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Most active GitHub users (git.io/top)

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The count of contributions (summary of Pull Requests, opened issues and commits) to public repos at GitHub.com from Wed, 21 Sep 2022 till Thu, 21 Sep 2023.

Because of GitHub search limitations, only 1000 first users according to amount of followers are included. If you are not in the list you don't have enough followers. See raw data and source code. Algorithm in pseudocode:

githubUsers

前端工程師面試問題集

@版本 2.0.0

譯注：此翻譯版，主要給不能流利的讀英文的人看，相關專有名詞還是保留原文。翻譯不好地方請協助pull request.

此repository包含了一些前端開發的面試問題，來審查一個有潛力的面試者。這並不是建議你對同一個面試者問上所有的問 (那會花費好幾小時)。從列表中挑幾個題目，應該就夠幫助你審查面試者是否擁有你需要的技能。

Rebecca Murphey 的 Baseline For Front-End Developers 也是一篇很棒且值得讀的文章在你開始面試之前。

Using Google Maps API and R

This script uses RCurl and RJSONIO to download data from Google's API to get the latitude, longitude, location type, and formatted address

library(RCurl)
library(RJSONIO)
library(plyr)

303 See Other

Location: https://github.com/wsargent/docker-cheat-sheet

Hi there!

The docker cheat sheet has moved to a Github project under https://github.com/wsargent/docker-cheat-sheet.

Please click on the link above to go to the cheat sheet.

	<!DOCTYPE html>
	<html>
	<head>
	<script type="text/javascript" src="http://mbostock.github.com/d3/d3.js"></script>
	<script type="text/javascript" src="https://ajax.googleapis.com/ajax/libs/jquery/1.7.2/jquery.min.js"></script>
	</head>
	<body>
	<table id="split">
	<thead></thead>
	<tbody></tbody>

	<head>
	<title>meteor_servercall</title>
	</head>

	<body>
	{{> simple}}
	{{> passData}}
	</body>

	<template name="simple">

	# $Id: Nielsen2012Python_case.py,v 1.2 2012/09/02 16:55:25 fn Exp $

	# Define a url as a Python string (note we are only getting 100 documents)
	url = "http://wikilit.referata.com/" + \
	"wiki/Special:Ask/" + \
	"-5B-5BCategory:Publications-5D-5D/" + \
	"-3FHas-20author%3DAuthor(s)/-3FYear/" + \
	"-3FPublished-20in/-3FAbstract/-3FHas-20topic%3DTopic(s)/" + \
	"-3FHas-20domain%3DDomain(s)/" + \
	"format%3D-20csv/limit%3D-20100/offset%3D0"

	#!/bin/bash

	# Definitely make sure you create a directory to run this in.

	# Set this to match the mongodb link for your architecture
	# http://www.mongodb.org/downloads
	# arch="linux-i686"
	# arch="osx-x86_64"
	arch="linux-x86_64"

	# load the package and data set "Teams"
	install.packages("Lahman")
	library("Lahman")
	data(Teams)
	#
	#
	# CREATE LEAGUE SUMMARY TABLES
	# ============================
	#
	# select a sub-set of teams from 1901 [the establishment of the American League] forward to 2012

	# This is free and unencumbered software released into the public domain.
	# See UNLICENSE.

	import numpy as np
	import numpy.core.arrayprint as arrayprint
	import contextlib

	#
	# cc-wiki
	# http://stackoverflow.com/questions/2891790/pretty-printing-of-numpy-array