def make_tests_delta(self):
"""Add tests delta between two latest test rounds to json_stats."""
logger.info(f'Generating tests delta for {self.model_name}.')
date = self.latest_round.date_str[:10]
test_name = None
test_data = self.latest_round.json_results[0].get('test_data')
if test_data:
test_name = test_data.get('name')
if not self.previous_round:
tests_delta = {
'applied_hashes_delta': {
'added': [],
'removed': []
}
}
else:
applied_delta = self.latest_round.find_delta_hashes(
self.previous_round, 'applied_tests')
tests_delta = {'applied_hashes_delta': applied_delta}
msg = _make_delta_msg(self.model_name,
'applied_tests',
applied_delta,
date,
test_corpus=self.test_corpus,
test_name=test_name)
if msg:
logger.info(msg['message'])
for mc_type in self.latest_round.mc_types_results:
if not self.previous_round or mc_type not in \
self.previous_round.mc_types_results:
tests_delta[mc_type] = {
'passed_hashes_delta': {
'added': [],
'removed': []
}
}
else:
passed_delta = self.latest_round.find_delta_hashes(
self.previous_round, 'passed_tests', mc_type=mc_type)
tests_delta[mc_type] = {'passed_hashes_delta': passed_delta}
msg = _make_delta_msg(self.model_name,
'passed_tests',
passed_delta,
date,
mc_type,
test_corpus=self.test_corpus,
test_name=test_name)
if msg:
logger.info(msg['message'])
self.json_stats['tests_delta'] = tests_delta
def test_delta_msg():
# No message when no delta
msg = _make_delta_msg('test', 'stmts', {'added': []}, '2020-01-01',
new_papers=2)
assert not msg
# No message with no new papers
msg = _make_delta_msg('test', 'stmts', {'added': [1234, 2345]},
'2020-01-01', new_papers=None)
assert not msg, msg
# New statements with new papers message
msg = _make_delta_msg('test', 'stmts', {'added': [1234, 2345]},
'2020-01-01', new_papers=5)
assert set(msg.keys()) == {
'message', 'start', 'middle', 'delta_part', 'url'}
assert msg['message'] == (
'Today I read 5 new publications and learned 2 new mechanisms. See '
'https://emmaa.indra.bio/dashboard/test?tab=model&date='
'2020-01-01#addedStmts for more details.'), msg['message']
# New applied tests message
msg = _make_delta_msg('test', 'applied_tests', {'added': [1234, 2345]},
'2020-01-01', test_corpus='simple_tests',
test_name='Simple tests corpus')
assert set(msg.keys()) == {
'message', 'start', 'middle', 'delta_part', 'url'}
assert msg['message'] == (
'Today I applied 2 new tests in the Simple tests corpus. '
'See https://emmaa.indra.bio/dashboard/test?'
'tab=tests&test_corpus=simple_tests&date=2020-01-01'
'#newAppliedTests for more details.'), msg['message']
# New passed tests message
msg = _make_delta_msg('test', 'passed_tests', {'added': [1234, 2345]},
'2020-01-01', 'pysb', test_corpus='simple_tests',
test_name='Simple tests corpus', is_tweet=True)
assert set(msg.keys()) == {
'message', 'start', 'middle', 'delta_part', 'url'}
assert msg['message'] == (
'Today I explained 2 new observations in the Simple tests '
'corpus with my @PySysBio model. See '
'https://emmaa.indra.bio/dashboard/test?tab=tests'
'&test_corpus=simple_tests&date=2020-01-01#newPassedTests '
'for more details.'), msg['message']
def make_model_delta(self):
"""Add model delta between two latest model states to json_stats."""
logger.info(f'Generating model delta for {self.model_name}.')
if not self.previous_round:
self.json_stats['model_delta'] = {
'statements_hashes_delta': {
'added': [],
'removed': []
}
}
else:
stmts_delta = self.latest_round.find_delta_hashes(
self.previous_round, 'statements')
self.json_stats['model_delta'] = {
'statements_hashes_delta': stmts_delta
}
msg = _make_delta_msg(self.model_name, 'stmts', stmts_delta,
self.latest_round.date_str[:10])
if msg:
logger.info(msg['message'])
def get_all_update_messages(deltas, is_tweet=False):
"""Get all messages for model deltas that can be further used in tweets and
email notifications.
Parameters
----------
deltas : dict
A dictionary containing deltas for a model and its test results
returned by get_model_deltas function.
is_tweet : bool
Whether messages are generated for Twitter (used to determine the
formatting of model types).
Returns
-------
msg_dicts : list[dict]
A list of individual message dictionaries that can be used for tweets
or email notifications.
"""
msg_dicts = []
model_name = deltas['model_name']
date = deltas['date']
# Model message
stmts_delta = deltas.get('stmts_delta')
new_papers = deltas.get('new_papers')
stmts_msg = _make_delta_msg(model_name,
'stmts',
stmts_delta,
date,
new_papers=new_papers,
is_tweet=is_tweet)
if stmts_msg:
logger.info(stmts_msg['message'])
msg_dicts.append(stmts_msg)
# Tests messages
for test_corpus, test_delta in deltas['tests'].items():
applied_delta = test_delta.get('applied_tests')
test_name = test_delta.get('name')
applied_msg = _make_delta_msg(model_name,
'applied_tests',
applied_delta,
date,
test_corpus=test_corpus,
test_name=test_name,
is_tweet=is_tweet)
if applied_msg:
logger.info(applied_msg['message'])
msg_dicts.append(applied_msg)
for mc_type in test_delta.get('passed', {}):
passed_delta = test_delta['passed'][mc_type]
passed_msg = _make_delta_msg(model_name,
'passed_tests',
passed_delta,
date,
mc_type,
test_corpus=test_corpus,
test_name=test_name,
is_tweet=is_tweet)
if passed_msg:
logger.info(passed_msg['message'])
msg_dicts.append(passed_msg)
return msg_dicts