Daniel Ramirez javamonn

The introduction to Reactive Programming you've been missing

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

Using Python 3 + Google Cloud Vision API's OCR to extract text from photos and scanned documents

Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.

The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.

On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:

####### 1. A low-resolution photo of road signs

This demonstrates the implementation of full text search for documents in Indexed DB.

Word-breaking and stemming is used to create a list of terms for each document.
Document records are annotated with the list of terms when added to the database.
A multi-entry index on the list of terms is populated.
A query is similarly processed into a list of terms.
A join over the terms is implemented using multiple cursors on the index.

The necessity of annotating records with the word list to populate the index is a limitation of the current Indexed DB API. A feature request to support custom

Highlight Selection Ranges

Code here takes a DOM Selection Range instance and starts traversing a DOM starting from startContainer up to endContainer and wraps Text elements with elements that have semi-transparent background & swaps img elements with clones that are styled to have semi-transparent yellow overlay.

Issues

Only handles selecting text and images & would not cover divs with backgrounds for instance.

Overview

Syncing an Ethereum node is largely reliant on latency and IOPS, I/O Per Second, of the storage. Budget SSDs will struggle to an extent, and some won't be able to sync at all. IOPS can roughly be used as proxy of / predictor for latency. Measuring latency directly is arguably better.

This document aims to snapshot some known good and known bad models.

The drive lists are ordered by interface and then by capacity and alphabetically by vendor name, not by preference. The lists are not exhaustive at all. @mwpastore linked a filterable spreadsheet in comments that has a far greater variety of drives and their characteristics. Filter it by DRAM yes, NAND Type TLC, Form Factor M.2, and desired capacity.

For size, 4TB is a very conservative choice. The smaller 2TB drive should last an Ethereum full node until at least sometime 2026, with the [pre-merge history expiry](https://hackmd.io/@hBXHLw_9Qq2va4pRt

	function upload(name, file, callback) {
	Ti.include('lib/sha-aws.js'); // file comes from this URL's project: http://aws.amazon.com/code/Amazon-S3/3236824658053653
	Ti.include('lib/webtoolkit.utf8.js'); // code for this file from this URL: http://www.webtoolkit.info/javascript-utf8.html
	Ti.include('lib/date.js'); // file comes from this URL: http://www.mattkruse.com/javascript/date/source.html

	var AWSAccessKeyID = appGlobal.config.s3AccessKey;
	var AWSSecretAccessKey = appGlobal.config.s3SecretKey;

	var AWSBucketName = appGlobal.config.s3BucketName;
	var AWSHost = appGlobal.config.s3Host;

	class RouteRecognizer
	attr_reader :paths

	# To use this inside your app, call:
	# `RouteRecognizer.new.initial_path_segments`
	# This returns an array, e.g.: ['assets','blog','team','faq','users']

	INITIAL_SEGMENT_REGEX = %r{^\/([^\/\(:]+)}

	def initialize

	.
	├── actions
	├── stores
	├── views
	│ ├── Anonymous
	│ │ ├── __tests__
	│ │ ├── views
	│ │ │ ├── Home
	│ │ │ │ ├── __tests__
	│ │ │ │ └── Handler.js

	# Start a 3 node cluster and join it together automatically. Uses
	# local ephemeral disk for database storage.

	apiVersion: extensions/v1beta1
	kind: Deployment
	metadata:
	name: couchdb
	spec:
	replicas: 3
	template:

	/*
	Slaying a UI Anti Pattern in ReasonML
	Based on Kris Jenkins original writing.
	http://blog.jenkster.com/2016/06/how-elm-slays-a-ui-antipattern.html
	*/
	type remoteData 'e 'a =
	\| NotAsked
	\| Loading
	\| Failure 'e
	\| Success 'a;