Rafael Henrique da Silva Correia rafaelhenrique

Commit, clone a container

To 'clone' a container, you'll have to make an image of that container first, you can do so by "committing" the container. Docker will (by default) pause all processes running in the container during commit to preserve data-consistency.

For example;

docker commit --message="Snapshot of my container" my_container my_container_snapshot:yymmdd

PSQL

Magic words:

psql -U postgres

Some interesting flags (to see all, use -h or --help depending on your psql version):

-E: will describe the underlaying queries of the \ commands (cool for learning!)
-l: psql will list all databases and then exit (useful if the user you connect with doesn't has a default database, like at AWS RDS)

Octave CheatSheet

GNU Octave is a high-level interpreted language, primarily intended for numerical computations.
(via GNU Octave)

Hint: I also mad an octave docset for Dash: https://github.com/obstschale/octave-docset

Basics

Markdown cheatsheet

(Also see [remarkable][], the markdown parser created by the author of this cheatsheet)

	class AllowPUTAsCreateMixin(object):
	"""
	The following mixin class may be used in order to support PUT-as-create
	behavior for incoming requests.
	"""
	def update(self, request, args, *kwargs):
	partial = kwargs.pop('partial', False)
	instance = self.get_object_or_none()
	serializer = self.get_serializer(instance, data=request.data, partial=partial)
	serializer.is_valid(raise_exception=True)

	package main

	import "fmt"

	func sumSlices(x[]float64, y[]float64) float64 {

	totalx := 0.0
	for _, valuex := range x {
	totalx += valuex
	}

	func readLine(path string) {
	inFile, _ := os.Open(path)
	defer inFile.Close()
	scanner := bufio.NewScanner(inFile)
	scanner.Split(bufio.ScanLines)

	for scanner.Scan() {
	fmt.Println(scanner.Text())
	}
	}

	# Output to a jpeg file
	set terminal jpeg size 1280,720

	# Set the aspect ratio of the graph
	set size 1, 1

	# The file to write to
	set output "timeseries.jpg"

	# The graph title

	#!/usr/bin/env python
	"""
	Produces load on all available CPU cores
	"""

	from multiprocessing import Pool
	from multiprocessing import cpu_count

	def f(x):
	while True: