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How to use _check_attributes method in autotest
Best Python code snippet using autotest_python
test_integration.py
Source:test_integration.py 
...36class TestManager(FixtureTestCase):37 datasets = [PenData, PencilData, FountainPenData, BallPointPenData]38class TestSpecializedQuerySet(FixtureTestCase):39 datasets = [PenData, PencilData, FountainPenData, BallPointPenData]40 def _check_attributes(self, normal_objects, specialized_objects):41 """42 Helper test to run through the two querysets and43 test various attributes44 """45 for normal_object, specialized_object in zip(46 normal_objects, specialized_objects47 ):48 eq_(normal_object.__class__, WritingImplement)49 assert_not_equal(specialized_object.__class__, WritingImplement)50 compare_generalization_to_specialization(51 normal_object,52 specialized_object53 )54 ok_(isinstance(specialized_object, WritingImplement))55 def test_all(self):56 """Check the all() method works correctly"""57 all_objects = WritingImplement.objects.order_by('name')58 all_specializations = WritingImplement.specializations.order_by('name')59 eq_(len(all_objects), len(all_specializations))60 self._check_attributes(all_objects, all_specializations)61 def test_filter(self):62 """Check the filter() method works correctly"""63 filtered_objects = WritingImplement.objects \64 .filter(length__gte=10) \65 .filter(name__endswith='pen')66 filtered_specializations = WritingImplement.specializations \67 .filter(name__endswith='pen') \68 .filter(length__gte=10)69 self._check_attributes(filtered_objects, filtered_specializations)70 single_filter = WritingImplement.specializations.filter(71 name__endswith='pen', length__gte=1072 )73 eq_(single_filter[0], filtered_specializations[0])74 def test_exclude(self):75 """Check the exclude() method works correctly"""76 excluded_objects = WritingImplement.objects.exclude(length__lt=9)77 excluded_specializations = \78 WritingImplement.specializations.exclude(length__lt=9)79 self._check_attributes(excluded_objects, excluded_specializations)80 def test_slice_index(self):81 """82 Check that querysets can be sliced by a single index value correctly83 """84 all_objects = WritingImplement.objects.order_by('name')85 all_specializations = WritingImplement.specializations.order_by('name')86 eq_(len(all_objects), len(all_specializations))87 for i in range(len(all_objects)):88 o = all_objects[i]89 s = all_specializations[i]90 compare_generalization_to_specialization(o, s)91 def test_slice_range(self):92 """Test various range slices for compatibility"""93 # Two numbers:94 sliced_objects = WritingImplement.objects.order_by('name')[1:4]95 sliced_specializations = \96 WritingImplement.specializations.order_by('name')[1:4]97 self._check_attributes(sliced_objects, sliced_specializations)98 # Just end point:99 sliced_objects = WritingImplement.objects.order_by('length')[:3]100 sliced_specializations = \101 WritingImplement.specializations.order_by('length')[:3]102 self._check_attributes(sliced_objects, sliced_specializations)103 # Just start point:104 sliced_objects = WritingImplement.objects.order_by('-length')[1:]105 sliced_specializations = \106 WritingImplement.specializations.order_by('-length')[1:]107 self._check_attributes(sliced_objects, sliced_specializations)108 def test_order(self):109 """Test various orderings for compatibility"""110 # By name:111 ordered_objects = WritingImplement.objects.order_by('name')112 ordered_specializations = \113 WritingImplement.specializations.order_by('name')114 self._check_attributes(ordered_objects, ordered_specializations)115 # By inverse length and then name:116 ordered_objects = WritingImplement.objects.order_by('-length', 'name')117 ordered_specializations = WritingImplement.specializations.order_by(118 '-length', 'name'119 )120 self._check_attributes(ordered_objects, ordered_specializations)121 def test_get(self):122 """Check that the get() method behaves correctly"""123 general = WritingImplement.objects.get(name=PenData.GeneralPen.name)124 specialized = WritingImplement.specializations.get(125 name=PenData.GeneralPen.name126 )127 self._check_attributes([general], [specialized])128 def test_values(self):129 """Check values returns a ValuesQuerySet in both cases"""130 normal_values = WritingImplement.objects.values('pk', 'name')131 specialized_values = \132 WritingImplement.specializations.values('pk', 'name')133 ok_(isinstance(normal_values, ValuesQuerySet))134 ok_(isinstance(specialized_values, ValuesQuerySet))135 for normal_item, specialized_item in zip(136 normal_values, specialized_values137 ):138 eq_(normal_item['name'], specialized_item['name'])139 eq_(normal_item['pk'], specialized_item['pk'])140 def test_values_list(self):141 """Check values_list returns a ValuesListQuerySet in both cases"""142 normal_values = WritingImplement.objects.values_list('pk', 'length')143 specialized_values = WritingImplement.specializations.values_list(144 'pk', 'length'145 )146 ok_(isinstance(normal_values, ValuesListQuerySet))147 ok_(isinstance(specialized_values, ValuesListQuerySet))148 for (n_pk, n_length), (s_pk, s_length) in zip(149 normal_values, specialized_values150 ):151 eq_(n_pk, s_pk)152 eq_(n_length, s_length)153 def test_flat_values_list(self):154 """155 Check value_list with flat=True returns a ValuesListQuerySet in both156 cases157 """158 normal_values = WritingImplement.objects.values_list('pk', flat=True)159 specialized_values = WritingImplement.specializations.values_list(160 'pk', flat=True161 )162 ok_(isinstance(normal_values, ValuesListQuerySet))163 ok_(isinstance(specialized_values, ValuesListQuerySet))164 eq_(list(normal_values), list(specialized_values))165 def test_aggregate(self):166 """Aggregations work on both types of querysets in the same manner"""167 normal_aggregate = WritingImplement.objects.aggregate(Avg('length'))168 specialized_aggregate = \169 WritingImplement.specializations.aggregate(Avg('length'))170 eq_(normal_aggregate, specialized_aggregate)171 def test_count(self):172 """Counts work over both types of querysets"""173 normal_count = WritingImplement.objects.filter(length__lt=13).count()174 specialized_count = \175 WritingImplement.objects.filter(length__lt=13).count()176 eq_(normal_count, specialized_count)177 def test_in_bulk(self):178 """In bulk works across both types of queryset"""179 ids = list(WritingImplement.objects.values_list('pk', flat=True))[2:]180 normal_bulk = WritingImplement.objects.in_bulk(ids)181 specialized_bulk = WritingImplement.specializations.in_bulk(ids)182 eq_(normal_bulk.keys(), specialized_bulk.keys())183 self._check_attributes(normal_bulk.values(), specialized_bulk.values())184 def test_update(self):185 """update() works the same across querysets"""186 original_lengths = list(187 WritingImplement.objects.order_by('length').values_list(188 'length', flat=True189 )190 )191 WritingImplement.specializations.all().update(length=1+F('length'))192 new_lengths = list(193 WritingImplement.objects.order_by('length').values_list(194 'length', flat=True195 )196 )197 for original_length, new_length in zip(original_lengths, new_lengths):198 eq_(original_length+1, new_length)199 def test_complex_query(self):200 """SpecializedQuerysets can be constructed from Q objects"""201 q_small = Q(length__lt=10)202 q_large = Q(length__gt=13)203 normal_objects = WritingImplement.objects.filter(q_small | q_large)204 specialized_objects = WritingImplement.specializations.filter(205 q_small | q_large206 )...
logic.py
Source:logic.py
2import pandas as pd3def _overlapping_period(row, df, start_date, end_date):4 _df = df[df.index != row.name]5 return ~((row[start_date] <= _df[end_date]) & (row[end_date] >= _df[end_date])).any()6def _check_attributes(gdf, attributes):7 for i in attributes:8 if type(i) == str:9 if not i in gdf.columns:10 raise KeyError(fr"'{i}' not in columns: {gdf.columns.to_list()}. Rule cannot be executed")11def LE(gdf, left, right, dtype=bool):12 """13 Evaluate if left is less or equal to/than right14 Parameters15 ----------16 gdf : GeoDataFrame17 Input GeoDataFrame18 left : str, numeric19 Left column or value in expression20 right : TYPE21 Right column or value in expression22 dtype : dtype, optional23 dtype assigned to result Series24 The default is bool.25 Returns26 -------27 result : Series28 Pandas Series (default dtype = bool)29 """30 _check_attributes(gdf, [left, right])31 expression = f"{left} <= {right}".lower()32 return gdf.eval(expression).astype(dtype)33def LT(gdf, left, right, dtype=bool):34 """35 Evaluate if left is less than right36 Parameters37 ----------38 gdf : GeoDataFrame39 Input GeoDataFrame40 left : str, numeric41 Left column or value in expression42 right : TYPE43 Right column or value in expression44 dtype : dtype, optional45 dtype assigned to result Series46 The default is bool.47 Returns48 -------49 result : Series50 Pandas Series (default dtype = bool)51 """52 _check_attributes(gdf, [left, right])53 expression = f"{left} < {right}".lower()54 return gdf.eval(expression).astype(dtype)55def GT(gdf, left, right, dtype=bool):56 """57 Evaluate if left is greater than right58 Parameters59 ----------60 gdf : GeoDataFrame61 Input GeoDataFrame62 left : str, numeric63 Left column or value in expression64 right : TYPE65 Right column or value in expression66 dtype : dtype, optional67 dtype assigned to result Series68 The default is bool.69 Returns70 -------71 result : Series72 Pandas Series (default dtype = bool)73 """74 _check_attributes(gdf, [left, right])75 expression = f"{left} > {right}".lower()76 return gdf.eval(expression).astype(dtype)77def GE(gdf, left, right, dtype=bool):78 """Evaluate if left is greater or equal to/than right79 Parameters80 ----------81 gdf : GeoDataFrame82 Input GeoDataFrame83 left : str, numeric84 Left column or value in expression85 right : TYPE86 Right column or value in expression87 dtype : dtype, optional88 dtype assigned to result Series89 The default is bool.90 Returns91 -------92 result : Series93 Pandas Series (default dtype = bool)94 """95 _check_attributes(gdf, [left, right])96 expression = f"{left} >= {right}".lower()97 return gdf.eval(expression).astype(dtype)98def EQ(gdf, left, right, dtype=bool):99 """Evalate if left an right expression are equal100 Parameters101 ----------102 gdf : GeoDataFrame103 Input GeoDataFrame104 left : str, numeric105 Left column or value in expression106 right : TYPE107 Right column or value in expression108 dtype : dtype, optional109 dtype assigned to result Series110 The default is bool.111 Returns112 -------113 result : Series114 Pandas Series (default dtype = bool)115 """116 _check_attributes(gdf, [left, right])117 expression = f"{left} == {right}".lower()118 return gdf.eval(expression).astype(dtype)119def BE(gdf, parameter, min, max, inclusive=False):120 """Evaluate if parameter-value is between min/max inclusive (true/false)121 Parameters122 ----------123 gdf : GeoDataFrame124 Input GeoDataFrame125 parameter: str126 Input column with numeric values127 min : numeric128 Lower limit of function129 max : numeric130 Upper limit of function131 inclusive : bool, optional132 To include min and max133 The default is False.134 Returns135 -------136 result : Series137 Pandas Series (default dtype = bool)138 """139 _check_attributes(gdf, [parameter, min, max])140 if inclusive:141 series = GE(gdf, parameter, min, dtype=bool) & LE(142 gdf, parameter, max, dtype=bool143 )144 else:145 series = GT(gdf, parameter, min, dtype=bool) & LT(146 gdf, parameter, max, dtype=bool147 )148 return series149def ISIN(gdf, parameter, array):150 """Evaluate if values in parameter are in array151 Parameters152 ----------153 gdf : GeoDataFrame154 Input GeoDataFrame155 parameter: str156 Input column with numeric values157 array : list158 list of possible values that return True159 Returns160 -------161 result : Series162 Pandas Series (default dtype = bool)163 """164 _check_attributes(gdf, [parameter])165 return gdf[parameter].isin(array)166def NOTIN(gdf, parameter, array):167 """Evaluate if values in parameter are not in array168 Parameters169 ----------170 gdf : GeoDataFrame171 Input GeoDataFrame172 parameter: str173 Input column with numeric values174 array : list175 list of possible values that return False176 Returns177 -------178 result : Series179 Pandas Series (default dtype = bool)180 """181 _check_attributes(gdf, [parameter])182 return ~ISIN(gdf, parameter, array)183def NOTNA(gdf, parameter):184 """Evaluate if values in parameter ar not NaN or None185 Parameters186 ----------187 gdf : GeoDataFrame188 Input GeoDataFrame189 parameter: str190 Input column with numeric values191 Returns192 -------193 result : Series194 Pandas Series (default dtype = bool)195 """196 _check_attributes(gdf, [parameter])197 return gdf[parameter].notna()198def join_object_exists(gdf, join_gdf, join_object):199 """Evaluate if defined related_object id exists in globalid parameter of200 related object-table.201 Parameters202 ----------203 gdf : GeoDataFrame204 Input GeoDataFrame205 related_gdf : GeoDataFrame206 Input GeoDataFrame with related objects207 object: str208 HyDAMO object name of related object-layer209 Returns210 -------211 result : Series212 Pandas Series (default dtype = bool)213 """214 _check_attributes(join_gdf, ["globalid"])215 _check_attributes(gdf, [f"{join_object}id"])216 return gdf[f"{join_object}id"].isin(join_gdf["globalid"])217def consistent_period(gdf,218 max_gap=1,219 groupers=["pompid", "regelmiddelid"],220 priority="prioriteit",221 start_date="beginperiode",222 date_format = "%d%m",223 end_date="eindperiode"):224 """Check if a periodic-based table is time-consistent225 Parameters226 ----------227 gdf : GeoDataFrame228 Input GeoDataFrame229 max_gap: int...
ast_walker.py
Source:ast_walker.py
...4 self._walk_with_attrs(node, attributes, nodes)5 else:6 self._walk_with_list_of_attrs(node, attributes, nodes)7 def _walk_with_attrs(self, node, attributes, nodes):8 if self._check_attributes(node, attributes):9 nodes.append(node)10 else:11 if "children" in node and node["children"]:12 for child in node["children"]:13 self._walk_with_attrs(child, attributes, nodes)14 def _walk_with_list_of_attrs(self, node, list_of_attributes, nodes):15 if self._check_list_of_attributes(node, list_of_attributes):16 nodes.append(node)17 else:18 if "children" in node and node["children"]:19 for child in node["children"]:20 self._walk_with_list_of_attrs(child, list_of_attributes, nodes)21 def _check_attributes(self, node, attributes):22 for name in attributes:23 if name == "attributes":24 if "attributes" not in node or not self._check_attributes(node["attributes"], attributes["attributes"]):25 return False26 else:27 if name not in node or node[name] != attributes[name]:28 return False29 return True30 def _check_list_of_attributes(self, node, list_of_attributes):31 for attrs in list_of_attributes:32 if self._check_attributes(node, attrs):33 return True...
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