def get_expanded_card_data(self, project: scoring_base.ScoringProject) \
-> network_pb2.ContactLeads:
"""Retrieve data for the expanded card."""
contact_leads = self._list_contact_leads(project)
sorted_leads = sorted(contact_leads,
key=lambda l: (-len(l.filters), random.random()))
return network_pb2.ContactLeads(leads=[
network_pb2.ContactLead(
name=project.populate_template(
project.translate_string(template.name)),
email_example=project.populate_template(
project.translate_string(template.email_template)),
contact_tip=project.translate_string(template.contact_tip))
for template in sorted_leads
])
def list_jobboards(
project: scoring_base.ScoringProject
) -> Iterator[jobboard_pb2.JobBoard]:
"""List all job boards for this project."""
all_job_boards = _JOBBOARDS.get_collection(project.database)
for job_board_template in scoring_base.filter_using_score(
all_job_boards, lambda j: j.filters, project):
job_board = jobboard_pb2.JobBoard()
job_board.CopyFrom(job_board_template)
job_board.link = project.populate_template(job_board.link)
yield job_board
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute a score for the given ScoringProject."""
reasons = []
if project.details.area_type < geo_pb2.COUNTRY:
return scoring_base.NULL_EXPLAINED_SCORE
reasons.append(
project.populate_template(
project.translate_static_string(
'vous nous avez dit être prêt%eFeminine à déménager')))
local_stats = project.local_diagnosis()
if local_stats.imt.yearly_avg_offers_per_10_candidates and \
local_stats.num_less_stressful_departements:
reasons.append(
project.translate_static_string(
"il y a beaucoup plus d'offres par habitants dans d'autres villes"
))
return scoring_base.ExplainedScore(2, reasons)
return scoring_base.NULL_EXPLAINED_SCORE
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute a score for the given ScoringProject."""
close_jobs = self.get_close_jobs(project)
search_since_nb_months = round(project.get_search_length_now())
score_modifier = 0
reasons: list[str] = []
if len(close_jobs.close_jobs) + len(close_jobs.evolution_jobs) < 2:
return scoring_base.NULL_EXPLAINED_SCORE
# TODO(cyrille): Make this more robust.
force_in_stuck_market = None
# TODO(cyrille): Rather use market_stress to avoid depending on diagnostic to be computed.
if project.details.diagnostic.category_id == 'stuck-market':
force_in_stuck_market = scoring_base.ExplainedScore(1, reasons)
if project.get_user_age() >= 45:
return force_in_stuck_market or scoring_base.NULL_EXPLAINED_SCORE
if project.details.passionate_level >= project_pb2.PASSIONATING_JOB:
score_modifier = -1
else:
reasons.append(
project.populate_template(
project.translate_static_string(
"vous n'êtes pas trop attaché%eFeminine à votre métier"
)))
if project.details.job_search_has_not_started or search_since_nb_months <= 1:
return scoring_base.ExplainedScore(2 + score_modifier, reasons)
reasons = [
project.translate_static_string(
'vous cherchez depuis {} mois').format(search_since_nb_months)
]
if search_since_nb_months >= 12:
return scoring_base.ExplainedScore(3, reasons)
if search_since_nb_months >= 9:
return scoring_base.ExplainedScore(2, reasons)
if search_since_nb_months >= 6:
return scoring_base.ExplainedScore(1, reasons)
return force_in_stuck_market or scoring_base.NULL_EXPLAINED_SCORE
