Stupid Dev vuthaihoc

1) What is Asynchronous call?

A function that enables processing to continue without waiting for function to return the value.

2) What is Full-text search ?

In this we can match a word or phrase in multiple columns and fetch rows accordingly. The Full-text searches are supported for MyISAM tables only ex. : SELECT * FROM articles WHERE MATCH (title,body) AGAINST ('database');

Benchmarking Nginx with Go

There are a lot of ways to serve a Go HTTP application. The best choices depend on each use case. Currently nginx looks to be the standard web server for every new project even though there are other great web servers as well. However, how much is the overhead of serving a Go application behind an nginx server? Do we need some nginx features (vhosts, load balancing, cache, etc) or can you serve directly from Go? If you need nginx, what is the fastest connection mechanism? This are the kind of questions I'm intended to answer here. The purpose of this benchmark is not to tell that Go is faster or slower than nginx. That would be stupid.

So, these are the different settings we are going to compare:

Go HTTP standalone (as the control group)
Nginx proxy to Go HTTP
Nginx fastcgi to Go TCP FastCGI
Nginx fastcgi to Go Unix Socket FastCGI

Discover Graph Databases with Neo4j and PHP

Graph databases are now one of the core technologies of companies dealing with highly connected data.

Business graphs, social graphs, knowledge graphs, interest graphs and media graphs are frequently in the (technology) news. And for a reason. The graph model represents a very flexible way of handling relationships in your data. And graph databases provide fast and efficient storage, retrieval and querying for it.

Neo4j, the most popular graph database, has proven that ability to deal with massive amount of high connected data in many use-cases.

	#!/usr/bin/env python

	"""
	Extracts title from PDF files (Python 3).
	Depends on: pdf, pyPDF2, PDFMiner3k, unidecode.
	Usage:
	pdftitle -d tmp --rename *.pdf{}
	"""

	from io import StringIO

	<!-- Goes into viewer.html just before ending </body> -->
	<script>
	let pinchZoomEnabled = false;
	function enablePinchZoom(pdfViewer) {
	let startX = 0, startY = 0;
	let initialPinchDistance = 0;
	let pinchScale = 1;
	const viewer = document.getElementById("viewer");
	const container = document.getElementById("viewerContainer");
	const reset = () => { startX = startY = initialPinchDistance = 0; pinchScale = 1; };

	(function (context, trackingId, options) {
	const history = context.history;
	const doc = document;
	const nav = navigator \|\| {};
	const storage = localStorage;
	const encode = encodeURIComponent;
	const pushState = history.pushState;
	const typeException = 'exception';
	const generateId = () => Math.random().toString(36);
	const getId = () => {

	- Problem 1: Cho mảng nhiều chiều
	[
	a => 1,
	b => 2,
	c => [
	d => 4,
	e => 5,
	f => [ g => 6]
	]
	]

	# coding=UTF-8
	import nltk
	from nltk.corpus import brown

	# This is a fast and simple noun phrase extractor (based on NLTK)
	# Feel free to use it, just keep a link back to this post
	# http://thetokenizer.com/2013/05/09/efficient-way-to-extract-the-main-topics-of-a-sentence/
	# Create by Shlomi Babluki
	# May, 2013

	<html>
	<body>

	<!-- really dirty! this is just a test drive ;) -->

	<script type="text/javascript" src="https://raw.github.com/mozilla/pdf.js/gh-pages/build/pdf.js"></script>
	<script type="text/javascript">
	function renderPDF(url, canvasContainer, options) {

	var options = options \|\| { scale: 1 };