Question

我正在编写这个程序，希望得到这个输出：

True
True
False
False

我和＃34;没有＆＃34;打印在我的预期输出之间：

True
None
True
None
False
None
False
None

我不知道为什么这些＆＃34;没有＆＃34;字符串正在打印，任何帮助将不胜感激！这是我的代码：

# function:   check_answer
# input:      two numbers (number1 & number2, both integers); an answer (an integer)
#             and an operator (+ or -, expressed as a String)
# processing: determines if the supplied expression is correct.  for example, if the operator
#             is "+", number1 = 1, number2 = 2 and answer = 3 then the expression is correct
#             (1 + 2 = 3).
# output:     returns True if the expression is correct, False if it is not correct

def check_answer (number1, number2, answer, operator):
    if operator == "+":
        test = number1 + number2
        if test == answer:
            print ("True")
        else:
            print ("False")
    if operator == "-":
        test2 = number1 - number2
        if test2 == answer:
            print ("True")
        else:
            print ("False")
    return

answer1 = check_answer(1, 2, 3, "+")
print (answer1)
answer2 = check_answer(1, 2, -1, "-")
print (answer2)
answer3 = check_answer(9, 5, 3, "+")
print (answer3)
answer4 = check_answer(8, 2, 4, "-")
print (answer4)

非常感谢!!

Answer 1

这是因为[O] Py4JJavaError Traceback (most recent call last) <ipython-input-101-31527190732e> in <module>() ----> 1 user_cnt = all_twt_rdd.flatMap(lambda line: line.split(" ")).take(2) /home/notebook/spark-1.6.0-bin-hadoop2.6/python/pyspark/rdd.pyc in take(self, num) 1295 1296 p = range(partsScanned, min(partsScanned + numPartsToTry, totalParts)) -> 1297 res = self.context.runJob(self, takeUpToNumLeft, p) 1298 1299 items += res /home/notebook/spark-1.6.0-bin-hadoop2.6/python/pyspark/context.pyc in runJob(self, rdd, partitionFunc, partitions, allowLocal) 937 # SparkContext#runJob. 938 mappedRDD = rdd.mapPartitions(partitionFunc) --> 939 port = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, partitions) 940 return list(_load_from_socket(port, mappedRDD._jrdd_deserializer)) 941 /home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py in __call__(self, *args) 811 answer = self.gateway_client.send_command(command) 812 return_value = get_return_value( --> 813 answer, self.gateway_client, self.target_id, self.name) 814 815 for temp_arg in temp_args: /home/notebook/spark-1.6.0-bin-hadoop2.6/python/pyspark/sql/utils.pyc in deco(*a, **kw) 43 def deco(*a, **kw): 44 try: ---> 45 return f(*a, **kw) 46 except py4j.protocol.Py4JJavaError as e: 47 s = e.java_exception.toString() /home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/py4j-0.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name) 306 raise Py4JJavaError( 307 "An error occurred while calling {0}{1}{2}.\n". --> 308 format(target_id, ".", name), value) 309 else: 310 raise Py4JError( Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 50.0 failed 1 times, most recent failure: Lost task 0.0 in stage 50.0 (TID 456, localhost): org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/worker.py", line 111, in main process() File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/worker.py", line 106, in process serializer.dump_stream(func(split_index, iterator), outfile) File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/serializers.py", line 263, in dump_stream vs = list(itertools.islice(iterator, batch)) File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/pyspark/rdd.py", line 1293, in takeUpToNumLeft yield next(iterator) File "<ipython-input-101-31527190732e>", line 1, in <lambda> File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/sql/types.py", line 1272, in __getattr__ raise AttributeError(item) AttributeError: split at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166) at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207) at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125) at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) at org.apache.spark.scheduler.Task.run(Task.scala:89) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799) at scala.Option.foreach(Option.scala:236) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858) at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:393) at org.apache.spark.api.python.PythonRDD.runJob(PythonRDD.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381) at py4j.Gateway.invoke(Gateway.java:259) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:209) at java.lang.Thread.run(Thread.java:745) Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/worker.py", line 111, in main process() File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/worker.py", line 106, in process serializer.dump_stream(func(split_index, iterator), outfile) File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/serializers.py", line 263, in dump_stream vs = list(itertools.islice(iterator, batch)) File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/pyspark/rdd.py", line 1293, in takeUpToNumLeft yield next(iterator) File "<ipython-input-101-31527190732e>", line 1, in <lambda> File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/sql/types.py", line 1272, in __getattr__ raise AttributeError(item) AttributeError: split at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166) at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207) at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125) at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) at org.apache.spark.scheduler.Task.run(Task.scala:89) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) ... 1 more之类的调用 - 你的函数没有返回任何内容，这就是你看到print(answer1)打印的原因。只是不要打印函数返回的内容：

None

或者，从函数返回check_answer(1, 2, 3, "+") check_answer(1, 2, -1, "-") check_answer(9, 5, 3, "+") check_answer(8, 2, 4, "-")并打印结果：

True/False

作为旁注，您可以使用operator模块并将操作字符串映射到实际操作来简化您的功能。 def check_answer(number1, number2, answer, operator): if operator == "+": test = number1 + number2 return test == answer if operator == "-": test2 = number1 - number2 return test2 == answer answer1 = check_answer(1, 2, 3, "+") print (answer1) answer2 = check_answer(1, 2, -1, "-") print (answer2) answer3 = check_answer(9, 5, 3, "+") print (answer3) answer4 = check_answer(8, 2, 4, "-") print (answer4)和+的工作示例：

Python＆＃34;无＆＃34;印花

1 个答案: