Python 数据流-未调用函数-错误-未定义名称

我在Google Dataflow上与Apache Beam合作，通过lambda函数调用函数，得到一个错误，函数名未定义

output_tweets = (lines
                     | 'decode' >> beam.Map(lambda x: x.decode('utf-8'))
                     | 'assign window key' >> beam.WindowInto(window.FixedWindows(10))
                     | 'batch into n batches' >> BatchElements(min_batch_size=49, max_batch_size=50)
                     | 'sentiment analysis' >> beam.FlatMap(lambda x: sentiment(x))
                     )

这是我的Apache Beam调用，在最后一行中提到了函数感悟，这给了我一个问题

函数代码如下（我认为这无关紧要）：

我得到了下面的回溯

  File "stream.py", line 97, in <lambda>
NameError: name 'sentiment' is not defined [while running 'generatedPtransform-441']

文件“stream.py”，第97行，在
NameError:未定义名称“情绪”[在运行“GeneratedPtTransform-441”时]

---

有什么想法吗？

这个问题的发生有两个原因

函数

定义是否与beam管道存在于同一个python文件中

函数的定义是否在beam管道中调用之前

我做了一个如下的快速测试，如果遵循以上两个步骤，它就会按预期工作

def testing(messages):
    return messages.lower()

windowed_lower_word_counts = (windowed_words
                              | beam.Map(lambda word: testing(word))
                              | "count" >> beam.combiners.Count.PerElement())

ib.show(windowed_lower_word_counts, include_window_info=True)

0   b'have'     3   2020-04-19 06:04:39.999999+0000 2020-04-19 06:04:30.000000+0000 (10s)   Pane 0
1   b'ransom'   1   2020-04-19 06:04:39.999999+0000 2020-04-19 06:04:30.000000+0000 (10s)   Pane 0
2   b'let'      1   2020-04-19 06:04:39.999999+0000 2020-04-19 06:04:30.000000+0000 (10s)   Pane 0
3   b'me'       1   2020-04-19 06:04:39.999999+0000 2020-04-19 06:04:30.000000+0000 (10s)   Pane 0

如果函数是在调用后定义的，那么我们会得到如下所示的错误

windowed_lower_word_counts = (windowed_words
                              | beam.Map(lambda word: testing_after(word))
                              | "count" >> beam.combiners.Count.PerElement())

ib.show(windowed_lower_word_counts, include_window_info=True)

ERROR:apache_beam.runners.direct.executor:Exception at bundle <apache_beam.runners.direct.bundle_factory._Bundle object at 0x7f478f344820>, due to an exception.
 Traceback (most recent call last):
  File "apache_beam/runners/common.py", line 954, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 552, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "/root/apache-beam-custom/packages/beam/sdks/python/apache_beam/transforms/core.py", line 1482, in <lambda>
    wrapper = lambda x: [fn(x)]
  File "<ipython-input-19-f34e29a17836>", line 2, in <lambda>
    | beam.Map(lambda word: testing_after_new(word))
NameError: name 'testing_after' is not defined

def testing_after(messages):
    return messages.lower()

windowed\u lower\u words\u counts=（windowed\u words
|beam.Map（lambda词：在（词）之后测试）
|“count”>>beam.combiners.count.PerElement（））
ib.show（带窗口的较低单词计数，包括窗口信息=真）
错误：apache_beam.runners.direct.executor:bundle异常
函数在同一脚本中，其定义在管道运行之前。我观察到的一件事是，如果我在没有lambda的情况下调用该函数，并且只使用beam.Map，它就到达了该函数。你知道为什么吗？如果你看一下它，就会发现用户定义的函数应该是3种类型之一
types.BuiltinFunctionType，types.MethodType，types.FunctionType
。因此，传递函数名是正确的方法，我们的示例中也提到了这一点。在您提到的示例中，您无法在员工中找到情绪，您可能必须在课堂中传递这些情绪。如果这有帮助，请接受答案。嘿@jayadeep jayaraman，这很有效。但是，如果调用仅仅是
beam.Map（x）
，beam.Map也可以工作。结果是，它给了我一个
discovery.build
错误，即使库已导入。我不确定这是不是该问的地方。
windowed_lower_word_counts = (windowed_words
                              | beam.Map(lambda word: testing_after(word))
                              | "count" >> beam.combiners.Count.PerElement())

ib.show(windowed_lower_word_counts, include_window_info=True)

ERROR:apache_beam.runners.direct.executor:Exception at bundle <apache_beam.runners.direct.bundle_factory._Bundle object at 0x7f478f344820>, due to an exception.
 Traceback (most recent call last):
  File "apache_beam/runners/common.py", line 954, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 552, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "/root/apache-beam-custom/packages/beam/sdks/python/apache_beam/transforms/core.py", line 1482, in <lambda>
    wrapper = lambda x: [fn(x)]
  File "<ipython-input-19-f34e29a17836>", line 2, in <lambda>
    | beam.Map(lambda word: testing_after_new(word))
NameError: name 'testing_after' is not defined

def testing_after(messages):
    return messages.lower()