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Readme Bootstrap General aspects between Elm and JS | DailyDrip 2017-05-08 by Franzé Jr. This is Part 1 in a series about Elm for JavaScript Developers. I've been programming in JavaScript for a while, and hearing people speak so highly about Elm inspired me to give it a try! Studying Elm has raised several questions about this language. The idea of this text is to introduce Elm to JavaScript developers like myself. If you're reading this, you're probably aware of what Elm is, but let's go overt it. In this blog series, we will compare Elm with JavaScript. Let's do a Hello World in Elm to get started! mkdir hello_world cd hello_world vim HelloWorld.elm We will create a basic Elm module that outputs Hello, World! import Html exposing (text) main = text "Hello, World!" We want to generate an HTML text node, so we import the Html module and expose its text function. We can use elm-reactor: an interactive development tool that makes it easy to develop and run Elm applications: elm-reactor Syntax Let's look at some differences: Functions sum a b = a + b Yay!

Five simple database design tips A flawed database can affect all areas of your application, so getting the design right is of paramount importance. Check out Builder's five simple design tips, and share some of your own. If an enterprise’s data is its lifeblood, then the database design can be the most important part of an application. Volumes have been written on this topic, and entire college degrees have been built around it. I’ll get the show started by listing my five favorite tips and giving a brief explanation of the rationale behind each one. #1: Use meaningful field namesI once worked on a project I inherited from another programmer who liked to name fields using the name of the onscreen control that displayed the data from that field. Unless you are using a system that restricts you to short field names, make them as descriptive as possible—within reason, of course. Obviously, the existing system is not perfect; otherwise, you wouldn’t be building a new one.

A dive into spatial search algorithms – Vladimir Agafonkin – Medium I’m obsessed with software performance. One of my main responsibilities at Mapbox is discovering ways to make our mapping platform faster. And when it comes to processing and displaying spatial data at scale, there’s no concept more useful and important than a spatial index. Spatial indices are a family of algorithms that arrange geometric data for efficient search. For example, doing queries like “return all buildings in this area”, “find 1000 closest gas stations to this point”, and returning results within milliseconds even when searching millions of objects. Spatial indices form the foundation of databases like PostGIS, which is at the core of our platform. In the last 4 years, I’ve built a bunch of ultra-fast JavaScript libraries for spatial search: rbush, rbush-knn, kdbush, geokdbush (with a few more to come). Spatial search problems Spatial data has two fundamental query types: nearest neighbors and range queries. K nearest neighbors An intuitive way to do this is: a rectangle?

Ten Common Database Design Mistakes No list of mistakes is ever going to be exhaustive. People (myself included) do a lot of really stupid things, at times, in the name of “getting it done.” This list simply reflects the database design mistakes that are currently on my mind, or in some cases, constantly on my mind. I have done this topic two times before. If you’re interested in hearing the podcast version, visit Greg Low’s super-excellent SQL Down Under. Before I start with the list, let me be honest for a minute. So, the list: Poor design/planning Ignoring normalization Poor naming standards Lack of documentation One table to hold all domain values Using identity/guid columns as your only key Not using SQL facilities to protect data integrity Not using stored procedures to access data Trying to build generic objects Lack of testing Poor design/planning “If you don’t know where you are going, any road will take you there” – George Harrison Ignoring Normalization Are there always 12 payments? Poor naming standards Security

Software Testing Anti-patterns · Codepipes Blog 21 Apr 2018 Introduction There are several articles out there that talk about testing anti-patterns in the software development process. In this article I wanted to take a step back and catalog some high-level testing anti-patterns that are technology agnostic. Terminology Unfortunately, testing terminology has not reached a common consensus yet. If you have never encountered the testing pyramid before, I would urge you to become familiar with it first before going on. The testing pyramid deserves a whole discussion on its own, especially on the topic of the amount of tests needed for each category. Therefore the two major test categories mentioned as unit and integration tests from now on are: Unit tests are the category of tests that have wider acceptance regarding the naming and what they mean. Integration tests (also called service tests, or even component tests) focus on a whole component. As a basic rule of thumb if …then it is an integration test and not a unit test. Wrong!

Unity 3 – April 2013 patterns & practices Developer Center April 2013 Unity is a lightweight, extensible dependency injection container with support for instance and type interception. Overview Unity is a lightweight, extensible dependency injection container with support for constructor, property, and method call injection. Simplified object creation, especially for hierarchical object structures and dependencies. Unity is a general-purpose container for use in any type of Microsoft.NET Framework-based application. In addition, Unity is extensible. This release adds support for Windows Store apps as well as the registration by convention feature to ease the task of configuring Unity. Audience Requirements These reusable components and guidance are intended primarily for software developers and software architects. Contents of This Release Microsoft Unity 3 contains the following: Binaries. System Requirements Supported architectures: x86 and x64. For a rich development environment, the following are recommended:

Your first GraphQL component – Abhi Aiyer – Medium If you follow my musings surely you must know how enamored I am with GraphQL. Frequently asked questions I get aren’t really about how it works anymore, but rather: How do I get started and build something? Today I want to get you your first win. Today, let’s build a little UI Component who’s data is backed by a GraphQL API. Since this is more of a front-end tutorial, we will be picking from a list of public GraphQL APIs. There were many options for a public API here: and what we go over here can apply to any of these! I’m going to try to go step-by-step here, so try and follow along! Project Setup Okay so to save ourselves a configuration nightmare, let’s use the wonderful (but slow :P) create-react-app $ yarn global add create-react-app $ create-react-app INSERT_YOUR_OWN_NAME Okay now go watch a show, or do some burpees. Done? $ cd INSERT_YOUR_OWN_NAME $ yarn add apollo-client react-apollo -S Start the Server Clone this repo: $ yarn $ npm start Nice! Wow!

Codecademy Labs exercism.io c# - Best Practices of fault toleration and reliability for scheduled tasks or services A Gentle Introduction to Algorithm Complexity Analysis Dionysis "dionyziz" Zindros <dionyziz@gmail.com> Introduction A lot of programmers that make some of the coolest and most useful software today, such as many of the stuff we see on the Internet or use daily, don't have a theoretical computer science background. However, theoretical computer science has its uses and applications and can turn out to be quite practical. This text is also targeted at the junior high school and high school students from Greece or anywhere else internationally competing in the International Olympiad in Informatics, an algorithms competition for students, or other similar competitions. I believe this text will be helpful for industry programmers who don't have too much experience with theoretical computer science (it is a fact that some of the most inspiring software engineers never went to college). Throughout this article, you will find various pointers that link you to interesting material often outside the scope of the topic under discussion. Motivation 5.

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