折腾：
【已解决】Flask中ms的tts返回401感觉是获取token错误导致无法生成语音文件
虽然已经解决了Azure的获取token的问题了，但是此处又发现其他的问题：
Mac本地调试单个Flask的实例的时候，对于单个文件中，不同函数中共享全局变量的值：
resources/tts.py
<code>gMsToken = ""
def initAudioService():
"""
init audio service related related:
init token
:return:
"""
# log = app.logger
log.info("initAudioService")
createAudioTempFolder()
# getBaiduToken()
getAzureSpeechToken()
log.info("Init audio service complete")
def getAzureSpeechToken():
"""get Microsoft Azure speech service token key"""
# log = app.logger
global gMsToken
log.info("getAzureSpeechToken: gMsToken=%s", gMsToken)
gMsToken = refreshAzureSpeechToken()
log.info("after getAzureSpeechToken: gMsToken=%s", gMsToken)
def msTTS(unicodeText,
voiceName=settings.MS_TTS_VOICE_NAME,
voiceRate=settings.MS_TTS_VOICE_RATE,
voiceVolume=settings.MS_TTS_VOICE_VOLUME):
"""call ms azure tts to generate audio(mp3/wav/...) from text"""
global gMsToken
# log = app.logger
log.info("msTTS: unicodeText=%s, gMsToken=%s", unicodeText, gMsToken)
if not gMsToken:
getAzureSpeechToken()
isOk = False
audioBinData = None
errNo = 0
errMsg = "Unknown error"
msTtsUrl = settings.MS_TTS_URL
log.info("msTtsUrl=%s", msTtsUrl)
reqHeaders = {
"Content-Type": "application/ssml+xml",
"X-Microsoft-OutputFormat": settings.MS_TTS_OUTPUT_FORMAT,
"Ocp-Apim-Subscription-Key": settings.MS_TTS_SECRET_KEY,
"Authorization": "Bear " + gMsToken
}
log.info("reqHeaders=%s", reqHeaders)
...
################################################################################
# Global Init
################################################################################
# testAudioSynthesis()
initAudioService()
log.info("TTS init complete")
</code>其中的全局变量：gMsToken，用来保存ms的tts的token，
是可以正常工作的。
但是，在：
【未解决】在线环境中用gunicorn部署的产品demo无法正常初始化运行
把Flask通过gunicorn+supervisor部署到在线服务器的生产环境中后，由于多个实例和线程：
gunicorn的线程设置为cpu core个数 * 2 + 1，所以4核就是4×2+1=9个Flask的实例
然后从log中发现个问题：
<code>[2018-08-28 18:29:07,783 INFO tts.py:129 getAzureSpeechToken] getAzureSpeechToken: gMsToken= [2018-08-28 18:29:07,998 INFO tts.py:131 getAzureSpeechToken] after getAzureSpeechToken: gMsToken=eyJhbGciOiJodHRwOi8vd3d3LnczLm9yZy8yMDAxLzA0L3htbGRzaWctbW9yZSNobWFjLXNoYTI1NiIsInR5cCI6IkpXVCJ9.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.R8Zfe0YyPhzpe-QITjGmbpJuSP1tpa5elFG0YYPVAyM [2018-08-28 18:29:07,999 INFO tts.py:123 initAudioService] Init audio service complete [2018-08-28 18:29:08,000 INFO tts.py:439 <module>] TTS init complete [2018-08-28 18:29:08,000 INFO qa.py:18 <module>] resourcesPath=/xxx/robotDemo/resources [2018-08-28 18:29:08,072 INFO qa.py:26 <module>] aiContext=<DialogueManager.Context object at 0x7f7eb0d6cbe0> [2018-08-28 18:29:08,197 INFO tts.py:131 getAzureSpeechToken] after getAzureSpeechToken: gMsToken=eyJhbGciOiJodHRwOi8vd3d3LnczLm9yZy8yMDAxLzA0L3htbGRzaWctbW9yZSNobWFjLXNoYTI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJ1cm46bXMuY29nbml0aXZlc2VydmljZXMiLCJleHAiOiIxNTM1NDUyNzQ3IiwicmVnaW9uIjoid2VzdHVzIiwic3Vic2NyaXB0aW9uLWlkIjoiNzU5ZWE5MjcyZjhiNDdhMzg5MWVkYzQ5ODhhMmFkNDEiLCJwcm9kdWN0LWlkIjoiU3BlZWNoU2VydmljZXMuUzAiLCJjb2duaXRpdmUtc2VydmljZXMtZW5kcG9pbnQiOiJodHRwczovL2FwaS5jb2duaXRpdmUubWljcm9zb2Z0LmNvbS9pbnRlcm5hbC92MS4wLyIsImF6dXJlLXJlc291cmNlLWlkIjoiL3N1YnNjcmlwdGlvbnMvZDA1NWNjMjMtZDY5OS00YjAyLTg0YzgtMDBlOTVmNzA4ZDFmL3Jlc291cmNlR3JvdXBzL1NwZWVjaC9wcm92aWRlcnMvTWljcm9zb2Z0LkNvZ25pdGl2ZVNlcnZpY2VzL2FjY291bnRzL0F6dXJlLVNwZWVjaCIsInNjb3BlIjoic3BlZWNoc2VydmljZXMiLCJhdWQiOiJ1cm46bXMuc3BlZWNoc2VydmljZXMud2VzdHVzIn0.R8Zfe0YyPhzpe-QITjGmbpJuSP1tpa5elFG0YYPVAyM [2018-08-28 18:29:08,198 INFO tts.py:123 initAudioService] Init audio service complete [2018-08-28 18:29:08,198 INFO tts.py:439 <module>] TTS init complete [2018-08-28 18:29:08,198 INFO qa.py:18 <module>] resourcesPath=/xxx/robotDemo/resources [2018-08-28 18:29:08,265 INFO qa.py:26 <module>] aiContext=<DialogueManager.Context object at 0x7f7eb0d69c50> [2018-08-28 18:29:08,434 INFO tts.py:131 getAzureSpeechToken] after getAzureSpeechToken: gMsToken=eyJhbGciOiJodHRwOi8vd3d3LnczLm9yZy8yMDAxLzA0L3htbGRzaWctbW9yZSNobWFjLXNoYTI1NiIsInR5cCI6IkpXVCJ9.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.xAr4O88waREMaTgzPOt4s7J8yLglU4nnSwmaz01qavc [2018-08-28 18:29:08,435 INFO tts.py:123 initAudioService] Init audio service complete [2018-08-28 18:29:08,436 INFO tts.py:439 <module>] TTS init complete [2018-08-28 18:29:08,436 INFO qa.py:18 <module>] resourcesPath=/xxx/robotDemo/resources [2018-08-28 18:29:08,474 INFO tts.py:131 getAzureSpeechToken] after getAzureSpeechToken: gMsToken=eyJhbGcixxx4nnSwmaz01qavc [2018-08-28 18:29:08,475 INFO tts.py:123 initAudioService] Init audio service complete [2018-08-28 18:29:08,476 INFO tts.py:439 <module>] TTS init complete [2018-08-28 18:29:08,476 INFO qa.py:18 <module>] resourcesPath=/xxx/robotDemo/resources [2018-08-28 18:29:08,496 INFO tts.py:131 getAzureSpeechToken] after getAzureSpeechToken: gMsToken=eyJhbGcixxx4s7J8yLglU4nnSwmaz01qavc [2018-08-28 18:29:08,497 INFO tts.py:123 initAudioService] Init audio service complete [2018-08-28 18:29:08,497 INFO tts.py:439 <module>] TTS init complete [2018-08-28 18:29:08,497 INFO qa.py:18 <module>] resourcesPath=/xxx/robotDemo/resources [2018-08-28 18:29:08,512 INFO qa.py:26 <module>] aiContext=<DialogueManager.Context object at 0x7f7eb0d68cc0> [2018-08-28 18:29:08,571 INFO qa.py:26 <module>] aiContext=<DialogueManager.Context object at 0x7f7eb0d68da0> [2018-08-28 18:29:08,603 INFO qa.py:26 <module>] aiContext=<DialogueManager.Context object at 0x7f7eb0d69d30> [2018-08-28 18:29:08,753 INFO tts.py:131 getAzureSpeechToken] after getAzureSpeechToken: gMsToken=None [2018-08-28 18:29:08,755 INFO tts.py:123 initAudioService] Init audio service complete [2018-08-28 18:29:08,755 INFO tts.py:439 <module>] TTS init complete [2018-08-28 18:29:08,755 INFO qa.py:18 <module>] resourcesPath=/xxx/robotDemo/resources [2018-08-28 18:29:08,822 INFO tts.py:131 getAzureSpeechToken] after getAzureSpeechToken: gMsToken=None [2018-08-28 18:29:08,823 INFO tts.py:123 initAudioService] Init audio service complete [2018-08-28 18:29:08,823 INFO tts.py:439 <module>] TTS init complete [2018-08-28 18:29:08,824 INFO qa.py:18 <module>] resourcesPath=/xxx/robotDemo/resources [2018-08-28 18:29:08,841 INFO qa.py:26 <module>] aiContext=<DialogueManager.Context object at 0x7f7eb0d69e80> [2018-08-28 18:29:08,893 INFO qa.py:26 <module>] aiContext=<DialogueManager.Context object at 0x7f7eb0d69ef0> [2018-08-28 18:29:08,998 INFO tts.py:131 getAzureSpeechToken] after getAzureSpeechToken: gMsToken=eyJhbGcixxxnSwmaz01qavc [2018-08-28 18:29:08,999 INFO tts.py:123 initAudioService] Init audio service complete [2018-08-28 18:29:09,000 INFO tts.py:439 <module>] TTS init complete [2018-08-28 18:29:09,000 INFO qa.py:18 <module>] resourcesPath=/xxx/robotDemo/resources [2018-08-28 18:29:09,129 INFO qa.py:26 <module>] aiContext=<DialogueManager.Context object at 0x7f7eb0d69f60> [2018-08-28 18:29:09,132 INFO tts.py:131 getAzureSpeechToken] after getAzureSpeechToken: gMsToken=None [2018-08-28 18:29:09,134 INFO tts.py:123 initAudioService] Init audio service complete </code>
可见问题：
（1）其中有些gMsToken是有正常的值，有些是None
-》导致后续代码中msTTS中reqHeaders的gMsToken是None，无法正常使用ms的tss
（2）另外：本身（多个实例，多个进程中）去获取多个ms的token，本身也是浪费和不好的做法：
获取新的token -》导致刚刚获取的旧的token失效了
-》所以希望是：
能够多个线程，全局共享一个token
-》而在合并兜底对话期间，借鉴到别人的代码中：
nlp/search/qa/iqa.py
<code>class Singleton(type):
"""
reference: https://stackoverflow.com/questions/31875/is-there-a-simple-elegant-way-to-define-singletons
"""
_instances = {}
def __call__(cls, *args, **kwargs):
if cls not in cls._instances:
cls._instances[cls] = super(
Singleton, cls).__call__(*args, **kwargs)
return cls._instances[cls]
class SearchBasedQA(metaclass=Singleton):
static_bt = None
...
</code>是可以通过singleton单例，去实现全局，多线程，多进程，共享一个变量或类的
所以后续去尝试去搞定：
Flask 部署后 多实例 全局变量的共享冲突/被覆盖的问题，
看看除了 单例singleton之外 是否还有其他更好的办法
不过还是先去看看：
【部分解决】Python中实现多线程或多进程中的单例singleton
然后优化后的，全局的，所有线程都共享一个实例，单例，去获取ms的azure的tts的token的代码是：
common/ThreadSafeSingleton.py
<code>import functools
import threading
thread_lock = threading.Lock()
print("ThreadSafeSingleton: thread_lock=%s" % thread_lock)
# refer: https://stackoverflow.com/questions/50566934/why-is-this-singleton-implementation-not-thread-safe
def synchronized(lock):
""" Synchronization decorator """
def wrapper(f):
print("synchronized: wrapper: f=%s, lock=%s" % (f, lock))
@functools.wraps(f)
def inner_wrapper(*args, **kw):
print("functools.wraps: args=%s, kw=%s" % (args, kw))
with lock:
return f(*args, **kw)
print("inner_wrapper%s" % inner_wrapper)
return inner_wrapper
return wrapper
# class Singleton(type):
class ThreadSafeSingleton(type):
_instances = {}
@synchronized(thread_lock)
def __call__(cls, *args, **kwargs):
print("synchronized __call__: cls=%s, args=%s, kwargs=%s" % (cls, args, kwargs))
print("cls._instances=%s" % cls._instances)
if cls not in cls._instances:
# cls._instances[cls] = super(Singleton, cls).__call__(*args, **kwargs)
cls._instances[cls] = super(ThreadSafeSingleton, cls).__call__(*args, **kwargs)
print("after added _instances: cls._instances=%s" % cls._instances)
return cls._instances[cls]
</code>然后在此期间，为了正常的能用上多线程的全局的单例的log，再去：
【已解决】把Flask中的app的logger改造成单例以避免循环引用和多次初始化Flask的实例
然后：
【部分解决】Python中实现多线程或多进程中的单例singleton
但是：
不过，对于此处的业务逻辑来说，倒是暂时可以继续试用的：
因为之前
gunicorn：多worker（9个），type时sync，导致多process
导致多个ms的token去初始化，其中部分（3）个token初始化有误
而现在改为：
gunicorn：单worker，type为gevent，的确是单process
虽然不知何故，flask的app中的log中还有3个process去初始化token，但是返回都是200，token都正常
-》后续调用ms的tts去文字转语音，暂时还是可以正常使用的。