Repository: great-expectations/great_expectations

Issue:
Use cleaner solution for non-truncating division in python 2
Prefer `from __future__ import division` to `1.*x/y`


Discussion:
Done inline during improve_partitions push.

Resolving patch:
diff --git a/contrib/experimental/great_expectations_experimental/expectations/expect_column_values_geometry_distance_to_address_to_be_between.py b/contrib/experimental/great_expectations_experimental/expectations/expect_column_values_geometry_distance_to_address_to_be_between.py
new file mode 100644
--- /dev/null
+++ b/contrib/experimental/great_expectations_experimental/expectations/expect_column_values_geometry_distance_to_address_to_be_between.py
@@ -0,0 +1,313 @@
+from typing import Optional
+
+import pandas as pd
+import pygeos as geos
+from geopy import geocoders
+from geopy.distance import distance, lonlat
+
+from great_expectations.core.expectation_configuration import ExpectationConfiguration
+from great_expectations.exceptions import InvalidExpectationConfigurationError
+from great_expectations.execution_engine import (
+    PandasExecutionEngine,
+    SparkDFExecutionEngine,
+    SqlAlchemyExecutionEngine,
+)
+from great_expectations.expectations.expectation import ColumnMapExpectation
+from great_expectations.expectations.metrics import (
+    ColumnMapMetricProvider,
+    column_condition_partial,
+)
+
+
+# This class defines a Metric to support your Expectation.
+# For most ColumnMapExpectations, the main business logic for calculation will live in this class.
+class ColumnValuesGeometryDistanceToAddress(ColumnMapMetricProvider):
+
+    # This is the id string that will be used to reference your metric.
+    condition_metric_name = "column_values.geometry.distance_to_address"
+    condition_value_keys = (
+        "column_shape_format",
+        "place",
+        "geocoder",
+        "geocoder_config",
+        "min_value",
+        "max_value",
+        "strict_min",
+        "strict_max",
+        "units",
+    )
+
+    # This method implements the core logic for the PandasExecutionEngine
+    @column_condition_partial(engine=PandasExecutionEngine)
+    def _pandas(cls, column, **kwargs):
+
+        column_shape_format = kwargs.get("column_shape_format")
+        place = kwargs.get("place")
+        geocoder = kwargs.get("geocoder")
+        geocoder_config = kwargs.get("geocoder_config")
+        min_value = kwargs.get("min_value")
+        max_value = kwargs.get("max_value")
+        strict_min = kwargs.get("strict_min")
+        strict_max = kwargs.get("strict_max")
+        units = kwargs.get("units")
+
+        if min_value is None and max_value is None:
+            raise ValueError("min_value and max_value cannot both be None")
+        if min_value is not None and max_value is not None and min_value > max_value:
+            raise ValueError("min_value cannot be greater than max_value")
+
+        if geocoder not in ["nominatim", "pickpoint", "openmapquest"]:
+            raise NotImplementedError(
+                "The geocoder is not implemented for this method."
+            )
+
+        # find the reference shape with the geocoder.
+        if geocoder is not None:
+            try:
+                # Specify the default parameters for Nominatim and run query. User is responsible for config and query params otherwise.
+                query_params = dict(exactly_one=True, geometry="wkt")
+                location = cls.geocode(geocoder, geocoder_config, place, query_params)
+            except:
+                raise Exception(
+                    "Geocoding configuration and query failed to produce a valid result."
+                )
+        else:
+            raise Exception(
+                "A valid geocoder must be provided for this method. See GeoPy for reference."
+            )
+
+        # Load the column into a pygeos Geometry vector from numpy array (Series not supported).
+        if column_shape_format == "wkt":
+            shape_test = geos.from_wkt(column.to_numpy(), on_invalid="ignore")
+        elif column_shape_format == "wkb":
+            shape_test = geos.from_wkb(column.to_numpy(), on_invalid="ignore")
+        elif column_shape_format == "lonlat":
+            shape_df = pd.DataFrame(column.to_list(), columns=("lon", "lat"))
+            shape_test = geos.points(shape_df.lon, y=shape_df.lat)
+        elif column_shape_format == "latlon":
+            shape_df = pd.DataFrame(column.to_list(), columns=("lat", "lon"))
+            shape_test = geos.points(shape_df.lon, y=shape_df.lat)
+        else:
+            raise NotImplementedError("Column values shape format not implemented.")
+
+        # verify that all shapes are points and if not, convert to centroid point.
+        points_test = pd.Series(shape_test)
+        if not points_test.apply(lambda x: geos.get_type_id(x) == 0).all():
+            points_test = points_test.map(geos.centroid)
+
+        # convert the geos point to a geopy point.
+        points_test = points_test.apply(lambda x: lonlat(geos.get_x(x), geos.get_y(x)))
+
+        if location is None:
+            raise Exception("Geocoding failed to return a result.")
+        else:
+            point_ref = lonlat(location.longitude, location.latitude)
+
+        # calculate the distance between the points using geopy
+        if units in ["km", "kilometers", "kilometres", "kilometer", "kilometre"]:
+            column_dist = points_test.apply(lambda p: distance(p, point_ref).km)
+        elif units in ["m", "meters", "metres", "meter", "metre"]:
+            column_dist = points_test.apply(lambda p: distance(p, point_ref).m)
+        elif units in ["mi", "miles", "mile"]:
+            column_dist = points_test.apply(lambda p: distance(p, point_ref).mi)
+        elif units in ["ft", "feet", "foot"]:
+            column_dist = points_test.apply(lambda p: distance(p, point_ref).ft)
+        else:
+            raise NotImplementedError(
+                "Unit conversion has not yet been implemented. Please use one of km, m, mi, ft"
+            )
+
+        # Evaluate the between statement (from column_values_between.py)
+        if min_value is None:
+            if strict_max:
+                return column_dist < max_value
+            else:
+                return column_dist <= max_value
+
+        elif max_value is None:
+            if strict_min:
+                return min_value < column_dist
+            else:
+                return min_value <= column_dist
+
+        else:
+            if strict_min and strict_max:
+                return (min_value < column_dist) & (column_dist < max_value)
+            elif strict_min:
+                return (min_value < column_dist) & (column_dist <= max_value)
+            elif strict_max:
+                return (min_value <= column_dist) & (column_dist < max_value)
+            else:
+                return (min_value <= column_dist) & (column_dist <= max_value)
+
+    @staticmethod
+    def geocode(geocoder, config, query, query_config):
+        cls = geocoders.get_geocoder_for_service(geocoder)
+        geolocator = cls(**config)
+        location = geolocator.geocode(query, **query_config)
+        return location
+
+    # #This method defines the business logic for evaluating your metric when using a SqlAlchemyExecutionEngine
+    # @column_condition_partial(engine=SqlAlchemyExecutionEngine)
+    # def _sqlalchemy(cls, column, _dialect, **kwargs):
+    #     raise NotImplementedError
+
+    # #This method defines the business logic for evaluating your metric when using a SparkDFExecutionEngine
+    # @column_condition_partial(engine=SparkDFExecutionEngine)
+    # def _spark(cls, column, **kwargs):
+    #     raise NotImplementedError
+
+
+# This class defines the Expectation itself
+class ExpectColumnValuesGeometryDistanceToAddressToBeBetween(ColumnMapExpectation):
+    """
+    Expect that column values as geometry points to be between a certain distance from a geocoded object. 
+    
+    expect_column_values_geometry_distance_to_address_to_be_between is a :func:`column_map_expectation <great_expectations.dataset.dataset.MetaDataset.column_map_expectation>`.
+    
+    Args:
+        column (str): \
+            The column name.
+            Column values must be provided in lon-lat or lat-long tuples/lists, WKT or WKB format, which are commom formats for GIS Database formats.
+            WKT can be accessed thhrough the ST_AsText() or ST_AsBinary() functions in queries for PostGIS and MSSQL. 
+            Values must be in longitude - latitude coordinates for this method to work with geocoding.
+    
+    Keyword Args:
+        place: str
+            The country, place, address, etc. to query. Expect to return a point from geocoder (Default: OpenStreetMaps (Nominatim)).
+            Note that this method uses the Latitude - Longitude Point returned by the geocoder, and not the shape(geometry)
+        column_shape_format: str
+            Geometry format for 'column' (wkt, wkb, lonlat, latlon). Column values can be provided in WKT or WKB format, which are commom formats for GIS Database formats.
+            latlon or lonlat also supports tuple pairs or list pairs in either Longtitude or Latitude first formats. 
+            WKT can be accessed thhrough the ST_AsText() or ST_AsBinary() functions in queries for PostGIS and MSSQL.
+            
+        geocoder: str
+            Geocoder from GeoPy to use to return the shape. While this is generic, the api is required to be available from GeoPy and must return a geometry.
+        
+        geocoder_config: dict(str)
+            arguments to initialize the GeoPy geocoder. e.g. for paid services, an API_key is usually required. See GeoPy for reference.
+            
+    Returns:
+        An ExpectationSuiteValidationResult
+    
+    Notes:
+        The user is responsible to transform the column to a WKT or WKB format that is in the WGS84 coordianate system for earth. 
+        Any geometry can be provided in the column value, but if it is not a POINT, the centroid will be evaluated. 
+        Invalid geometries import as None and fail the test.
+        Other Coordinate Reference Systems are not yet supported.
+    """
+
+    # These examples will be shown in the public gallery.
+    # They will also be executed as unit tests for your Expectation.
+    examples = [
+        {
+            "data": {
+                "point_array": [
+                    "POINT(-75.682729 45.4437213)",
+                    "POINT(-75.6987003 45.4237274)",
+                    "POINT(-75.69660 45.428057)",
+                    "POINT(-75.668226 45.321924)",
+                    "POINT(-75.702662 45.420936)",
+                ],
+            },
+            "tests": [
+                {
+                    "title": "positive_test_with_points",
+                    "exact_match_out": False,
+                    "include_in_gallery": True,
+                    "in": {
+                        "column": "point_array",
+                        "place": "24 Sussex Drive, Ottawa, ON",
+                        "min_value": None,
+                        "max_value": 25,
+                        "units": "km",
+                    },
+                    "out": {
+                        "success": True,
+                    },
+                },
+                {
+                    "title": "negative_test_with_points",
+                    "exact_match_out": False,
+                    "include_in_gallery": True,
+                    "in": {
+                        "column": "point_array",
+                        "place": "24 Sussex Drive, Ottawa, ON",
+                        "min_value": 1,
+                        "max_value": 5,
+                        "units": "miles",
+                    },
+                    "out": {"success": False, "unexpected_index_list": [0, 3]},
+                },
+            ],
+        }
+    ]
+
+    # This is the id string of the Metric used by this Expectation.
+    # For most Expectations, it will be the same as the `condition_metric_name` defined in your Metric class above.
+    map_metric = "column_values.geometry.distance_to_address"
+
+    # This is a list of parameter names that can affect whether the Expectation evaluates to True or False
+    success_keys = (
+        "mostly",
+        "column_shape_format",
+        "place",
+        "geocoder",
+        "geocoder_config",
+        "min_value",
+        "max_value",
+        "units",
+    )
+
+    # This dictionary contains default values for any parameters that should have default values
+    default_kwarg_values = {
+        "mostly": 1,
+        "column_shape_format": "wkt",
+        "geocoder": "nominatim",
+        "geocoder_config": dict(user_agent="great_expectations.hacakthon-2022"),
+        "units": "km",
+    }
+
+    def validate_configuration(self, configuration: Optional[ExpectationConfiguration]):
+        """
+        Validates that a configuration has been set, and sets a configuration if it has yet to be set. Ensures that
+        necessary configuration arguments have been provided for the validation of the expectation.
+
+        Args:
+            configuration (OPTIONAL[ExpectationConfiguration]): \
+                An optional Expectation Configuration entry that will be used to configure the expectation
+        Returns:
+            True if the configuration has been validated successfully. Otherwise, raises an exception
+        """
+
+        super().validate_configuration(configuration)
+        if configuration is None:
+            configuration = self.configuration
+
+        min_val = None
+        max_val = None
+        if "min_value" in configuration.kwargs:
+            min_val = configuration.kwargs["min_value"]
+        if "max_value" in configuration.kwargs:
+            max_val = configuration.kwargs["max_value"]
+        assert (
+            min_val is not None or max_val is not None
+        ), "min_value and max_value cannot both be None"
+
+        return True
+
+    # This object contains metadata for display in the public Gallery
+    library_metadata = {
+        "tags": [
+            "geospatial",
+            "hackathon-2022",
+        ],  # Tags for this Expectation in the Gallery
+        "contributors": [  # Github handles for all contributors to this Expectation.
+            "@pjdobson",  # Don't forget to add your github handle here!
+        ],
+        "requirements": ["pygeos", "geopy"],
+    }
+
+
+if __name__ == "__main__":
+    ExpectColumnValuesGeometryDistanceToAddressToBeBetween().print_diagnostic_checklist()


Test patch: