Romain Beucher rbeucher

Postgres Cheatsheet

This is a collection of the most common commands I run while administering Postgres databases. The variables shown between the open and closed tags, "<" and ">", should be replaced with a name you choose. Postgres has multiple shortcut functions, starting with a forward slash, "". Any SQL command that is not a shortcut, must end with a semicolon, ";". You can use the keyboard UP and DOWN keys to scroll the history of previous commands you've run.

Setup

installation, Ubuntu

http://www.postgresql.org/download/linux/ubuntu/ https://help.ubuntu.com/community/PostgreSQL

Setting Up Django-Shell Jupyter Notebook in Docker Container

This guide assumes that your django application already running in the container.

1. Install required python packages

You will have to make sure that django-extensions and jupyter packages are installed in the container's python virtual environment.

If you need to shell into the container as root user to do this, you can do so from the host PC:

	## About
	# This script will download the maps and associated meta data for 250k
	# Geological Maps at http://www.geoscience.gov.au/geoportal-geologicalmaps/
	#
	# Running `make all` shall suffice to run this script.

	# ## License
	# This script is licensed CC0 by Andrew Harvey <[email protected]>
	#
	# To the extent possible under law, the person who associated CC0

	import json, datetime

	class RoundTripEncoder(json.JSONEncoder):
	DATE_FORMAT = "%Y-%m-%d"
	TIME_FORMAT = "%H:%M:%S"
	def default(self, obj):
	if isinstance(obj, datetime.datetime):
	return {
	"_type": "datetime",
	"value": obj.strftime("%s %s" % (

	def inside_polygon(x, y, points):
	"""
	Return True if a coordinate (x, y) is inside a polygon defined by
	a list of verticies [(x1, y1), (x2, x2), ... , (xN, yN)].

	Reference: http://www.ariel.com.au/a/python-point-int-poly.html
	"""
	n = len(points)
	inside = False
	p1x, p1y = points[0]

	from stocks import wsgi
	from django.core.exceptions import ObjectDoesNotExist
	from api.models import Stock, Company

	import csv

	csvpath = r'prices.csv'
	batch_size = 500

	t1 = time.time()

	import matplotlib
	from matplotlib.axes import Axes
	from matplotlib.patches import Circle
	from matplotlib.path import Path
	from matplotlib.ticker import NullLocator, Formatter, FixedLocator
	from matplotlib.transforms import Affine2D, BboxTransformTo, Transform
	from matplotlib.projections import register_projection
	import matplotlib.spines as mspines
	import matplotlib.axis as maxis
	import matplotlib.pyplot as plt