def score_and_explain(self, project):
"""Compute a score for the given ScoringProject."""
discrimination_reason = project.translate_string(
'vous nous avez dit que les employeurs ne '
'vous donnent pas votre chance')
relevant_frustrations = {
user_pb2.AGE_DISCRIMINATION:
discrimination_reason,
user_pb2.ATYPIC_PROFILE:
discrimination_reason,
user_pb2.NO_OFFERS:
project.translate_string(
"vous nous avez dit ne pas trouver d'offres correspondant "
'à vos critères'),
user_pb2.SEX_DISCRIMINATION:
discrimination_reason,
}
its_easy = project.translate_string(
"c'est plus facile à faire qu'on peut le croire")
# TODO(pascal): Make this dynamic if we get data for after Feb 2018.
if project.now >= datetime.datetime(2018, 2, 7):
return scoring_base.NULL_EXPLAINED_SCORE
frustration_reasons = {
relevant_frustrations[frustration]
for frustration in project.user_profile.frustrations
if frustration in relevant_frustrations
}
if frustration_reasons or project.get_search_length_now() > 3:
return scoring_base.ExplainedScore(
2,
list(frustration_reasons) or [its_easy])
return scoring_base.ExplainedScore(1, [its_easy])
def score_and_explain(self, project):
"""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 = []
if len(close_jobs.close_jobs) + len(close_jobs.evolution_jobs) < 2:
return scoring_base.NULL_EXPLAINED_SCORE
if project.get_user_age() >= 45:
return scoring_base.NULL_EXPLAINED_SCORE
if project.details.passionate_level >= project_pb2.PASSIONATING_JOB:
score_modifier = -1
else:
reasons.append(
project.translate_string(
"vous n'êtes pas trop attaché 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_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 scoring_base.NULL_EXPLAINED_SCORE
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute a score for the given ScoringProject."""
first_modes = project.get_fap_modes()
if job_pb2.SPONTANEOUS_APPLICATION in first_modes:
return scoring_base.ExplainedScore(3, [
project.translate_static_string(
"c'est le canal de recrutement n°1 pour votre métier")
])
# In the category missing-diploma, we always have the alternance strategy which requires
# spontaneous application data.
if project.details.diagnostic.category_id == 'missing-diploma':
return scoring_base.ExplainedScore(2, [
project.translate_static_string(
"c'est le meilleur moyen de trouver un contrat en alternance"
)
])
second_modes = project.get_fap_modes(rank='second')
if job_pb2.SPONTANEOUS_APPLICATION in second_modes:
return scoring_base.ExplainedScore(2, [
project.translate_static_string(
"c'est un des meilleurs canaux de recrutement pour votre métier"
)
])
if project.details.diagnostic.category_id == 'bravo' and \
user_profile_pb2.NO_OFFERS in project.user_profile.frustrations:
return scoring_base.ExplainedScore(2, [
project.translate_static_string(
"vous nous avez dit ne pas trouver assez d'offres.")
])
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.translate_string(
"vous n'êtes pas trop attaché 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_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
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute a score for the given ScoringProject."""
local_jobbing = self.get_local_jobbing(project)
if len(local_jobbing.reorient_jobbing_jobs) < 2:
return scoring_base.NULL_EXPLAINED_SCORE
score_modifier = 0
reasons: list[str] = []
if project.details.passionate_level == project_pb2.LIFE_GOAL_JOB:
score_modifier = -2
if project.job_group_info().growth_2012_2022 < .1:
score_modifier = -1
if score_modifier >= 0:
reasons.append(
project.translate_static_string(
'votre métier ne vous tient pas trop à cœur'))
if project.user_profile.highest_degree <= job_pb2.CAP_BEP:
return scoring_base.ExplainedScore(3 + score_modifier, reasons)
if project.user_profile.highest_degree <= job_pb2.BAC_BACPRO:
return scoring_base.ExplainedScore(max(2 + score_modifier, 1),
reasons)
if project.user_profile.highest_degree <= job_pb2.BTS_DUT_DEUG:
return scoring_base.ExplainedScore(1, 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."""
associations = self.list_associations(project)
search_length_reason = project.translate_static_string(
"vous nous avez dit que vous êtes en recherche d'emploi "
'depuis %jobSearchLengthAtCreation')
if not associations:
return scoring_base.NULL_EXPLAINED_SCORE
if user_profile_pb2.MOTIVATION in project.user_profile.frustrations:
return scoring_base.ExplainedScore(3, [
project.translate_static_string(
'vous nous avez dit avoir du mal à garder votre ' +
'motivation au top')
])
if len(associations) >= 3 and project.get_search_length_at_creation(
) >= 6:
return scoring_base.ExplainedScore(3, [search_length_reason])
if project.get_search_length_at_creation() >= 12:
return scoring_base.ExplainedScore(3, [search_length_reason])
return scoring_base.ExplainedScore(2, [
project.translate_static_string(
"l'accompagnement humain peut beaucoup vous apporter")
])
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
if project.details.diagnostic.category_id == 'enhance-methods-to-interview':
return scoring_base.ExplainedScore(3, [])
reasons = [
project.translate_static_string(
"vous nous avez dit avoir passé beaucoup d'entretiens sans succès"
)
]
if project.details.total_interview_count < 0:
num_interviews = 0
elif project.details.total_interview_count > 0:
num_interviews = project.details.total_interview_count
else:
num_interviews = _NUM_INTERVIEWS.get(
project.details.total_interviews_estimate, 0)
job_search_length_months = project.get_search_length_at_creation()
if job_search_length_months < 1:
job_search_length_months = 1
num_monthly_interviews = num_interviews / job_search_length_months
if num_monthly_interviews > _max_monthly_interviews(project):
return scoring_base.ExplainedScore(3, reasons)
# Whatever the number of month of search, trigger 3 if the user did more than 5 interviews:
if num_interviews >= _NUM_INTERVIEWS[project_pb2.DECENT_AMOUNT]:
return scoring_base.ExplainedScore(3, reasons)
if project.details.diagnostic.category_id == 'bravo':
return scoring_base.ExplainedScore(1, [])
return scoring_base.NULL_EXPLAINED_SCORE
def score_and_explain(self, project):
"""Compute a score for the given ScoringProject."""
missions = self.volunteering_missions(project).missions
if not missions:
return scoring_base.NULL_EXPLAINED_SCORE
if project.get_search_length_at_creation() < 9:
return scoring_base.ExplainedScore(1, [])
return scoring_base.ExplainedScore(2, [
'ça fait du bien de garder une activité sociale dans une recherche longue'
])
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute a score for the given ScoringProject."""
frustration_reasons = list(self._get_frustrations_reasons(project))
its_easy = project.translate_static_string(
"c'est plus facile à faire qu'on peut le croire")
if frustration_reasons or project.get_search_length_now() > 3:
return scoring_base.ExplainedScore(
2, frustration_reasons or [its_easy])
return scoring_base.ExplainedScore(1, [its_easy])
def score_and_explain(self, project):
"""Compute a score for the given ScoringProject."""
application_modes = project.job_group_info().application_modes.values()
first_modes = set(fap_modes.modes[0].mode for fap_modes in application_modes)
first_modes.discard(job_pb2.UNDEFINED_APPLICATION_MODE)
if first_modes == {job_pb2.PERSONAL_OR_PROFESSIONAL_CONTACTS}:
return scoring_base.ExplainedScore(2, [project.translate_string(
'les embauches se font surtout par les contacts personnels ou professionnels dans'
' votre métier')])
return scoring_base.ExplainedScore(1, [project.translate_string(
"c'est un bon moyen d'étendre votre réseau")])
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute a score for the given ScoringProject."""
if (self._num_interviews_increase(project) >= 2 and
project.details.job_search_length_months <= 6):
return scoring_base.ExplainedScore(3, [project.translate_string(
"nous pensons qu'avec votre profil vous pourriez "
"décrocher plus d'entretiens")])
if project.details.diagnostic.category_id == 'bravo' and \
user_pb2.RESUME in project.user_profile.frustrations:
return scoring_base.ExplainedScore(1, [project.translate_string(
'vous nous avez dit avoir du mal à rédiger votre CV')])
return scoring_base.NULL_EXPLAINED_SCORE
def score_and_explain(self, project):
"""Compute a score for the given ScoringProject."""
nearby_cities = self.list_nearby_cities(project)
if not nearby_cities:
return scoring_base.NULL_EXPLAINED_SCORE
if project.details.mobility.area_type > geo_pb2.CITY and \
any(c.relative_offers_per_inhabitant >= 2 for c in nearby_cities):
return scoring_base.ExplainedScore(
3, ["il y a beaucoup plus d'offres par habitants dans d'autres villes"])
return scoring_base.ExplainedScore(
2, ["il est toujours bon d'avoir une idée des offres dans les autres villes"])
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute a score for the given ScoringProject."""
if project.details.network_estimate != self._network_level:
return scoring_base.NULL_EXPLAINED_SCORE
first_modes = project.get_fap_modes()
first_modes.discard(job_pb2.UNDEFINED_APPLICATION_MODE)
if first_modes == {job_pb2.PERSONAL_OR_PROFESSIONAL_CONTACTS}:
return scoring_base.ExplainedScore(3, [
'le réseau est le canal n°1 pour trouver un métier %inDomain'
])
return scoring_base.ExplainedScore(2, [])
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute a score for the given ScoringProject."""
if project.details.weekly_applications_estimate <= project_pb2.LESS_THAN_2 or \
project.details.job_search_length_months < 2:
return scoring_base.ExplainedScore(3, [project.translate_string(
'vous nous avez dit que vous en êtes au début de '
'vos candidatures')])
if project.details.diagnostic.category_id == 'bravo' and \
user_pb2.RESUME in project.user_profile.frustrations:
return scoring_base.ExplainedScore(1, [project.translate_string(
'vous nous avez dit avoir du mal à rédiger votre CV')])
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."""
for opened_strategy in project.details.opened_strategies:
if opened_strategy.strategy_id in self._strategies:
return scoring_base.ExplainedScore(
3, ['vous avez démarré une stratégie qui correspond'])
for strategy in project.details.strategies:
if strategy.strategy_id in self._strategies:
return scoring_base.ExplainedScore(2, [
"c'est une stratégie qui pourrait marcher dans votre cas"
])
return scoring_base.ExplainedScore(1, [])
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute the score for a given project and explains it.
Requirements are:
- being between 16 and 30 y.o if having a handicap or between 16 and 25 otherwise
- having low or no experience (intern maximum)
"""
age = project.get_user_age()
seniority = project.details.seniority
reasons: list[str] = []
if age < 16 or seniority > project_pb2.INTERN:
return scoring_base.NULL_EXPLAINED_SCORE
if project.user_profile.has_handicap and age <= 30:
reasons = [
project.translate_static_string('vous avez entre 16 et 30 ans')
]
if age <= 25:
reasons = [
project.translate_static_string('vous avez entre 16 et 25 ans')
]
if not reasons:
return scoring_base.NULL_EXPLAINED_SCORE
return scoring_base.ExplainedScore(2, reasons)
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute a score for the given ScoringProject."""
reasons: List[str] = []
# For now we just match for people willing to move to the whole country.
# There might be cases where we should be able to recommend to people who want to move to
# their own region, but it would add complexity to find them.
is_not_ready_to_move = project.details.area_type < geo_pb2.COUNTRY
is_not_single = project.user_profile.family_situation != user_pb2.SINGLE
has_advanced_degree = project.user_profile.highest_degree >= job_pb2.LICENCE_MAITRISE
is_not_young = project.get_user_age() > 30
looks_only_for_cdi = project.details.employment_types == [job_pb2.CDI]
if (is_not_ready_to_move or is_not_young or is_not_single
or has_advanced_degree or looks_only_for_cdi):
return scoring_base.NULL_EXPLAINED_SCORE
reasons.append(
project.translate_string(
'vous nous avez dit être prêt%eFeminine à déménager'))
reasons.append(
project.translate_string('vous êtes disponible familialement'))
if len(self._get_seasonal_departements(project).departement_stats) > 1:
reasons.append(
project.translate_string(
"il y a plus d'offres saisonnières par habitants dans d'autres villes"
))
return scoring_base.ExplainedScore(2, reasons)
return scoring_base.NULL_EXPLAINED_SCORE
def _score_and_explain_after_filters(project):
"""A helper function to give a score and an explanation for all advices in the module,
once some prerequisite filters have been met.
"""
if project.user_profile.has_car_driving_license != user_pb2.FALSE:
return scoring_base.NULL_EXPLAINED_SCORE
reasons = []
license_required = next(
(license.percent_required
for license in project.job_group_info().requirements.driving_licenses
if license.driving_license == job_pb2.CAR), 0)
if license_required:
reasons.append(
project.translate_string(
'le permis est important dans votre métier'))
score_modifier = 0
if _license_helps_mobility(project.details.mobility):
reasons.append(
project.translate_string('le permis augmenterait votre mobilité'))
score_modifier = 1
if not reasons:
return scoring_base.NULL_EXPLAINED_SCORE
score = min(
3, score_modifier +
(3 if license_required > 30 else
2 if license_required > 10 else 1 if license_required else 0))
return scoring_base.ExplainedScore(score, reasons)
def _score_and_explain_after_filters(project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""A helper function to give a score and an explanation for all advices in the module,
once some prerequisite filters have been met.
"""
if project.user_profile.has_car_driving_license != boolean_pb2.FALSE:
return scoring_base.NULL_EXPLAINED_SCORE
reasons = []
license_required = next(
(license.percent_required
for license in project.job_group_info().requirements.driving_licenses
if license.driving_license == job_pb2.CAR), 0)
if license_required:
reasons.append(
project.translate_static_string(
'le permis est important dans votre métier'))
score_modifier = 0
if _license_helps_mobility(project.details):
reasons.append(
project.translate_static_string(
'le permis augmenterait votre mobilité'))
score_modifier = 1
if not reasons:
return scoring_base.NULL_EXPLAINED_SCORE
score = min(
3,
score_modifier + (
# Example at 80% is civil engineer F1106.
3 if license_required > 80 else
# Example at 67% is translator E1108.
2 if license_required > 67 else
# Example at 50% is chiropractor J1408.
1 if license_required > 50 else 0))
return scoring_base.ExplainedScore(score, reasons)
def score_and_explain(self, project):
"""Compute a score for the given ScoringProject."""
# This job group has jobs that are too different to consider them as a
# small change.
# TODO(pascal): Check for other such job groups and move the config to
# a class property.
if project.details.target_job.job_group.rome_id == 'K2401':
return scoring_base.NULL_EXPLAINED_SCORE
specific_jobs = project.requirements().specific_jobs
if not specific_jobs or specific_jobs[
0].code_ogr == project.details.target_job.code_ogr:
return scoring_base.NULL_EXPLAINED_SCORE
try:
target_job_percentage = next(
j.percent_suggested for j in specific_jobs
if j.code_ogr == project.details.target_job.code_ogr)
except StopIteration:
target_job_percentage = 0
has_way_better_job = target_job_percentage + 30 < specific_jobs[
0].percent_suggested
has_better_job = target_job_percentage + 5 < specific_jobs[
0].percent_suggested
is_looking_for_new_job = project.details.kind == project_pb2.REORIENTATION
reasons = []
if has_way_better_job:
reasons.append(
project.translate_string(
"il y a beaucoup plus d'offres dans des métiers proches"))
elif (project.get_search_length_at_creation() > 6 and has_better_job):
reasons.append(
project.translate_string(
"il y a plus d'offres dans des métiers proches"))
if is_looking_for_new_job:
reasons.append(
project.translate_string(
'vous nous avezdit vouloir vous reconvertir'))
if reasons:
return scoring_base.ExplainedScore(3, reasons)
return scoring_base.ExplainedScore(2, [
project.translate_string(
"il y a un bon nombre d'offres dans des métiers proches")
])
def score_and_explain(self, project):
"""Compute a score for the given ScoringProject."""
application_modes = project.job_group_info().application_modes.values()
first_modes = set(
fap_modes.modes[0].mode for fap_modes in application_modes
if len(fap_modes.modes))
if job_pb2.SPONTANEOUS_APPLICATION in first_modes:
return scoring_base.ExplainedScore(3, [project.translate_string(
"c'est le canal de recrutement n°1 pour votre métier")])
second_modes = set(
fap_modes.modes[1].mode for fap_modes in application_modes
if len(fap_modes.modes) > 1)
if job_pb2.SPONTANEOUS_APPLICATION in second_modes:
return scoring_base.ExplainedScore(2, [project.translate_string(
"c'est un des meilleurs canaux de recrutement pour votre métier")])
return scoring_base.NULL_EXPLAINED_SCORE
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute the score for a given project and explains it."""
skills = self._get_skills(project)
if not skills.skills:
return scoring_base.NULL_EXPLAINED_SCORE
return scoring_base.ExplainedScore(2, [])
def score_and_explain(self, project):
"""Compute the score for a given project and explains it."""
age = project.get_user_age()
if age < 16:
return scoring_base.NULL_EXPLAINED_SCORE
score, reasons = _score_and_explain_after_filters(project)
if not score:
return scoring_base.NULL_EXPLAINED_SCORE
return scoring_base.ExplainedScore(max(1, score - 1), reasons)
def score_and_explain(self, project):
"""Compute a score for the given ScoringProject."""
if (self._num_interviews_increase(project) >= 2
and project.details.job_search_length_months <= 6):
return scoring_base.ExplainedScore(3, [
project.translate_string(
"nous pensons qu'avec votre profil vous pourriez "
"décrocher plus d'entretiens")
])
return scoring_base.NULL_EXPLAINED_SCORE
def score_and_explain(self, project): # pylint: disable=no-self-use
"""Compute a score for the given ScoringProject."""
if project.details.weekly_applications_estimate <= project_pb2.LESS_THAN_2 or \
project.details.job_search_length_months < 2:
return scoring_base.ExplainedScore(3, [
project.translate_string(
'vous nous avez dit que vous en êtes au début de '
'vos candidatures')
])
return scoring_base.NULL_EXPLAINED_SCORE
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute the score for a given project and explains it."""
age = project.get_user_age()
if age < 16:
return scoring_base.NULL_EXPLAINED_SCORE
score, reasons = _score_and_explain_after_filters(project)
if not score:
return scoring_base.NULL_EXPLAINED_SCORE
# We bring more value in the driving-license-euro and
# driving-license-low-income so we show this one after (lower score).
return scoring_base.ExplainedScore(max(1, score - 1), reasons)
def score_and_explain(self, project):
"""Compute a score for the given ScoringProject."""
reasons = []
if project.details.mobility.area_type != geo_pb2.COUNTRY and \
project.details.mobility.area_type != geo_pb2.WORLD:
return scoring_base.NULL_EXPLAINED_SCORE
reasons.append(
project.translate_string(
'vous nous avez dit être prêt%eFeminine à déménager'))
if _find_best_departements(None, project):
reasons.append(
project.translate_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."""
has_any_covid_risk_info = jobs.has_covid_risk_info(project.database)
has_any_automation_risk_info = jobs.has_automation_risk_info(
project.database)
if not has_any_covid_risk_info and not has_any_automation_risk_info:
raise scoring_base.NotEnoughDataException(
'No data about jobs being affected by Covid or automation', {
'data.job_group_info.covid_risk',
'data.job_group_info.automation_risk'
})
# Total risk from 0 to 100.
total_risk = 0
# Covid risk: 0 if safe or no covid data at all, 25 if unknown, 50 if risky.
covid_risk = project.job_group_info().covid_risk
if covid_risk == job_pb2.COVID_RISKY:
total_risk += 50
elif not covid_risk and has_any_covid_risk_info:
total_risk += 25
# Automation risk: 0 if super safe or no covid data at all, 25 if unknown, 50 if very risky.
automation_risk = project.job_group_info().automation_risk
if automation_risk:
total_risk += automation_risk // 2
elif has_any_automation_risk_info:
total_risk += 25
if total_risk <= 15:
# This job is as safe as it can be, no need to explore for more.
return scoring_base.NULL_EXPLAINED_SCORE
# 81+ => 3
return scoring_base.ExplainedScore(min((total_risk - 15) / 22, 3), [
project.translate_static_string(
"il existe des métiers avec peu de risques d'automatisation",
),
])
def score_and_explain(self, project: scoring_base.ScoringProject) \
-> scoring_base.ExplainedScore:
"""Compute a score for the given ScoringProject."""
relevant_salons = self._get_relevant_salons(project)
if not relevant_salons:
return scoring_base.NULL_EXPLAINED_SCORE
reasons = []
# TODO(cyrille): Refine this depending on salons' locations.
if project.details.area_type >= geo_pb2.COUNTRY:
reasons.append(project.translate_static_string('vous êtes mobile partout en France'))
elif any(salon.HasField('location') for salon in relevant_salons):
reasons.append(project.translate_static_string(
'certains salons concernent votre zone géographique'))
if any(salon.job_group_ids for salon in relevant_salons):
reasons.append(
f'des entreprises {project.job_group_info().in_domain} recherchent du monde')
return scoring_base.ExplainedScore(1, reasons)
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
