JSON and SVG from PostGIS into Google Sheets

At PostGIS Day 2023, one of our speakers showed off a really cool demo for getting JSON and SVGs in and out of Postgres / PostGIS and into Google Sheets. Brian Timoney put together several open source projects in such a cool way that I just had to try it myself. If you want to see his demo video, it is on YouTube. With Brian’s blessing, I’m writing up some additional details with a few of the sample code bits for those of you that want to try this or something similar for your own projects.

So what do we have here? We have Postgres data that is coming into Google sheets in real time, tied to a custom SVG.

hockey spreadsheet.png

Before we dive in, an overview of things that I’ll cover to make this happen :

Running pg_featureserv from inside a database
Serving JSON data from Postgres with pg_featureserv
Functions to create SVG imasges
Serving SVG images from Postgres with pg_featureserv
JSON & SVGs delivered to Google Sheets

postgis svg google sheet overview image

pg_svg functions

Brian wrote some special stuff for the goal and shot data in his examples to get it just right so if you want to play with a sample of that, here’s some data for you.

Sample data

-- Regular season goals of Colorado Avalanche for 2021-2022 season
--

-- information derived from public NHL API
-- shot locations normalized for offensive end of ice
-- hex_id was derived for a demo for the 2022 PostGIS Day demo

SET client_encoding = 'UTF8';

CREATE TABLE public.goals (
    rec_num integer,
    game_id text,
    this_event text,
    this_event_code text,
    players text,
    playerid text,
    player_role text,
    x_coord text,
    y_coord text,
    team_scored text,
    period_num text,
    period_type text,
    plot_x numeric,
    plot_y numeric,
    plot_pt public.geometry(Point,32613),
    hex_id numeric
);

ALTER TABLE public.goals OWNER TO postgres;

INSERT INTO public.goals VALUES (26, '2021020005', 'Goal', 'COL24', 'Jack Johnson', '8471677', 'Scorer', '-77.0', '1.0', 'Colorado Avalanche', '1', 'REGULAR', 77.0, -1.0, '01010000000000000000405340000000000000F0BF', 258);
INSERT INTO public.goals VALUES (5997, '2021020982', 'Goal', 'SJS204', 'Darren Helm', '8471794', 'Scorer', '-76.0', '5.0', 'Colorado Avalanche', '1', 'REGULAR', 76.0, -5.0, '0101000000000000000000534000000000000014C0', 257);
INSERT INTO public.goals VALUES (2432, '2021020415', 'Goal', 'COL45', 'Darren Helm', '8471794', 'Scorer', '-75.0', '-3.0', 'Colorado Avalanche', '1', 'REGULAR', 75.0, 3.0, '01010000000000000000C052400000000000000840', 258);

Sample data for the rink (this is a DXF CAD file encoded as a geometry string)

  -- Rink map created from random DXF file found on internet
  --
  -- ** IMPORTANT: SRID of 32613 is fake!! It is just an arbitrary X/Y plane

SET client_encoding = 'UTF8';

CREATE TABLE public.therink ( id_num integer, geom
public.geometry(MultiLineString,32613) );

ALTER TABLE public.therink OWNER TO postgres;

INSERT INTO public.therink VALUES (1,
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The special visual functions you will see with the shots and the rink are done with some functions for Postgres in pg_svg. This isn’t really an extension, it is just a handy functions you can load into any Postgres database to help create SVGs. To load this in your database download it and run something like:

psql postgres://postgres:123155012sdfxxcwsdfweweff@p.aqlunx3nqvebfh2bgffjj364ey.db.postgresbridge.com:5432/postgres < pg-svg-lib.sql

Brian wrote two sample SVG shot chart functions for this project. One large and one small that could fit inside a spreadsheet if that’s your final data destination.

Big chart function

-- FUNCTION: postgisftw.big_chart(text)

-- pg_featureserv looks for functions in the 'postgisftw' schema

-- ** IMPORTANT  SRID 32613 is 'fake', just needed a planar projection to work with the arbitrary X/Y of the rink

CREATE OR REPLACE FUNCTION postgisftw.big_chart(
	player_id text DEFAULT '8476455'::text) -- if no id, then Landeskog goals
    RETURNS TABLE(svg text)
    LANGUAGE 'plpgsql'
    COST 100
    STABLE STRICT PARALLEL UNSAFE
    ROWS 1000

AS $BODY$
BEGIN
  RETURN QUERY

  -- we only want to display the offensive end of the rink
with half_rink as (
select st_intersection(therink.geom,ST_SetSRID(ST_MakeBox2D(ST_Point(-0.1, 42.55), ST_Point(101, -42.55)), 32613))
as geom
from therink
),

goals as (
-- collect all of a player's goals into a single geometry
select 	ST_SetSRID(st_collect(geom)::geometry, 32613) as geom
	from
(	SELECT
	st_intersection(ST_SetSRID(goals.plot_pt,32613),ST_SetSRID(ST_MakeBox2D(ST_Point(-0.1, 42.55), ST_Point(101, -42.55)), 32613))
 	as geom
 	from postgisftw.goals
	WHERE playerid ILIKE player_id || '%'

)q1
),
   -- get player name, team total number of goals for title display
playerinfo AS (

	select UPPER(q1.players) as this_player,min(q1.team_scored) as this_team
	, count(q1.playerid)::text as num_goals from
	(
	select a.players,a.playerid,a.team_scored
	from postgisftw.goals a WHERE playerid ILIKE player_id || '%'
	) q1
	group by q1.players

),

-- make the SVG document

shapes AS (

  --rink styling
  SELECT geom, svgShape( geom,
    style => svgStyle(  'stroke', '#2E9AFE',
                        'stroke-width', 0.5::text )
					   )
    svg FROM half_rink

  UNION ALL
	-- goals styling
	SELECT geom, svgShape( geom,
    style => svgStyle(  'stroke', '#F5A9A9',
                        'stroke-width', 0.5::text,
					  	'fill','#FF0040'
					    					 )
					   )
    svg FROM goals

	UNION ALL
	-- player name, team, and total number of goals
	-- create an arbitrary point underneath the rink and reasonably centered
	SELECT NULL, svgText(ST_SetSRID(ST_MakePoint(50,-46),32613),this_player||'  ('||this_team||') -  '||num_goals||' goals',
	style => svgStyle(  'fill', '#585858', 'text-anchor', 'middle', 'font', 'bold 3px sans-serif' ) )
    svg
	from playerinfo

)
-- create the final viewbox
-- Martin Davis uses a sensible default of expanding the collected geometry
-- since our rink geometry is static, I hard coded a viewbox
SELECT svgDoc( array_agg( shapes.svg ),
	viewbox => '-2.1 -44.5 104.4 93'
    --viewbox => svgViewbox( ST_Expand( ST_Extent(geom), 2))
  ) AS svg FROM shapes
  ;
END;
$BODY$;

ALTER FUNCTION postgisftw.big_chart(text)
    OWNER TO postgres;

The big chart will be centered in the browser with no height and width specification in the first line. In addition, we have added a title line with player name, team, and number of goals.

Cell size chart function

  -- FUNCTION: postgisftw.cell_chart(text)

  -- DROP FUNCTION IF EXISTS postgisftw.cell_chart(text);

  -- pg_featureserv looks for functions in the 'postgisftw' schema

  -- TO GET OUR CHART TO DISPLAY REASONABLY IN Google Sheets we need three adjustments:
  --  1) 'shrink' the geometries to 40% of their default size applying ST_SCALE
  --  2) Use ST_TRANSLATE to slide the upper left corner of the rink to (0,0) -- as much as practical
  --  3) Add a hard coded set of height and width values to the final SVG document

  -- ** IMPORTANT  SRID 32613 is 'fake', just needed a planar projection to work with the arbitrary X/Y of the rink

  CREATE OR REPLACE FUNCTION postgisftw.cell_chart(
  	rec_num_id text DEFAULT '4668'::text -- if no id, then Landeskog goal
  	)
      RETURNS TABLE(svg text)
      LANGUAGE 'plpgsql'
      COST 100
      STABLE STRICT PARALLEL UNSAFE
      ROWS 1000

  AS $BODY$
  BEGIN
    RETURN QUERY

  with half_rink as (

  select st_translate(     -- Scale and Translate for Google Sheets use case
  	st_scale(q1.geom,0.4,0.4)
  	,-2,-18
  ) as geom from
  	(
  		-- we only want to display the offensive end of the rink
  		select st_intersection(therink.geom,ST_SetSRID(ST_MakeBox2D(ST_Point(-0.1, 42.55), ST_Point(101, -42.55)), 32613))
  		as geom
  		from therink
  	) q1
  ),
  goals as (
  select
  	st_translate(   -- Scale and Translate for Google Sheets use case
  	st_scale(q2.geom,0.4,0.4)
  	,-2,-18 )
  	 as geom from
  	(
  		-- collect all of a player's goals into a single geometry
  		SELECT ST_SetSRID(st_collect(geom)::geometry, 32613) as geom
  		from
  		(	SELECT
  			st_intersection(ST_SetSRID(goals.plot_pt,32613),ST_SetSRID(ST_MakeBox2D(ST_Point(-0.1, 42.55), ST_Point(101, -42.55)), 32613))
  			as geom
  			from postgisftw.goals
  			WHERE rec_num = rec_num_id::INTEGER -- uses the rec_num id fed into the function
  		)q1
  	)q2
  ),

  shapes AS (

    -- Rink SVG + styling
    SELECT geom, svgShape( geom,
      style => svgStyle(  'stroke', '#2E9AFE',
                          'stroke-width', 0.5::text )
  					   )
      svg FROM half_rink

    UNION ALL

  	-- goals SVG + styling
  	SELECT geom, svgShape( geom,
      style => svgStyle(  'stroke', '#F5A9A9',
                          'stroke-width', 0.5::text,
  					  	'fill','#FF0040'
  					    					 )
  					   )
      svg FROM goals

  )
  	--IMPORTANT we are hard-coding the extent of the document + adding height and width explicitly
  	--Google Sheets needs the height and width of the document specified (apparently)

  SELECT svgDoc( array_agg( shapes.svg ),
   	'0 0 43 36" width="43mm" height="36mm '  --**WARNING -- hard coded values
    ) AS svg FROM shapes
    ;
  END;
  $BODY$;

  ALTER FUNCTION postgisftw.cell_chart(text)
      OWNER TO postgres;

The small chart is scaled down, and the content is shifted to the origin of the SVG coordinate space ( 0,0 is in the upper left corner). In the small chart, you can see we have added width and height parameters in millimeters.

pg_featureserv = JSON and SVG URLs from Postgres

pg_featureserv is a project that will run a separate lightweight Go server on top of your Postgres database to expose JSON, Geojson, and (newly) SVGs. pg_featureserv requires data to have a spatial reference id (SRID). You can just use a stand-in SRID and that is what is in the example data and functions.

pg_featureserv can be run as its own server and you can also run it from inside your database using the Crunchy Bridge Container Apps feature, based off of the podman project. To build a pg_featureserv container in a database, you’ll run something like this:

SELECT run_container('-dt -p 5433:5433/tcp -e DATABASE_URL="postgres://postgres:Rb3bZ1VZ7dZIUiFiy62J0OHVZybYROJjoDId@p.aqlunx3nqvebfh2bgffjj364ey.db.postgresbridge.com:5432/postgres" -e PGFS_SERVER_HTTPPORT=5433 docker.io/pramsey/pg_featureserv:latest');

pg_featureserv will then be running in a web browser at a link like http://p.aqlunx3nqvebfh2bgffjj364ey.db.postgresbridge.com:5433. To get data from pg_featureserv, you make requests with URLs for the data you want. Here’s a couple of samples:

JSON:

http://p.aqlunx3nqvebfh2bgffjj364ey.db.postgresbridge.com:5433/collections/postgisftw.goals/items.json

SVG:

http://p.aqlunx3nqvebfh2bgffjj364ey.db.postgresbridge.com:5433/functions/postgisftw.cell_chart/items.svg

You can further qualify URLs with player details and other queries in the url strings, like this:

http://p.aqlunx3nqvebfh2bgffjj364ey.db.postgresbridge.com:5433/functions/postgisftw.cell_chart/items.svg?player_id=8471677

Here’s your resulting SVG file displayed at a browser URL.

svg in browser featureservs

Google sheets import of JSON and SVG

To load the JSON data into a Google Sheet, the fastest approach is to use Apps Scripts to write some JavaScript to process the JSON into an array of rows containing an array of columns. In a Google Sheet, go to Extensions > App Scripts. Create a new blank script, and replace the generated code with the following:

function ImportJSON(url) {
	const response = UrlFetchApp.fetch(url)
	const jsonString = response.getContentText()
	const data = JSON.parse(jsonString).features.map(feature => ({
		point_x: feature.geometry.coordinates[0],
		point_y: feature.geometry.coordinates[1],
		...feature.properties,
	}))

	const columns = [
		'players',
		'team_scored',
		'period_num',
		'this_event',
		'this_event_code',
		'playerid',
		'game_id',
		'rec_num',
	]

	const rows = data.map(item => columns.map(column => item[column]))

	return [columns].concat(rows)
}

Please note this is a specialized version of the function to only select specific columns and reorder them. To make it more general, replace the columns variable instantiation with something like the following:

const columns = Object.keys(data[0])

Consider renaming the file to something like ImportJSON.gs then save the file as the last step. This will provide an ImportJSON() function we can use within the Google Sheet. In your Google Sheet, enter into a cell like A1 and use the something like this to combine bring in the JSON data with a limit or filters:

=ImportJSON("http://p.aqlunx3nqvebfh2bgffjj364ey.db.postgresbridge.com:5433/collections/postgisftw.goals/items.json?limit=50")

This will load the JSON data into the Google Sheet starting at A1.

To make a SVG ready for Google Sheet, use the Google Sheets IMAGE function with the pg_featureserv URL. Concatenating the URL lets us tie the JSON row to the right SVG data.

=IMAGE(CONCATENATE("http://p.aqlunx3nqvebfh2bgffjj364ey.db.postgresbridge.com:5433/functions/postgisftw.cell_chart/items.svg?rec_num_id=", B1))

Here’s a view of our final spreadsheet

google sheet screenshot

Open source for the win

Crunchy Data supports both pg_featureserv and pg_svg until I saw this talk, I had no idea they would work together. Martin obviously did because he wrote them both! The best part is that our fully managed Crunchy Bridge supported all of this, so it was super easy for me to set this up on a test sersver and tear it down when I'm finished testing.

Thanks to Jay Zawrotny for the javascript assistance. A huge thank you to Brian Timoney for letting me experiment with his hockey code and SVGs.

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