badbye

library(httr2)
library(knitr)

AZURE_API_URL = "https://xxx.openai.azure.com/openai/deployments/davinci-003/completions?api-version=2022-12-01"
AZURE_API_KEY = "xxx"
PROMPT = "你是一个优秀的文学家和工程师。你将逐行翻译 Human 给定的 markdown 格式的文本，返回流畅易懂的中文。如果给定的内容中某一行以`<--`开头，以`-->`结尾，则忽略该行不翻译。\n行内的文本遇到以下规则时，... 所表示的内容也不翻译：\n1. `r ...`\n2. \\ref(...)\n\nHuman: China is the greatest country in the world. ^[You have to admit it.]\n<-- The US may disagree -->\nsee table \\ref(tb), its population is `r 10**8`.\nAI: 中国是世界上最伟大的国家。 ^[你必须承认这个事实。]\n<-- The US may disagree -->\n见表 \\ref(tb)， 它的人口数量是 `r 10**8`。\n\nHuman: %s\nAI: "

  
commented = function(line) {
  if (is_commented(line)) line else paste0('<!-- ', line, ' -->')

badbye

Kyuubi & Aliyun ADB Spark

AnalyticDB MySQL Spark 是阿里云 AnalyticDB 产品中的 Serverless Spark 服务， 取代了之前的 DLA Serverless Spark。产品内部已经集成了交互式查询、Notebook 等服务，也提供 API 调用，但仍旧不够灵活。如果能够与 Kyuubi 结合，就可以有更丰富的 JDBC、REST API 连接方式。

Kyuubi 与 Spark 的连接大致分三步：

1. 通过 spark-submit 启动一个 SparkSQLEngine，启动后 Spark Server 会把自己注册到 Zookeeper 服务中
2. Kyuubi Server 通过 Zookeeper 查到到 Spark Server 的地址
3. Kyuubi Server 连接 Spark Server，为客户端提供交互式查询服务

badbye

$('#continueButton').click()
var keeps = $("#pageContainer").parentsUntil('body').toArray().concat($("#pageContainer").children().toArray())
var divs = $("div:not(#pageContainer)").toArray()
divs.filter(x => keeps.indexOf(x) < 0).forEach(x => x.remove())
window.print()

badbye

# encoding: utf8

import gradio
import re
import numpy as np


# A very simplistic function that capitalizes each letter in the given string
def big(x):
    if re.match('^[a-zA-Z]+$', x):

badbye

<script src='https://cdnjs.cloudflare.com/ajax/libs/jquery/3.3.1/jquery.min.js'></script>
<script src='https://cdnjs.cloudflare.com/ajax/libs/jquery-zoom/1.7.21/jquery.zoom.min.js'></script>

<script>
(function () {
  $('.hover_large img')
    .wrap('<span style="display:inline-block"></span>')
    .css('display', 'block')
    .parent()
    .zoom();

badbye

# referenece: https://ieeexplore.ieee.org/document/7345473/
# 验证该论文的分布式计算结果


#' 准备数据
X = matrix(rnorm(400), 20, 20)
Y = rnorm(20)

#' 计算分隔数据的 index
splitByRowIndex = function(nrows, size){

badbye

# referenece: https://ieeexplore.ieee.org/document/7345473/
# 验证该论文的分布式计算结果


#' 准备数据
X = matrix(rnorm(400), 20, 20)
Y = rnorm(20)

#' 计算分隔数据的 index
splitByRowIndex = function(nrows, size){

badbye

Sys.setlocale("LC_CTYPE", "UTF-8")

.setDefaultFont = function(windowsFont = 'song', linuxFont = 'monaco', macOSFont = 'STHeiti'){
  # set base font for different system
  osType = as.character(Sys.info()["sysname"])
  baseFont = ifelse(osType == 'Darwin', macOSFont,
                    ifelse(osType == 'Linux', linuxFont, windowsFont))
  
  message(sprintf('System: %s; base font: %s', osType, baseFont))
  # for base plot 

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import time

# python3.6.1: `%s` is 10 tiems faster than `format`
>>> t1=time.time();c=['%s %s' %(1, 2) for i in range(10000)];time.time()-t1
0.0005083084106445312
>>> t1=time.time();c=['{0} {1}'.format(1, 2) for i in range(10000)];time.time()-t1
0.005129098892211914

# python2.7.10 `%s` is 2 tiems faster than `format`
>>> t1=time.time();c=['{0} {1}'.format(1, 2) for i in range(10000)];time.time()-t1

badbye

# encoding: utf8

"""
Created on 2017.10.24

@author: yalei
"""

import numpy as np