Xiao Han xiaohan2012

There are certain files created by particular editors, IDEs, operating systems, etc., that do not belong in a repository. But adding system-specific files to the repo's .gitignore is considered a poor practice. This file should only exclude files and directories that are a part of the package that should not be versioned (such as the node_modules directory) as well as files that are generated (and regenerated) as artifacts of a build process.

All other files should be in your own global gitignore file:

Create a file called .gitignore in your home directory and add any filepath patterns you want to ignore.
Tell git where your global gitignore file is.

Note: The specific name and path you choose aren't important as long as you configure git to find it, as shown below. You could substitute .config/git/ignore for .gitignore in your home directory, if you prefer.

Cython

Cython has two major benefits:

Making python code faster, particularly things that can't be done in scipy/numpy
Wrapping/interfacing with C/C++ code

Cython gains most of it's benefit from statically typing arguments. However, statically typing is not required, in fact, regular python code is valid cython (but don't expect much of a speed up). By incrementally adding more type information, the code can speed up by several factors. This gist just provides a very basic usage of cython.

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

	;; make sure you've set your default project with:
	;; gcloud config set project <project-name>

	(require 'tramp)
	(add-to-list 'tramp-methods
	'("gcssh"
	(tramp-login-program "gcloud compute ssh")
	(tramp-login-args (("%h")))
	(tramp-async-args (("-q")))
	(tramp-remote-shell "/bin/sh")

	#include <cstddef> /* NULL */
	#include <metis.h>
	#include <iostream>


	// Install metis from:
	// http://glaros.dtc.umn.edu/gkhome/fetch/sw/metis/metis-5.1.0.tar.gz

	// Build with
	// g++ metis.cc -lmetis

	#!/usr/bin/env python
	# -- coding: utf-8 --
	"""
	calculate a weighted median
	@author Jack Peterson ([email protected])
	"""
	from __future__ import division
	import numpy as np

	def weighted_median(data, weights):

	# (C) Mathieu Blondel, November 2013
	# License: BSD 3 clause

	import numpy as np


	def ranking_precision_score(y_true, y_score, k=10):
	"""Precision at rank k

	Parameters

	class Person (db.Document):

	name = db.StringField(required=True)
	created_date = db.ComplexDateTimeField(default=datetime.datetime.utcnow(), required=True)

	def to_dict(self):
	return helper.mongo_to_dict(self,[])

	#helper.py
	def mongo_to_dict(obj, exclude_fields):