Joseph Kim joekim

Storybook Docs w/ CRA & TypeScript

This is a quick-and-dirty walkthrough to set up a fresh project with Storybook Docs, Create React App, and TypeScript. If you're looking for a tutorial, please see Design Systems for Developers, which goes into much more depth but does not use Typescript.

The purpose of this walkthrough is a streamlined Typescript / Docs setup that works out of the box, since there are countless permutations and variables which can influence docs features, such as source code display, docgen, and props tables.

Step 1: Initialize CRA w/ TS

npx create-react-app cra-ts --template typescript

If using Typescript to write a ReactNative Project in VSCode, you'll find that VSCode cannot stop at any breakpoint in TypeScript files. You must create breakpoints in JS files.

This post will answer why this problem appears and how to solve that.

Enviroment: VSCode (1.1.1 or 1.2.0) and ReactNative Tool Extension (0.1.4)

Solution Target: Debugger will work on break points in TypeScript files, in a ReactNative Project

Example Project structure:

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

Thoughts on Swift 2 Errors

When Swift was first announced, I was gratified to see that one of the (few) philosophies that it shared with Objective-C was that exceptions should not be used for control flow, only for highlighting fatal programming errors at development time.

So it came as a surprise to me when Swift 2 brought (What appeared to be) traditional exception handling to the language.

Similarly surprised were the functional Swift programmers, who had put their faith in the Haskell-style approach to error handling, where every function returns an enum (or monad, if you like) containing either a valid result or an error. This seemed like a natural fit for Swift, so why did Apple instead opt for a solution originally designed for clumsy imperative languages?

I'm going to cover three things in this post:

console.log wrap resolving for your wrapped console logs

I've heard this before:

What I really get frustrated by is that I cannot wrap console.* and preserve line numbers

We enabled this in Chrome DevTools via blackboxing a bit ago.

If you blackbox the script file the contains the console log wrapper, the script location shown in the console will be corrected to the original source file and line number. Click, and the full source is looking longingly into your eyes.

	function* runTimer(getState) {

	while(yield take('START')) {
	while(true) {
	const {stop, tick} = yield race({
	stop : take('STOP'),
	tick : call(wait, ONE_SECOND);
	})
	if ( !stop ) {
	yield put(actions.tick());

	Disclaimer: The instructions are the collective efforts from a few places online.
	Nothing here is my original. But I want to put them together in one place to save people from spending the same time as I did.

	First off, bundle.
	==================

	1. cd to the project directory
	2. Start the react-native packager if not started
	3. Download the bundle to the asset folder:
	curl "http://localhost:8081/index.android.bundle?platform=android" -o "android/app/src/main/assets/index.android.bundle"

	//
	// main.swift
	// Test
	//
	// Created by Chris Eidhof on 29/08/15.
	// Copyright © 2015 Chris Eidhof. All rights reserved.
	//

	import Foundation
	import Quartz

	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)

	/**
	* Fancy ID generator that creates 20-character string identifiers with the following properties:
	*
	* 1. They're based on timestamp so that they sort after any existing ids.
	* 2. They contain 72-bits of random data after the timestamp so that IDs won't collide with other clients' IDs.
	* 3. They sort lexicographically (so the timestamp is converted to characters that will sort properly).
	* 4. They're monotonically increasing. Even if you generate more than one in the same timestamp, the
	* latter ones will sort after the former ones. We do this by using the previous random bits
	* but "incrementing" them by 1 (only in the case of a timestamp collision).
	*/