Using PostGIS with SQLAlchemy

Wyatt — Tue, 30 Jan 2007 06:35:17 +0000

The development version of the Trip Planner uses a Postgres/PostGIS backend (instead of MySQL) SQLAlchemy as the ORM (instead of raw SQL), and PCL for Python geometry types (instead of our own ugly hacked versions).

Question: How do you move geometries out of Postgres/PostGIS into PCL types via SQLAlchemy and vice versa?

Answer: Create a custom geometry column type.

Here’s our SQLAlchemy geometry type definition and subtypes (points, linestrings, and multilinestrings; adding other types should be trivial):

sqltypes.py

Look here for an example of using it:

tables.py

The type is pretty simple. The only tricky part was figuring out how the database stores the geometry. It’s in ASCII hex, so we use binascii.a2b_hex to get a binary representation and feed that to the PCL fromWKB factory. In the other direction we use binascii.b2a_hex on the WKB representation of the PCL geometry.

[8/7/09: Updated links to source code. Note: latest version uses Shapely, not PCL.]

Python Cartographic Library (PCL) — Installing Just the Spatial Package

Wyatt — Mon, 25 Sep 2006 08:26:48 +0000

So let’s say you need a spatial geometry library for Python. You could write your own; you could also use the PCL. The PCL includes some packages we don’t need, like one for MapServer rendering. I only installed the minimum needed to get the spatial package working (which I’ll talk about below).

[Note: "geometry" refers to points, lines, polygons and other geometric forms used to represent real-world objects. Examples: intersection (point), street (line), zip code boundary (polygon).]

I wrote a rudimentary geometry library for the trip planner that’s been working fine, but now I need to do some more “advanced” stuff related to using PostGIS and SQLAlchemy. In particular, I want to convert database values to Python objects and vice versa.

The first part (database to Python) is fairly easy and our current library already does that, but it’s convoluted in that it gets the database value as well-known text (WKT), parses that, and creates a Python object. From what I can tell, the PCL can go straight from well-known binary (WKB) geometry to Python objects.

The second part (Python to database) is harder because it involves converting a Python object to a binary geometry value. I don’t know anything about the binary geometry format and I don’t want to know, and it looks like with the PCL I don’t need to know.

I’m assuming PostGIS and PCL will get along together because they both rely on the same libraries, proj4 and geos. We’ll see.

The installation was fairly straightforward. The PCL includes five sub-packages. We had to install two of them, PCL-Referencing and PCL-Spatial. PCL-Referencing requires proj4. PCL-Spatial requires PCL-Referencing and geos >= 2.2.2. Something in there also requires the OGR library, which is included with GDAL.

The basic steps are, install proj, geos, and gdal, then install PCL-Referencing, and lastly install PCL-Spatial. On Ubuntu 6.06 (Dapper), here’s what I actually did:

Installed proj4 using apt-get
Installed libgdal using apt-get
Installed geos 2.2.3 from source into /usr/lib. I installed this over a slightly older version of geos installed using apt-get; hopefully that won’t cause any issues.
Checked out the PCL trunk:
svn co http://svn.gispython.org/gispy/PCL/trunk PCL
Installed PCL-Referencing with the usual python setup.py install
Installed PCL-Spatial with the usual…

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Using PostGIS with SQLAlchemy

Python Cartographic Library (PCL) — Installing Just the Spatial Package