpu_time
+        self._max_real_time = max_real_time
+        self._max_memory = max_memory
+        self._test_case_dir = test_case_dir
+        # 进程池
+        self._pool = Pool(processes=max_running_number)
+        # 测试用例配置项
+        self._test_case_info = self._load_test_case_info()
+
+    def _load_test_case_info(self):
+        # 读取测试用例信息 转换为dict
+        try:
+            f = open(self._test_case_dir + "info")
+            return json.loads(f.read())
+        except IOError:
+            raise JudgeClientError("Test case config file not found")
+        except ValueError:
+            raise JudgeClientError("Test case config file format error")
+
+    def _generate_command(self, test_case_id):
+        """
+        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
+        """
+        # todo 系统调用白名单 chroot等参数
+        command = "lrun" + \
+                  " --max-cpu-time " + str(self._max_cpu_time / 1000.0) + \
+                  " --max-real-time " + str(self._max_real_time / 1000.0) + \
+                  " --max-memory " + str(self._max_memory * 1000 * 1000) + \
+                  " --network false" + \
+                  " --uid " + str(lrun_uid) + \
+                  " --gid " + str(lrun_gid)
+
+        execute_command = self._language["execute_command"].format(exe_path=self._exe_path)
+
+        command += (" " +
+                    execute_command +
+                    # 0就是stdin
+                    " 0<" + self._test_case_dir + str(test_case_id) + ".in" +
+                    # 1就是stdout
+                    " 1>" + judger_workspace + str(test_case_id) + ".out" +
+                    # 3是stderr，包含lrun的输出和程序的异常输出
+                    " 3>&2")
+        return command
+
+    def _parse_lrun_output(self, output):
+        # 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
+        error = None
+        # 倒序找到MEMORY的位置
+        output_start = output.rfind("MEMORY")
+        if output_start == -1:
+            raise JudgeClientError("Lrun result parse error")
+        # 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
+        if output_start != 0:
+            error = output[0:output_start]
+        # 分离出lrun的输出
+        output = output[output_start:]
+
+        return error, parse_lrun_output(output)
+
+    def _compare_output(self, test_case_id):
+        test_case_md5 = self._test_case_info["test_cases"][str(test_case_id)]["output_md5"]
+        output_path = judger_workspace + str(test_case_id) + ".out"
+
+        try:
+            f = open(output_path, "rb")
+        except IOError:
+            # 文件不存在等引发的异常 返回结果错误
+            return False
+
+        # 计算输出文件的md5 和之前测试用例文件的md5进行比较
+        md5 = hashlib.md5()
+        while True:
+            data = f.read(2 ** 8)
+            if not data:
+                break
+            md5.update(data)
+
+        # 对比文件是否一致
+        # todo 去除最后的空行
+        return md5.hexdigest() == test_case_md5
+
+    def _judge_one(self, test_case_id):
+        # 运行lrun程序 接收返回值
+        command = self._generate_command(test_case_id)
+        status_code, output = commands.getstatusoutput(command)
+        if status_code:
+            raise JudgeClientError(output)
+        error, run_result = self._parse_lrun_output(output)
+
+        run_result["test_case_id"] = test_case_id
+
+        # 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
+        if run_result["exit_code"] or run_result["term_sig"] or run_result["siginaled"] or error:
+            run_result["result"] = result["runtime_error"]
+            return run_result
+
+        # 代表内存或者时间超过限制了
+        if run_result["exceed"]:
+            if run_result["exceed"] == "memory":
+                run_result["result"] = result["memory_limit_exceeded"]
+            elif run_result["exceed"] in ["cpu_time", "real_time"]:
+                run_result["result"] = result["time_limit_exceeded"]
+            else:
+                raise JudgeClientError("Error exceeded type: " + run_result["exceed"])
+            return run_result
+
+        # 下面就是代码正常运行了 需要判断代码的输出是否正确
+        if self._compare_output(test_case_id):
+            run_result["result"] = result["accepted"]
+        else:
+            run_result["result"] = result["wrong_answer"]
+
+        return run_result
+
+    def run(self):
+        # 添加到任务队列
+        _results = []
+        results = []
+        for i in range(self._test_case_info["test_case_number"]):
+            _results.append(self._pool.apply_async(_run, (self, i + 1)))
+        self._pool.close()
+        self._pool.join()
+        for item in _results:
+            # 注意多进程中的异常只有在get()的时候才会被引发
+            # http://stackoverflow.com/questions/22094852/how-to-catch-exceptions-in-workers-in-multiprocessing
+            try:
+                results.append(item.get())
+            except Exception as e:
+                # todo logging
+                print e
+                results.append({"result": result["system_error"]})
+        return results
+
+    def __getstate__(self):
+        # 不同的pool之间进行pickle的时候要排除自己，否则报错
+        # http://stackoverflow.com/questions/25382455/python-notimplementederror-pool-objects-cannot-be-passed-between-processes
+        self_dict = self.__dict__.copy()
+        del self_dict['_pool']
+        return self_dict