def _make_strategy(
project: scoring.ScoringProject, module: strategy_pb2.StrategyModule,
advice_scores: dict[str, float]) -> Optional[strategy_pb2.Strategy]:
if module.is_for_alpha and not project.features_enabled.alpha:
return None
score = project.score(module.trigger_scoring_model)
if not score:
return None
score = min(score * 100 / 3, 100 - project.details.diagnostic.overall_score)
pieces_of_advice = []
for advice in module.pieces_of_advice:
user_advice_id = next((a for a in advice_scores if a.startswith(advice.advice_id)), None)
if not user_advice_id:
if advice.is_required:
# A necessary advice is missing, we drop everything.
return None
continue
pieces_of_advice.append(strategy_pb2.StrategyAdvice(
advice_id=user_advice_id,
teaser=project.populate_template(project.translate_string(advice.teaser_template)),
why=project.populate_template(project.translate_string(advice.why_template))))
if _SPECIFIC_TO_JOB_ADVICE_ID in advice_scores:
specific_to_job_config = project.specific_to_job_advice_config()
if specific_to_job_config and module.strategy_id in specific_to_job_config.strategy_ids:
pieces_of_advice.append(strategy_pb2.StrategyAdvice(
advice_id=_SPECIFIC_TO_JOB_ADVICE_ID))
if not pieces_of_advice and not module.external_url_template:
# Don't want to show a strategy without any advice modules.
return None
strategy = project.details.strategies.add(
description=project.populate_template(project.translate_airtable_string(
'strategyModules', module.strategy_id, 'description_template',
hint=module.description_template)),
score=int(score),
is_secondary=score <= 10,
title=project.translate_airtable_string(
'strategyModules', module.strategy_id, 'title', hint=module.title),
header=project.populate_template(project.translate_airtable_string(
'strategyModules', module.strategy_id, 'header_template',
hint=module.header_template)),
strategy_id=module.strategy_id,
external_url=project.populate_template(module.external_url_template),
infinitive_title=project.translate_airtable_string(
'strategyModules', module.strategy_id, 'infinitive_title',
hint=module.infinitive_title),
action_ids=module.action_ids,
description_speech=project.populate_template(project.translate_airtable_string(
'strategyModules', module.strategy_id, 'description_speech',
hint=module.description_speech, is_genderized=True)),
)
if strategy.external_url and pieces_of_advice:
logging.error(
'Strategy %s has both an external URL and some pieces of advice:\n%s',
strategy.strategy_id, ', '.join(a.advice_id for a in pieces_of_advice))
# Sort found pieces of advice by descending score.
pieces_of_advice.sort(key=lambda a: advice_scores[a.advice_id], reverse=True)
strategy.pieces_of_advice.extend(pieces_of_advice)
return strategy
def _compute_diagnostic_topic_score(
topic: 'diagnostic_pb2.DiagnosticTopic',
scorers: Iterable[diagnostic_pb2.DiagnosticSubmetricScorer],
scoring_project: scoring.ScoringProject) \
-> Optional[diagnostic_pb2.SubDiagnostic]:
"""Create the score for a given diagnostic submetric on a given project.
Args:
topic: the diagnostic topic we wish to evaluate
scorers: a list of scorers for the given topic, with a weight on each.
scoring_project: the project we want to score
Returns:
the populated subdiagnostic protobuf.
"""
topic_score = 0.
topic_weight = 0.
sub_diagnostic = diagnostic_pb2.SubDiagnostic(topic=topic)
for scorer in scorers:
try:
score = scoring_project.score(scorer.trigger_scoring_model)
except scoring.NotEnoughDataException:
continue
# Use default weight of 1
weight = scorer.weight or 1
weighted_score = score * weight
topic_score += weighted_score
topic_weight += weight
if not topic_weight:
return None
sub_diagnostic.score = round(topic_score / topic_weight * 100 / 3)
return sub_diagnostic
def _make_strategy(
project: scoring.ScoringProject, module: strategy_pb2.StrategyModule,
advice_scores: Dict[str, float]) -> Optional[strategy_pb2.Strategy]:
score = project.score(module.trigger_scoring_model)
if not score:
return None
score = min(score * 100 / 3,
100 - project.details.diagnostic.overall_score)
pieces_of_advice = []
for advice in module.pieces_of_advice:
user_advice_id = next(
(a for a in advice_scores if a.startswith(advice.advice_id)), None)
if not user_advice_id:
if advice.is_required:
# A necessary advice is missing, we drop everything.
return None
continue
pieces_of_advice.append(
strategy_pb2.StrategyAdvice(
advice_id=user_advice_id,
teaser=project.populate_template(
project.translate_string(advice.teaser_template)),
header=project.populate_template(
project.translate_string(advice.header_template))))
if _SPECIFIC_TO_JOB_ADVICE_ID in advice_scores:
specific_to_job_config = project.specific_to_job_advice_config()
if specific_to_job_config and module.strategy_id in specific_to_job_config.strategy_ids:
pieces_of_advice.append(
strategy_pb2.StrategyAdvice(
advice_id=_SPECIFIC_TO_JOB_ADVICE_ID))
if not pieces_of_advice:
# Don't want to show a strategy without any advice modules.
return None
strategy = project.details.strategies.add(
description=project.populate_template(
project.translate_string(module.description_template)),
score=int(score),
is_secondary=score <= 10,
title=project.translate_string(module.title),
header=project.populate_template(
project.translate_string(module.header_template)),
strategy_id=module.strategy_id)
# Sort found pieces of advice by descending score.
pieces_of_advice.sort(key=lambda a: advice_scores[a.advice_id],
reverse=True)
strategy.pieces_of_advice.extend(pieces_of_advice)
return strategy
def _get_relevance_from_its_model(
main_challenge: diagnostic_pb2.DiagnosticMainChallenge,
project: scoring.ScoringProject,
has_missing_fields: bool,
relevant_should_be_neutral: bool) \
-> 'diagnostic_pb2.MainChallengeRelevance.V':
if main_challenge.relevance_scoring_model:
relevance_score = project.score(main_challenge.relevance_scoring_model)
if relevance_score <= 0:
return diagnostic_pb2.NOT_RELEVANT
if relevance_score >= 3 and not relevant_should_be_neutral:
return diagnostic_pb2.RELEVANT_AND_GOOD
return diagnostic_pb2.NEUTRAL_RELEVANCE
if has_missing_fields:
return diagnostic_pb2.NEUTRAL_RELEVANCE
return diagnostic_pb2.NEUTRAL_RELEVANCE if relevant_should_be_neutral else \
diagnostic_pb2.RELEVANT_AND_GOOD
def _get_relevance_from_its_model(
category: diagnostic_pb2.DiagnosticCategory,
project: scoring.ScoringProject,
has_missing_fields: bool) \
-> diagnostic_pb2.CategoryRelevance:
if category.relevance_scoring_model:
relevance_score = project.score(category.relevance_scoring_model)
if relevance_score <= 0:
return diagnostic_pb2.NOT_RELEVANT
if relevance_score >= 3:
return diagnostic_pb2.RELEVANT_AND_GOOD
return diagnostic_pb2.NEUTRAL_RELEVANCE
try:
return _CATEGORIES_RELEVANCE_GETTERS[category.category_id](project)
except KeyError:
if has_missing_fields:
return diagnostic_pb2.NEUTRAL_RELEVANCE
return diagnostic_pb2.RELEVANT_AND_GOOD