isaacs

echo 'export PATH=$HOME/local/bin:$PATH' >> ~/.bashrc
. ~/.bashrc
mkdir ~/local
mkdir ~/node-latest-install
cd ~/node-latest-install
curl http://nodejs.org/dist/node-latest.tar.gz | tar xz --strip-components=1
./configure --prefix=~/local
make install # ok, fine, this step probably takes more than 30 seconds...
curl https://www.npmjs.org/install.sh | sh

vsajip

import logging
try:
    import Queue as queue
except ImportError:
    import queue
import threading

class QueueHandler(logging.Handler):
    """
    This handler sends events to a queue. Typically, it would be used together

pksunkara

# vi: ft=dosini
[user]
	name = Pavan Kumar Sunkara
	email = pavan.sss1991@gmail.com
	username = pksunkara
[core]
	editor = nvim
	whitespace = fix,-indent-with-non-tab,trailing-space,cr-at-eol
	pager = delta
[column]

gregplaysguitar

# -*- coding: utf-8 -*-

"""
Whoosh backend for haystack that implements character folding, as per 
http://packages.python.org/Whoosh/stemming.html#character-folding .

Tested with Haystack 2.4.0 and Whooch 2.7.0

To use, put this file on your path and add it to your haystack settings, eg.

dupuy

Markdown and reStructuredText

GitHub supports several lightweight markup languages for documentation; the most popular ones (generally, not just at GitHub) are Markdown and reStructuredText. Markdown is sometimes considered easier to use, and is often preferred when the purpose is simply to generate HTML. On the other hand, reStructuredText is more extensible and powerful, with native support (not just embedded HTML) for tables, as well as things like automatic generation of tables of contents.

awidegreen

Introduction

• C-a == Ctrl-a
• M-a == Alt-a

General

:q        close
:w        write/saves
:wa[!]    write/save all windows [force]
:wq       write/save and close

kroger

# -*- coding: utf-8 -*-

import sys, os

sys.path.insert(0, os.path.abspath('extensions'))

extensions = ['sphinx.ext.autodoc', 'sphinx.ext.doctest', 'sphinx.ext.todo',
              'sphinx.ext.coverage', 'sphinx.ext.pngmath', 'sphinx.ext.ifconfig',
              'epub2', 'mobi', 'autoimage', 'code_example']

dan-blanchard

For ETS's SKLL project, we found out the hard way that Travis-CI's support for numpy and scipy is pretty abysmal. There are pre-installed versions of numpy for some versions of Python, but those are seriously out of date, and scipy is not there are at all. The two most popular approaches for working around this are to (1) build everything from scratch, or (2) use apt-get to install more recent (but still out of date) versions of numpy and scipy. Both of these approaches lead to longer build times, and with the second approach, you still don't have the most recent versions of anything. To circumvent these issues, we've switched to using Miniconda (Anaconda's lightweight cousin) to install everything.

A template for installing a simple Python package that relies on numpy and scipy using Miniconda is provided below. Since it's a common s

pv

import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial import Voronoi

def voronoi_finite_polygons_2d(vor, radius=None):
    """
    Reconstruct infinite voronoi regions in a 2D diagram to finite
    regions.

    Parameters

mattiaslundberg

# Install ARCH Linux with encrypted file-system and UEFI
# The official installation guide (https://wiki.archlinux.org/index.php/Installation_Guide) contains a more verbose description.

# Download the archiso image from https://www.archlinux.org/
# Copy to a usb-drive
dd if=archlinux.img of=/dev/sdX bs=16M && sync # on linux

# Boot from the usb. If the usb fails to boot, make sure that secure boot is disabled in the BIOS configuration.

# Set swedish keymap