def verify_response(response, expectation):
print(response)
if response.split(" ")[0] == "yeah" or response.split(" ")[
0] == "had" or response.split(" ")[0] == "fun" or response.split(
" ")[0] == "weekend" or response.split(" ")[0] == "went":
return False
accepted = []
if expectation == "action":
accepted = [
"Arts & Entertainment", "Books & Literature",
"Computers & Electronics", "Games", "Hobbies & Leisure",
"Home & Garden", "Jobs & Education", "Online Communities",
"People & Society", "Pets & Animals", "Shopping", "Sports",
"Travel"
]
classification = classify(response)
for (category, confidence) in classification.items():
try:
end = category[1:].index("/")
broad_category = category[1:end + 1]
except:
broad_category = category[1:]
print(broad_category)
if broad_category in accepted:
return True
return False
def test_classify(capsys):
with open(os.path.join(RESOURCES, 'query_text1.txt'), 'r') as f:
text = f.read()
classify_text_tutorial.classify(text)
out, err = capsys.readouterr()
assert 'category' in out
def test_classify(capsys):
with open(os.path.join(RESOURCES, 'query_text1.txt'), 'r') as f:
text = f.read()
classify_text_tutorial.classify(text)
out, err = capsys.readouterr()
assert 'category' in out
def test_classify(capsys):
with open(os.path.join(RESOURCES, "query_text1.txt"), "r") as f:
text = f.read()
classify_text_tutorial.classify(text)
out, err = capsys.readouterr()
assert "category" in out