def test_my_guess_honors_max_length_by_truncating_longest():
y = [
deploy.Prediction(2, '567890', 0.024),
deploy.Prediction(7, '012', 0.046),
]
# before truncation:
# '\n2. 567890 2.40%\n7. 012 4.60%'
max_length = 26
reply = messages.Messages.my_guess(y, preface='', max_length=max_length)
assert reply == '\n2. 567 2.40%\n7. 012 4.60%'
assert len(reply) <= max_length
def test_my_guess_honors_max_length_by_truncating_all():
y = [
deploy.Prediction(2, '567', 0.091),
deploy.Prediction(4, '789', 0.012),
]
# before truncation:
# '\n2. 567 9.10%\n4. 789 1.20%'
max_length = 22
reply = messages.Messages.my_guess(y, preface='', max_length=max_length)
assert reply == '\n2. 5 9.10%\n4. 7 1.20%'
assert len(reply) <= max_length
def my_guess(cls, y, top_n=3, max_length=None, preface="Probable Anime:"):
if not len(y):
return cls.unknown_image()
pred_lines = []
max_category_length = 0
max_category_length_index = 0
for i, pred in enumerate(y[:top_n]):
pred_lines.append(
deploy.Prediction(
"{}.".format(pred.rank),
pred.category,
"{:.2%}".format(pred.probability),
))
if max_category_length < len(pred.category):
max_category_length_index = i
max_category_length = len(pred.category)
newline_count = len(pred_lines)
pred_length = sum(
sum(map(len, pred)) + len(pred) - 1 for pred in pred_lines)
current_length = len(preface) + newline_count + pred_length
# truncate category name(s) if needed
if max_length is not None and current_length > max_length:
lengthy_pred = pred_lines[max_category_length_index]
excess_length = current_length - max_length
# don't penalize the longest category if it's going to be truncated too much
if len(lengthy_pred.category) * 0.5 < excess_length:
subtract_from_everyone_length = int(
math.ceil(excess_length / len(pred_lines)))
pred_lines = [
deploy.Prediction(
pred.rank,
pred.category[:-subtract_from_everyone_length],
pred.probability) for pred in pred_lines
]
else:
shortened_pred = deploy.Prediction(
lengthy_pred.rank, lengthy_pred.category[:-excess_length],
lengthy_pred.probability)
pred_lines[max_category_length_index] = shortened_pred
reply = "{}\n{}".format(
preface, "\n".join(" ".join(pred) for pred in pred_lines))
return reply[:max_length] if max_length is not None else reply
def classify(self, **params):
try:
r = requests.get(self._base_url, params=params, timeout=60).json()
if 'error' in r:
raise exc.RemoteError(r['error'])
return map(lambda guess: deploy.Prediction(**guess), r['y'])
except requests.exceptions.Timeout:
raise exc.TimeoutError
def classify(self, *args, **kwargs):
message = at_random(
"I hope a mock message like this won't get caught by Twitter's spam filter",
"But I must explain to you how all this mistaken idea was born",
"At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis",
"Excepteur sint occaecat cupidatat non proident",
)
return [deploy.Prediction(1, message, 100)]