Filip Krawczyk filipkrw

Stevey's Google Platforms Rant

I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.

I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

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.

Prerequisites

The app that uses tailwind + external component library (CL) (but not 3rdparty, your company internal one, for example)
The component library also uses tailwind

The goal

To be able to purge safely unused tailwind classes from the build (https://tailwindcss.com/docs/controlling-file-size)

Solution

The idea here is simple: we're going to purge css on the app side + whitelist classes that component library is using.

	"""
	Implementation of pairwise ranking using scikit-learn LinearSVC

	Reference: "Large Margin Rank Boundaries for Ordinal Regression", R. Herbrich,
	T. Graepel, K. Obermayer.

	Authors: Fabian Pedregosa <[email protected]>
	Alexandre Gramfort <[email protected]>
	"""

	import itertools

	import numpy as np

	from sklearn.linear_model import SGDClassifier, SGDRanking
	from sklearn import metrics
	from minirank.compat import RankSVM as MinirankSVM
	from scipy import stats

	from django.conf import settings
	from django.utils.safestring import mark_safe

	from wagtail.wagtailadmin.edit_handlers import BaseFieldPanel


	class BaseColorFieldPanel(BaseFieldPanel):
	def render_js(self):
	big_javascript_block = """
	(function() {

	using UnityEngine;

	/*
	* Most functions taken from Tween.js - Licensed under the MIT license
	* at https://github.com/sole/tween.js
	* Quadratic.Bezier by @fonserbc - Licensed under WTFPL license
	*/
	public delegate float EasingFunction(float k);

	public class Easing

	function Add-EnvPath {
	param(
	[Parameter(Mandatory=$true)]
	[string] $Path,

	[ValidateSet('Machine', 'User', 'Session')]
	[string] $Container = 'Session'
	)

	if ($Container -ne 'Session') {

	// connect() is a function that injects Redux-related props into your component.
	// You can inject data and callbacks that change that data by dispatching actions.
	function connect(mapStateToProps, mapDispatchToProps) {
	// It lets us inject component as the last step so people can use it as a decorator.
	// Generally you don't need to worry about it.
	return function (WrappedComponent) {
	// It returns a component
	return class extends React.Component {
	render() {
	return (

	import imageio
	import os, sys

	class TargetFormat(object):
	GIF = ".gif"
	MP4 = ".mp4"
	AVI = ".avi"

	def convertFile(inputpath, targetFormat):
	"""Reference: http://imageio.readthedocs.io/en/latest/examples.html#convert-a-movie"""