def make_json_to_array_by_period(self, period): return conv.condition( conv.test_isinstance(dict), conv.pipe( # Value is a dict of (period, value) couples. conv.uniform_mapping( conv.pipe( conv.function(periods.period), conv.not_none, ), conv.pipe( conv.make_item_to_singleton(), conv.uniform_sequence(self.json_to_dated_python, ), conv.empty_to_none, conv.function(lambda cells_list: np.array( cells_list, dtype=self.dtype)), ), drop_none_values=True, ), conv.empty_to_none, ), conv.pipe( conv.make_item_to_singleton(), conv.uniform_sequence(self.json_to_dated_python, ), conv.empty_to_none, conv.function( lambda cells_list: np.array(cells_list, dtype=self.dtype)), conv.function(lambda array: {period: array}), ), )
def validate_dated_value_json(value, state = None): if value is None: return None, None container = state.ancestors[-1] value_converter = dict( boolean = conv.condition( conv.test_isinstance(int), conv.test_in((0, 1)), conv.test_isinstance(bool), ), float = conv.condition( conv.test_isinstance(int), conv.anything_to_float, conv.test_isinstance(float), ), integer = conv.condition( conv.test_isinstance(float), conv.pipe( conv.test(lambda number: round(number) == number), conv.function(int), ), conv.test_isinstance(int), ), rate = conv.condition( conv.test_isinstance(int), conv.anything_to_float, conv.test_isinstance(float), ), )[container.get('format') or 'float'] # Only parameters have a "format". return value_converter(value, state = state or conv.default_state)
def validate_dated_value_json(value, state=None): if value is None: return None, None container = state.ancestors[-1] value_converter = dict( boolean=conv.condition( conv.test_isinstance(int), conv.test_in((0, 1)), conv.test_isinstance(bool), ), float=conv.condition( conv.test_isinstance(int), conv.anything_to_float, conv.test_isinstance(float), ), integer=conv.condition( conv.test_isinstance(float), conv.pipe( conv.test(lambda number: round(number) == number), conv.function(int), ), conv.test_isinstance(int), ), rate=conv.condition( conv.test_isinstance(int), conv.anything_to_float, conv.test_isinstance(float), ), )[container.get('format') or 'float'] # Only parameters have a "format". return value_converter(value, state=state or conv.default_state)
def input_to_dated_python(self): return conv.pipe( conv.test(year_or_month_or_day_re.match, error=N_('Invalid date')), conv.function(lambda birth: '-'.join( (birth.split('-') + ['01', '01'])[:3])), conv.iso8601_input_to_date, )
def input_to_json_data(value, state=None): return conv.pipe( conv.make_input_to_json(), conv.test_isinstance(dict), conv.struct( dict( resultat_officiel=conv.pipe( conv.test_isinstance(dict), conv.uniform_mapping( conv.pipe( conv.test_isinstance(basestring), conv.not_none, ), conv.pipe( conv.test_isinstance(dict), conv.struct( dict( code=conv.pipe( conv.test_isinstance(basestring), conv.not_none, ), name=conv.pipe( conv.test_isinstance(basestring), conv.not_none, ), value=conv.pipe( conv.test_isinstance(float), conv.not_none, ), ), ), conv.not_none, ), ), conv.not_none, ), scenario=conv.pipe( conv.test_isinstance(dict), conv.struct( dict( test_case=conv.pipe( conv.test_isinstance(dict), # For each entity convert its members from a dict to a list. conv.uniform_mapping( conv.noop, conv.pipe( conv.test_isinstance(dict), conv.function( transform_entity_member_by_id_to_members ), ), ), ), ), default=conv.noop, ), tax_benefit_system.Scenario.make_json_to_instance( tax_benefit_system=tax_benefit_system), conv.not_none, ), ), ), )(value, state=state or conv.default_state)
def json_to_dated_python(self): return conv.pipe( conv.condition( conv.test_isinstance((float, int)), # YAML stores strings containing only digits as numbers. conv.function(str), ), conv.test_isinstance(basestring_type), )
def json_to_dated_python(self): return conv.pipe( conv.condition( conv.test_isinstance((float, int)), # YAML stores strings containing only digits as numbers. conv.function(str), ), conv.test_isinstance(basestring_type), conv.test(lambda value: len(value) <= self.variable.max_length), )
def validate_node_json(node, state=None): if node is None: return None, None if state is None: state = conv.default_state validated_node, errors = conv.pipe( conv.condition( conv.test_isinstance(list), conv.uniform_sequence( validate_node_json, drop_none_items=True, ), conv.pipe( conv.condition( conv.test_isinstance(basestring_type), conv.function(lambda code: dict(code=code)), conv.test_isinstance(dict), ), conv.struct( dict( children=conv.pipe( conv.test_isinstance(list), conv.uniform_sequence( validate_node_json, drop_none_items=True, ), conv.empty_to_none, ), code=conv.pipe( conv.test_isinstance(basestring_type), conv.cleanup_line, ), ), constructor=collections.OrderedDict, default=conv.noop, drop_none_values='missing', keep_value_order=True, ), ), ), conv.empty_to_none, )(node, state=state) if validated_node is None or errors is not None: return validated_node, errors if isinstance(validated_node, dict) and not validated_node.get('children'): validated_node, errors = conv.struct( dict(code=conv.pipe( conv.test_in(tax_benefit_system.variables), conv.not_none, ), ), default=conv.noop, )(validated_node, state=state) return validated_node, errors
def json_to_dated_python(self): return conv.pipe( conv.condition( conv.test_isinstance(datetime.date), conv.noop, conv.condition( conv.test_isinstance(int), conv.pipe( conv.test_between(1870, 2099), conv.function(lambda year: datetime.date(year, 1, 1)), ), conv.pipe( conv.test_isinstance(basestring_type), conv.test(year_or_month_or_day_re.match, error = N_('Invalid date')), conv.function(lambda birth: '-'.join((birth.split('-') + ['01', '01'])[:3])), conv.iso8601_input_to_date, ), ), ), conv.test_between(datetime.date(1870, 1, 1), datetime.date(2099, 12, 31)), )
def make_json_or_python_to_axes(tax_benefit_system): column_by_name = tax_benefit_system.variables return conv.pipe( conv.test_isinstance(list), conv.uniform_sequence( conv.pipe( conv.item_or_sequence( conv.pipe( conv.test_isinstance(dict), conv.struct( dict( count=conv.pipe( conv.test_isinstance(int), conv.test_greater_or_equal(1), conv.not_none, ), index=conv.pipe( conv.test_isinstance(int), conv.test_greater_or_equal(0), conv.default(0), ), max=conv.pipe( conv.test_isinstance((float, int)), conv.not_none, ), min=conv.pipe( conv.test_isinstance((float, int)), conv.not_none, ), name=conv.pipe( conv.test_isinstance(basestring_type), conv.test_in(column_by_name), conv.test( lambda column_name: tax_benefit_system. get_variable(column_name).dtype in (np.float32, np.int16, np.int32), error=N_( 'Invalid type for axe: integer or float expected' )), conv.not_none, ), period=conv.function(periods.period), ), ), ), drop_none_items=True, ), conv.make_item_to_singleton(), ), drop_none_items=True, ), conv.empty_to_none, )
def json_to_dated_python(self): enum = self.variable.possible_values possible_names = [item.name for item in list(enum)] if enum is None: return conv.pipe(conv.test_isinstance(basestring_type)) return conv.pipe( conv.test_isinstance(basestring_type), conv.pipe( # Verify that item belongs to enumeration. conv.test_in(possible_names), # Transform that item into enum object. conv.function(lambda enum_name: enum[enum_name])))
def json_to_python(self): return conv.condition( conv.test_isinstance(dict), conv.pipe( # Value is a dict of (period, value) couples. conv.uniform_mapping( conv.pipe( conv.function(periods.period), conv.not_none, ), self.json_to_dated_python, ), ), self.json_to_dated_python, )
def check_entities_and_role(test_case, tax_benefit_system, state): """ Check that the test_case describes entities consistent with the tax and benefit system. Will raise an error if : - An entity is not recognized - An entity role is not recognized - A variable is declared for an entity it is not defined for (e.g. salary for a family) """ test_case = deepcopy( test_case) # Avoid side-effects on other references to test_case entity_classes = { entity_class.plural: entity_class for entity_class in tax_benefit_system.entities } for entity_type_name, entities in test_case.items(): if entity_classes.get(entity_type_name) is None: raise ValueError("Invalid entity name: {}".format( entity_type_name).encode('utf-8')) entities, error = conv.pipe( conv.make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance(dict), drop_none_items=True, ), conv.function(set_entities_json_id), )(entities) if error is not None: raise ValueError("Invalid list of {}: {}. Error: {}".format( entity_type_name, entities, error).encode('utf-8')) if entities is None: entities = test_case[entity_type_name] = [ ] # YAML test runner may set these values to None entity_class = entity_classes[entity_type_name] valid_roles = dict( (role.key, role) if (role.max == 1) else (role.plural, role) for role in entity_class.roles) if not entity_class.is_person else {} for entity_json in entities: check_entity_fields(entity_json, entity_class, valid_roles, tax_benefit_system) for entity_class in entity_classes.values(): if test_case.get(entity_class.plural) is None: test_case[entity_class.plural] = [ ] # by convention, all entities must be declared in the test_case return test_case
def input_to_json_data(value, state=None): return conv.pipe( conv.make_input_to_json(), conv.test_isinstance(dict), conv.struct( dict( resultat_officiel=conv.pipe( conv.test_isinstance(dict), conv.uniform_mapping( conv.pipe(conv.test_isinstance(basestring), conv.not_none), conv.pipe( conv.test_isinstance(dict), conv.struct( dict( code=conv.pipe(conv.test_isinstance(basestring), conv.not_none), name=conv.pipe(conv.test_isinstance(basestring), conv.not_none), value=conv.pipe(conv.test_isinstance(float), conv.not_none), ) ), conv.not_none, ), ), conv.not_none, ), scenario=conv.pipe( conv.test_isinstance(dict), conv.struct( dict( test_case=conv.pipe( conv.test_isinstance(dict), # For each entity convert its members from a dict to a list. conv.uniform_mapping( conv.noop, conv.pipe( conv.test_isinstance(dict), conv.function(transform_entity_member_by_id_to_members), ), ), ) ), default=conv.noop, ), tax_benefit_system.Scenario.make_json_to_instance(tax_benefit_system=tax_benefit_system), conv.not_none, ), ) ), )(value, state=state or conv.default_state)
def json_or_python_to_attributes(value, state=None): if value is None: return value, None if state is None: state = conv.default_state # First validation and conversion step data, error = conv.pipe( conv.test_isinstance(dict), # TODO: Remove condition below, once every calls uses "period" instead of "date" & "year". self.cleanup_period_in_json_or_python, conv.struct( dict( axes=make_json_or_python_to_axes( self.tax_benefit_system), input_variables=conv.test_isinstance( dict ), # Real test is done below, once period is known. period=conv.pipe( conv.function(periods.period), conv.not_none, ), test_case=conv.test_isinstance( dict ), # Real test is done below, once period is known. ), ), )(value, state=state) if error is not None: return data, error # Second validation and conversion step data, error = conv.struct( dict( input_variables=make_json_or_python_to_input_variables( self.tax_benefit_system, data['period']), test_case=self.make_json_or_python_to_test_case( period=data['period'], repair=repair), ), default=conv.noop, )(data, state=state) if error is not None: return data, error # Third validation and conversion step errors = {} if data['input_variables'] is not None and data[ 'test_case'] is not None: errors['input_variables'] = state._( "Items input_variables and test_case can't both exist") errors['test_case'] = state._( "Items input_variables and test_case can't both exist") elif data['axes'] is not None and data["test_case"] is None: errors['axes'] = state._( "Axes can't be used with input_variables.") if errors: return data, errors if data['axes'] is not None: for parallel_axes_index, parallel_axes in enumerate( data['axes']): first_axis = parallel_axes[0] axis_count = first_axis['count'] axis_entity_key = tbs.get_variable( first_axis['name']).entity.key first_axis_period = first_axis['period'] or data['period'] for axis_index, axis in enumerate(parallel_axes): if axis['min'] >= axis['max']: errors.setdefault('axes', {}).setdefault( parallel_axes_index, {} ).setdefault(axis_index, {})['max'] = state._( "Max value must be greater than min value") column = tbs.get_variable(axis['name']) if axis['index'] >= len( data['test_case'][column.entity.plural]): errors.setdefault('axes', {}).setdefault( parallel_axes_index, {}).setdefault( axis_index, {})['index'] = state._( "Index must be lower than {}").format( len(data['test_case'][ column.entity.plural])) if axis_index > 0: if axis['count'] != axis_count: errors.setdefault('axes', {}).setdefault( parallel_axes_index, {} ).setdefault( axis_index, {} )['count'] = state._( "Parallel indexes must have the same count" ) if column.entity.key != axis_entity_key: errors.setdefault('axes', {}).setdefault( parallel_axes_index, {} ).setdefault( axis_index, {} )['period'] = state._( "Parallel indexes must belong to the same entity" ) axis_period = axis['period'] or data['period'] if axis_period.unit != first_axis_period.unit: errors.setdefault('axes', {}).setdefault( parallel_axes_index, {} ).setdefault( axis_index, {} )['period'] = state._( "Parallel indexes must have the same period unit" ) elif axis_period.size != first_axis_period.size: errors.setdefault('axes', {}).setdefault( parallel_axes_index, {} ).setdefault( axis_index, {} )['period'] = state._( "Parallel indexes must have the same period size" ) if errors: return data, errors self.axes = data['axes'] if data['input_variables'] is not None: self.input_variables = data['input_variables'] self.period = data['period'] if data['test_case'] is not None: self.test_case = data['test_case'] return self, None
def json_or_python_to_test_case(value, state = None): if value is None: return value, None if state is None: state = conv.default_state column_by_name = self.tax_benefit_system.column_by_name # First validation and conversion step test_case, error = conv.pipe( conv.test_isinstance(dict), conv.struct( dict( familles = conv.pipe( conv.condition( conv.test_isinstance(list), conv.pipe( conv.uniform_sequence( conv.test_isinstance(dict), drop_none_items = True, ), conv.function(lambda values: collections.OrderedDict( (value.pop('id', index), value) for index, value in enumerate(values) )), ), ), conv.test_isinstance(dict), conv.uniform_mapping( conv.pipe( conv.test_isinstance((basestring, int)), conv.not_none, ), conv.pipe( conv.test_isinstance(dict), conv.struct( dict(itertools.chain( dict( enfants = conv.pipe( conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance((basestring, int)), drop_none_items = True, ), conv.default([]), ), parents = conv.pipe( conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance((basestring, int)), drop_none_items = True, ), conv.default([]), ), ).iteritems(), ( (column.name, column.json_to_python) for column in column_by_name.itervalues() if column.entity == 'fam' ), )), drop_none_values = True, ), ), drop_none_values = True, ), conv.default({}), ), individus = conv.pipe( conv.condition( conv.test_isinstance(list), conv.pipe( conv.uniform_sequence( conv.test_isinstance(dict), drop_none_items = True, ), conv.function(lambda values: collections.OrderedDict( (value.pop('id', index), value) for index, value in enumerate(values) )), ), ), conv.test_isinstance(dict), conv.uniform_mapping( conv.pipe( conv.test_isinstance((basestring, int)), conv.not_none, ), conv.pipe( conv.test_isinstance(dict), conv.struct( dict( (column.name, column.json_to_python) for column in column_by_name.itervalues() if column.entity == 'ind' and column.name not in ( 'idfam', 'idfoy', 'idmen', 'quifam', 'quifoy', 'quimen') ), drop_none_values = True, ), ), drop_none_values = True, ), conv.empty_to_none, conv.not_none, ), ), ), )(value, state = state) if error is not None: return test_case, error # Second validation step familles_individus_id = list(test_case['individus'].iterkeys()) test_case, error = conv.struct( dict( familles = conv.uniform_mapping( conv.noop, conv.struct( dict( enfants = conv.uniform_sequence(conv.test_in_pop(familles_individus_id)), parents = conv.uniform_sequence(conv.test_in_pop(familles_individus_id)), ), default = conv.noop, ), ), ), default = conv.noop, )(test_case, state = state) remaining_individus_id = set(familles_individus_id) if remaining_individus_id: if error is None: error = {} for individu_id in remaining_individus_id: error.setdefault('individus', {})[individu_id] = state._(u"Individual is missing from {}").format( state._(u' & ').join( word for word in [ u'familles' if individu_id in familles_individus_id else None, ] if word is not None )) if error is not None: return test_case, error return test_case, error
def validate_node_xml_json(node, state=None): validated_node, errors = conv.pipe( conv.test_isinstance(dict), conv.struct( dict( code=conv.pipe( conv.test_isinstance(basestring_type), conv.cleanup_line, conv.not_none, ), color=conv.pipe( conv.test_isinstance(basestring_type), conv.function(lambda colors: colors.split(',')), conv.uniform_sequence( conv.pipe( conv.input_to_int, conv.test_between(0, 255), conv.not_none, ), ), conv.test( lambda colors: len(colors) == 3, error=N_('Wrong number of colors in triplet.')), conv.function(lambda colors: ','.join( to_unicode(color) for color in colors)), ), desc=conv.pipe( conv.test_isinstance(basestring_type), conv.cleanup_line, conv.not_none, ), NODE=conv.pipe( conv.test_isinstance(list), conv.uniform_sequence( validate_node_xml_json, drop_none_items=True, ), conv.empty_to_none, ), shortname=conv.pipe( conv.test_isinstance(basestring_type), conv.cleanup_line, conv.not_none, ), tail=conv.pipe( conv.test_isinstance(basestring_type), conv.cleanup_text, ), text=conv.pipe( conv.test_isinstance(basestring_type), conv.cleanup_text, ), typevar=conv.pipe( conv.test_isinstance(basestring_type), conv.input_to_int, conv.test_equals(2), ), ), constructor=collections.OrderedDict, drop_none_values='missing', keep_value_order=True, ), )(node, state=state or conv.default_state) if errors is not None: return validated_node, errors if not validated_node.get('NODE'): validated_node, errors = conv.struct( dict(code=conv.test_in(tax_benefit_system.variables), ), default=conv.noop, )(validated_node, state=state) return validated_node, errors
def json_or_python_to_test_case(value, state=None): if value is None: return value, None if state is None: state = conv.default_state column_by_name = self.tax_benefit_system.column_by_name # First validation and conversion step test_case, error = conv.pipe( conv.test_isinstance(dict), conv.struct( dict( foyers_fiscaux=conv.pipe( conv.make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance(dict), drop_none_items=True, ), conv.function(scenarios.set_entities_json_id), conv.uniform_sequence( conv.struct( dict( itertools.chain( dict( declarants=conv.pipe( conv. make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance( (basestring, int)), drop_none_items=True, ), conv.default([]), ), id=conv.pipe( conv.test_isinstance( (basestring, int)), conv.not_none, ), personnes_a_charge=conv.pipe( conv. make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance( (basestring, int)), drop_none_items=True, ), conv.default([]), ), ).iteritems(), ((column.name, column.json_to_python) for column in column_by_name.itervalues() if column.entity == 'fam'), )), drop_none_values=True, ), drop_none_items=True, ), conv.default([]), ), individus=conv.pipe( conv.make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance(dict), drop_none_items=True, ), conv.function(scenarios.set_entities_json_id), conv.uniform_sequence( conv.struct( dict( itertools.chain( dict(id=conv.pipe( conv.test_isinstance( (basestring, int)), conv.not_none, ), ).iteritems(), ((column.name, column.json_to_python) for column in column_by_name.itervalues() if column.entity == 'ind' and column.name not in ('idfam', 'idfoy', 'idmen', 'quifam', 'quifoy', 'quimen')), )), drop_none_values=True, ), drop_none_items=True, ), conv.empty_to_none, conv.not_none, ), menages=conv.pipe( conv.make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance(dict), drop_none_items=True, ), conv.function(scenarios.set_entities_json_id), conv.uniform_sequence( conv.struct( dict( itertools.chain( dict( autres=conv.pipe( # personnes ayant un lien autre avec la personne de référence conv. make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance( (basestring, int)), drop_none_items=True, ), conv.default([]), ), # conjoint de la personne de référence conjoint=conv.test_isinstance( (basestring, int)), enfants=conv.pipe( # enfants de la personne de référence ou de son conjoint conv. make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance( (basestring, int)), drop_none_items=True, ), conv.default([]), ), id=conv.pipe( conv.test_isinstance( (basestring, int)), conv.not_none, ), personne_de_reference=conv. test_isinstance( (basestring, int)), ).iteritems(), ((column.name, column.json_to_python) for column in column_by_name.itervalues() if column.entity == 'men'), )), drop_none_values=True, ), drop_none_items=True, ), conv.default([]), ), ), ), )(value, state=state) if error is not None: return test_case, error # Second validation step foyers_fiscaux_individus_id = [ individu['id'] for individu in test_case['individus'] ] menages_individus_id = [ individu['id'] for individu in test_case['individus'] ] test_case, error = conv.struct( dict( foyers_fiscaux=conv.uniform_sequence( conv.struct( dict( declarants=conv.uniform_sequence( conv.test_in_pop( foyers_fiscaux_individus_id)), personnes_a_charge=conv.uniform_sequence( conv.test_in_pop( foyers_fiscaux_individus_id)), ), default=conv.noop, ), ), menages=conv.uniform_sequence( conv.struct( dict( autres=conv.uniform_sequence( conv.test_in_pop(menages_individus_id)), conjoint=conv.test_in_pop( menages_individus_id), enfants=conv.uniform_sequence( conv.test_in_pop(menages_individus_id)), personne_de_reference=conv.test_in_pop( menages_individus_id), ), default=conv.noop, ), ), ), default=conv.noop, )(test_case, state=state) individu_by_id = { individu['id']: individu for individu in test_case['individus'] } if repair: # Affecte à un foyer fiscal chaque individu qui n'appartient à aucun d'entre eux. new_foyer_fiscal = dict( declarants=[], personnes_a_charge=[], ) new_foyer_fiscal_id = None for individu_id in foyers_fiscaux_individus_id[:]: # Tente d'affecter l'individu à un foyer fiscal d'après son ménage. menage, menage_role = find_menage_and_role( test_case, individu_id) if menage_role == u'personne_de_reference': conjoint_id = menage[u'conjoint'] if conjoint_id is not None: foyer_fiscal, other_role = find_foyer_fiscal_and_role( test_case, conjoint_id) if other_role == u'declarants' and len( foyer_fiscal[u'declarants']) == 1: # Quand l'individu n'est pas encore dans un foyer fiscal, mais qu'il est personne de # référence dans un ménage, qu'il y a un conjoint dans ce ménage et que ce # conjoint est seul déclarant dans un foyer fiscal, alors ajoute l'individu comme # autre déclarant de ce foyer fiscal. foyer_fiscal[u'declarants'].append(individu_id) foyers_fiscaux_individus_id.remove(individu_id) elif menage_role == u'conjoint': personne_de_reference_id = menage[ u'personne_de_reference'] if personne_de_reference_id is not None: foyer_fiscal, other_role = find_foyer_fiscal_and_role( test_case, personne_de_reference_id) if other_role == u'declarants' and len( foyer_fiscal[u'declarants']) == 1: # Quand l'individu n'est pas encore dans un foyer fiscal, mais qu'il est conjoint # dans un ménage, qu'il y a une personne de référence dans ce ménage et que # cette personne est seul déclarant dans un foyer fiscal, alors ajoute l'individu # comme autre déclarant de ce foyer fiscal. foyer_fiscal[u'declarants'].append(individu_id) foyers_fiscaux_individus_id.remove(individu_id) elif menage_role == u'enfants' and ( menage['personne_de_reference'] is not None or menage[u'conjoint'] is not None): for other_id in (menage['personne_de_reference'], menage[u'conjoint']): if other_id is None: continue foyer_fiscal, other_role = find_foyer_fiscal_and_role( test_case, other_id) if other_role == u'declarants': # Quand l'individu n'est pas encore dans un foyer fiscal, mais qu'il est enfant dans # un ménage, qu'il y a une personne à charge ou un conjoint dans ce ménage et que # celui-ci est déclarant dans un foyer fiscal, alors ajoute l'individu comme # personne à charge de ce foyer fiscal. foyer_fiscal[u'personnes_a_charge'].append( individu_id) foyers_fiscaux_individus_id.remove(individu_id) break if individu_id in foyers_fiscaux_individus_id: # L'individu n'est toujours pas affecté à un foyer fiscal. individu = individu_by_id[individu_id] age = find_age(individu, period.start.date) if len(new_foyer_fiscal[u'declarants']) < 2 and ( age is None or age >= 18): new_foyer_fiscal[u'declarants'].append(individu_id) else: new_foyer_fiscal[u'personnes_a_charge'].append( individu_id) if new_foyer_fiscal_id is None: new_foyer_fiscal[ u'id'] = new_foyer_fiscal_id = unicode( uuid.uuid4()) test_case[u'foyers_fiscaux'].append( new_foyer_fiscal) foyers_fiscaux_individus_id.remove(individu_id) # Affecte à un ménage chaque individu qui n'appartient à aucun d'entre eux. new_menage = dict( autres=[], conjoint=None, enfants=[], personne_de_reference=None, ) new_menage_id = None for individu_id in menages_individus_id[:]: # Tente d'affecter l'individu à un ménage d'après son foyer fiscal. foyer_fiscal, foyer_fiscal_role = find_foyer_fiscal_and_role( test_case, individu_id) if foyer_fiscal_role == u'declarants' and len( foyer_fiscal[u'declarants']) == 2: for declarant_id in foyer_fiscal[u'declarants']: if declarant_id != individu_id: menage, other_role = find_menage_and_role( test_case, declarant_id) if other_role == u'personne_de_reference' and menage[ u'conjoint'] is None: # Quand l'individu n'est pas encore dans un ménage, mais qu'il est déclarant # dans un foyer fiscal, qu'il y a un autre déclarant dans ce foyer fiscal et que # cet autre déclarant est personne de référence dans un ménage et qu'il n'y a # pas de conjoint dans ce ménage, alors ajoute l'individu comme conjoint de ce # ménage. menage[u'conjoint'] = individu_id menages_individus_id.remove(individu_id) elif other_role == u'conjoint' and menage[ u'personne_de_reference'] is None: # Quand l'individu n'est pas encore dans un ménage, mais qu'il est déclarant # dans une foyer fiscal, qu'il y a un autre déclarant dans ce foyer fiscal et # que cet autre déclarant est conjoint dans un ménage et qu'il n'y a pas de # personne de référence dans ce ménage, alors ajoute l'individu comme personne # de référence de ce ménage. menage[ u'personne_de_reference'] = individu_id menages_individus_id.remove(individu_id) break elif foyer_fiscal_role == u'personnes_a_charge' and foyer_fiscal[ u'declarants']: for declarant_id in foyer_fiscal[u'declarants']: menage, other_role = find_menage_and_role( test_case, declarant_id) if other_role in (u'personne_de_reference', u'conjoint'): # Quand l'individu n'est pas encore dans un ménage, mais qu'il est personne à charge # dans un foyer fiscal, qu'il y a un déclarant dans ce foyer fiscal et que ce # déclarant est personne de référence ou conjoint dans un ménage, alors ajoute # l'individu comme enfant de ce ménage. menage[u'enfants'].append(individu_id) menages_individus_id.remove(individu_id) break if individu_id in menages_individus_id: # L'individu n'est toujours pas affecté à un ménage. if new_menage[u'personne_de_reference'] is None: new_menage[u'personne_de_reference'] = individu_id elif new_menage[u'conjoint'] is None: new_menage[u'conjoint'] = individu_id else: new_menage[u'enfants'].append(individu_id) if new_menage_id is None: new_menage[u'id'] = new_menage_id = unicode( uuid.uuid4()) test_case[u'menages'].append(new_menage) menages_individus_id.remove(individu_id) remaining_individus_id = set(foyers_fiscaux_individus_id).union( menages_individus_id) if remaining_individus_id: individu_index_by_id = { individu[u'id']: individu_index for individu_index, individu in enumerate( test_case[u'individus']) } if error is None: error = {} for individu_id in remaining_individus_id: error.setdefault( 'individus', {})[individu_index_by_id[individu_id]] = state._( u"Individual is missing from {}").format( state._(u' & ').join(word for word in [ u'foyers_fiscaux' if individu_id in foyers_fiscaux_individus_id else None, u'menages' if individu_id in menages_individus_id else None, ] if word is not None)) if error is not None: return test_case, error # Third validation step individu_by_id = test_case['individus'] test_case, error = conv.struct( dict( foyers_fiscaux=conv.pipe( conv.uniform_sequence( conv.struct( dict( declarants=conv.pipe( conv.empty_to_none, conv.not_none, conv.test( lambda declarants: len(declarants) <= 2, error=N_( u'A "foyer_fiscal" must have at most 2 "declarants"' ), ), # conv.uniform_sequence(conv.pipe( # conv.test(lambda individu_id: # find_age(individu_by_id[individu_id], period.start.date, # default = 100) >= 18, # error = u"Un déclarant d'un foyer fiscal doit être agé d'au moins 18" # u" ans", # ), # conv.test( # lambda individu_id: individu_id in parents_id, # error = u"Un déclarant ou un conjoint sur la déclaration d'impôt, doit" # u" être un parent dans sa famille", # ), # )), ), personnes_a_charge=conv.uniform_sequence( conv.test( lambda individu_id: individu_by_id[ individu_id].get('inv', False) or find_age(individu_by_id[ individu_id], period.start.date, default=0) < 25, error= u"Une personne à charge d'un foyer fiscal doit avoir moins de" u" 25 ans ou être invalide", ), ), ), default=conv.noop, ), ), conv.empty_to_none, conv.not_none, ), # individus = conv.uniform_sequence( # conv.struct( # dict( # date_naissance = conv.test( # lambda date_naissance: period.start.date - date_naissance >= datetime.timedelta(0), # error = u"L'individu doit être né au plus tard le jour de la simulation", # ), # ), # default = conv.noop, # drop_none_values = 'missing', # ), # ), menages=conv.pipe( conv.uniform_sequence( conv.struct( dict(personne_de_reference=conv.not_none, ), default=conv.noop, ), ), conv.empty_to_none, conv.not_none, ), ), default=conv.noop, )(test_case, state=state) return test_case, error
def json_or_python_to_test_case(value, state=None): if value is None: return value, None if state is None: state = conv.default_state column_by_name = self.tax_benefit_system.column_by_name # First validation and conversion step test_case, error = conv.pipe( conv.test_isinstance(dict), conv.struct( dict( individus=conv.pipe( conv.make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence(conv.test_isinstance(dict), drop_none_items=True), conv.function(scenarios.set_entities_json_id), conv.uniform_sequence( conv.struct( dict( itertools.chain( dict( id=conv.pipe(conv.test_isinstance((basestring, int)), conv.not_none) ).iteritems(), ( (column.name, column.json_to_python) for column in column_by_name.itervalues() if column.entity == "ind" and column.name not in ("idmen", "quimen") ), ) ), drop_none_values=True, ), drop_none_items=True, ), conv.empty_to_none, conv.not_none, ), menages=conv.pipe( conv.make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence(conv.test_isinstance(dict), drop_none_items=True), conv.function(scenarios.set_entities_json_id), conv.uniform_sequence( conv.struct( dict( itertools.chain( dict( autres=conv.pipe( conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance((basestring, int)), drop_none_items=True ), conv.default([]), ), conjoint=conv.pipe( conv.test_isinstance(basestring, int), conv.default(None) ), enfants=conv.pipe( conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance((basestring, int)), drop_none_items=True ), conv.default([]), ), id=conv.pipe(conv.test_isinstance((basestring, int)), conv.not_none), personne_de_reference=conv.pipe( conv.test_isinstance(basestring, int), conv.default(None) ), ).iteritems(), ( (column.name, column.json_to_python) for column in column_by_name.itervalues() if column.entity == "men" ), ) ), drop_none_values=True, ), drop_none_items=True, ), conv.default({}), ), ) ), )(value, state=state) if error is not None: return test_case, error # Second validation step menages_individus_id = [individu["id"] for individu in test_case["individus"]] test_case, error = conv.struct( dict( menages=conv.uniform_sequence( conv.struct( dict( autres=conv.uniform_sequence(conv.test_in_pop(menages_individus_id)), conjoint=conv.test_in_pop(menages_individus_id), enfants=conv.uniform_sequence(conv.test_in_pop(menages_individus_id)), personne_de_reference=conv.test_in_pop(menages_individus_id), ), default=conv.noop, ) ) ), default=conv.noop, )(test_case, state=state) remaining_individus_id = set(menages_individus_id) if remaining_individus_id: individu_index_by_id = { individu[u"id"]: individu_index for individu_index, individu in enumerate(test_case[u"individus"]) } if error is None: error = {} for individu_id in remaining_individus_id: error.setdefault("individus", {})[individu_index_by_id[individu_id]] = state._( u"Individual is missing from {}" ).format( state._(u" & ").join( word for word in [u"menages" if individu_id in menages_individus_id else None] if word is not None ) ) if error is not None: return test_case, error return test_case, error
def make_json_or_python_to_test(tax_benefit_system): validate = conv.struct( dict( itertools.chain( dict( absolute_error_margin=conv.pipe( conv.test_isinstance((float, int)), conv.test_greater_or_equal(0), ), axes=make_json_or_python_to_axes(tax_benefit_system), description=conv.pipe( conv.test_isinstance(basestring_type), conv.cleanup_line, ), input_variables=conv.pipe( conv.test_isinstance(dict), conv.uniform_mapping( conv.pipe( conv.test_isinstance(basestring_type), conv.not_none, ), conv.noop, ), conv.empty_to_none, ), keywords=conv.pipe( conv.make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.pipe( conv.test_isinstance(basestring_type), conv.cleanup_line, ), drop_none_items=True, ), conv.empty_to_none, ), name=conv.pipe( conv.test_isinstance(basestring_type), conv.cleanup_line, ), output_variables=conv.test_isinstance(dict), period=conv.pipe( conv.function(periods.period), conv.not_none, ), relative_error_margin=conv.pipe( conv.test_isinstance((float, int)), conv.test_greater_or_equal(0), ), ).items(), ((entity.plural, conv.pipe( conv.make_item_to_singleton(), conv.test_isinstance(list), )) for entity in tax_benefit_system.entities), )), ) def json_or_python_to_test(value, state=None): if value is None: return value, None if state is None: state = conv.default_state value, error = conv.pipe( conv.test_isinstance(dict), validate, )(value, state=state) if error is not None: return value, error value, error = conv.struct( dict(output_variables=make_json_or_python_to_input_variables( tax_benefit_system, value['period']), ), default=conv.noop, )(value, state=state) if error is not None: return value, error test_case = value.copy() absolute_error_margin = test_case.pop('absolute_error_margin') axes = test_case.pop('axes') description = test_case.pop('description') input_variables = test_case.pop('input_variables') keywords = test_case.pop('keywords') name = test_case.pop('name') output_variables = test_case.pop('output_variables') period = test_case.pop('period') relative_error_margin = test_case.pop('relative_error_margin') if test_case is not None and all( entity_members is None for entity_members in test_case.values()): test_case = None scenario, error = tax_benefit_system.Scenario.make_json_to_instance( repair=True, tax_benefit_system=tax_benefit_system)(dict( axes=axes, input_variables=input_variables, period=period, test_case=test_case, ), state=state) if error is not None: return scenario, error return { key: value for key, value in dict( absolute_error_margin=absolute_error_margin, description=description, keywords=keywords, name=name, output_variables=output_variables, relative_error_margin=relative_error_margin, scenario=scenario, ).items() if value is not None }, None return json_or_python_to_test
def validate_value_json(value, state = None): if value is None: return None, None container = state.ancestors[-1] value_converter = dict( boolean = conv.condition( conv.test_isinstance(int), conv.test_in((0, 1)), conv.test_isinstance(bool), ), float = conv.condition( conv.test_isinstance(int), conv.anything_to_float, conv.test_isinstance(float), ), integer = conv.condition( conv.test_isinstance(float), conv.pipe( conv.test(lambda number: round(number) == number), conv.function(int), ), conv.test_isinstance(int), ), rate = conv.condition( conv.test_isinstance(int), conv.anything_to_float, conv.test_isinstance(float), ), )[container.get('format') or 'float'] # Only parameters have a "format". state = conv.add_ancestor_to_state(state, value) validated_value, errors = conv.pipe( conv.test_isinstance(dict), conv.struct( { u'comment': conv.pipe( conv.test_isinstance(basestring), conv.cleanup_text, ), u'from': conv.pipe( conv.test_isinstance(basestring), conv.iso8601_input_to_date, conv.date_to_iso8601_str, conv.not_none, ), u'to': conv.pipe( conv.test_isinstance(basestring), conv.iso8601_input_to_date, conv.date_to_iso8601_str, conv.not_none, ), u'value': conv.pipe( value_converter, conv.not_none, ), }, constructor = collections.OrderedDict, drop_none_values = 'missing', keep_value_order = True, ), )(value, state = state) conv.remove_ancestor_from_state(state, value) return validated_value, errors
def validate_value_json(value, state=None): if value is None: return None, None container = state.ancestors[-1] value_converter = dict( boolean=conv.condition( conv.test_isinstance(int), conv.test_in((0, 1)), conv.test_isinstance(bool), ), float=conv.condition( conv.test_isinstance(int), conv.anything_to_float, conv.test_isinstance(float), ), integer=conv.condition( conv.test_isinstance(float), conv.pipe( conv.test(lambda number: round(number) == number), conv.function(int), ), conv.test_isinstance(int), ), rate=conv.condition( conv.test_isinstance(int), conv.anything_to_float, conv.test_isinstance(float), ), )[container.get('format') or 'float'] # Only parameters have a "format". state = conv.add_ancestor_to_state(state, value) validated_value, errors = conv.pipe( conv.test_isinstance(dict), conv.struct( { u'comment': conv.pipe( conv.test_isinstance(basestring), conv.cleanup_text, ), u'from': conv.pipe( conv.test_isinstance(basestring), conv.iso8601_input_to_date, conv.date_to_iso8601_str, conv.not_none, ), u'to': conv.pipe( conv.test_isinstance(basestring), conv.iso8601_input_to_date, conv.date_to_iso8601_str, conv.not_none, ), u'value': conv.pipe( value_converter, conv.not_none, ), }, constructor=collections.OrderedDict, drop_none_values='missing', keep_value_order=True, ), )(value, state=state) conv.remove_ancestor_from_state(state, value) return validated_value, errors
def input_to_period_tuple(value, state=None): """Convert an input string to a period tuple. .. note:: This function doesn't return a period, but a tuple that allows to construct a period. >>> input_to_period_tuple('2014') (('year', 2014), None) >>> input_to_period_tuple('2014:2') (('year', 2014, 2), None) >>> input_to_period_tuple('2014-2') (('month', (2014, 2)), None) >>> input_to_period_tuple('2014-3:12') (('month', (2014, 3), 12), None) >>> input_to_period_tuple('2014-2-3') (('day', (2014, 2, 3)), None) >>> input_to_period_tuple('2014-3-4:2') (('day', (2014, 3, 4), 2), None) >>> input_to_period_tuple('year:2014') (('year', '2014'), None) >>> input_to_period_tuple('year:2014:2') (('year', '2014', '2'), None) >>> input_to_period_tuple('year:2014-2:2') (('year', '2014-2', '2'), None) """ if value is None: return value, None if state is None: state = conv.default_state split_value = tuple( clean_fragment for clean_fragment in (fragment.strip() for fragment in value.split(':')) if clean_fragment) if not split_value: return None, None if len(split_value) == 1: split_value = tuple( clean_fragment for clean_fragment in (fragment.strip() for fragment in split_value[0].split('-')) if clean_fragment) if len(split_value) == 1: return conv.pipe( conv.input_to_strict_int, conv.test_greater_or_equal(0), conv.function(lambda year: ('year', year)), )(split_value[0], state=state) if len(split_value) == 2: return conv.pipe( conv.struct(( conv.pipe( conv.input_to_strict_int, conv.test_greater_or_equal(0), ), conv.pipe( conv.input_to_strict_int, conv.test_between(1, 12), ), ), ), conv.function(lambda month_tuple: ('month', month_tuple)), )(split_value, state=state) if len(split_value) == 3: return conv.pipe( conv.struct(( conv.pipe( conv.input_to_strict_int, conv.test_greater_or_equal(0), ), conv.pipe( conv.input_to_strict_int, conv.test_between(1, 12), ), conv.pipe( conv.input_to_strict_int, conv.test_between(1, 31), ), ), ), conv.function(lambda day_tuple: ('day', day_tuple)), )(split_value, state=state) return split_value, state._( 'Instant string contains too much "-" for a year, a month or a day' ) if len(split_value) == 2: split_start = tuple( clean_fragment for clean_fragment in (fragment.strip() for fragment in split_value[0].split('-')) if clean_fragment) size, error = conv.input_to_int(split_value[1], state=state) if error is None: if len(split_start) == 1: start, error = conv.pipe( conv.input_to_strict_int, conv.test_greater_or_equal(0), )(split_start[0], state=state) if error is None: return ('year', start, size), None elif len(split_start) == 2: start, error = conv.struct(( conv.pipe( conv.input_to_strict_int, conv.test_greater_or_equal(0), ), conv.pipe( conv.input_to_strict_int, conv.test_between(1, 12), ), ), )(split_start, state=state) if error is None: return ('month', start, size), None elif len(split_start) == 3: start, error = conv.struct(( conv.pipe( conv.input_to_strict_int, conv.test_greater_or_equal(0), ), conv.pipe( conv.input_to_strict_int, conv.test_between(1, 12), ), conv.pipe( conv.input_to_strict_int, conv.test_between(1, 31), ), ), )(split_start, state=state) if error is None: return ('day', start, size), None return split_value, None
def json_or_python_to_test_case(value, state=None): if value is None: return value, None if state is None: state = conv.default_state column_by_name = self.tax_benefit_system.column_by_name # First validation and conversion step test_case, error = conv.pipe( conv.test_isinstance(dict), conv.struct( dict( individus=conv.pipe( conv.make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance(dict), drop_none_items=True, ), conv.function(scenarios.set_entities_json_id), conv.uniform_sequence( conv.struct( dict( itertools.chain( dict(id=conv.pipe( conv.test_isinstance( (basestring, int)), conv.not_none, ), ).iteritems(), ((column.name, column.json_to_python) for column in column_by_name.itervalues() if column.entity == 'ind' and column.name not in ('idmen', 'quimen')), )), drop_none_values=True, ), drop_none_items=True, ), conv.empty_to_none, conv.not_none, ), menages=conv.pipe( conv.make_item_to_singleton(), conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance(dict), drop_none_items=True, ), conv.function(scenarios.set_entities_json_id), conv.uniform_sequence( conv.struct( dict( itertools.chain( dict( autres=conv.pipe( conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance( (basestring, int)), drop_none_items=True, ), conv.default([]), ), conjoint=conv.pipe( conv.test_isinstance( basestring, int), conv.default(None), ), enfants=conv.pipe( conv.test_isinstance(list), conv.uniform_sequence( conv.test_isinstance( (basestring, int)), drop_none_items=True, ), conv.default([]), ), id=conv.pipe( conv.test_isinstance( (basestring, int)), conv.not_none, ), personne_de_reference=conv. pipe( conv.test_isinstance( basestring, int), conv.default(None), ), ).iteritems(), ((column.name, column.json_to_python) for column in column_by_name.itervalues() if column.entity == 'men'), )), drop_none_values=True, ), drop_none_items=True, ), conv.default({}), ), ), ), )(value, state=state) if error is not None: return test_case, error # Second validation step menages_individus_id = [ individu['id'] for individu in test_case['individus'] ] test_case, error = conv.struct( dict(menages=conv.uniform_sequence( conv.struct( dict( autres=conv.uniform_sequence( conv.test_in_pop(menages_individus_id)), conjoint=conv.test_in_pop(menages_individus_id), enfants=conv.uniform_sequence( conv.test_in_pop(menages_individus_id)), personne_de_reference=conv.test_in_pop( menages_individus_id), ), default=conv.noop, ), ), ), default=conv.noop, )(test_case, state=state) remaining_individus_id = set(menages_individus_id) if remaining_individus_id: individu_index_by_id = { individu[u'id']: individu_index for individu_index, individu in enumerate( test_case[u'individus']) } if error is None: error = {} for individu_id in remaining_individus_id: error.setdefault( 'individus', {})[individu_index_by_id[individu_id]] = state._( u"Individual is missing from {}").format( state._(u' & ').join(word for word in [ u'menages' if individu_id in menages_individus_id else None, ] if word is not None)) if error is not None: return test_case, error return test_case, error