python lambda中的keyerror-alexa技能

Question

构建我的第一个 AlexaSkill 并尝试使用 https://medium.com/crowdbotics/how-to-build-a-custom-amazon-alexa-skill-step-by-step-my-favorite-chess-player-dcc0edae53fb。我对国际象棋脚本进行了一些更改，而不是对其进行了一些更改，以侮辱某人的气味而不是玩家的生物。

如果玩家名不匹配则执行时，代码会正确流动，但是当玩家名与我在代码中的某个人匹配时，我会收到一个 keyerror。

错误详情

2021-01-24T14:53:02.721+00:00

复制“爸爸”：KeyError Traceback（最后一次调用）：文件 “/var/task/lambda_function.py”，第 24 行，在 lambda_handler 中 return intent_scheme(event) 文件“/var/task/lambda_function.py”，第 53 行，intent_scheme 返回 player_bio(event) 文件“/var/task/lambda_function.py”，第 69 行，在 player_bio 返回 output_json_builder_with_reprompt_and_card(Player_BIOGRAPHY[name.lower()], card_TEXT, card_TITLE, reprompt_MSG, False) KeyError: 'daddy'

执行代码

#------------------------------Part1--------------------------------
# In this part we define a list that contains the player names, and 
# a dictionary with player biographies
Player_LIST = ["John", "Horatio", "Daddy", "Mummy"]

Player_BIOGRAPHY = {"John":"peeee-you, Jasper smells like a stinky pair of week old socks that have been left out in the rain",

"Horatio":"Ughhhh, Horatio smells just like an elephant's bum that has been sweltering in the desert for a month",

"Mummy":"Mummy smells beautiful, like the scent of freshly cut roses or sweet perfume",

"Daddy":"Oh wow, the worst. He smells like a combination of burnt popcorn and rotting fish combined with sewer water and stinky armpits"}
#------------------------------Part2--------------------------------
# Here we define our Lambda function and configure what it does when 
# an event with a Launch, Intent and Session End Requests are sent. # The Lambda function responses to an event carrying a particular 
# Request are handled by functions such as on_launch(event) and 
# intent_scheme(event).
def lambda_handler(event, context):
    if event['session']['new']:
        on_start()
    if event['request']['type'] == "LaunchRequest":
        return on_launch(event)
    elif event['request']['type'] == "IntentRequest":
        return intent_scheme(event)
    elif event['request']['type'] == "SessionEndedRequest":
        return on_end()
#------------------------------Part3--------------------------------
# Here we define the Request handler functions
def on_start():
    print("Session Started.")

def on_launch(event):
    onlunch_MSG = "Hi, welcome to the Stinkbot Alexa Skill. My favourite players are: " + ', '.join(map(str, Player_LIST)) + ". "\
    "If you would like to hear more about a particular player, you could say for example: Does daddy smell?"
    reprompt_MSG = "Do you want to hear more about a particular player?"
    card_TEXT = "Pick a player."
    card_TITLE = "Choose player."
    return output_json_builder_with_reprompt_and_card(onlunch_MSG, card_TEXT, card_TITLE, reprompt_MSG, False)

def on_end():
    print("Session Ended.")
#-----------------------------Part3.1-------------------------------
# The intent_scheme(event) function handles the Intent Request. 
# Since we have a few different intents in our skill, we need to 
# configure what this function will do upon receiving a particular 
# intent. This can be done by introducing the functions which handle 
# each of the intents.
def intent_scheme(event):
    
    intent_name = event['request']['intent']['name']

    if intent_name == "playerBio":
        return player_bio(event)        
    elif intent_name in ["AMAZON.NoIntent", "AMAZON.StopIntent", "AMAZON.CancelIntent"]:
        return stop_the_skill(event)
    elif intent_name == "AMAZON.HelpIntent":
        return assistance(event)
    elif intent_name == "AMAZON.FallbackIntent":
        return fallback_call(event)
#---------------------------Part3.1.1-------------------------------
# Here we define the intent handler functions
def player_bio(event):
    name=event['request']['intent']['slots']['player']['value']
    player_list_lower=[w.lower() for w in Player_LIST]
    if name.lower() in player_list_lower:
        reprompt_MSG = "Do you want to hear more about a particular player?"
        card_TEXT = "You've picked " + name.lower()
        card_TITLE = "You've picked " + name.lower()
        return output_json_builder_with_reprompt_and_card(Player_BIOGRAPHY[name.lower()], card_TEXT, card_TITLE, reprompt_MSG, False)
    else:
        wrongname_MSG = "You haven't used the full name of a player. If you have forgotten which players you can pick say Help."
        reprompt_MSG = "Do you want to hear more about a particular player?"
        card_TEXT = "Use the full name."
        card_TITLE = "Wrong name."
        return output_json_builder_with_reprompt_and_card(wrongname_MSG, card_TEXT, card_TITLE, reprompt_MSG, False)
        
def stop_the_skill(event):
    stop_MSG = "Thank you. Bye!"
    reprompt_MSG = ""
    card_TEXT = "Bye."
    card_TITLE = "Bye Bye."
    return output_json_builder_with_reprompt_and_card(stop_MSG, card_TEXT, card_TITLE, reprompt_MSG, True)
    
def assistance(event):
    assistance_MSG = "You can choose among these players: " + ', '.join(map(str, Player_LIST)) + ". Be sure to use the full name when asking about the player."
    reprompt_MSG = "Do you want to hear more about a particular player?"
    card_TEXT = "You've asked for help."
    card_TITLE = "Help"
    return output_json_builder_with_reprompt_and_card(assistance_MSG, card_TEXT, card_TITLE, reprompt_MSG, False)

def fallback_call(event):
    fallback_MSG = "I can't help you with that, try rephrasing the question or ask for help by saying HELP."
    reprompt_MSG = "Do you want to hear more about a particular player?"
    card_TEXT = "You've asked a wrong question."
    card_TITLE = "Wrong question."
    return output_json_builder_with_reprompt_and_card(fallback_MSG, card_TEXT, card_TITLE, reprompt_MSG, False)
#------------------------------Part4--------------------------------
# The response of our Lambda function should be in a json format. 
# That is why in this part of the code we define the functions which 
# will build the response in the requested format. These functions
# are used by both the intent handlers and the request handlers to 
# build the output.
def plain_text_builder(text_body):
    text_dict = {}
    text_dict['type'] = 'PlainText'
    text_dict['text'] = text_body
    return text_dict

def reprompt_builder(repr_text):
    reprompt_dict = {}
    reprompt_dict['outputSpeech'] = plain_text_builder(repr_text)
    return reprompt_dict
    
def card_builder(c_text, c_title):
    card_dict = {}
    card_dict['type'] = "Simple"
    card_dict['title'] = c_title
    card_dict['content'] = c_text
    return card_dict    

def response_field_builder_with_reprompt_and_card(outputSpeach_text, card_text, card_title, reprompt_text, value):
    speech_dict = {}
    speech_dict['outputSpeech'] = plain_text_builder(outputSpeach_text)
    speech_dict['card'] = card_builder(card_text, card_title)
    speech_dict['reprompt'] = reprompt_builder(reprompt_text)
    speech_dict['shouldEndSession'] = value
    return speech_dict

def output_json_builder_with_reprompt_and_card(outputSpeach_text, card_text, card_title, reprompt_text, value):
    response_dict = {}
    response_dict['version'] = '1.0'
    response_dict['response'] = response_field_builder_with_reprompt_and_card(outputSpeach_text, card_text, card_title, reprompt_text, value)
    return response_dict

Answer 1

在 player_bio 函数中，您返回 return output_json_builder_with_reprompt_and_card(Player_BIOGRAPHY[name.lower()], card_TEXT, card_TITLE, reprompt_MSG, False)。您正在使用 name.lower()（即小写字符串）从 Player_BIOGRAPHY 字典中获取项目，但该字典中的键是标题大小写的。将name.lower() 替换为name.title()