Пример #1
0
    def set_up(self):

        data_df = read_csv("datapoints/tests/_data/calc_data.csv")
        self.create_metadata()
        self.user = User.objects.get(username="******")

        self.test_df = data_df[data_df["is_raw"] == 1]
        self.target_df = data_df[data_df["is_raw"] == 0]

        ltr = LocationTreeCache()
        ltr.main()
Пример #2
0
    def set_up(self):

        data_df = read_csv('datapoints/tests/_data/calc_data.csv')
        self.create_metadata()
        self.user = User.objects.get(username="******")

        self.test_df = data_df[data_df['is_raw'] == 1]
        self.target_df = data_df[data_df['is_raw'] == 0]

        ltr = LocationTreeCache()
        ltr.main()
Пример #3
0
    def test_cache_location_tree(self):
        '''
        The point of this test is that it the cache_location_tree function
        creates database rows that represents each parent / child relationship
        between all locations, from the stored information.

        That is, if we say that NYC is a sub-location of NYState, and NYState
        is a sub-location of U.S.A. , then that means that we should have a row
        in the LocationTree table rebresenting the fact that both Nystate AND
        U.S.A. are parent_location's on New York City.
        '''

        location_batch = []

        office = Office.objects.create(name='not important')
        location_type_country = LocationType.objects.create(name='Country',\
            admin_level=0,id=1)
        location_type_state = LocationType.objects.create(name='State',\
            admin_level=1,id=2)
        location_type_city = LocationType.objects.create(name='City',\
            admin_level=2,id=3)
        location_type_city = LocationType.objects.create(name='Neighborhood',\
            admin_level=3,id=4)

        location_data = {
                'id':[1,2,3,4,5,6,7,8],
                'location_type_id':[1,2,3,2,2,2,3,4],
                'name': ['U.S.A.','New York State','New York City','Texas',\
                    'California','Maine','Portland, ME','Brooklyn'],
                'parent_location_id': [None,1,2,1,1,1,6,3]
            }

        df = DataFrame.from_dict(location_data)
        df.set_index('id', inplace=True, drop=False, append=False)
        no_nan_df = df.where((notnull(df)), None)

        for ix, loc in no_nan_df.iterrows():
            location_batch.append(Location(**{
                'id':loc.id,
                'name':loc.name,
                'location_code': unicode(loc.name).replace(' ',''),
                'office_id':office.id,
                'location_type_id':loc.location_type_id,
                'parent_location_id':loc.parent_location_id
            }))

        Location.objects.bulk_create(location_batch)

        ## now use the following function to transform the location_tree ##
        ltc = LocationTreeCache()
        ltc.main()

        location_tree_in_db = LocationTree.objects.all()\
            .values_list('location_id','parent_location_id')

        ## the ultimate parent, should have a with itself is parent ##
        self.assertTrue((1,1) in location_tree_in_db)

        ## Brooklyn However should not be the parent of itself ##
        self.assertFalse((8,8) in location_tree_in_db)

        ## new york city has a parent of NY State AND U.S.A ##
        self.assertTrue((3,1) in location_tree_in_db)
        self.assertTrue((3,2) in location_tree_in_db)

        ## Portland ME has a parent of Maine AND U.S.A ##
        self.assertTrue((7,1) in location_tree_in_db)
        self.assertTrue((7,6) in location_tree_in_db)

        # ## new york state and maine are children of USA #
        self.assertTrue((2,1) in location_tree_in_db)
        self.assertTrue((6,1) in location_tree_in_db)

        ## Brooklkyn has, NYC, NYState and USA as parents ##
        self.assertTrue((8,3) in location_tree_in_db)
        self.assertTrue((8,2) in location_tree_in_db)
        self.assertTrue((8,1) in location_tree_in_db)
Пример #4
0
    def test_cache_location_tree(self):
        '''
        The point of this test is that it the cache_location_tree function
        creates database rows that represents each parent / child relationship
        between all locations, from the stored information.

        That is, if we say that NYC is a sub-location of NYState, and NYState
        is a sub-location of U.S.A. , then that means that we should have a row
        in the LocationTree table rebresenting the fact that both Nystate AND
        U.S.A. are parent_location's on New York City.
        '''

        location_batch = []

        office = Office.objects.create(name='not important')
        location_type_country = LocationType.objects.create(name='Country',\
            admin_level=0,id=1)
        location_type_state = LocationType.objects.create(name='State',\
            admin_level=1,id=2)
        location_type_city = LocationType.objects.create(name='City',\
            admin_level=2,id=3)
        location_type_city = LocationType.objects.create(name='Neighborhood',\
            admin_level=3,id=4)

        location_data = {
                'id':[1,2,3,4,5,6,7,8],
                'location_type_id':[1,2,3,2,2,2,3,4],
                'name': ['U.S.A.','New York State','New York City','Texas',\
                    'California','Maine','Portland, ME','Brooklyn'],
                'parent_location_id': [None,1,2,1,1,1,6,3]
            }

        df = DataFrame.from_dict(location_data)
        df.set_index('id', inplace=True, drop=False, append=False)
        no_nan_df = df.where((notnull(df)), None)

        for ix, loc in no_nan_df.iterrows():
            location_batch.append(
                Location(
                    **{
                        'id': loc.id,
                        'name': loc.name,
                        'location_code': unicode(loc.name).replace(' ', ''),
                        'office_id': office.id,
                        'location_type_id': loc.location_type_id,
                        'parent_location_id': loc.parent_location_id
                    }))

        Location.objects.bulk_create(location_batch)

        ## now use the following function to transform the location_tree ##
        ltc = LocationTreeCache()
        ltc.main()

        location_tree_in_db = LocationTree.objects.all()\
            .values_list('location_id','parent_location_id')

        ## the ultimate parent, should have a with itself is parent ##
        self.assertTrue((1, 1) in location_tree_in_db)

        ## Brooklyn However should not be the parent of itself ##
        self.assertFalse((8, 8) in location_tree_in_db)

        ## new york city has a parent of NY State AND U.S.A ##
        self.assertTrue((3, 1) in location_tree_in_db)
        self.assertTrue((3, 2) in location_tree_in_db)

        ## Portland ME has a parent of Maine AND U.S.A ##
        self.assertTrue((7, 1) in location_tree_in_db)
        self.assertTrue((7, 6) in location_tree_in_db)

        # ## new york state and maine are children of USA #
        self.assertTrue((2, 1) in location_tree_in_db)
        self.assertTrue((6, 1) in location_tree_in_db)

        ## Brooklkyn has, NYC, NYState and USA as parents ##
        self.assertTrue((8, 3) in location_tree_in_db)
        self.assertTrue((8, 2) in location_tree_in_db)
        self.assertTrue((8, 1) in location_tree_in_db)