2017-04-18 44 views
0

我想合併兩個代碼。
A.py是webpy代碼。
B.py是Google雲語音(STT)示例代碼。[python]我想合併兩個代碼,但發生webpy錯誤類型'exceptions.keyerror'

但是當我合併兩個代碼,它發生webpy錯誤

type 'exceptions.keyerror' 

我插入A.py代碼B.pymain()第一線。

如何合併此代碼?

這是A.py

import web 

urls = ("/.*", "hello") 
app = web.application(urls, globals()) 

class hello: 
    def GET(self): 
     return 'Hello, world!' 

if __name__ == "__main__": 
    app.run() 

這是B.py(谷歌colud語音(STT)例如代碼)

# 
# Licensed under the Apache License, Version 2.0 (the "License"); 
# you may not use this file except in compliance with the License. 
# You may obtain a copy of the License at 
# 
#  http://www.apache.org/licenses/LICENSE-2.0 
# 
# Unless required by applicable law or agreed to in writing, software 
# distributed under the License is distributed on an "AS IS" BASIS, 
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 
# See the License for the specific language governing permissions and 
# limitations under the License. 
"""Sample that streams audio to the Google Cloud Speech API via GRPC.""" 

from __future__ import division 

import contextlib 
import functools 
import re 
import signal 
import sys 
import web 

import google.auth 
import google.auth.transport.grpc 
import google.auth.transport.requests 
from google.cloud.proto.speech.v1beta1 import cloud_speech_pb2 
from google.rpc import code_pb2 
import grpc 
import pyaudio 
from six.moves import queue 

# Audio recording parameters 
RATE = 48000 
CHUNK = int(RATE/10) # 100ms 

# The Speech API has a streaming limit of 60 seconds of audio*, so keep the 
# connection alive for that long, plus some more to give the API time to figure 
# out the transcription. 
# * https://g.co/cloud/speech/limits#content 
DEADLINE_SECS = 60 * 3 + 5 
SPEECH_SCOPE = 'https://www.googleapis.com/auth/cloud-platform' 

def make_channel(host, port): 
    """Creates a secure channel with auth credentials from the environment.""" 
    # Grab application default credentials from the environment 
    credentials, _ = google.auth.default(scopes=[SPEECH_SCOPE]) 

    # Create a secure channel using the credentials. 
    http_request = google.auth.transport.requests.Request() 
    target = '{}:{}'.format(host, port) 

    return google.auth.transport.grpc.secure_authorized_channel(
     credentials, http_request, target) 

def _audio_data_generator(buff): 
    """A generator that yields all available data in the given buffer. 

    Args: 
     buff - a Queue object, where each element is a chunk of data. 
    Yields: 
     A chunk of data that is the aggregate of all chunks of data in `buff`. 
     The function will block until at least one data chunk is available. 
    """ 
    stop = False 
    while not stop: 
     # Use a blocking get() to ensure there's at least one chunk of data. 
     data = [buff.get()] 

     # Now consume whatever other data's still buffered. 
     while True: 
      try: 
       data.append(buff.get(block=False))`enter code here` 
      except queue.Empty: 
       break 

     # `None` in the buffer signals that the audio stream is closed. Yield 
     # the final bit of the buffer and exit the loop. 
     if None in data: 
      stop = True 
      data.remove(None) 

     yield b''.join(data) 

def _fill_buffer(buff, in_data, frame_count, time_info, status_flags): 
    """Continuously collect data from the audio stream, into the buffer.""" 
    buff.put(in_data) 
    return None, pyaudio.paContinue 

# [START audio_stream] 
@contextlib.contextmanager 
def record_audio(rate, chunk): 
    """Opens a recording stream in a context manager.""" 
    # Create a thread-safe buffer of audio data 
    buff = queue.Queue() 

    audio_interface = pyaudio.PyAudio() 
    audio_stream = audio_interface.open(
     format=pyaudio.paInt16, 
     # The API currently only supports 1-channel (mono) audio 

     channels=1, rate=rate, 
     input=True, frames_per_buffer=chunk, 
     # Run the audio stream asynchronously to fill the buffer object. 
     # This is necessary so that the input device's buffer doesn't overflow 
     # while the calling thread makes network requests, etc. 
     stream_callback=functools.partial(_fill_buffer, buff), 
    ) 

    yield _audio_data_generator(buff) 

    audio_stream.stop_stream() 
    audio_stream.close() 
    # Signal the _audio_data_generator to finish 
    buff.put(None) 
    audio_interface.terminate() 
# [END audio_stream] 

def request_stream(data_stream, rate, interim_results=True): 
    """Yields `StreamingRecognizeRequest`s constructed from a recording audio 
    stream. 

    Args: 
     data_stream: A generator that yields raw audio data to send. 
     rate: The sampling rate in hertz. 
     interim_results: Whether to return intermediate results, before the 
      transcription is finalized. 
    """ 
    # The initial request must contain metadata about the stream, so the 
    # server knows how to interpret it. 
    recognition_config = cloud_speech_pb2.RecognitionConfig(
     # There are a bunch of config options you can specify. See 
       encoding='LINEAR16', # raw 16-bit signed LE samples 
     sample_rate=rate, # the rate in hertz 
     # See http://g.co/cloud/speech/docs/languages 
     # for a list of supported languages. 
     language_code='ko-KR', # a BCP-47 language tag 
    ) 
    streaming_config = cloud_speech_pb2.StreamingRecognitionConfig(
     interim_results=interim_results, 
     config=recognition_config, 
    ) 

    yield cloud_speech_pb2.StreamingRecognizeRequest(
     streaming_config=streaming_config) 

    for data in data_stream: 
     # Subsequent requests can all just have the content 
     yield cloud_speech_pb2.StreamingRecognizeRequest(audio_content=data) 

def listen_print_loop(recognize_stream): 
    """Iterates through server responses and prints them. 

    The recognize_stream passed is a generator that will block until a response 
    is provided by the server. When the transcription response comes, print it. 

    In this case, responses are provided for interim results as well. If the 
    response is an interim one, print a line feed at the end of it, to allow 
    the next result to overwrite it, until the response is a final one. For the 
    final one, print a newline to preserve the finalized transcription. 
    """ 
    num_chars_printed = 0 
    for resp in recognize_stream: 
     if resp.error.code != code_pb2.OK: 
      raise RuntimeError('Server error: ' + resp.error.message) 

     if not resp.results: 
      continue 

     # Display the top transcription 
     result = resp.results[0] 
     transcript = result.alternatives[0].transcript 

     # Display interim results, but with a carriage return at the end of the 
     # line, so subsequent lines will overwrite them. 
     # 
     # If the previous result was longer than this one, we need to print 
     # some extra spaces to overwrite the previous result 
     overwrite_chars = ' ' * max(0, num_chars_printed - len(transcript)) 

     if not result.is_final: 
      sys.stdout.write(transcript + overwrite_chars + '\r') 
      sys.stdout.flush() 

      num_chars_printed = len(transcript) 
     else: 
      print(transcript + overwrite_chars) 

      # Exit recognition if any of the transcribed phrases could be 
      # one of our keywords. 
      if re.search(r'\b(exit|quit)\b', transcript, re.I): 
       print('Exiting..') 
       break 

      num_chars_printed = 0 

def main(): 
    urls = ("/.*", "hello") 
    app = web.application(urls, globals()) 

    class hello: 
     def GET(self): 
      return 'Hello, world!' 

    app.run() 

    service = cloud_speech_pb2.SpeechStub(
     make_channel('speech.googleapis.com', 443)) 

    # For streaming audio from the microphone, there are three threads. 
    # First, a thread that collects audio data as it comes in 
    with record_audio(RATE, CHUNK) as buffered_audio_data: 
     # Second, a thread that sends requests with that data 
     requests = request_stream(buffered_audio_data, RATE) 
     # Third, a thread that listens for transcription responses 
     recognize_stream = service.StreamingRecognize(
      requests, DEADLINE_SECS) 

     # Exit things cleanly on interrupt 
     signal.signal(signal.SIGINT, lambda *_: recognize_stream.cancel()) 

     # Now, put the transcription responses to use. 
     try: 
      listen_print_loop(recognize_stream) 

      recognize_stream.cancel() 
     except grpc.RpcError as e: 
      code = e.code() 
      # CANCELLED is caused by the interrupt handler, which is expected. 
      if code is not code.CANCELLED: 
       raise 

if __name__ == '__main__': 
    main() 

回答

0

誤差指這樣的事實的web.py將尋找可從全球範圍訪問的class hello。你已經在main()中定義了你的class hello。 web.py永遠不會找到它。

這就是說,還有其他的問題。您在主內的app.run()的呼叫啓動web.py網絡服務器並永不返回,因此在此之後沒有任何事情會被執行。

結合兩個代碼示例需要理解這兩個片段。閱讀文檔,並繼續嘗試。