python-bigquery-sqlalchemy/sqlalchemy_bigquery/geography.py at main · dataplf/python-bigquery-sqlalchemy · GitHub

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# Permission is hereby granted, free of charge, to any person obtaining a copy of

# this software and associated documentation files (the "Software"), to deal in

# the Software without restriction, including without limitation the rights to

# use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of

# the Software, and to permit persons to whom the Software is furnished to do so,

# subject to the following conditions:

# The above copyright notice and this permission notice shall be included in all

# copies or substantial portions of the Software.

# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR

# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS

# FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR

# COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER

# IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN

# CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

import geoalchemy2

from geoalchemy2.shape import to_shape

import geoalchemy2.functions

from shapely import wkb, wkt

import sqlalchemy.ext.compiler

from sqlalchemy.sql.elements import BindParameter

SRID = 4326 # WGS84, https://spatialreference.org/ref/epsg/wgs-84/

class WKB(geoalchemy2.WKBElement):

"""

Well-Known-Binary data wrapper.

WKB objects hold geographic data in a binary format known as

"Well-Known Binary",

<https://en.wikipedia.org/wiki/Well-known_text_representation_of_geometry>.

These objects are returned from queries and can be used in insert

and queries.

The WKB class is a subclass of the Geoalchemy2 WKBElement class

customized for working with BigQuery.

"""

geom_from_extended_version = "ST_GeogFromWKB"

def __init__(self, data):

super().__init__(data, SRID, True)

@property

def wkt(self):

"""

Return the WKB object as a WKT object.

"""

return WKT(to_shape(self).wkt)

class WKT(geoalchemy2.WKTElement):

"""

Well-Known-Text data wrapper.

WKT objects hold geographic data in a text format known as

"Well-Known Text",

<https://en.wikipedia.org/wiki/Well-known_text_representation_of_geometry>.

You generally shouldn't need to create WKT objects directly, as

text arguments to geographic functions and inserts to GEOGRAPHY

columns are automatically coerced to geographic data.

The WKT class is a subclass of the Geoalchemy2 WKTElement class

customized for working with BigQuery.

"""

geom_from_extended_version = "ST_GeogFromText"

def __init__(self, data):

super().__init__(data, SRID, True)

@property

def wkb(self):

"""

Return the WKT object as a WKB object.

"""

return WKB(wkb.dumps(wkt.loads(self.data)))

class GEOGRAPHY(geoalchemy2.Geography):

"""

GEOGRAPHY type

Use this to define BigQuery GEOGRAPHY columns::

class Lake(Base):

__tablename__ = 'lakes'

name = Column(String)

geog = column(GEOGRAPHY)

See https://googleapis.dev/python/sqlalchemy-bigquery/latest/geography.html

"""

def __init__(self):

super().__init__(

geometry_type=None,

spatial_index=False,

srid=SRID,

)

self.extended = True

# Un-inherit the bind function that adds an ST_GeogFromText.

# It's unnecessary and causes BigQuery to error.

# Some things to note about this:

# 1. bind_expression can't always know the value. When multiple

# rows are being inserted, the values may be different in each

# row. As a consequence, we have to treat all the values as WKT.

# 2. This applies equally to explicitly converting with

# st_geogfromtext, or implicitly with the geography parameter

# conversion.

# 3. We handle different types using bind_processor, below.

bind_expression = sqlalchemy.sql.type_api.TypeEngine.bind_expression

def bind_processor(self, dialect):

"""

SqlAlchemy plugin that controls how values are converted to parameters

When we bind values, we always bind as text. We have to do

this because when we decide how to bind, we don't always know

what the values will be.

This is not a user-facing method.

"""

def process(bindvalue):

if isinstance(bindvalue, WKT):

return bindvalue.data

elif isinstance(bindvalue, WKB):

return bindvalue.wkt.data

else:

return bindvalue

return process

@staticmethod

def ElementType(data, srid=SRID, extended=True):

"""

Plugin for the Geoalchemy2 framework for constructing WKB objects.

The framework wants a callable, which it assumes is a class

(this the name), for constructing a geographic element.

We don't want `WKB` to accept extra arguments that it checks

and ignores, so we do that in this wrapper.

This is not a user-facing method.

"""

if srid != SRID:

raise AssertionError("Bad srid", srid)

if not extended:

raise AssertionError("Extended must be True.")

return WKB(data)

@sqlalchemy.ext.compiler.compiles(geoalchemy2.functions.GenericFunction, "bigquery")

def _fixup_st_arguments(element, compiler, **kw):

"""

Compiler-plugin for the BigQuery that overrides how geographic functions are handled

Geographic function (ST_...) get turned into

`geoalchemy2.functions.GenericFunction` objects by

Geoalchemy2. The code here overrides how they're handeled.

We want arguments passed to have the GEOGRAPHY type associated

with them, when appropriate, where "when appropriate" is

determined by the `function documentation

<https://cloud.google.com/bigquery/docs/reference/standard-sql/geography_functions>`_..

This is not a user-facing function.

"""

argument_types = _argument_types.get(element.name.lower())

if argument_types:

for argument_type, argument in zip(argument_types, element.clauses.clauses):

if isinstance(argument, BindParameter) and (

argument.type is not argument_type

or not isinstance(argument.type, argument_type)

argument.type = argument_type()

return compiler.visit_function(element, **kw)

_argument_types = dict(

st_area=(GEOGRAPHY,),

st_asbinary=(GEOGRAPHY,),

st_asgeojson=(GEOGRAPHY,),

st_astext=(GEOGRAPHY,),

st_boundary=(GEOGRAPHY,),

st_centroid=(GEOGRAPHY,),

st_centroid_agg=(GEOGRAPHY,),

st_closestpoint=(

GEOGRAPHY,

st_clusterdbscan=(GEOGRAPHY,),

st_contains=(

GEOGRAPHY,

st_convexhull=(GEOGRAPHY,),

st_coveredby=(

GEOGRAPHY,

st_covers=(

GEOGRAPHY,

st_difference=(

GEOGRAPHY,

st_dimension=(GEOGRAPHY,),

st_disjoint=(

GEOGRAPHY,

st_distance=(

GEOGRAPHY,

st_dump=(GEOGRAPHY,),

st_dwithin=(

GEOGRAPHY,

st_endpoint=(GEOGRAPHY,),

st_equals=(

GEOGRAPHY,

st_exteriorring=(GEOGRAPHY,),

st_geohash=(GEOGRAPHY,),

st_intersection=(

GEOGRAPHY,

st_intersects=(

GEOGRAPHY,

st_intersectsbox=(GEOGRAPHY,),

st_iscollection=(GEOGRAPHY,),

st_isempty=(GEOGRAPHY,),

st_length=(GEOGRAPHY,),

st_makeline=(

GEOGRAPHY,

st_makepolygon=(

GEOGRAPHY,

st_makepolygonoriented=(GEOGRAPHY,),

st_maxdistance=(

GEOGRAPHY,

st_npoints=(GEOGRAPHY,),

st_numpoints=(GEOGRAPHY,),

st_perimeter=(GEOGRAPHY,),

st_pointn=(GEOGRAPHY,),

st_simplify=(GEOGRAPHY,),

st_snaptogrid=(GEOGRAPHY,),

st_startpoint=(GEOGRAPHY,),

st_touches=(

GEOGRAPHY,

st_union=(

GEOGRAPHY,

st_union_agg=(GEOGRAPHY,),

st_within=(

GEOGRAPHY,

st_x=(GEOGRAPHY,),

st_y=(GEOGRAPHY,),

)

__all__ = ["GEOGRAPHY", "WKB", "WKT"]

python-bigquery-sqlalchemy/sqlalchemy_bigquery/geography.py at main · dataplf/python-bigquery-sqlalchemy · GitHub

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