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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