def weather(text):
print("weather")
'''
Tests if the text is about weather and identifies any time words
@param text: the text to analyze
@return: a dictionary, format is specified at the top of the file
'''
output = {"test_result": False, "info": {}}
#posessive determiner and noun phrase
#how to detect longer city names (san francisco)
#how to detect city, state format or city, country format
expression = r"""
NP: {<DT|JJ|NN.*>*<NN.*>}
POS_DT: {<NN.*><POS><NN.*>*}
"""
#NP: {<DT|JJ|NN.*>+}
#the keywords we want to detect
target_words = utils.load_words("data/weather_topic_words.txt")
time_words = utils.load_words("data/weather_time_words.txt")
chunks, keywords = nlp_util.match_regex_and_keywords(
text, expression, target_words)
print(chunks)
#if we found a weather related phrase
if len(chunks) > 0:
output["test_result"] = True
output["info"]["keywords"] = keywords
return output
def weather(text, parse_location=True):
# print("weather")
'''
Tests if the text is about weather and identifies any time words
@param text: the text to analyze
@param parse_location: whether to set the location in the info field
of the dictionary. This should be set to False when using
chatterbot logic adapters since location would otherwise be parsed
twice.
@return: a dictionary, format is specified at the top of the file
'''
output = {"test_result": False, "text": text, "info": {}}
#posessive determiner and noun phrase
expression = r"""
NP: {<DT|JJ|NN.*>*<NN.*>}
POS_DT: {<NN.*><POS><NN.*>*}
"""
#NP: {<DT|JJ|NN.*>+}
#the keywords we want to detect
target_words = utils.load_words("data/weather_topic_words.txt")
time_words = utils.load_words("data/weather_time_words.txt")
chunks, keywords = nlp_util.match_regex_and_keywords(text,
expression,
keywords=target_words)
# print("Chunks: ", chunks)
#if we found a weather related phrase
if len(chunks) > 0 and chunks[0].label() != "S":
output["test_result"] = True
output["info"]["keywords"] = keywords
if parse_location:
#attempt to find a location
location = nlp_util.search_for_location(text)
output["info"]["location"] = {}
if len(location) > 0:
output["info"]["location"]["exists"] = True
output["info"]["location"]["name"] = location
else:
output["info"]["location"]["exists"] = False
output["info"]["location"]["name"] = ""
# print("Weather output: ", output)
return output
def restaurant(text):
'''
Checks if the text is about restaurants
@param text: the text to analyze
@return: a dictionary, format is specified at the top of the file
'''
output = {"test_result": False, "info": {}}
# trying to remove all the non-alphabet characters in the string
regex = re.compile('([^\s\w]|_)+')
text = regex.sub('', text)
target_words = utils.load_words("data/restaurant_topic_words.txt")
for word in target_words:
if word == "eat":
word = " eat"
if word in text:
output["test_result"] = True
if output["test_result"] == False:
return output
return output
def restaurant(text, parse_location=True):
'''
Checks if the text is about restaurants
@param text: the text to analyze
@param parse_location: whether to set the location in the info field
of the dictionary. This should be set to False when using
chatterbot logic adapters since location would otherwise be parsed
twice.
@return: a dictionary, format is specified at the top of the file
'''
output = {"test_result": False, "text": text, "info": {}}
# trying to remove all the non-alphabet characters in the string
regex = re.compile('([^\s\w]|_)+')
text = regex.sub('', text)
target_words = utils.load_words("data/restaurant_topic_words.txt")
for word in target_words:
if word == "eat":
word = " eat"
if word in text:
output["test_result"] = True
if output["test_result"] == False:
return output
if parse_location:
#attempt to find a location
location = nlp_util.search_for_location(text)
output["info"]["location"] = {}
if len(location) > 0:
output["info"]["location"]["exists"] = True
output["info"]["location"]["name"] = location
else:
output["info"]["location"]["exists"] = False
output["info"]["location"]["name"] = ""
return output