John J Czaplewski jczaplew

Rolling tiles sans Tilemill

Perhaps you've had problems programmatically creating tiles with Tilemill, or are concerned about the future stability of project (or you just like playing with geo software).

Install mapnik and TileStache

brew install mapnik --with-gdal --with-postgresql
sudo pip install -U PIL modestmaps simplejson werkzeug
git clone https://github.com/TileStache/TileStache.git TileStache
cd TileStache

Hi ---- person sending email ---,

That does sounds interesting - I love --- book title ---. However, it is my understanding that Packt Publishing is a for-profit corporation and will be selling this book, yet wants me to contribute pro bono. Because there are so many nonprofits that are in desperate need of people, I cannot justify donating my spare time to an entity that will turn around and profit from it.

Unless you are willing to pay me (with money, not a book), or donate all profits from the sale of this book to a charity, I am not interested in reviewing this book. Time is too precious.

Best,

--- you ---

Follow up on https://twitter.com/johnjcz/status/570227819709493249

Overall both are great, but have different deficiencies

pgweb

Pros:

Fast
Hackable
Free
Keyboard shortcuts

Save get_data.sh
chmod +x get_data.sh
./get_data.sh
This will produce a folder columns that contains a shapefile of all Macrostrat column geometry, and a folder mibasin that contains a shapefile of the GMUS data for the Michigan Basin

	CREATE DATABASE test;
	CREATE EXTENSION postgis;
	CREATE SCHEMA rasters;

	CREATE TABLE rasters.my_rasters (
	id serial NOT NULL,
	rast raster,
	CONSTRAINT enforce_pixel_types_rast CHECK ((public._raster_constraint_pixel_types(rast) = '{16BSI}'::text[]))
	);

	from bs4 import BeautifulSoup
	import json

	xml = ""
	with open("dump/sentences.txt.xml") as input:
	xml = input.read()

	soup = BeautifulSoup(xml, "xml")

	output = {"sentences": [{

	import urllib2
	import sys, os
	from StringIO import StringIO
	from zipfile import ZipFile
	import psycopg2
	import subprocess

	# Connect to Postgres
	pg_conn = psycopg2.connect(dbname="database", user="you", host="localhost", port=5432)
	pg_cur = pg_conn.cursor()

	// Convert Javascript date to Pg YYYY MM DD HH MI SS

	function pgFormatDate(date) {
	/* Via http://stackoverflow.com/questions/3605214/javascript-add-leading-zeroes-to-date */
	function zeroPad(d) {
	return ("0" + d).slice(-2)
	}

	var parsed = new Date(date)

	CREATE TABLE test (
	some_arrays int[]
	);

	INSERT INTO test (some_arrays) VALUES (array[1,2,3]), (array[3,4,5]), (array[5,6,7]), (array[7,8,9]);

	WITH first_query AS (
	SELECT 1 AS arbitrary_group_by, unnest(some_arrays) AS my_numbers
	FROM test
	)

	CREATE TABLE pattern_test (field1 text, field2 text);
	INSERT INTO pattern_test VALUES ('abc', '123 abc 546'), ('def', '123def546'), ('xyz', 'xyz something'), ('abo', 'something about something');

	-- We want to find all records where field2 contains field1 as a distinct string (i.e. get records 0 and 2)
	-- ~* is similar to ILIKE, but accepts a regular expression
	-- '\y' will make sure that field1 is always a distinct object in field2

	SELECT * FROM pattern_test WHERE field2 ~* concat('\y',field1,'\y');