Chia-Chi Chang c3h3

## fib.py
from itertools import islice, imap, tee
from operator import add

def tail(iterable):
  return islice(iterable, 1, None)

def take(n, iterable):
  return list(islice(iterable, 0, n))

def fibs():

## bot.py
import werobot

robot = werobot.WeRoBot(token='')


@robot.handler
def echo(message):
    return 'Hello World!'

robot.config['HOST'] = '0.0.0.0'

## gist:0fac4740f035c9026e8636b87b75a391
import requests
from pyquery import PyQuery

url = "https://cn.shopbop.com/sale-bags/br/v=1/15355.htm "
res =requests.get(url)
S = PyQuery(res.text)

S("[data-productid]").map(lambda i,e: PyQuery(e).attr("data-productid"))

## gist:71a413de75efd40726e9e6e567bdb33c

      
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                c3h3
                / gist:71a413de75efd40726e9e6e567bdb33c
            
            
              Created
              January 3, 2018 16:24
                — forked from allex/gist:11203573
            
              
                Ubuntu 安装中文字体
              
          
    环境 (Environment)

版本：Ubuntu 14.04 LTS
默认语言：English(United States)
安装 (Setup)

Debian 和 Ubuntu 下对中文支持比较好的字体有： fonts-droid、ttf-wqy-zenhei 和 ttf-wqy-microhei 等，除了文泉驿系列字体外，比较流行的免费中文字体还有文鼎提供的楷体和上海宋，包名分别是： fonts-arphic-ukai 和 fonts-arphic-uming。

  
## slides
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [

## slides-dem
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [

## fib.sql
-- http://www.sqlite.org/lang_with.html --
WITH RECURSIVE
  fib(current, next) AS (
    SELECT 0 current, 1 next
    UNION ALL
    SELECT fib.next current, fib.current + fib.next next
    FROM fib
    LIMIT 20
  )
SELECT current FROM fib

## webapp-jinja-v1-home.html
<html>
  <head>
      <link rel="stylesheet" type="text/css" href="../static/css/site.css">
    <title>{{title}}</title>
  </head>
  <body>
      <h2>{{text.content}}!</h2>
      <ul>
        {% for text in data %}
        <li>

## simulate_stop_limit.R
library(quantstrat)
library(magrittr)

Xt = getSymbols('2498.TW', auto.assign = F)

# 1st Step: Attach MA indicators onto symbol
Xt$MA5 = Xt %>% Cl %>% SMA(5)
Xt$MA60 = Xt %>% Cl %>% SMA(60)


## get_colatour_data.R
library(httr)
library(rvest)
library(XML)
library(testit)
library(magrittr)

# origin="TPE"
# destination="SEA"

getAirlineCode <- function(origin="TPE", destination="SEA") {
	from itertools import islice, imap, tee
	from operator import add

	def tail(iterable):
	return islice(iterable, 1, None)

	def take(n, iterable):
	return list(islice(iterable, 0, n))

	def fibs():
	import werobot

	robot = werobot.WeRoBot(token='')


	@robot.handler
	def echo(message):
	return 'Hello World!'

	robot.config['HOST'] = '0.0.0.0'
	import requests
	from pyquery import PyQuery

	url = "https://cn.shopbop.com/sale-bags/br/v=1/15355.htm "
	res =requests.get(url)
	S = PyQuery(res.text)

	S("[data-productid]").map(lambda i,e: PyQuery(e).attr("data-productid"))
	{
	"cells": [
	{
	"cell_type": "markdown",
	"metadata": {
	"slideshow": {
	"slide_type": "slide"
	}
	},
	"source": [
	-- http://www.sqlite.org/lang_with.html --
	WITH RECURSIVE
	fib(current, next) AS (
	SELECT 0 current, 1 next
	UNION ALL
	SELECT fib.next current, fib.current + fib.next next
	FROM fib
	LIMIT 20
	)
	SELECT current FROM fib
	<html>
	<head>
	<link rel="stylesheet" type="text/css" href="../static/css/site.css">
	<title>{{title}}</title>
	</head>
	<body>
	<h2>{{text.content}}!</h2>
	<ul>
	{% for text in data %}
	<li>
	library(quantstrat)
	library(magrittr)

	Xt = getSymbols('2498.TW', auto.assign = F)

	# 1st Step: Attach MA indicators onto symbol
	Xt$MA5 = Xt %>% Cl %>% SMA(5)
	Xt$MA60 = Xt %>% Cl %>% SMA(60)
	library(httr)
	library(rvest)
	library(XML)
	library(testit)
	library(magrittr)

	# origin="TPE"
	# destination="SEA"

	getAirlineCode <- function(origin="TPE", destination="SEA") {