How-To Tutorials

In the article by, Craig Clayton, author of the book, iOS 10 Programming for Beginners, we went over the basics of Swift to get you warmed up. Now, we will dig deeper and learn some more programming concepts. These concepts will build on what you have already learned. In this article, we will cover the following topics: Ranges Control flow (For more resources related to this topic, see here.) Creating a Playground project Please launch Xcode and click on Get started with a playground. The options screen for creating a new playground screen will appear: Please name your new Playground SwiftDiggingDeeper and make sure that your Platform is set to iOS. Now, let's delete everything inside of your file and toggle on the Debug panel using either the toggle button or Cmd + Shift + Y. Your screen should look like mine: Ranges These generic data types represent a sequence of numbers. Let's look at the image below to understand: Closed range Notice that, in the image above, we have numbers ranging from 10 to 20. Rather than having to write each value, we can use ranges to represent all of these numbers in shorthand form. In order to do this, let's remove all of the numbers in the image except 10 and 20. Now that we have removed those numbers, we need a way to tell Swift that we want to include all of the numbers that we just deleted. This is where the range operator (…) comes into play. So, in Playgrounds, let's create a constant called range and set it equal to 10...20: let range = 10...20 The range that we just entered says that we want the numbers between 10 and 20 as well as both 10 and 20 themselves. This type of range is known as a closed range. We also have what is called a half closed range. Half closed range Let's make another constant called half closed range and set it equal to 10..<20: let halfClosedRange = 10..<20 A half closed range is the same as a closed range except that the end value will not be included. In this example, that means that 10 through 19 will be included and 20 will be excluded. At this point, you will notice that your results panel just shows you CountableClosedRange(10...20) and CountableRange(10..<20). We cannot see all the numbers within the range. In order to see all the numbers, we need to use a loop. Control flow In Swift, we use a variety of control statements. For-In Loop One of the most common control statements is a for-in loop. A for-in loop allows you to iterate over each element in a sequence. Let's see what a for-loop looks like: for <value> in <sequence> { // Code here } So, we start our for-in loop with for, which is followed by <value>. This is actually a local constant (only the for-in loop can access it) and can be any name you like. Typically, you will want to give this value an expressive name. Next, we have in, which is followed by <sequence>. This is where we want to give it our sequence of numbers. Let's write the following into Playgrounds: for value in range { print("closed range - (value)") } Notice that, in our debug panel, we see all of the numbers we wanted in our range: Let's do the same for our variable halfClosedRange by adding the following: for index in halfClosedRange { print("half closed range - (index)") } In our debug panel, we see that we get the numbers 10 through 19. One thing to note is that these two for-in loops have different variables. In the first loop, we used value, and in the second one, we used index. You can make these whatever you choose. In addition, in the two examples, we used constants, but we could actually just use the ranges within the loop. Please add the following: for index in 0...3 { print("range inside - (index)") } Now, you will see 0 to 3 print inside the debug panel: What if you wanted numbers to go in reverse order? Let's input the following for-in loop: for index in (10...20).reversed() { print("reversed range - (index)") } We now have the numbers in descending order in our debug panel. When we add ranges into a for-in loop, we have to wrap our range inside parentheses so that Swift recognizes that our period before reversed() is not a decimal. The while Loop A while loop executes a Boolean expression at the start of the loop, and the set of statements run until a condition becomes false. It is important to note that while loops can be executed zero or more times. Here is the basic syntax of a while loop: while <condition> { // statement } Let's write a while loop in Playgrounds and see how it works. Please add the following: var y = 0 while y < 50 { y += 5 print("y:(y)") } So, this loop starts with a variable that begins at zero. Before the while loop executes, it checks to see if y is less than 50; and, if so, it continues into the loop. By using the += operator, we increment y by 5 each time. Our while loop will continue to do this until y is no longer less than 50. Now, let's add the same while loop after the one we created and see what happens: while y < 50 { y += 5 print("y:(y)") } You will notice that the second while loop never runs. This may not seem like it is important until we look at our next type of loop. The repeat-while loop A repeat-while loop is pretty similar to a while loop in that it continues to execute the set of statements until a condition becomes false. The main difference is that the repeat-while loop does not evaluate its Boolean condition until the end of the loop. Here is the basic syntax of a repeat-while loop: repeat { // statement } <condition> Let's write a repeat-while loop in Playgrounds and see how it works. Type the following into Playgrounds: var x = 0 repeat { x += 5 print("x:(x)") } while x < 100 print("repeat completed x: (x)") So, our repeat-while loop executes first and increments x by 5, and afterwards (as opposed to checking the condition before as with a while loop), it checks to see if x is less than 100. This means that our repeat-while loop will continue until the condition hits 100. But here is where it gets interesting. Let's add another repeat-while loop after the one we just created: repeat { x += 5 print("x:(x)") } while x < 100 print("repeat completed again x: (x)") This time, the repeat…while loop incremented to 105. This happens because the Boolean expression does not get evaluated until after it is incremented by 5. Knowing this behavior will help you pick the right loop for your situation. So far, we have looked at three loops: the for-in loop, the while loop, and the repeat-while loop. We will use the for-in loop again, but first we need to talk about collections. Summary The article summarizes Ranges and control flow using Xcode 8. Resources for Article: Further resources on this subject: Tools inTypeScript [article] Design with Spring AOP [article] Thinking Functionally [article]

In this article by Donabel Santos author of the book Tableau 10 Business Intelligence Cookbook would like to offer you perhaps a personal, and maybe a not-so-conventional way to introduce Tableau. I’d like to highlight a few key concepts and tricks that I think would be useful to you as you go along. These are certainly points I highlight on the board whenever I do training on Tableau. If you feel like we are jumping too far ahead, please go ahead and start with the following section Tableau Primer. Come back to this section when you are ready for the tips and tricks. (For more resources related to this topic, see here.) Instead of thinking of Tableau as this software tool that has a steep learning curve, it is useful to think of it as a blank slate. You will draw on it, keep on adding things, removing things until something makes sense or something insightful pops out. After you work with Tableau for a while and get more comfortable with its functionalities, it might even feel like an extension of your brain to some degree. When you get access to data, you might automatically open Tableau to try and understand what’s in that data. Undo is your best friend Do not be afraid to make mistakes, and do not be afraid to explore in Tableau. Do not come in with strict prejudice – for example thinking that you can only use a time series graph when you have a measure and a date field. The best way to learn and explore how powerful Tableau is to try anything and everything. It’s one of the best tools to experiment. If you make a mistake, or if you don’t like what you see, no sweat. Just click on this friendly undo button and you are back to your previous view. If you are more of a shortcut person, it will be Ctrl + Z on a PC or Command + Z on a Mac. It doesn’t change your original data This is another common concern that comes up in my training sessions or whenever I talk to people about Tableau. No, Tableau does not write back to your data source. All the changes you make will be stored in Tableau like creating calculated fields, changing data types, editing aliases will be stored in your Tableau workbook or data source. Drag and drop Tableau is a highly drag and drop software. Although you can use the menu or a right click instead of a drag and drop for the same tasks, dragging and dropping is often faster. It also flows with your train of thought. Look for visual cues Tableau leverages its visual culture in your design area, so when you create views in Tableau, some of the visual cues and icons can help you along the way. A number of the visual cues have been discussed in this section. However, there may be some lesser known (or less noticeable) visual cues: Italicized field names mean they are Tableau-generated fields: Dual axis charts create fused pills. Notice the area when the two pills touch – they’re straight instead of curved: When you zoom in to maps, or when you search for a place, your map gets pinned (or fixed to this place) until you unpin it: Know the difference between blue (discrete) and green (continuous) Knowing the difference between blue and green will take you far in the Tableau world. The data type icons you will find beside your field names in the side bar are colored either blue or green. When you drag fields onto shelves and cards, the pills are also colored blue and green. Simply speaking, blue means discrete and green means continuous. Discrete means individual, separate, countable and finite. Continuous means range, and technically, there is an infinite number of values within this range. What’s more important is how these are manifested in Tableau. A blue discrete field will produce header, and a green continuous field will produce an axis. If dropped onto the Color shelf, for example, a blue discrete field will use individual, finite colors. A green continuous field will use a range (gradient) of colors. Some confusion also arises when we see that, by default, Tableau places numeric fields under Measures and are colored green, and categorical information under Dimensions are colored blue. These won’t always be the case. We can have numeric values that are discrete – for example an Order Number. We can also see non-numerical, discrete fields under Measures. Learn a few key shortcuts Shortcuts are great, but it’s typically faster to work when you know a few of them. Here are some of my favorite shortcuts: Shortcut What it does Right click + Drag Opens the Drop Field menu, which allows you to specify exactly which variation of the field you want to use Double click Adds the field to the view I particularly like this when creating text tables. After you place your first measure in Text, you can add more measures to your text table by double clicking on the succeeding measures Ctrl + Arrow Adjusts the height/width of the rows/columns in the view Ctrl + H Presentation mode You can find the complete list of shortcuts here: http://bit.ly/tableau-shortcuts Unpackage option The .twbx file is a Tableau packaged workbook, which means it packages local files with your Tableau workbook. When you right click a .twbx file in a machine that has Tableau Desktop installed in it, you will see a new option called Unpackage. When you unpack a .twbx file, you will get the .twb file and another folder that contains all the local files that were used in the original workbook: Just keep in mind that data (at least the file-based data sources and extracts) get packaged with your .twbx files. This is an important security and data governance consideration when you are deciding how to share your workbooks with others. Table calculations are calculations on your table. How you structure or lay out your table (or view) will affect your table calculations. Table calculations are highly influenced by: Layout Filters Scope and Direction Let’s say, for example, you are calculating Percent of Total in your view. If you swap the fields in your Rows and Columns, i.e. changing the layout, your numbers will change If you filter some of the products out, your numbers will change If you decide to compute Pane Down instead of Table Across, your numbers will change If you’re looking for the common use cases for table calculations, check out the Tableau article entitled Top 10 Tableau Table Calculations which can be found here: http://bit.ly/top10tablecalcs LODs Rock Many of the tasks that required complex table calculations or data blending have been greatly simplified by LODs (Level of Detail expressions). LODs allow us to have multiple levels of detail within a single view, and this increases the possibilities in Tableau. To learn more about Level of Detail expressions, I encourage you to check out the following: Understanding Level of Detail Expressions: http://bit.ly/UnderstandingLOD Top 15 LOD Expressions: http://bit.ly/top15LOD It is possible …. Another common question that comes up is can I do <this> or is it possible to do <this>. The answer to many of the questions is yes, and many will include calculations and/or parameters. However, not all solutions will be quick and straightforward. Some may require multiple calculated fields, table calculations, LOD expressions, regular expressions, R scripts etc. Summary In this article we have seen the basics of Tableau as this software tool that has a steep learning curve, it is useful to think of it as a blank slate. You will draw on it, keep on adding things, removing things until something makes sense or something insightful pops out. After you work with Tableau for a while and get more comfortable with its functionalities, it might even feel like an extension of your brain to some degree. When you get access to data, you might automatically open Tableau to try and understand what’s in that data. Resources for Article: Further resources on this subject: Say Hi to Tableau [article] Getting Started with Tableau Public [article] R and its Diverse Possibilities [article]

In this article by Jan Just Keijser, author of the book OpenVPN Cookbook - Second Edition, we will cover the following recipes: (For more resources related to this topic, see here.) OpenVPN secret keys Using IPv6 OpenVPN secret keys This recipe uses OpenVPN secret keys to secure the VPN tunnel. This shared secret key is used to encrypt the traffic between the client and the server. Getting ready Install OpenVPN 2.3.9 or higher on two computers. Make sure that the computers are connected over a network. For this recipe, the server computer was running CentOS 6 Linux and OpenVPN 2.3.9 and the client was running Windows 7 Pro 64bit and OpenVPN 2.3.10. How to do it... First, we generate a secret key on the server (listener): [root@server]# openvpn --genkey --secret secret.key We transfer this key to the client side over a secure channel (for example, using scp): Next, we launch the server (listening)-side OpenVPN process: [root@server]# openvpn --ifconfig 10.200.0.1 10.200.0.2 --dev tun --secret secret.key Then, we launch the client-side OpenVPN process: [WinClient] C:>"Program FilesOpenVPNbinopenvpn.exe" --ifconfig 10.200.0.2 10.200.0.1 --dev tun --secret secret.key --remote openvpnserver.example.com The connection is established: How it works... The server listens to the incoming connections on the UDP port 1194. The client connects to the server on this port. After the initial handshake, the server configures the first available TUN device with the IP address 10.200.0.1 and it expects the remote end (peer address) to be 10.200.0.2. The client does the opposite. There's more... By default, OpenVPN uses two symmetric keys when setting up a point-to-point connection: A Cipher key to encrypt the contents of the packets being exchanged. An HMAC key to sign packets. When packets arrive that are not signed using the appropriate HMAC key they are dropped immediately. This is the first line of defense against a "Denial of Service" attack. The same set of keys are used on both ends, and both the keys are derived from the file specified using the --secret parameter. An OpenVPN secret key file is formatted as follows: # # 2048 bit OpenVPN static key # -----BEGIN OpenVPN Static key V1----- <16 lines of random bytes> -----END OpenVPN Static key V1----- From the random bytes, the OpenVPN Cipher and HMAC keys are derived. Note that these keys are the same for each session! Using IPv6 In this recipe, we extend the complete site-to-site network to include support for IPv6. Getting ready Install OpenVPN 2.3.9 or higher on two computers. Make sure that the computers are connected over a network. For this recipe, the server computer was running CentOS 6 Linux and OpenVPN 2.3.9 and the client was running Fedora 22 Linux and OpenVPN 2.3.10. We'll use the secret.key file from the OpenVPN Secret keys recipe here. We use the following network layout: How to do it... Create the server configuration file: dev tun proto udp local openvpnserver.example.com lport 1194 remote openvpnclient.example.com rport 1194 secret secret.key 0 ifconfig 10.200.0.1 10.200.0.2 route 192.168.4.0 255.255.255.0 tun-ipv6 ifconfig-ipv6 2001:db8:100::1 2001:db8:100::2 user nobody group nobody # use "group nogroup" on some distros persist-tun persist-key keepalive 10 60 ping-timer-rem verb 3 daemon log-append /tmp/openvpn.log Save it as example1-9-server.conf. On the client side, we create the configuration file: dev tun proto udp local openvpnclient.example.com lport 1194 remote openvpnserver.example.com rport 1194 secret secret.key 1 ifconfig 10.200.0.2 10.200.0.1 route 172.31.32.0 255.255.255.0 tun-ipv6 ifconfig-ipv6 2001:db8:100::2 2001:db8:100::1 user nobody group nobody # use "group nogroup" on some distros persist-tun persist-key keepalive 10 60 ping-timer-rem verb 3 Save it as example1-9-client.conf. We start the tunnel on both ends: [root@server]# openvpn --config example1-9-server.conf And: [root@client]# openvpn --config example1-9-client.conf Now our site-to-site tunnel is established. After the connection comes up, the machines on the LANs behind both end points can be reached over the OpenVPN tunnel. Note that the client OpenVPN session is running in the foreground. Next, we ping the IPv6 address of the server endpoint to verify that IPv6 traffic over the tunnel is working: [client]$ ping6 -c 4 2001:db8:100::1 PING 2001:db8:100::1(2001:db8:100::1) 56 data bytes 64 bytes from 2001:db8:100::1: icmp_seq=1 ttl=64 time=7.43 ms 64 bytes from 2001:db8:100::1: icmp_seq=2 ttl=64 time=7.54 ms 64 bytes from 2001:db8:100::1: icmp_seq=3 ttl=64 time=7.77 ms 64 bytes from 2001:db8:100::1: icmp_seq=4 ttl=64 time=7.42 ms --- 2001:db8:100::1 ping statistics --- 4 packets transmitted, 4 received, 0% packet loss, time 3005ms rtt min/avg/max/mdev = 7.425/7.546/7.778/0.177 ms Finally, we abort the client-side session by pressing Ctrl + C. The following screenshot lists the full client-side log: How it works... The following command enables IPv6 support next to the default IPv4 support: tun-ipv6 ifconfig-ipv6 2001:db8:100::2 2001:db8:100::1 Also, in the client configuration, the options daemon and log-append are not present, hence all OpenVPN output is sent to the screen and the process continues running in the foreground. There's more... Log file errors If we take a closer look at the client-side connection output, we see a few error messages after pressing Ctrl + C, most notably the following: RTNETLINK answers: operation not permitted This is a side-effect when using the user nobody option to protect an OpenVPN setup, and it often confuses new users. What happens is this: OpenVPN starts as the root user, opens the appropriate tun device, and sets the right IPv4 and IPv6 addresses on this tun interface. For extra security, OpenVPN then switches to the nobody user, dropping all privileges associated with the user root. When OpenVPN terminates (in our case, by pressing Ctrl + C), it closes access to the tun device and tries to remove the IPv4 and IPv6 addresses assigned to that device. At this point, the error messages appear, as the user nobody is not allowed to perform these operations. Upon termination of the OpenVPN process, the Linux kernel closes the tun device and all configuration settings are removed. In this case, these error messages are harmless, but in general, one should pay close attention to the warning and error messages that are printed by OpenVPN. IPv6-only tunnel With OpenVPN 2.3, it is required to always enable IPv4 support. From OpenVPN 2.4 onward, it is possible to set up an "IPv6-only" connection. Summary In this article, we extended the complete site-to-site network to include support for IPv6 with OpenVPN secret keys. Resources for Article: Further resources on this subject: Introduction to OpenVPN [Article] A quick start – OpenCV fundamentals [Article] Untangle VPN Services [Article]

In this article by Manuel Guilbault, the author of the book Learning Aurelia, we will how Aurelia is such a modern framework. brainchild of Rob Eisenberg, father of Durandal, it is based on cutting edge Web standards, and is built on modern software architecture concepts and ideas, to offer a powerful toolset and an awesome developer experience. (For more resources related to this topic, see here.) This article will teach you how Aurelia works, and how you can use it to build real-world applications from A to Z. In fact, while reading the article and following the examples, that’s exactly what you will do. You will start by setting up your development environment and creating the project, then I will walk you through concepts such as routing, templating, data-binding, automated testing, internationalization, and bundling. We will discuss application design, communication between components, and integration of third parties. We will cover every topic most modern, real-world single-page applications require. In this first article, we will start by defining some terms that will be used throughout the article. We will quickly cover some core Aurelia concepts. Then we will take a look at the core Aurelia libraries and see how they interact with each other to form a complete, full-featured framework. We will see also what tools are needed to develop an Aurelia application and how to install them. Finally, we will start creating our application and explore its global structure. Terminology As this article is about a JavaScript framework, JavaScript plays a central role in it. If you are not completely up to date with the terminology, which has changed a lot in the last few years, let me clear things up. JavaScript (or JS) is a dialect, or implementation, of the ECMAScript (ES) standard. It is not the only implementation, but it definitely is the most popular. In this article, I will use the JS acronym to talk about actual JavaScript code or code files and the ES acronym when talking about an actual version of the ECMAScript standard. Like everything in computer programing, the ECMAScript standard evolves over time. At the moment of writing, the latest version is ES2016 and was published in June 2016. It was originally called ES7, but TC39, the committee drafting the specification, decided to change their approval and naming model, hence the new name. The previous version, named ES2015 (ES6) before the naming model changed, was published in June 2015 and was a big step forward as compared to the version before it. This older version, named ES5, was published in 2009 and was the most recent version for 6 years, so it is now widely supported by all modern browsers. If you have been writing JavaScript in the last five years, you should be familiar with ES5. When they decided to change the ES naming model, the TC39 committee also chose to change the specification’s approval model. This decision was made in an effort to publish new versions of the language at a quicker pace. As such, new features are being drafted and discussed by the community, and must pass through an approval process. Each year, a new version of the specification will be released, comprising the features that were approved during the year. Those upcoming features are often referred to as ESNext. This term encompasses language features that are approved or at least pretty close to approval but not yet published. It can be reasonable to expect that most or at least some of those features will be published in the next language version. As ES2015 and ES2016 are still recent things, they are not fully supported by most browsers. Moreover, ESNext features have typically no browser support at all. Those multiple names can be pretty confusing. To make things simpler, I will stick with the official names ES5 for the previous version, ES2016 for the current version and ESNext for the next version. Before going any further, you should make yourself familiar with the features introduced by ES2016 and with ESNext decorators, if you are not already. We will use these features throughout the article. If you don’t know where to start with ES2015 and ES2016, you can find a great overview of the new features on Babel’s website: https://babeljs.io/docs/learn-es2015/ As for ESNext decorators, Addy Osmani, a Google engineer, explained them pretty well: https://medium.com/google-developers/exploring-es7-decorators-76ecb65fb841 For further reading, you can take a look at the feature proposals (decorators, class property declarations, async functions, and so on) for future ES versions: https://github.com/tc39/proposals Core concepts Before we start getting our hands dirty, there are a couple of core concepts that need to be explained. Conventions First, Aurelia relies a lot on conventions. Most of those conventions are configurable, and can be changed if they don’t suit your needs. Each time we’ll encounter a convention throughout the article, we will see how to change it whenever possible. Components Components are a first class citizen of Aurelia. What is an Aurelia component? It is a pair made of an HTML template, called the view, and a JavaScript class, called the view-model. The view is responsible for displaying the component, while the view-model controls its data and behavior. Typically, the view sits in an .html file and the view-model in a .js file. By convention, those two files are bound through a naming rule, they must be in the same directory and have the same name (except for their extension, of course). Here’s an example of an empty component with no data, no behavior, and a static template: component.js export class MyComponent {} component.html <template> <p>My component</p> </template> A component must comply with two constraints, a view’s root HTML element must be the template element, and the view-model class must be exported from the .js file. As a rule of thumb, the only function that should be exported by a component’s JS file should be the view-model class. If multiple classes or functions are exported, Aurelia will iterate on the file’s exported functions and classes and will use the first it finds as the view-model. However, since the enumeration order of an object’s keys is not deterministic as per the ES specification, nothing guarantees that the exports will be iterated in the same order they were declared, so Aurelia may pick the wrong class as the component’s view-model. The only exception to that rule is some view resources In addition to its view-model class, a component’s JS file can export things like value converters, binding behaviors, and custom attributes basically any view resource that can’t have a view, which excludes custom elements. Components are the main building blocks of an Aurelia application. Components can use other components; they can be composed to form bigger or more complex components. Thanks to the slot mechanism, you can design a component’s template so parts of it can be replaced or customized. Architecture Aurelia is not your average monolithic framework. It is a set of loosely coupled libraries with well-defined abstractions. Each of its core libraries solves a specific and well-defined problem common to single-page applications. Aurelia leverages dependency injection and a plugin architecture so you can discard parts of the framework and replace them with third-party or even your own implementations. Or you can just throw away features you don’t need so your application is lighter and faster to load. The core Aurelia libraries can be divided into multiple categories. Let’s have a quick glance. Core features The following libraries are mostly independent and can be used by themselves if needed. They each provide a focused set of features and are at the core of Aurelia: aurelia-dependency-injection: A lightweight yet powerful dependency injection container. It supports multiple lifetime management strategies and child containers. aurelia-logging: A simple logger, supporting log levels and pluggable consumers. aurelia-event-aggregator: A lightweight message bus, used for decoupled communication. aurelia-router: A client-side router, supporting static, parameterized or wildcard routes, and child routers. aurelia-binding: An adaptive and pluggable data-binding library. aurelia-templating: An extensible HTML templating engine. Abstraction layers The following libraries mostly define interfaces and abstractions in order to decouple concerns and enable extensibility and pluggable behaviors. This does not mean that some of the libraries in the previous section do not expose their own abstractions besides their features. Some of them do. But the libraries described in the current section have almost no other purpose than defining abstractions: aurelia-loader: An abstraction defining an interface for loading JS modules, views, and other resources. aurelia-history: An abstraction defining an interface for history management used by routing. aurelia-pal: An abstraction for platform-specific capabilities. It is used to abstract away the platform on which the code is running, such as a browser or Node.js. Indeed, this means that some Aurelia libraries can be used on the server side. Default implementations The following libraries are the default implementations of abstractions exposed by libraries from the two previous sections: aurelia-loader-default: An implementation of the aurelia-loader abstraction for SystemJS and require-based loaders. aurelia-history-browser: An implementation of the aurelia-history abstraction based on standard browser hash change and push state mechanisms. aurelia-pal-browser: An implementation of the aurelia-pal abstraction for the browser. aurelia-logging-console: An implementation of the aurelia-logging abstraction for the browser console. Integration layers The following libraries’ purpose is to integrate some of the core libraries together. They provide interface implementations and adapters, along with default configuration or behaviors: aurelia-templating-router: An integration layer between the aurelia-router and the aurelia-templating libraries. aurelia-templating-binding: An integration layer between the aurelia-templating and the aurelia-binding libraries. aurelia-framework: An integration layer that brings together all of the core Aurelia libraries into a full-featured framework. aurelia-bootstrapper: An integration layer that brings default configuration for aurelia-framework and handles application starting. Additional tools and plugins If you take a look at Aurelia’s organization page on GitHub at https://github.com/aurelia, you will see many more repositories. The libraries listed in the previous sections are just the core of Aurelia—the tip of the iceberg, if I may. Many other libraries exposing additional features or integrating third-party libraries are available on GitHub, some of them developed and maintained by the Aurelia team, many others by the community. I strongly suggest that you explore the Aurelia ecosystem by yourself after reading this article, as it is rapidly growing, and the Aurelia community is doing some very exciting things. Tooling In the following section, we will go over the tools needed to develop our Aurelia application. Node.js and NPM Aurelia being a JavaScript framework, it just makes sense that its development tools are also in JavaScript. This means that the first thing you need to do when getting started with Aurelia is to install Node.js and NPM on your development environment. Node.js is a server-side runtime environment based on Google’s V8 JavaScript engine. It can be used to build complete websites or web APIs, but it is also used by a lot of front-end projects to perform development and build tasks, such as transpiling, linting, and minimizing. NPM is the de facto package manager for Node.js. It uses http://www.npmjs.com as its main repository, where all available packages are stored. It is bundled with Node.js, so if you install Node.js on your computer, NPM will also be installed. To install Node.js and NPM on your development environment, you simply need to go to https://nodejs.org/ and download the proper installer suiting your environment. If Node.js and NPM are already installed, I strongly recommend that you make sure to use at least the version 3 of NPM, as older versions may have issues collaborating with some of the other tools we’ll use. If you are not sure which version you have, you can check it by running the following command in a console: > npm –v If Node.js and NPM are already installed but you need to upgrade NPM, you can do so by running the following command: > npm install npm -g The Aurelia CLI Even though an Aurelia application can be built using any package manager, build system, or bundler you want, the preferred tool to manage an Aurelia project is the command line interface, a.k.a. the CLI. At the moment of writing, the CLI only supports NPM as its package manager and requirejs as its module loader and bundler, probably because they both are the most mature and stable. It also uses Gulp 4 behind the scene as its build system. CLI-based applications are always bundled when running, even in development environments. This means that the performance of an application during development will be very close to what it should be like in production. This also means that bundling is a recurring concern, as new external libraries must be added to some bundle in order to be available at runtime. In this article, we’ll stick with the preferred solution and use the CLI. There are however two appendices at the end of the article covering alternatives, a first for Webpack, and a second for SystemJS with JSPM. Installing the CLI The CLI being a command line tool, it should be installed globally, by opening a console and executing the following command: > npm install -g aurelia-cli You may have to run this command with administrator privileges, depending on your environment. If you already have it installed, make sure you have the latest version, by running the following command: > au -v You can then compare the version this command outputs with the latest version number tagged on GitHub, at https://github.com/aurelia/cli/releases/latest. If you don’t have the latest version, you can simply update it by running the following command: > npm install -g aurelia-cli If for some reason the command to update the CLI fails, simply uninstall then reinstall it: > npm uninstall aurelia-cli -g > npm install aurelia-cli -g This should reinstall the latest version. The project skeletons As an alternative to the CLI, project skeletons are available at https://github.com/aurelia/skeleton-navigation. This repository contains multiple sample projects, sitting on different technologies such as SystemJS with JSPM, Webpack, ASP .Net Core, or TypeScript. Prepping up a skeleton is easy. You simply need to download and unzip the archive from GitHub or clone the repository locally. Each directory contains a distinct skeleton. Depending on which one you chose, you’ll need to install different tools and run setup commands. Generally, the instructions in the skeleton’s README.md file are pretty clear. Our application Creating an Aurelia application using the CLI is extremely simple. You just need to open a console in the directory where you want to create your project and run the following command: > au new The CLI’s project creation process will start, and you should see something like this: The first thing the CLI will ask for is the name you want to give to your project. This name will be used both to create the directory in which the project will live and to set some values, such as the name property in the package.json file it will create. Let’s name our application learning-aurelia: Next, the CLI asks what technologies we want to use to develop our application. Here, you can select a custom transpiler such as TypeScript and a CSS preprocessor such as LESS or SASS. Transpiler: Little cousin of the compiler, it translates one programming language into another. In our case, it will be used to transform ESNext code, which may not be supported by all browsers, into ES5, which is understood by all modern browsers. The default choice is to use ESNext and plain CSS, and this is what we will choose: The following steps simply recap the choices we made and ask for confirmation to create the project, then ask if we want to install our project’s dependencies which it does by default. At this point, the CLI will create the project and run an npm install behind the scene. Once it completes, our application is ready to roll: At this point, the directory you ran au new in will contain a new directory named learning-aurelia. This sub-directory will contain the Aurelia project. We’ll explore it a bit in the following section. The CLI is likely to change and offer more options in the future, as there are plans to support additional tools and technologies. Don’t be surprised if you see different or new options when you run it. The path we followed to create our project uses Visual Studio Code as the default code editor. If you want to use another editor such as Atom, Sublime, or WebStorm, which are the other supported options at the moment of writing, you simply need to select option #3 custom transpilers, CSS pre-processors and more at the beginning of the creation process, then select the default answer for each question until asked to select your default code editor. The rest of the creation process should stay pretty much the same. Note that if you select a different code editor, your own experience may differ from the examples and screenshots you’ll find in this article, as Visual Studio Code is the editor that was used during writing. If you are a TypeScript developer, you may want to create a TypeScript project. I however recommend that you stick with plain ESNext, as every example and code sample in this article has been written in JS. Trying to follow with TypeScript may prove cumbersome, although you can try if you like the challenge. The Structure of a CLI-Based Project If you open the newly created project in a code editor, you should see the following file structure: node_modules: The standard NPM directory containing the project’s dependencies; src: The directory containing the application’s source code; test: The directory containing the application’s automated test suites. .babelrc: The configuration file for Babel, which is used by the CLI to transpile our application’s ESNext code into ES5 so most browsers can run it; index.html: The HTML page that loads and launches the application; karma.conf.js: The configuration file for Karma, which is used by the CLI to run unit tests; package.json: The standard Node.js project file. The directory contains other files such as .editorconfig, .eslintrc.json, and .gitignore that are of little interest to learn Aurelia, so we won’t cover them. In addition to all of this, you should see a directory named aurelia_project. This directory contains things related to the building and bundling of the application using the CLI. Let’s see what it’s made of. The aurelia.json file The first thing of importance in this directory is a file named aurelia.json. This file contains the configuration used by the CLI to test, build, and bundle the application. This file can change drastically depending on the choices you make during the project creation process. There are very few scenarios where this file needs to be modified by hand. Adding an external library to the application is such a scenario. Apart from this, this file should mostly never be updated manually. The first interesting section in this file is the platform: "platform": { "id": "web", "displayName": "Web", "output": "scripts", "index": "index.html" }, This section tells the CLI that the output directory where the bundles are written is named scripts. It also tells that the HTML index page, which will load and launch the application, is the index.html file. The next interesting part is the transpiler section: "transpiler": { "id": "babel", "displayName": "Babel", "fileExtension": ".js", "options": { "plugins": [ "transform-es2015-modules-amd" ] }, "source": "src/**/*.js" }, This section tells the CLI to transpile the application’s source code using Babel. It also defines additional plugins as some are already configured in .babelrc to be used when transpiling the source code. In this case, it adds a plugin that will output transpiled files as AMD-compliant modules, for requirejs compatibility. Tasks The aurelia_project directory contains a subdirectory named tasks. This subdirectory contains various Gulp tasks to build, run, and test the application. These tasks can be executed using the CLI. The first thing you can try is to run au without any argument: > au This will list all available commands, along with their available arguments. This list includes built-in commands such as new, which we used already, or generate, which we’ll see in the next section along with the Gulp tasks declared in the tasks directory. To run one of those tasks, simply execute au with the name of the task as its first argument: > au build This command will run the build task which is defined in aurelia_project/tasks/build.js. This task transpiles the application code using Babel, executes the CSS and markup preprocessors if any, and bundles the code in the scripts directory. After running it, you should see two new files in scripts: app-bundle.js and vendor-bundle.js. Those are the actual files that will be loaded by index.html when the application is launched. The former contains all application code both JS files and templates, while the later contains all external libraries used by the application including Aurelia libraries. You may have noticed a command named run in the list of available commands. This task is defined in aurelia_project/tasks/run.js, and executes the build task internally before spawning a local HTTP server to serve the application: > au run By default, the HTTP server will listen for requests on the port 9000, so you can open your favorite browser and go to http://localhost:9000/ to see the default, demo application in action. If you ever need to change the port number on which the development HTTP server runs, you just need to open aurelia_project/tasks/run.js, and locate the call to the browserSync function. The object passed to this function contains a property named port. You can change its value accordingly. The run task can accept a --watch switch: > au run --watch If this switch is present, the task will keep monitoring the source code and, when any code file changes, will rebuild the application and automatically refresh the browser. This can be pretty useful during development. Generators The CLI also offers a way to generate code, using classes defined in the aurelia_project/generators directory. At the moment of writing, there are generators to create custom attributes, custom elements, binding behaviors, value converters, and even tasks and generators, yes, there is a generator to generate generators. If you are not familiar with Aurelia at all, most of those concepts, value converters, binding behaviors, and custom attributes and elements probably mean nothing to you. Don’t worry. A generator can be executed using the built-in generate command: > au generate attribute This command will run the custom attribute generator. It will ask for the name of the attribute to generate then create it in the src/resources/attributes directory. If you take a look at this generator which is found in aurelia_project/generators/attribute.js, you’ll see that the file exports a single class named AttributeGenerator. This class uses the @inject decorator to declare various classes from the aurelia-cli library as dependencies and have instances of them injected in its constructor. It also defines an execute method, which is called by the CLI when running the generator. This method leverages the services provided by aurelia-cli to interact with the user and generate code files. The exact generator names available by default are attribute, element, binding-behavior, value-converter, task, and generator. Environments CLI-based applications support environment-specific configuration values. By default, the CLI supports three environments—development, staging, and production. The configuration object for each of these environments can be found in the different files dev.js, stage.js, and prod.js located in the aurelia_project/environments directory. A typical environment file looks like this: aurelia_project/environments/dev.js export default { debug: true, testing: true }; By default, the environment files are used to enable debugging logging and test-only templating features in the Aurelia framework depending on the environment we’ll see this in a next section. The environment objects can however be enhanced with whatever properties you may need. Typically, it could be used to configure different URLs for a backend, depending on the environment. Adding a new environment is simply a matter of adding a file for it in the aurelia_project/environments directory. For example, you can add a local environment by creating a local.js file in the directory. Many tasks, basically build and all other tasks using it, such as run and test expect an environment to be specified using the env argument: > au build --env prod Here, the application will be built using the prod.js environment file. If no env argument is provided, dev will be used by default. When executed, the build task just copies the proper environment file to src/environment.js before running the transpiler and bundling the output. This means that src/environment.js should never be modified by hand, as it will be automatically overwritten by the build task. The Structure of an Aurelia application The previous section described the files and folders that are specific to a CLI-based project. However, some parts of the project are pretty much the same whatever the build system and package manager are. These are the more global topics we will see in this section. The hosting page The first entry point of an Aurelia application is the HTML page loading and hosting it. By default, this page is named index.html and is located at the root of the project. The default hosting page looks like this: index.html <!DOCTYPE html> <html> <head> <meta charset="utf-8"> <title>Aurelia</title> </head> <body aurelia-app="main"> <script src="scripts/vendor-bundle.js" data-main="aurelia-bootstrapper"></script> </body> </html> When this page loads, the script element inside the body element loads the scripts/vendor-bundle.js file, which contains requirejs itself along with definitions for all external libraries and references to app-bundle.js. When loading, requirejs checks the data-main attribute and uses its value as the entry point module. Here, aurelia-bootstrapper kicks in. The bootstrapper first looks in the DOM for elements with the aurelia-app attribute, we can find such an attribute on the body element in the default index.html file. This attribute identifies elements acting as application viewports. The bootstrapper uses the attribute’s value as the name of the application’s main module and locates the module, loads it, and renders the resulting DOM inside the element, overwriting any previous content. The application is now running. Even though the default application doesn’t illustrate this scenario, it is possible for an HTML file to host multiple Aurelia applications. It just needs to contain multiple elements with an aurelia-app attribute, each element referring to its own main module. The main module By convention, the main module referred to by the aurelia-app attribute is named main, and as such is located under src/main.js. This file is expected to export a configure function, which will be called by the Aurelia bootstrapping process and will be passed a configuration object used to configure and boot the framework. By default, the main configure function looks like this: src/main.js import environment from './environment'; export function configure(aurelia) { aurelia.use .standardConfiguration() .feature('resources'); if (environment.debug) { aurelia.use.developmentLogging(); } if (environment.testing) { aurelia.use.plugin('aurelia-testing'); } aurelia.start().then(() => aurelia.setRoot()); } The configure function starts by telling Aurelia to use its defaults configuration, and to load the resources feature. It also conditionally loads the development logging plugin based on the environment’s debug property, and the testing plugin based on the environment’s testing property. This means that, by default, both plugins will be loaded in development, while none will be loaded in production. Lastly, the function starts the framework then attaches the root component to the DOM. The start method returns a Promise, whose resolution triggers the call to setRoot. If you are not familiar with Promises in JavaScript, I strongly suggest that you look it up before going any further, as they are a core concept in Aurelia. The root component At the root of any Aurelia application is a single component, which contains everything within the application. By convention, this root component is named app. It is composed of two files—app.html, which contains the template to render the component, and app.js, which contains its view-model class. In the default application, the template is extremely simple: src/app.html <template> <h1>${message}</h1> </template> This template is made of a single h1 element, which will contain the value of the view-model’s message property as text, thanks to string interpolation. The app view-model looks like this: src/app.js export class App { constructor() { this.message = 'Hello World!'; } } This file simply exports a class having a message property containing the string “Hello World!”. This component will be rendered when the application starts. If you run the application and navigate to the application in your favorite browser, you’ll see a h1 element containing “Hello World!”. You may notice that there is no reference to Aurelia in this component’s code. In fact, the view-model is just plain ESNext and it can be used by Aurelia as is. Of course, we’re going to leverage many Aurelia features in many of our view-models later on, so most of our view-models will in fact have dependencies on Aurelia libraries, but the key point here is that you don’t have to use any Aurelia library in your view-models if you don’t want to, because Aurelia is designed to be as less intrusive as possible. Conventional bootstrapping It is possible to leave the aurelia-app attribute empty in the hosting page: <body aurelia-app> In such a case, the bootstrapping process is much simpler. Instead of loading a main module containing a configure function, the bootstrapper will simply use the framework’s default configuration and load the app component as the application root. This can be a simpler way to get started for a very simple application, as it negates the need for the src/main.js file you can simply delete it. However, it means that you are stuck with the default framework configuration. You cannot load features nor plugins. For most real-life applications, you’ll need to keep the main module, which means specifying it as the aurelia-app attribute’s value. Customizing Aurelia configuration The configure function of the main module receives a configuration object, which is used to configure the framework: src/main.js //Omitted snippet… aurelia.use .standardConfiguration() .feature('resources'); if (environment.debug) { aurelia.use.developmentLogging(); } if (environment.testing) { aurelia.use.plugin('aurelia-testing'); } //Omitted snippet… Here, the standardConfiguration() method is a simple helper that encapsulates the following: aurelia.use .defaultBindingLanguage() .defaultResources() .history() .router() .eventAggregator(); This is the default Aurelia configuration. It loads the default binding language, the default templating resources, the browser history plugin, the router plugin, and the event aggregator. This is the default set of features that a typical Aurelia application uses. All those plugins will be covered at one point or another throughout this article. All those plugins are optional except the binding language, which is needed by the templating engine. If you don’t need one, just don’t load it. In addition to the standard configuration, some plugins are loaded depending on the environment’s settings. When the environment’s debug property is true, Aurelia’s console logger is loaded using the developmentLogging() method, so traces and errors can be seen in the browser console. When the environment’s testing property is true, the aurelia-testing plugin is loaded using the plugin method. This plugin registers some resources that are useful when debugging components. The last line in the configure function starts the application and displays its root component, which is named app by convention. You may, however, bypass the convention and pass the name of your root component as the first argument to setRoot, if you named it otherwise: aurelia.start().then(() => aurelia.setRoot('root')); Here, the root component is expected to sit in the src/root.html and src/root.js files. Summary Getting started with Aurelia is very easy, thanks to the CLI. Installing the tooling and creating an empty project is simply a matter of running a couple of commands, and it takes typically more time waiting for the initial npm install to complete than doing the actual setup. We’ll go over dependency injection and logging, and we’ll start building our application by adding components and configuring routes to navigate between them. Resources for Article: Further resources on this subject: Introduction to JavaScript [article] Breaking into Microservices Architecture [article] Create Your First React Element [article]

In this post, I will share with you my experience in designing and coding an extensible chat bot using YAML and JavaScript. I will show you that it's not always required to use AI, ML, or NPL to make a great bot. This won't be a step-by-step guide. My goal is to give you an overview of a project like this and inspire you to build your own. Getting Started The concept I will offer you consists of creating a collection of YAML scripts that will represent all the possible conversations that the bot can handle. When a new conversation starts, the YAML code gets converted to a JavaScript object that we can easily manage in Node.js. I have used WebSockets implemented with socket.io to transmit the messages back and forth. First, we need to agree on a set of commands that can be used to create the YAML scripts, let’s start with some essentials: messages: To send an array of messages from the bot to the user input: To ask the user for some data next: The action we want to perform next within the script script: The next script that will follow in the conversation with the user when, empty, not-empty: conditional statements YAML script example A sample script will look like the following:   Link to the gist Then we need to implement those commands in our bot engine. The Bot engine Using the WebSockets I send to the bot the name of the script that I want to play, the bot engine loads it and converts it to a JavaScript object. If the client doesn't know which script to play first, it can call a default script called “hello” that will introduce the bot. In each script, the first action to run will be the one with index 0. As per the example above, the first thing the bot will do is sending two messages to the user:   With the command next we jump to the next block, index = 1. Again we send another message and immediately after an input request.   At this point, the client receives the input request and allows the user to type the answer. Submitted the value, we send the data back to the bot that will append the information to a key-value store, where all data is received from the user live and is accessible via a key (for example,user_name). Using the when statement, we define conditional branches of the conversation. When dealing with data validation this is often this case. In the example, we want to make sure to get a valid name from the user, so if the value received is empty, we jump back in the script and ask for it again, continuing with the following steponly when the name is valid. Finally, the bot will send a message, this time containing a variable previously received and stored in the key-value store.   In the next script, we will see how to handle multiple choice and buttons, to allow the user to make a decision.   Link to the gist The conversation will start with a message from the bot,followed by an input request, with input type set as buttons_single_select which in the in client it translates to “display multiple buttons” using an array of options received with the input request:   When the user clicks on one of the options, the UI sends back the choice of the user to the bot which will eventually match it with one of the existing branches. Found the correct branch the bot engine will look for the next command to run, in this case is another another input request, this time expecting to receive an image from the client.   Once the file has been sent, the conversation ends just after the bot sends a last message confirming the file got uploaded successfully. Using YAML gives you the flexibility to build many different conversations and also allows you to easily implement A/B testing of your conversation. Implementing the bot engine with JavaScript / Node.js To build something able to play the YAML scripts above, you need to iterate the script commands until you find an explicit end command. It’s very important to keep in memory the index of current command in progress, so that you can move on as soon as the current task completes. When you meet a new command, you should pass it to a resolver that knows what each command does and is able to run the specific portion of code or function. Additionally, you will need a function that listens to the input received from the clients, validating and saving it into a key-value store. Extending the command set This approach allows you to create a large set of commands, that do different things including queries, Ajax requests, API calls to external services, etc. You can combine your command with a when statement so that a callback or promise can evolve in its specific branch depending on the result you got. Conclusion If you are wondering where the demo images come from, they are a screenshot of a React view built with the help of devices.css, a CSS package that provides the flat shape of iPhone, Android, and Windows phones in different colors only using pure CSS. I have built this view to test the bot, using socket.io-client for the WebSockets and React for the UI. This is not just a proof of concept; I am working on a project where we have currently implemented this logic. I invite you to review, think about it and leave a feedback. Thanks! About the author Andrea Falzetti is an enthusiastic full-stack developer based in London. He has been designing and developing web applications for over 5 years. He is currently focused on node.js, react, microservices architecture, serverless, conversational UI, chat bots and machine learning. He is currently working at Activate Media, where his role is to estimate, design and lead the development of web and mobile platforms.

In this article by Edward Snajder, the author of Raspberry Pi Zero Cookbook, we pick up from having our operating system installed and our Raspberry Pi Zero on our home network. We can now dive into some basic Linux commands. You will find knowing these commands useful any time you are working on a Linux machine. In this article, we'll start prepping with some Linux recipes: (For more resources related to this topic, see here.) Navigating a filesystem and viewing and searching the contents of a directory Creating a new file, editing it in an editor, and changing ownership Renaming and copying/moving the file/folder into a new directory Installing and uninstalling a program Navigating a filesystem and viewing and searching the contents of a directory If you aren’t already a Linux or Mac user, getting around the filesystem can seem pretty alien at first. Truly, if you’ve only used Windows Explorer, this is going to seem like a strange, alien process. Once you start getting the hang of things, though, you’ll find that getting around the Linux filesystem is easy and fun. Getting ready The only thing you need to get started is a client connection to your Raspberry Pi Zero. I like to use SSH, but you can certainly connect using the serial connection or a terminal in X Windows. How to do it… If you want to find out where you are in the filesystem, use pwd: pi@rpz14101:~$ pwd /home/pi This tells me I’m in the /home/pi directory, which is the default home directory for the pi user. Generally, every user you create should get a /home/username directory to keep their own files in. This can be done automatically with user creation and the adduser command. To look at the contents of the directory you are in, use the ls command: pi@rpz14101:~$ ls Desktop Downloads Pictures python_games share Videos Documents Music Public Scratch Templates To look in another directory, simply specify the directory you want to list (you may need to use sudo depending on where you are looking): pi@rpz14101:~$ sudo ls /opt/ cookbook.share pigpio sonic-pi vc minecraft-pi share testsudo.deleteme Wolfram This is a nice quick summary of what files are in the directory, but you will usually want a little more information about the files and directories. The ls command has a ton of options, all of which can be displayed with ls –help and explained in more detail with man ls. Some of the best ones to know are as follows: -a show all files (regular and hidden) -l show long format (more file information, in columns) -h human readable (turns bytes into MB or GB as appropriate) -t or -tr order in time order, or reverse time order My typical command when I start looking in a directory is this one: ls -ltrh This produces all non-hidden files, with human-readable sizes, in column format, and the newest file at the bottom: pi@rpz14101:~$ ls -ltrh /opt/ total 513M drwxr-xr-x 7 root root 4.0K May 27 04:11 vc drwxr-xr-x 3 root root 4.0K May 27 04:32 Wolfram drwxr-xr-x 3 root root 4.0K May 27 04:34 pigpio drwxr-xr-x 4 root root 4.0K May 27 04:36 minecraft-pi drwxr-xr-x 5 root root 4.0K May 27 04:36 sonic-pi -rw-r--r-- 1 root root 0 Jul 4 13:41 testsudo.deleteme drwxr-xr-x 2 root root 4.0K Jul 9 13:05 share -rwxr-xr-x 1 root root 512M Jul 24 17:53 cookbook.share One last trick: if you need this format but there are a lot of files in the directory you are searching, you will see a ton of text scroll by. Maybe you just need the most recent or largest files? We can do this with a pipe (|) and the tail command. Let’s take a directory with a lot of files, such as /usr/lib/. To list the five most recently modified files, I can pipe ls -ltrh to the tail command: pi@rpz14101:~$ ls -ltrh /usr/lib/ | tail -5 lrwxrwxrwx 1 root root 22 May 27 04:40 libwiringPiDev.so -> libwiringPiDev.so.2.32 drwxr-xr-x 2 root root 4.0K Jun 5 10:38 samba drwxr-xr-x 3 root root 4.0K Jul 4 22:48 pppd drwxr-xr-x 65 root root 60K Jul 24 15:48 arm-linux-gnueabihf drwxr-xr-x 2 root root 4.0K Jul 24 15:48 tmpfiles.d What about the five largest files? Instead of the t in -ltrh, I can use S: pi@rpz14101:~$ ls -lSrh /usr/lib/ | tail -5 -rw-r--r-- 1 root root 2.8M Sep 17 2014 libmozjs185.so.1.0.0 -rw-r--r-- 1 root root 2.8M Sep 30 2014 libqscintilla2.so.11.3.0 -rw-r--r-- 1 root root 2.9M Jun 5 2014 libcmis-0.4.so.4.0.1 -rw-r--r-- 1 root root 3.4M Jun 12 2015 libv8.so.3.14.5 -rw-r--r-- 1 root root 5.1M Aug 18 2014 libmwaw-0.3.so.3.0.1 A little creative piping and you can find exactly the file you are looking for. If not, another great tool for exploring the filesystem is tree. This gives a pseudo-graphical tree that shows how the files are structured in the system. It produces a lot of text, especially if you have it print an entire directory tree. If just looking into directory structures, you can use tree with the -d flag for directories only. The -L flag will reduce how deep you dive into nested directories: pi@rpz14101:~$ tree -d -L 2 /opt/ /opt/ ├── minecraft-pi │ ├── api │ └── data ├── pigpio │ └── cgi ├── share ├── sonic-pi │ ├── app │ ├── bin │ └── etc ├── vc │ ├── bin │ ├── include │ ├── lib │ ├── sbin │ └── src └── Wolfram └── WolframEngine Last, we will look at a couple of searching utilities, find and grep. The find command is a powerful function that finds files in whatever directories you specify. It is great for trying to find that mystery piece of software that installed itself in an odd place or the needle-in-a-haystack file in a directory that contains hundreds of files. For example, if I were to run tree in the /opt/sonic-pi/ directory, it would run on for several seconds, and thousands of files would shoot by. I, however, am only interested in finding files with cowbell in the name. I can use the find command to look for it: pi@rpz14101:~$ find /opt/sonic-pi/ -name *cowbell* /opt/sonic-pi/etc/samples/drum_cowbell.flac When looking for anything with cowbell in the filename, the find command returns the exactly location of anything that matches. There are tons of options for using the find command; start with find –help, and then try man find when you want to get really deep. The grep command can be used in a couple different ways when searching for files, and it is one of those commands you will find yourself using constantly while both loving and hating its awesome power. Let’s say you need to find something inside of a file—grep is the tool for you. It can also find things like find can, but generally, find is more efficient at finding filename patterns than grep is. If I use grep to look for cowbells in my sonic-pi directory, I’ll get a different, and more colorful, output: We don’t see the file with cowbell in the name like we did using find, but we find every file that contains cowbell inside of it. The -r flag tells grep to delve into subdirectories, and -i tells it to ignore cases with cowbells (so Cowbell and cowbell are both found, as shown in the screenshot). As you use Linux more often, both find and grep become regularly used tools for administration and file management. This won’t be the last time you use them! Creating a new file, editing it in an editor, and changing ownership There are a lot of different text editors to use on a Linux system from the command line. The program vi is the Ubuntu default, and the program you will find installed on pretty much any Linux system. Emacs is another popular editor, and lots of Linux users get quite passionate about which one is better. My preference is vim, which is generally known as vi improved. The nano text editor is another one that is commonly installed on Linux distros, and it is one of the most lightweight editors available. Getting ready For this recipe, we will work with vi, since that’s definitely going to be installed on your system. If you want to try out vim, you can install it using this: sudo apt-get vim How to do it… First we will go to our share directory: cd /home/pi/share Then, we will create an empty file using the touch command: touch ch3_touchfile.txt If you use the ls command from the previous directory, you can see that the size of the file is 0. You can also display the contents of the file with the cat command, which will return nothing in this case. The touch command is a great way to test whether you have permissions to create files in a specific directory. You can also create a new file with the editor itself: vi ch3_vifile.txt This will open the vi editor with a blank file named ch3_vifile.txt: Using vi or vim (or Emacs) for the first time is completely different from using something like OpenOffice or Microsoft Word. Vi works in two modes: insert (or edit) and command. Once you learn how to use command mode, vi becomes a very efficient editor for working on scripts in bash or Python. Edit mode, more or less, is the mode where you can type and edit text like a regular WYSIWYG editor. There are books written on becoming a power user of vi, well beyond the scope of this book. Getting a handle on the basics is the best place to start: With the empty file, you can jump into edit mode by pressing the i or a keys. The editor will switch to insert mode, as shown by the -- INSERT -- in the bottom left of the screen. Then you can you start typing in your text: To get out of insert mode, press the Esc key. The :w command will save the file, and the :q command will quit. You can combine them, so :wq saves the file and quits. You can verify that the contents were saved with the cat command: pi@rpz14101:~$ cat ch3_vifile.txt Hello from the Raspberry Pi Zero Cookbook! Let’s take another look at the ls command and some of the information the -l format includes. We will take a look at the files we’ve created so far in this recipe: pi@rpz14101:~$ ls -ltrh *.txt -rw-r--r-- 1 pi pi 43 Jul 25 11:23 ch3_vifile.txt -rw-r--r-- 1 pi pi 0 Jul 25 11:24 ch3_touchfile.txt File Permissions Number of links Owner:Group Size Modification Date File Name -rw-r--r-- 1 pi:pi 43 Jul 25 11:23 ch3_vifile.txt We can see that since we made the files as the pi user, the owner of the file and the group owner are pi. By default, when a new user is created, a group container is created as well, so root has a root group, user rpz has an rpz group, and so on. We can change the ownership settings of a file with the chown command. Be careful, since you can take away your own access, though you can always sudo your way back. The chmod command will change who is allowed to do what with a file. Let’s look at ownership changes and what impact they will have with a few examples: pi@rpz14101:~ $ ls -ltrh *.txt -rw-r--r-- 1 pi pi 0 Jul 25 13:28 ch3_touchfile.txt -rwx------ 1 pi pi 43 Jul 25 13:28 ch3_vifile.txt pi@rpz14101:~ $ cat ch3_vifile.txt Hello from the Raspberry Pi Zero Cookbook! pi@rpz14101:~ $ sudo chown rpz:rpz ch3_vifile.txt pi@rpz14101:~ $ cat ch3_vifile.txt cat: ch3_vifile.txt: Permission denied pi@rpz14101:~ $ sudo cat ch3_vifile.txt Hello from the Raspberry Pi Zero Cookbook! pi@rpz14101:~ $ sudo chown rpz:pi ch3_vifile.txt pi@rpz14101:~ $ cat ch3_vifile.txt cat: ch3_vifile.txt: Permission denied pi@rpz14101:~ $ sudo chmod 750 ch3_vifile.txt pi@rpz14101:~ $ cat ch3_vifile.txt Hello from the Raspberry Pi Zero Cookbook! pi@rpz14101:~ $ sudo chown root:root ch3_vifile.txt pi@rpz14101:~ $ cat ch3_vifile.txt cat: ch3_vifile.txt: Permission denied pi@rpz14101:~ $ sudo chmod 755 ch3_vifile.txt pi@rpz14101:~ $ cat ch3_vifile.txt Hello from the Raspberry Pi Zero Cookbook! The chmod values are documented very well, and with a little practice, you can get your file permissions and ownership set up in a way that is both secure and easy to work with. Renaming and copying/moving the file/folder into a new directory A common activity on any filesystem is the practice of copying and moving files, and even directories, from one place to another. You might do it to make a backup copy of something, or you might decide that the contents should live in a more appropriate location. This recipe will explore how to manipulate files in the Raspbian system. Getting ready If you are still in your terminal from the last recipe, we are going to use the same files from the previous recipe. We should have the ownership back to pi:pi; if not, run the following: sudo chown pi:pi /home/pi/*.txt How to do it… First, let’s make a new directory. We’ll put it under the /home/pi/share/ folder so it is accessible to other computers on your home network. To make a directory, use the mkdir command: pi@rpz14101:~$ mkdir /home/pi/share/ch3 We can look at the new directory with the ls command: pi@rpz14101:~$ ls -ltrh /home/pi/share/ total 4.0K -rw-r--r-- 1 pi pi 0 Jul 24 15:56 helloNetwork.yes drwxr-xr-x 2 pi pi 4.0K Jul 25 13:06 ch3 A great flag to go with the mkdir command is -p. This will allow you to create directories and subdirectories in one command. Without it, if I try to create a subdirectory that doesn’t already exist, I’ll get an error: pi@rpz14101:~$ mkdir /home/pi/share/ch3/nested/folders mkdir: cannot create directory ‘/home/pi/share/ch3/nested/folders’: No such file or directory With the -p flag, it works without a problem: pi@rpz14101:~$ mkdir -p /home/pi/share/ch3/nested/folders The tree command shows the structure of our ch3 directory: pi@rpz14101:~$ tree /home/pi/share /home/pi/share ├── ch3 │ └── nested │ └── folders └── helloNetwork.yes 3 directories, 1 file Now, let’s move our files to our new ch3 directory. The copy and move commands—cp and mv, respectively—are the tools we will use. Copying a file from one place to another is as simple as indicating the file's source and destination. The following command will make a copy of vifile.txt and save it as vifile.txt.copy in the /home/pi/share/ch3/ directory: cp /home/pi/ch3_vifile.txt /home/pi/share/ch3/ch3_vifile.txt.copy We can copy files as well as directories and their contents as long as you have enough disk space. To move or rename a file, we use the mv command. This takes the file given in the source and moves it to the destination provided. As simple as the cp command, let’s move all of our files to the share directory: mv /home/pi/ch3_vifile.txt /home/pi/share/ch3/ch3_vifile.txt.moved mv /home/pi/ch3_touchfile.txt /home/pi/share/ch3/ch3_touchfile.txt If we look at the tree of our share directory, we will see everything nicely organized: pi@rpz14101:~$ tree /home/pi/share/ /home/pi/share/ ├── ch3 │ ├── ch3_touchfile.txt │ ├── ch3_vifile.txt.copy │ ├── ch3_vifile.txt.moved │ └── nested │ └── folders └── helloNetwork.yes 3 directories, 4 files Installing and uninstalling a program We’ve installed a few programs throughout the book so far, but have yet to delve into the apt-get command and the family of software-installation utilities. Now, we will learn how to install and uninstall any program available for Raspbian as well as how to search for new software and run updates. Getting ready Stay in your terminal window, and get ready to install some applications! How to do it… The apt-* commands are a suite of utilities that allow you to do various things with installed packages. To install a package, we use the apt-get tool, and the install command, like this: sudo apt-get install <packagename> Let’s install something cool—how about a Matrix screensaver? It is super easy and works great from the command line. To look for a package, we use the apt-cache search command. apt-cache is another tool in the apt-* family of utilities, and it checks the software database for matches. Running sudo apt-cache search matrix results tons of results! The word "matrix" is a little too popular for us computer and math nerds—we have matrixes everywhere! It would take forever to go through that list to find what we are looking for. Fortunately, we can take advantage of grep, which we touched on in an earlier recipe, to narrow down our results. One of the fun things about using Linux and the command line is the ways you can chain commands to do cool things: pi@rpz14101:~ $ sudo apt-cache search matrix | grep "The Matrix" cmatrix - simulates the display from "The Matrix" wmmatrix - View The Matrix in a Window Maker dock application That’s a bit more manageable! We could also have narrowed the list using this command: sudo apt-cache search “The Matrix” This returns fewer results than before, but a few more than the grep command. Whichever way you find it, we see that the cmatrix package is the one we are looking for. Installing is as simple as running this: pi@rpz14101:~ $ ` Reading package lists... Done Building dependency tree Reading state information... Done Suggested packages: cmatrix-xfont The following NEW packages will be installed: cmatrix 0 upgraded, 1 newly installed, 0 to remove and 0 not upgraded. Need to get 16.2 kB of archives. After this operation, 27.6 kB of additional disk space will be used. Get:1 http://mirrordirector.raspbian.org/raspbian/ jessie/main cmatrix armhf 1.2a-5 [16.2 kB] Fetched 16.2 kB in 1s (15.3 kB/s) Selecting previously unselected package cmatrix. (Reading database ... 121906 files and directories currently installed.) Preparing to unpack .../cmatrix_1.2a-5_armhf.deb ... Unpacking cmatrix (1.2a-5) ... Processing triggers for man-db (2.7.0.2-5) ... Setting up cmatrix (1.2a-5) ... After that, we are ready to go! Channel your inner Neo and run this command: cmatrix -s -b You should be in the Matrix! Try it on your serial and SSH connections, and even in the terminal on VNC: you’ll notice differences in the rendering behavior. There are literally thousands of software packages available to install in the repositories of our awesome open source communities. Pretty much anything you think a computer should be able to do, someone, or a group of people, has worked on a solution and pushed it out to the repositories.  We will be using apt-get a lot throughout this cookbook; it is one of the commands you’ll find yourself using all the time as you get more interested in Raspberry Pis and the Linux operating system. Running sudo apt-get update will check all repositories to see whether there are any version updates available. Here, you can see all of the locations it checks to see whether there is anything new for Raspbian: pi@rpz14101:~ $ sudo apt-get update Get:1 http://archive.raspberrypi.org jessie InRelease [13.2 kB] Get:2 http://mirrordirector.raspbian.org jessie InRelease [14.9 kB] Get:3 http://archive.raspberrypi.org jessie/main armhf Packages [144 kB] Get:4 http://mirrordirector.raspbian.org jessie/main armhf Packages [8,981 kB] Hit http://archive.raspberrypi.org jessie/ui armhf Packages Ign http://archive.raspberrypi.org jessie/main Translation-en_GB Get:5 http://mirrordirector.raspbian.org jessie/contrib armhf Packages [37.5 kB] Ign http://archive.raspberrypi.org jessie/main Translation-en Get:6 http://mirrordirector.raspbian.org jessie/non-free armhf Packages [70.3 kB] Ign http://archive.raspberrypi.org jessie/ui Translation-en_GB Ign http://archive.raspberrypi.org jessie/ui Translation-en Get:7 http://mirrordirector.raspbian.org jessie/rpi armhf Packages [1,356 B] Ign http://mirrordirector.raspbian.org jessie/contrib Translation-en_GB Ign http://mirrordirector.raspbian.org jessie/contrib Translation-en Ign http://mirrordirector.raspbian.org jessie/main Translation-en_GB Ign http://mirrordirector.raspbian.org jessie/main Translation-en Ign http://mirrordirector.raspbian.org jessie/non-free Translation-en_GB Ign http://mirrordirector.raspbian.org jessie/non-free Translation-en Ign http://mirrordirector.raspbian.org jessie/rpi Translation-en_GB Ign http://mirrordirector.raspbian.org jessie/rpi Translation-en Fetched 9,263 kB in 34s (272 kB/s) Reading package lists... Done After updating, apt-get upgrade will look at the versions of everything you have installed and upgrade anything to the latest version if there is one available. Depending on how many updates you have, this can take quite a while: pi@rpz14101:~ $ sudo apt-get upgrade Reading package lists... Done Building dependency tree Reading state information... Done Calculating upgrade... Done The following packages will be upgraded: dpkg-dev gir1.2-gdkpixbuf-2.0 initramfs-tools libavcodec56 libavformat56 libavresample2 libavutil54 libdevmapper-event1.02.1 libdevmapper1.02.1 libdpkg-perl python-picamera python3-picamera raspberrypi-kernel raspberrypi-net-mods ssh tzdata xarchiver 40 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. Need to get 57.0 MB of archives. After this operation, 415 kB of additional disk space will be used. Do you want to continue? [Y/n] y Get:1 http://archive.raspberrypi.org/debian/ jessie/main nodered armhf 0.14.5 [5,578 kB] … Adding 'diversion of /boot/overlays/w1-gpio.dtbo to /usr/share/rpikernelhack/overlays/w1-gpio.dtbo by rpikernelhack' … run-parts: executing /etc/kernel/postrm.d/initramfs-tools 4.4.11-v7+ /boot/kernel7.img Preparing to unpack .../raspberrypi-net-mods_1.2.3_armhf.deb ... Unpacking raspberrypi-net-mods (1.2.3) over (1.2.2) ... Processing triggers for man-db (2.7.0.2-5) ... … Setting up libssl1.0.0:armhf (1.0.1t-1+deb8u2) ... Setting up libxml2:armhf (2.9.1+dfsg1-5+deb8u2) ... … Removing 'diversion of /boot/overlays/w1-gpio-pullup.dtbo to /usr/share/rpikernelhack/overlays/w1-gpio-pullup.dtbo by rpikernelhack' … Setting up raspberrypi-net-mods (1.2.3) ... Modified /etc/network/interfaces detected. Leaving unchanged and writing new file as interfaces.new. Processing triggers for libc-bin (2.19-18+deb8u4) ... Processing triggers for initramfs-tools (0.120+deb8u2) ... You don’t really have to understand the details of what’s going on during the upgrade, and it will let you know if there were any problems at the end (and often what to do to fix them). Regularly updating and upgrading will keep all of your software current with all of the latest bug fixes and security patches. There’s more… You can also add and remove software from the GUI. If you log on to your Pi, either directly to a monitor or over VNC Server (a recipe we covered earlier), you can find the Add / Remove Software option under Menu | Preferences: The PiPackages utility makes it very easy to find software when you only have a general idea of what you are looking for. While you can do the same things with the apt commands, if you are browsing, this is a little easier on the eyes. The utility provides categorizations so you don’t have to scroll through every package. Clicking on a package provides a detailed description: Simply check the box and click on Apply or OK, and the software will be installed. Now you can install software on your Raspberry Pi Zero from the command line or GUI. Summary In this article, we looked at the basic file manipulation functionalities of Linux on a Raspberry Pi. We saw how to navigate the filesystem and create, edit, rename, copy, and move files and folders. We also saw how to change ownership of a file and install and uninstall programs. Resources for Article: Further resources on this subject: Sending Notifications using Raspberry Pi Zero [Article] Raspberry Pi LED Blueprints [Article] Hacking a Raspberry Pi project? Understand electronics first! [Article]

In this article by Habib Ahmed Qureshi, Ganesan Senthilvel, and Ovais Mehboob Ahmed Khan, author of the book Enterprise Application Architecture with .NET Core, you will learn how to architect and design highly scalable, robust, clean, and highly performant applications in .NET Core 1.0. (For more resources related to this topic, see here.) In this article, we will cover the following topics: Why we need Enterprise Architecture? Knowing the role of an architect Why we need Enterprise Architecture? We will need to define, or at least provide, some basic fixed points to identify enterprise architecture specifically. Sketch Before playing an enterprise architect role, I used to get confused with so many architectural roles and terms, such as architect, solution architect, enterprise architect, data architect, blueprint, system diagram, and so on. In general, the industry perception is that the IT architect role is to draw few boxes with few suggestions; rest is with the development community. They feel that the architect role is quite easy just by drawing the diagram and not doing anything else. Like I said, it is completely a perception of few associates in the industry, and I used to be dragged by this category earlier: However, my enterprise architect job has cleared this perception and understands the true value of an enterprise architect. Definition of Enterprise Architecture In simple terms, enterprise is nothing but human endeavor. The objective of an enterprise is where people are collaborating for a particular purpose supported by a platform. Let me explain with an example of an online e-commerce company. Employees of that company are people who worked together to produce the profit of the firm using their various platforms, such as infrastructure, software, equipment, building, and so on. Enterprise has the structure/arrangements of all these pieces/components to build the complete organization. This is the exact place where enterprise architecture plays its key role. Every enterprise has an enterprise architect. EA is a process of architecting that applies the discipline to produce the prescribed output components. This process needs the experience, skill, discipline, and descriptions. Consider the following image where EA anticipates the system in two key states: Every enterprise needs an enterprise architect, not an optional. Let me give a simple example. When you need a car for business activities, you have two choices, either drive yourself or rent a driver. Still, you will need the driving capability to operate the car. EA is pretty similar to it. As depicted in the preceding diagram, EA anticipates the system in two key states, which are as follows: How it currently is How will it be in the future Basically, they work on options/alternatives to move from current to future state of an enterprise system. In this process, Enterprise Architecture does the following: Creates the frameworks to manage the architect Details the descriptions of the architect Roadmaps to lay the best way to change/improve the architecture Defines constraint/opportunity Anticipates the costs and benefits Evaluates the risks and values In this process of architecting, the system applies the discipline to produce the prescribed output components. Stakeholders of Enterprise Architecture Enterprise Architecture is so special because to its holistic view of management and evolution of an enterprise holistically. It has the unique combination of specialist technology, such as architecture frameworks and design pattern practices. Such a special EA has the following key stakeholders/users in its eco system: S.No. Stakeholders Organizational actions 1  Strategic planner Capability planning Set strategic direction Impact analysis 2  Decision makers Investment Divestment Approvals for the project Alignment with strategic direction 3  Analyst Quality assurance Compliance Alignment with business goals 4  Architects, project managers Solution development Investigate the opportunities Analysis of the existing options Business benefits Though many organizations intervened without EAs, every firm has the strong belief that it is better to architect before creating any system. It is integrated in coherent fashion with proactively designed system instead of random ad hoc and inconsistent mode. In terms of business benefits, cost is the key factor in the meaning of Return on Investment (RoI). That is how the industry business is driven in this highly competitive IT world. EA has the opportunity to prove its value for its own stakeholders with three major benefits, ranging from tactical to strategic positions. They are as follows: Cost reduction by technology standardization Business Process Improvement (BPI) Strategic differentiation Gartner's research paper on TCO: The First Justification for Enterprise IT Architecture by Colleen Young is one of the good references to justify the business benefits of an Enterprise Architecture. Check out https://www.gartner.com/doc/388268/enterprise-architecture-benefits-justification for more information. In the grand scheme of cost saving strategy, technology standardization adds a lot of efficiency to make the indirect benefits. Let me share my experience in this space. In one of my earlier legacy organization, it was noticed that the variety of technologies and products were built to server the business purpose due to the historical acquisitions and mergers. The best solution was platform standardization. All businesses have processes; few life examples are credit card processing, employee on-boarding, student enrollment, and so on. In this methodology, there are people involved with few steps for the particular system to get things done. In means of the business growth, the processes become chaotic, which leads to the duplicate efforts across the departments. Here, we miss the cross learning of the mistakes and corrections. BPI is an industry approach that is designed to support the enterprise for the realignment of the existing business operational process into the significant improved process. It helps the enterprise to identify and adopt in a better way using the industry tools and techniques. BPI is originally designed to induce a drastic game changing effect in the enterprise performance instead of bringing the changes in the incremental steps. In the current highly competitive market, strategic differentiation efforts make the firm create the perception in customers minds of receiving something of greater value than offered by the competition. An effective differentiation strategy is the best tool to highlight a business's unique features and make it stand out from the crowd. As the outcome of strategic differentiation, the business should realize the benefits on Enterprise Architecture investment. Also, it makes the business to institute the new ways of thinking to add the new customer segments along with new major competitive strategies. Knowing the role of an architect When I planned to switch my career to architecture track, I had too many questions in mind. People were referring to so many titles in the industry, such as architect, solution architect, enterprise architect, data architect, infra architect, and so on that I didn't know where exactly do I need to start and end. Industry had so many confusions to opt for. To understand it better, let me give my own work experiences as the best use cases. In the IT industry, two higher-level architects are named as follows: Solution architect (SA) Enterprise architect (EA) In my view, Enterprise Architecture is a much broader discipline than Solution Architecture with the sum of Business Architecture, Application Architecture, Data Architecture, and Technology Architecture. It will be covered in detail in the subsequent section: SA is focused on a specific solution and addresses the technological details that are compiled to the standards, roadmaps, and strategic objectives of the business. On comparing with SA, EA is at senior level. In general, EA takes a strategic, inclusive, and long term view at goals, opportunities, and challenges facing the company. However, SA is assigned to a particular project/program in an enterprise to ensure technical integrity and consistency of the solution at every stage of its life cycle. Role comparison between EA and SA Let me explain the working experiences of two different roles—EA and SA. When I played the SA role for Internet based telephony system, my role needs to build the tools, such as code generation, automation, and so on around the existing telephony system. It needs the skill set of the Microsoft platform technology and telephony domain to understand the existing system in a better way and then provide the better solution to improve the productivity and performance of the existing ecosystem. I was not really involved in the enterprise-level decision making process. Basically, it was pretty much like an individual contributor to build effective and efficient solutions to improvise the current system. As the second work, let me share my experience on the EA role for a leading financial company. The job was to build the enterprise data hub using the emerging big data technology. Degree of comparisons If we plot EA versus SA graphically, EA needs the higher degree of strategy focus and technology breath, as depicted in the following image: In terms of roles and responsibilities, EA and SA differ in their scope. Basically, the SA scope is limited within a project team and the expected delivery is to make the system quality of the solution to the business. In the same time, the EA scope is beyond SA by identifying or envisioning the future state of an organization. Summary In this article, you understood the fundamental concepts of enterprise architecture, and its related business need and benefits. Resources for Article: Further resources on this subject: Getting Started with ASP.NET Core and Bootstrap 4 [Article] Setting Up the Environment for ASP.NET MVC 6 [Article] How to Set Up CoreOS Environment [Article]

In this article by Nathan Rozentals, author of the book Mastering TypeScript, Second Edition, you will learn how to build enterprise-ready, industrial web applications using TypeScript and leading JavaScript frameworks. In this article, we will cover the following topics: What is TypeScript? The benefits of TypeScript (For more resources related to this topic, see here.) What is TypeScript? TypeScript is both a language and a set of tools to generate JavaScript. It was designed by Anders Hejlsberg at Microsoft (the designer of C#) as an open source project to help developers write enterprise scale JavaScript. TypeScript generates JavaScript – it's as simple as that. Instead of requiring a completely new runtime environment, TypeScript generated JavaScript can reuse all of the existing JavaScript tools, frameworks, and wealth of libraries that are available for JavaScript. The TypeScript language and compiler, however, brings the development of JavaScript closer to a more traditional object-oriented experience. EcmaScript JavaScript as a language has been around for a long time, and is also governed by a language feature standard. The language defined in this standard is called ECMAScript, and each JavaScript interpreter must deliver functions and features that conform to this standard. The definition of this standard helped the growth of JavaScript and the web in general, and allowed websites to render correctly on many different browsers on many different operating systems. The ECMAScript standard was published in 1999 and is known as ECMA-262, third edition. With the popularity of the language, and the explosive growth of internet applications, the ECMAScript standard needed to be revised and updated. This process resulted in a draft specification for ECMAScript, called the fourth edition. Unfortunately, this draft suggested a complete overhaul of the language, and was not well received. Eventually, leaders from Yahoo, Google, and Microsoft tabled an alternate proposal which they called ECMAScript 3.1. This proposal was numbered 3.1, as it was a smaller feature set of the third edition, and sat between edition three and four of the standard. This proposal for language changes tabled earlier was eventually adopted as the fifth edition of the standard, and was called ECMAScript 5. The ECMAScript fourth edition was never published, but it was decided to merge the best features of both the fourth edition and the 3.1 feature set into a sixth edition named ECMAScript Harmony. The TypeScript compiler has a parameter that can switch between different versions of the ECMAScript standard. TypeScript currently supports ECMAScript 3, ECMAScript 5, and ECMAScript 6. When the compiler runs over your TypeScript, it will generate compile errors if the code you are attempting to compile is not valid for that standard. The team at Microsoft has committed to follow the ECMAScript standards in any new versions of the TypeScript compiler, so as new editions are adopted, the TypeScript language and compiler will follow suit. The benefits of TypeScript To give you a flavor of the benefits of TypeScript (and this is by no means the full list), let's have a very quick look at some of the things that TypeScript brings to the table: A compilation step Strong or static typing Type definitions for popular JavaScript libraries Encapsulation Private and public member variable decorators Compiling One of the most frustrating things about JavaScript development is the lack of a compilation step. JavaScript is an interpreted language, and therefore needs to be run in order to test that it is valid. Every JavaScript developer will tell horror stories of hours spent trying to find bugs in their code, only to find that they have missed a stray closing brace { , or a simple comma ,– or even a double quote " where there should have been a single quote ' . Even worse, the real headaches arrive when you misspell a property name, or unwittingly reassign a global variable. TypeScript will compile your code, and generate compilation errors where it finds these sorts of syntax errors. This is obviously very useful, and can help to highlight errors before the JavaScript is run. In large projects, programmers will often need to do large code merges and with today's tools doing automatic merges, it is surprising how often the compiler will pick up these types of errors. While tools to do this sort of syntax checking like JSLint have been around for years, it is obviously beneficial to have these tools integrated into your IDE. Using TypeScript in a continuous integration environment will also fail a build completely when compilation errors are found, further protecting your programmers against these types of bugs. Strong typing JavaScript is not strongly typed. It is a language that is very dynamic, as it allows objects to change their properties and behavior on the fly. As an example of this, consider the following code: var test = "this is a string"; test = 1; test = function(a, b) { return a + b; } On the first line of the preceding code, the variable test is bound to a string. It is then assigned a number, and finally is redefined to be a function that expects two parameters. Traditional object-oriented languages, however, will not allow the type of a variable to change, hence they are called strongly typed languages. While all of the preceding code is valid JavaScript and could be justified, it is quite easy to see how this could cause runtime errors during execution. Imagine that you were responsible for writing a library function to add two numbers, and then another developer inadvertently reassigned your function to subtract these numbers instead. These sorts of errors may be easy to spot in a few lines of code, but it becomes increasingly difficult to find and fix these as your code base and your development team grows. Another feature of strong typing is that the IDE you are working in understands what type of variable you are working with, and can bring better autocomplete or Intellisense options to the fore. TypeScript's syntactic sugar TypeScript introduces a very simple syntax to check the type of an object at compile time. This syntax has been referred to as syntactic sugar, or more formally, type annotations. Consider the following TypeScript code: var test: string = "this is a string"; test = 1; test = function(a, b) { return a + b; } Note on the first line of this code snippet, we have introduced a colon : and a string keyword between our variable and its assignment. This type annotation syntax means that we are setting the type of our variable to be of type string, and that any code that does not adhere to these rules will generate a compile error. Running the preceding code through the TypeScript compiler will generate two errors: hello.ts(3,1): error TS2322: Type 'number' is not assignable to type 'string'. hello.ts(4,1): error TS2322: Type '(a: any, b: any) => any' is not assignable to type 'string'. The first error is fairly obvious. We have specified that the variable test is a string, and therefore attempting to assign a number to it will generate a compile error. The second error is similar to the first, and is, in essence, saying that we cannot assign a function to a string. In this way, the TypeScript compiler introduces strong or static typing to your JavaScript code, giving you all of the benefits of a strongly typed language. TypeScript is therefore described as a superset of JavaScript. Type definitions for popular JavaScript libraries As we have seen, TypeScript has the ability to annotate JavaScript, and bring strong typing to the JavaScript development experience. But how do we strongly type existing JavaScript libraries? The answer is surprisingly simple—by creating a definition file. TypeScript uses files with a .d.ts extension as a sort of header file, similar to languages such as C++, to superimpose strongly typing on existing JavaScript libraries. These definition files hold information that describes each available function, and or variables, along with their associated type annotations. Let's have a quick look at what a definition would look like. As an example, I have lifted a function from the popular Jasmine unit testing framework, called describe: var describe = function(description, specDefinitions) { return jasmine.getEnv().describe(description, specDefinitions); }; Note that this function has two parameters—description and specDefinitions. But JavaScript does not tell us what sort of variables these are. We would need to have a look at the Jasmine documentation to figure out how to call this function. If we head over to http://jasmine.github.io/2.0/introduction.html, we will see an example of how to use this function: describe("A suite", function () { it("contains spec with an expectation", function () { expect(true).toBe(true); }); }); From the documentation, then, we can easily see that the first parameter is a string, and the second parameter is a function. But there is nothing in JavaScript that forces us to conform to this API. As mentioned before, we could easily call this function with two numbers or inadvertently switch the parameters around, sending a function first, and a string second. We will obviously start getting runtime errors if we do this, but TypeScript using a definition file can generate compile-time errors before we even attempt to run this code. Let's have a look at a piece of the jasmine.d.ts definition file: declare function describe( description: string, specDefinitions: () => void ): void; This is the TypeScript definition for the describe function. Firstly, declare function describe tells us that we can use a function called describe, but that the implementation of this function will be provided at runtime. Clearly, the description parameter is strongly typed to a string, and the specDefinitions parameter is strongly typed to be a function that returns void. TypeScript uses the double braces () syntax to declare functions, and the arrow syntax to show the return type of the function. So () => void is a function that does not return anything. Finally, the describe function itself will return void. If our code were to try and pass in a function as the first parameter, and a string as the second parameter (clearly breaking the definition of this function), as shown in the following example: describe(() => { /* function body */}, "description"); TypeScript will generate the following error: hello.ts(11,11): error TS2345: Argument of type '() => void' is not assignable to parameter of type 'string'. This error is telling us that we are attempting to call the describe function with invalid parameters,andit clearly shows that TypeScript will generate errors if we attempt to use external JavaScript libraries incorrectly. DefinitelyTyped Soon after TypeScript was released, Boris Yankov started a Git Hub repository to house definition files, called Definitely Typed (http://definitelytyped.org). This repository has now become the first port of call for integrating external libraries into TypeScript, and it currently holds definitions for over 1,600 JavaScript libraries. Encapsulation One of the fundamental principles of object-oriented programming is encapsulation—the ability to define data, as well as a set of functions that can operate on that data, into a single component. Most programming languages have the concept of a class for this purpose, providing a way to define a template for data and related functions. Let's first take a look at a simple TypeScript class definition: class MyClass { add(x, y) { return x + y; } } varclassInstance = new MyClass(); var result = classInstance.add(1,2); console.log(`add(1,2) returns ${result}`); This code is pretty simple to read and understand. We have created a class, named MyClass, with a simple add function. To use this class we simply create an instance of it, and call the add function with two arguments. JavaScript, unfortunately, does not have a class statement, but instead uses functions to reproduce the functionality of classes. Encapsulation through classes is accomplished by either using the prototype pattern, or by using the closure pattern. Understanding prototypes and the closure pattern, and using them correctly, is considered a fundamental skill when writing enterprise-scale JavaScript. A closure is essentially a function that refers to independent variables. This means that variables defined within a closure function remember the environment in which they were created. This provides JavaScript with a way to define local variables, and provide encapsulation. Writing the MyClass definition in the preceding code, using a closure in JavaScript, would look something like the following: varMyClass = (function () { // the self-invoking function is the // environment that will be remembered // by the closure function MyClass() { // MyClass is the inner function, // the closure } MyClass.prototype.add = function (x, y) { return x + y; }; return MyClass; }()); varclassInstance = new MyClass(); var result = classInstance.add(1, 2); console.log("add(1,2) returns " + result); We start with a variable called MyClass, and assign it to a function that is executed immediately note the })(); syntax near the bottom of the closure definition. This syntax is a common way to write JavaScript in order to avoid leaking variables into the global namespace. We then define a new function named MyClass, and return this new function to the outer calling function. We then use the prototype keyword to inject a new function into the MyClass definition. This function is named add and takes two parameters, returning their sum. The last few lines of the code show how to use this closure in JavaScript. Create an instance of the closure type, and then execute the add function. Running this code will log add(1,2) returns 3 to the console, as expected. Looking at the JavaScript code versus the TypeScript code, we can easily see how simple the TypeScript looks compared to the equivalent JavaScript. Remember how we mentioned that JavaScript programmers can easily misplace a brace {, or a bracket (? Have a look at the last line in the closure definition—})();. Getting one of these brackets or braces wrong can take hours of debugging to find. Public and private accessors A further object oriented principle that is used in Encapsulation is the concept of data hiding that is the ability to have public and private variables. Private variables are meant to be hidden to the user of a particular class as these variables should only be used by the class itself. Inadvertently exposing these variables can easily cause runtime errors. Unfortunately, JavaScript does not have a native way of declaring variables private. While this functionality can be emulated using closures, a lot of JavaScript programmers simply use the underscore character _ to denote a private variable. At runtime though, if you know the name of a private variable you can easily assign a value to it. Consider the following JavaScript code: varMyClass = (function() { function MyClass() { this._count = 0; } MyClass.prototype.countUp = function() { this._count ++; } MyClass.prototype.getCountUp = function() { return this._count; } return MyClass; }()); var test = new MyClass(); test._count = 17; console.log("countUp : " + test.getCountUp()); The MyClass variable is actually a closure with a constructor function, a countUp function, and a getCountUp function. The variable _count is supposed to be a private member variable that is used only within the scope of the closure. Using the underscore naming convention gives the user of this class some indication that the variable is private, but JavaScript will still allow you to manipulate the variable _count. Take a look at the second last line of the code snippet. We are explicitly setting the value of _count to 17 which is allowed by JavaScript, but not desired by the original creator of the class. The output of this code would be countUp : 17. TypeScript, however, introduces the public and private keywords that can be used on class member variables. Trying to access a class member variable that has been marked as private will generate a compile time error. As an example of this, the JavaScript code above can be written in TypeScript, as follows: class CountClass { private _count: number; constructor() { this._count = 0; } countUp() { this._count ++; } getCount() { return this._count; } } varcountInstance = new CountClass() ; countInstance._count = 17; On the second line of our code snippet, we have declared a private member variable named _count. Again, we have a constructor, a countUp, and a getCount function. If we compile this file, the compiler will generate an error: hello.ts(39,15): error TS2341: Property '_count' is private and only accessible within class 'CountClass'. This error is generated because we are trying to access the private variable _count in the last line of the code. The TypeScript compiler, therefore, is helping us to adhere to public and private accessors by generating a compile error when we inadvertently break this rule. Summary In this article, we took a quick look at what TypeScript is and what benefits it can bring to the JavaScript development experience. Resources for Article: Further resources on this subject: Introducing Object Oriented Programmng with TypeScript [article] Understanding Patterns and Architecturesin TypeScript [article] Writing SOLID JavaScript code with TypeScript [article]

This article by Mario Castro Contreras, author of the book Go Design Patterns, introduces you to the Creational design patterns that are explained in the book. As the title implies, this article groups common practices for creating objects. Creational patterns try to give ready-to-use objects to users instead of asking for their input, which, in some cases, could be complex and will couple your code with the concrete implementations of the functionality that should be defined in an interface. (For more resources related to this topic, see here.) Singleton design pattern – Having a unique instance of an object in the entire program Have you ever done interviews for software engineers? It's interesting that when you ask them about design patterns, more than 80% will start saying Singleton design pattern. Why is that? Maybe it's because it is one of the most used design patterns out there or one of the easiest to grasp. We will start our journey on creational design patterns because of the latter reason. Description Singleton pattern is easy to remember. As the name implies, it will provide you a single instance of an object, and guarantee that there are no duplicates. At the first call to use the instance, it is created and then reused between all the parts in the application that need to use that particular behavior. Objective of the Singleton pattern You'll use Singleton pattern in many different situations. For example: When you want to use the same connection to a database to make every query When you open a Secure Shell (SSH) connection to a server to do a few tasks, and don't want to reopen the connection for each task If you need to limit the access to some variable or space, you use a Singleton as the door to this variable. If you need to limit the number of calls to some places, you create a Singleton instance to make the calls in the accepted window The possibilities are endless, and we have just mentioned some of them. Implementation Finally, we have to implement the Singleton pattern. You'll usually write a static method and instance to retrieve the Singleton instance. In Go, we don't have the keyword static, but we can achieve the same result by using the scope of the package. First, we create a structure that contains the object which we want to guarantee to be a Singleton during the execution of the program: package creational type singleton struct{ count int } var instance *singleton func GetInstance() *singleton { if instance == nil { instance = new(singleton) } return instance } func (s *singleton) AddOne() int { s.count++ return s.count } We must pay close attention to this piece of code. In languages like Java or C++, the variable instance would be initialized to NULL at the beginning of the program. In Go, you can initialize a pointer to a structure as nil, but you cannot initialize a structure to nil (the equivalent of NULL). So the var instance *singleton line defines a pointer to a structure of type Singleton as nil, and the variable called instance. We created a GetInstance method that checks if the instance has not been initialized already (instance == nil), and creates an instance in the space already allocated in the line instance = new(singleton). Remember, when we use the keyword new, we are creating a pointer to the type between the parentheses. The AddOne method will take the count of the variable instance, raise it by one, and return the current value of the counter. Lets run now our unit tests again: $ go test -v -run=GetInstance === RUN TestGetInstance --- PASS: TestGetInstance (0.00s) PASS ok Factory method – Delegating the creation of different types of payments The Factory method pattern (or simply, Factory) is probably the second-best known and used design pattern in the industry. Its purpose is to abstract the user from the knowledge of the structure it needs to achieve a specific purpose. By delegating this decision to a Factory, this Factory can provide the object that best fits the user needs or the most updated version. It can also ease the process of downgrading or upgrading of the implementation of an object if needed. Description When using the Factory method design pattern, we gain an extra layer of encapsulation so that our program can grow in a controlled environment. With the Factory method, we delegate the creation of families of objects to a different package or object to abstract us from the knowledge of the pool of possible objects we could use. Imagine that you have two ways to access some specific resource: by HTTP or FTP. For us, the specific implementation of this access should be invisible. Maybe, we just know that the resource is in HTTP or in FTP, and we just want a connection that uses one of these protocols. Instead of implementing the connection by ourselves, we can use the Factory method to ask for the specific connection. With this approach, we can grow easily in the future if we need to add an HTTPS object. Objective of the Factory method After the previous description, the following objectives of the Factory Method design pattern must be clear to you: Delegating the creation of new instances of structures to a different part of the program Working at the interface level instead of with concrete implementations Grouping families of objects to obtain a family object creator Implementation We will start with the GetPaymentMethod method. It must receive an integer that matches with one of the defined constants of the same file to know which implementation it should return. package creational import ( "errors" "fmt" ) type PaymentMethod interface { Pay(amount float32) string } const ( Cash = 1 DebitCard = 2 ) func GetPaymentMethod(m int) (PaymentMethod, error) { switch m { case Cash: return new(CashPM), nilcase DebitCard: return new(DebitCardPM), nil default: return nil, errors.New(fmt.Sprintf("Payment method %d not recognizedn", m)) } } We use a plain switch to check the contents of the argument m (method). If it matches any of the known methods—cash or debit card, it returns a new instance of them. Otherwise, it will return a nil and an error indicating that the payment method has not been recognized. Now we can run our tests again to check the second part of the unit tests: $go test -v -run=GetPaymentMethod . === RUN TestGetPaymentMethodCash --- FAIL: TestGetPaymentMethodCash (0.00s) factory_test.go:16: The cash payment method message wasn't correct factory_test.go:18: LOG: === RUN TestGetPaymentMethodDebitCard --- FAIL: TestGetPaymentMethodDebitCard (0.00s) factory_test.go:28: The debit card payment method message wasn't correct factory_test.go:30: LOG: === RUN TestGetPaymentMethodNonExistent --- PASS: TestGetPaymentMethodNonExistent (0.00s) factory_test.go:38: LOG: Payment method 20 not recognized FAIL exit status 1 FAIL Now we do not get the errors saying it couldn't find the type of payment methods. Instead, we receive a message not correct error when it tries to use any of the methods that it covers. We also got rid of the Not implemented message that was being returned when we asked for an unknown payment method. Lets implement the structures now: type CashPM struct{} type DebitCardPM struct{} func (c *CashPM) Pay(amount float32) string { return fmt.Sprintf("%0.2f paid using cashn", amount) } func (c *DebitCardPM) Pay(amount float32) string { return fmt.Sprintf("%#0.2f paid using debit cardn", amount) } We just get the amount, printing it in a nice formatted message. With this implementation, the tests will all passing now: $ go test -v -run=GetPaymentMethod . === RUN TestGetPaymentMethodCash --- PASS: TestGetPaymentMethodCash (0.00s) factory_test.go:18: LOG: 10.30 paid using cash === RUN TestGetPaymentMethodDebitCard --- PASS: TestGetPaymentMethodDebitCard (0.00s) factory_test.go:30: LOG: 22.30 paid using debit card === RUN TestGetPaymentMethodNonExistent --- PASS: TestGetPaymentMethodNonExistent (0.00s) factory_test.go:38: LOG: Payment method 20 not recognized PASS ok Do you see the LOG: messages? They aren't errors—we just print some information that we receive when using the package under test. These messages can be omitted unless you pass the -v flag to the test command: $ go test -run=GetPaymentMethod . ok Abstract Factory – A factory of factories After learning about the factory design pattern is when we grouped a family of related objects in our case payment methods, one can be quick to think: what if I group families of objects in a more structured hierarchy of families? Description The Abstract Factory design pattern is a new layer of grouping to achieve a bigger (and more complex) composite object, which is used through its interfaces. The idea behind grouping objects in families and grouping families is to have big factories that can be interchangeable and can grow more easily. In the early stages of development, it is also easier to work with factories and abstract factories than to wait until all concrete implementations are done to start your code. Also, you won't write an Abstract Factory from the beginning unless you know that your object's inventory for a particular field is going to be very large and it could be easily grouped into families. The objective Grouping related families of objects is very convenient when your object number is growing so much that creating a unique point to get them all seems the only way to gain flexibility of the runtime object creation. Following objectives of the Abstract Factory method must be clear to you: Provide a new layer of encapsulation for Factory methods that returns a common interface for all factories Group common factories into a super Factory (also called factory of factories) Implementation The implementation of every factory is already done for the sake of brevity. They are very similar to the factory method with the only difference being that in the factory method, we don't use an instance of the factory, because we use the package functions directly. The implementation of the vehicle factory is as follows: func GetVehicleFactory(f int) (VehicleFactory, error) { switch f { case CarFactoryType: return new(CarFactory), nil case MotorbikeFactoryType: return new(MotorbikeFactory), nil default: return nil, errors.New(fmt.Sprintf("Factory with id %d not recognizedn", f)) } } Like in any factory, we switched between the factory possibilities to return the one that was demanded. As we have already implemented all concrete vehicles, the tests must be run too: go test -v -run=Factory -cover . === RUN TestMotorbikeFactory --- PASS: TestMotorbikeFactory (0.00s) vehicle_factory_test.go:16: Motorbike vehicle has 2 wheels vehicle_factory_test.go:22: Sport motorbike has type 1 === RUN TestCarFactory --- PASS: TestCarFactory (0.00s) vehicle_factory_test.go:36: Car vehicle has 4 seats vehicle_factory_test.go:42: Luxury car has 4 doors. PASS coverage: 45.8% of statements ok All of them passed. Take a close look and note that we have used the -cover flag when running the tests to return a coverage percentage of the package 45.8%. What this tells us is that 45.8% of the lines are covered by the tests we have written, but 54.2% is still not under the tests. This is because we haven't covered the cruise motorbike and the Family car with tests. If you write those tests, the result should rise to around 70.8%. Prototype design pattern The last pattern we will see in this article is the Prototype pattern. Like all creational patterns, this too comes in handy when creating objects and it is very common to see the Prototype pattern surrounded by more patterns. Description The aim of the Prototype pattern is to have an object or a set of objects that are already created at compilation time, but which you can clone as many times as you want at runtime. This is useful, for example, as a default template for a user who has just registered with your webpage or a default pricing plan in some service. The key difference between this and a Builder pattern is that objects are cloned for the user instead of building them at runtime. You can also build a cache-like solution, storing information using a prototype. Objective Maintain a set of objects that will be cloned to create new instances Free CPU of complex object initialization to take more memory resources We will start with the GetClone method. This method should return an item of the specified type: type ShirtsCache struct {} func (s *ShirtsCache)GetClone(m int) (ItemInfoGetter, error) { switch m { case White: newItem := *whitePrototype return &newItem, nil case Black: newItem := *blackPrototype return &newItem, nil case Blue: newItem := *bluePrototype return &newItem, nil default: return nil, errors.New("Shirt model not recognized") } } The Shirt structure also needs a GetInfo implementation to print the contents of the instances. type ShirtColor byte type Shirt struct { Price float32 SKU string Color ShirtColor } func (s *Shirt) GetInfo() string { return fmt.Sprintf("Shirt with SKU '%s' and Color id %d that costs %fn", s.SKU, s.Color, s.Price) } Finally, lets run the tests to see that everything is now working: go test -run=TestClone -v . === RUN TestClone --- PASS: TestClone (0.00s) prototype_test.go:41: LOG: Shirt with SKU 'abbcc' and Color id 1 that costs 15.000000 prototype_test.go:42: LOG: Shirt with SKU 'empty' and Color id 1 that costs 15.000000 prototype_test.go:44: LOG: The memory positions of the shirts are different 0xc42002c038 != 0xc42002c040 PASS ok In the log (remember to set the -v flag when running the tests), you can check that shirt1 and shirt2 have different SKUs. Also, we can see the memory positions of both objects. Take into account that the positions shown on your computer will probably be different. Summary We have seen the creational design patterns commonly used in the software industry. Their purpose is to abstract the user from the creation of objects for handling complexity or maintainability purposes. Design patterns have been the foundation of thousands of applications and libraries since the nineties, and most of the software we use today has many of these creational patterns under the hood. Resources for Article: Further resources on this subject: Getting Started [article] Thinking Functionally [article] Auditing and E-discovery [article]

In this article by, Daniel Reis, the author of the book Odoo 10 Development Essentials, we will create our first Odoo application and learn the steps needed make it available to Odoo and install it. (For more resources related to this topic, see here.) Inspired by the notable http://todomvc.com/ project, we will build a simple To-Do application. It should allow us to add new tasks, mark them as completed, and finally clear the task list from all the already completed tasks. Understanding applications and modules It's common to hear about Odoo modules and applications. But what exactly is the difference between them? Module add-ons are building blocks for Odoo applications. A module can add new features to Odoo, or modify existing ones. It is a directory containing a manifest, or descriptor file, named __manifest__.py, plus the remaining files that implement its features. Applications are the way major features are added to Odoo. They provide the core elements for a functional area, such as Accounting or HR, based on which additional add-on modules modify or extend features. Because of this, they are highlighted in the Odoo Apps menu. If your module is complex, and adds new or major functionality to Odoo, you might consider creating it as an application. If you module just makes changes to existing functionality in Odoo, it is likely not an application. Whether a module is an application or not is defined in the manifest. Technically is does not have any particular effect on how the add-on module behaves. It is only used for highlight on the Apps list. Creating the module basic skeleton We should have the Odoo server at ~/odoo-dev/odoo/. To keep things tidy, we will create a new directory alongside it to host our custom modules, at ~/odoo-dev/custom-addons. Odoo includes a scaffold command to automatically create a new module directory, with a basic structure already in place. You can learn more about it with: $ ~/odoo-dev/odoo/odoo-bin scaffold --help You might want to keep this in mind when you start working your next module, but we won't be using it right now, since we will prefer to manually create all the structure for our module. An Odoo add-on module is a directory containing a __manifest__.py descriptor file. In previous versions, this descriptor file was named __openerp__.py. This name is still supported, but is deprecated. It also needs to be Python-importable, so it must also have an __init__.py file. The module's directory name is its technical name. We will use todo_app for it. The technical name must be a valid Python identifier: it should begin with a letter and can only contain letters, numbers, and the underscore character. The following commands create the module directory and create an empty __init__.py file in it, ~/odoo-dev/custom-addons/todo_app/__init__.py. In case you would like to do that directly from the command line, this is what you would use: $ mkdir ~/odoo-dev/custom-addons/todo_app $ touch ~/odoo-dev/custom-addons/todo_app/__init__.py Next, we need to create the descriptor file. It should contain only a Python dictionary with about a dozen possible attributes; of this, only the name attribute is required. A longer description attribute and the author attribute also have some visibility and are advised. We should now add a __manifest__.py file alongside the __init__.py file with the following content: { 'name': 'To-Do Application', 'description': 'Manage your personal To-Do tasks.', 'author': 'Daniel Reis', 'depends': ['base'], 'application': True, } The depends attribute can have a list of other modules that are required. Odoo will have them automatically installed when this module is installed. It's not a mandatory attribute, but it's advised to always have it. If no particular dependencies are needed, we should depend on the core base module. You should be careful to ensure all dependencies are explicitly set here; otherwise, the module may fail to install in a clean database (due to missing dependencies) or have loading errors, if by chance the other required modules are loaded afterwards. For our application, we don't need any specific dependencies, so we depend on the base module only. To be concise, we chose to use very few descriptor keys, but in a real word scenario, we recommend that you also use the additional keys since they are relevant for the Odoo apps store: summary: This is displayed as a subtitle for the module. version: By default, is 1.0. It should follow semantic versioning rules (see http://semver.org/ for details). license: By default, is LGPL-3. website: This is a URL to find more information about the module. This can help people find more documentation or the issue tracker to file bugs and suggestions. category: This is the functional category of the module, which defaults to Uncategorized. The list of existing categories can be found in the security groups form (Settings | User | Groups), in the Application field drop-down list. These other descriptor keys are also available: installable: It is by default True but can be set to False to disable a module. auto_install: If the auto_install module is set to True, this module will be automatically installed, provided all its dependencies are already installed. It is used for the Glue modules. Since Odoo 8.0, instead of the description key, we can use a README.rst or README.md file in the module's top directory. A word about licenses Choosing a license for your work is very important, and you should consider carefully what is the best choice for you, and its implications. The most used licenses for Odoo modules are the GNU Lesser General Public License (LGLP) and the Affero General Public License (AGPL). The LGPL is more permissive and allows commercial derivate work, without the need to share the corresponding source code. The AGPL is a stronger open source license, and requires derivate work and service hosting to share their source code. Learn more about the GNU licenses at https://www.gnu.org/licenses/. Adding to the add-ons path Now that we have a minimalistic new module, we want to make it available to the Odoo instance. For that, we need to make sure the directory containing the module is in the add-ons path, and then update the Odoo module list. We will position in our work directory and start the server with the appropriate add-ons path configuration: $ cd ~/odoo-dev $ ./odoo/odoo-bin -d todo --addons-path="custom-addons,odoo/addons" --save The --save option saves the options you used in a config file. This spares us from repeating them every time we restart the server: just run ./odoo-bin and the last saved options will be used. Look closely at the server log. It should have an INFO ? odoo: addons paths:[...] line. It should include our custom-addons directory. Remember to also include any other add-ons directories you might be using. For instance, if you also have a ~/odoo-dev/extra directory containing additional modules to be used, you might want to include them also using the option: --addons-path="custom-addons,extra,odoo/addons" Now we need the Odoo instance to acknowledge the new module we just added. Installing the new module In the Apps top menu, select the Update Apps List option. This will update the module list, adding any modules that may have been added since the last update to the list. Remember that we need the developer mode enabled for this option to be visible. That is done in the Settings dashboard, in the link at the bottom right, below the Odoo version number information . Make sure your web client session is working with the right database. You can check that at the top right: the database name is shown in parenthesis, right after the user name. A way to enforce using the correct database is to start the server instance with the additional option --db-filter=^MYDB$. The Apps option shows us the list of available modules. By default it shows only application modules. Since we created an application module we don't need to remove that filter to see it. Type todo in the search and you should see our new module, ready to be installed. Now click on the module's Install button and we're ready! The Model layer Now that Odoo knows about our new module, let's start by adding a simple model to it. Models describe business objects, such as an opportunity, sales order, or partner (customer, supplier, and so on.). A model has a list of attributes and can also define its specific business. Models are implemented using a Python class derived from an Odoo template class. They translate directly to database objects, and Odoo automatically takes care of this when installing or upgrading the module. The mechanism responsible for this is Object Relational Model (ORM). Our module will be a very simple application to keep to-do tasks. These tasks will have a single text field for the description and a checkbox to mark them as complete. We should later add a button to clean the to-do list from the old completed tasks. Creating the data model The Odoo development guidelines state that the Python files for models should be placed inside a models subdirectory. For simplicity, we won't be following this here, so let's create a todo_model.py file in the main directory of the todo_app module. Add the following content to it: # -*- coding: utf-8 -*- from odoo import models, fields class TodoTask(models.Model): _name = 'todo.task' _description = 'To-do Task' name = fields.Char('Description', required=True) is_done = fields.Boolean('Done?') active = fields.Boolean('Active?', default=True) The first line is a special marker telling the Python interpreter that this file has UTF-8 so that it can expect and handle non-ASCII characters. We won't be using any, but it's a good practice to have it anyway. The second line is a Python import statement, making available the models and fields objects from the Odoo core. The third line declares our new model. It's a class derived from models.Model. The next line sets the _name attribute defining the identifier that will be used throughout Odoo to refer to this model. Note that the actual Python class name , TodoTask in this case, is meaningless to other Odoo modules. The _name value is what will be used as an identifier. Notice that this and the following lines are indented. If you're not familiar with Python, you should know that this is important: indentation defines a nested code block, so these four lines should all be equally indented. Then we have the _description model attribute. It is not mandatory, but it provides a user friendly name for the model records, that can be used for better user messages. The last three lines define the model's fields. It's worth noting that name and active are special field names. By default, Odoo will use the name field as the record's title when referencing it from other models. The active field is used to inactivate records, and by default, only active records will be shown. We will use it to clear away completed tasks without actually deleting them from the database. Right now, this file is not yet used by the module. We must tell Python to load it with the module in the __init__.py file. Let's edit it to add the following line: from . import todo_model That's it. For our Python code changes to take effect the server instance needs to be restarted (unless it was using the --dev mode). We won't see any menu option to access this new model, since we didn't add them yet. Still we can inspect the newly created model using the Technical menu. In the Settings top menu, go to Technical | Database Structure | Models, search for the todo.task model on the list and then click on it to see its definition: If everything goes right, it is confirmed that the model and fields were created. If you can't see them here, try a server restart with a module upgrade, as described before. We can also see some additional fields we didn't declare. These are reserved fields Odoo automatically adds to every new model. They are as follows: id: A unique, numeric identifier for each record in the model. create_date and create_uid: These specify when the record was created and who created it, respectively. write_date and write_uid: These confirm when the record was last modified and who modified it, respectively. __last_update: This is a helper that is not actually stored in the database. It is used for concurrency checks. The View layer The View layer describes the user interface. Views are defined using XML, which is used by the web client framework to generate data-aware HTML views. We have menu items that can activate the actions that can render views. For example, the Users menu item processes an action also called Users, that in turn renders a series of views. There are several view types available, such as the list and form views, and the filter options made available are also defined by particular type of view, the search view. The Odoo development guidelines state that the XML files defining the user interface should be placed inside a views/ subdirectory. Let's start creating the user interface for our To-Do application. Adding menu items Now that we have a model to store our data, we should make it available on the user interface. For that we should add a menu option to open the To-do Task model so that it can be used. Create the views/todo_menu.xml file to define a menu item and the action performed by it: <?xml version="1.0"?> <odoo> <!-- Action to open To-do Task list --> <act_window id="action_todo_task" name="To-do Task" res_model="todo.task" view_mode="tree,form" /> <!-- Menu item to open To-do Task list --> <menuitem id="menu_todo_task" name="Todos" action="action_todo_task" /> </odoo> The user interface, including menu options and actions, is stored in database tables. The XML file is a data file used to load those definitions into the database when the module is installed or upgraded. The preceding code is an Odoo data file, describing two records to add to Odoo: The <act_window> element defines a client-side window action that will open the todo.task model with the tree and form views enabled, in that order The <menuitem> defines a top menu item calling the action_todo_task action, which was defined before Both elements include an id attribute. This id , also called an XML ID, is very important: it is used to uniquely identify each data element inside the module, and can be used by other elements to reference it. In this case, the <menuitem> element needs to reference the action to process, and needs to make use of the <act_window> id for that. Our module does not know yet about the new XML data file. This is done by adding it to the data attribute in the __manifest__.py file. It holds the list of files to be loaded by the module. Add this attribute to the descriptor's dictionary: 'data': ['views/todo_menu.xml'], Now we need to upgrade the module again for these changes to take effect. Go to the Todos top menu and you should see our new menu option available: Even though we haven't defined our user interface view, clicking on the Todos menu will open an automatically generated form for our model, allowing us to add and edit records. Odoo is nice enough to automatically generate them so that we can start working with our model right away. Odoo supports several types of views, but the three most important ones are: tree (usually called list views), form, and search views. We'll add an example of each to our module. Creating the form view All views are stored in the database, in the ir.ui.view model. To add a view to a module, we declare a <record> element describing the view in an XML file, which is to be loaded into the database when the module is installed. Add this new views/todo_view.xml file to define our form view: <?xml version="1.0"?> <odoo> <record id="view_form_todo_task" model="ir.ui.view"> <field name="name">To-do Task Form</field> <field name="model">todo.task</field> <field name="arch" type="xml"> <form string="To-do Task"> <group> <field name="name"/> <field name="is_done"/> <field name="active" readonly="1"/> </group> </form> </field> </record> </odoo> Remember to add this new file to the data key in manifest file, otherwise our module won't know about it and it won't be loaded. This will add a record to the ir.ui.view model with the identifier view_form_todo_task. The view is for the todo.task model and is named To-do Task Form. The name is just for information; it does not have to be unique, but it should allow one to easily identify which record it refers to. In fact the name can be entirely omitted, in that case it will be automatically generated from the model name and the view type. The most important attribute is arch, and contains the view definition, highlighted in the XML code above. The <form> tag defines the view type, and in this case contains three fields. We also added an attribute to the active field to make it read-only. Adding action buttons Forms can have buttons to perform actions. These buttons are able to trigger workflow actions, run window actions—such as opening another form, or run Python functions defined in the model. They can be placed anywhere inside a form, but for document-style forms, the recommended place for them is the <header> section. For our application, we will add two buttons to run the methods of the todo.task model: <header> <button name="do_toggle_done" type="object" string="Toggle Done" class="oe_highlight" /> <button name="do_clear_done" type="object" string="Clear All Done" /> </header> The basic attributes of a button comprise the following: The string attribute that has the text to be displayed on the button The type attribute referring to the action it performs The name attribute referring to the identifier for that action The class attribute, which is an optional attribute to apply CSS styles, like in regular HTML The complete form view At this point, our todo.task form view should look like this: <form> <header> <button name="do_toggle_done" type="object" string="Toggle Done" class="oe_highlight" /> <button name="do_clear_done" type="object" string="Clear All Done" /> </header> <sheet> <group name="group_top"> <group name="group_left"> <field name="name"/> </group> <group name="group_right"> <field name="is_done"/> <field name="active" readonly="1" /> </group> </group> </sheet> </form> Remember that for the changes to be loaded to our Odoo database, a module upgrade is needed. To see the changes in the web client, the form needs to be reloaded: either click again on the menu option that opens it or reload the browser page (F5 in most browsers). The action buttons won't work yet, since we still need to add their business logic. The business logic layer Now we will add some logic to our buttons. This is done with Python code, using the methods in the model's Python class. Adding business logic We should edit the todo_model.py Python file to add to the class the methods called by the buttons. First we need to import the new API, so add it to the import statement at the top of the Python file: from odoo import models, fields, api The action of the Toggle Done button will be very simple: just toggle the Is Done? flag. For logic on records, use the @api.multi decorator. Here, self will represent a recordset, and we should then loop through each record. Inside the TodoTask class, add this: @api.multi def do_toggle_done(self): for task in self: task.is_done = not task.is_done return True The code loops through all the to-do task records, and for each one, modifies the is_done field, inverting its value. The method does not need to return anything, but we should have it to at least return a True value. The reason is that clients can use XML-RPC to call these methods, and this protocol does not support server functions returning just a None value. For the Clear All Done button, we want to go a little further. It should look for all active records that are done and make them inactive. Usually, form buttons are expected to act only on the selected record, but in this case, we will want it also act on records other than the current one: @api.model def do_clear_done(self): dones = self.search([('is_done', '=', True)]) dones.write({'active': False}) return True On methods decorated with @api.model, the self variable represents the model with no record in particular. We will build a dones recordset containing all the tasks that are marked as done. Then, we set on the active flag to False on them. The search method is an API method that returns the records that meet some conditions. These conditions are written in a domain, which is a list of triplets. The write method sets the values at once on all the elements of a recordset. The values to write are described using a dictionary. Using write here is more efficient than iterating through the recordset to assign the value to each of them one by one. Set up access security You might have noticed that upon loading, our module is getting a warning message in the server log: The model todo.task has no access rules, consider adding one. The message is pretty clear: our new model has no access rules, so it can't be used by anyone other than the admin super user. As a super user, the admin ignores data access rules, and that's why we were able to use the form without errors. But we must fix this before other users can use our model. Another issue yet to address is that we want the to-do tasks to be private to each user. Odoo supports row-level access rules, which we will use to implement that. Adding access control security To get a picture of what information is needed to add access rules to a model, use the web client and go to Settings | Technical | Security | Access Controls List: Here we can see the ACL for some models. It indicates, per security group, what actions are allowed on records. This information has to be provided by the module using a data file to load the lines into the ir.model.access model. We will add full access to the Employee group on the model. Employee is the basic access group nearly everyone belongs to. This is done using a CSV file named security/ir.model.access.csv. Let's add it with the following content: id,name,model_id:id,group_id:id,perm_read,perm_write,perm_create,perm_unlink acess_todo_task_group_user,todo.task.user,model_todo_task,base.group_user,1,1,1,1 The filename corresponds to the model to load the data into, and the first line of the file has the column names. These are the columns provided by the CSV file: id: It is the record external identifier (also known as XML ID). It should be unique in our module. name: This is a description title. It is only informative and it's best if it's kept unique. Official modules usually use a dot-separated string with the model name and the group. Following this convention, we used todo.task.user. model_id: This is the external identifier for the model we are giving access to. Models have XML IDs automatically generated by the ORM: for todo.task, the identifier is model_todo_task. group_id: This identifies the security group to give permissions to. The most important ones are provided by the base module. The Employee group is such a case and has the identifier base.group_user. The last four perm fields flag the access to grant read, write, create, or unlink (delete) access. We must not forget to add the reference to this new file in the __manifest__.py descriptor's data attribute It should look like this: 'data': [ 'security/ir.model.access.csv', 'views/todo_view.xml', 'views/todo_menu.xml', ], As before, upgrade the module for these additions to take effect. The warning message should be gone, and we can confirm that the permissions are OK by logging in with the user demo (password is also demo). If we run our tests now it they should only fail the test_record_rule test case. Summary We created a new module from the start, covering the most frequently used elements in a module: models, the three basic types of views (form, list, and search), business logic in model methods, and access security. Always remember, when adding model fields, an upgrade is needed. When changing Python code, including the manifest file, a restart is needed. When changing XML or CSV files, an upgrade is needed; also, when in doubt, do both: restart the server and upgrade the modules. Resources for Article: Further resources on this subject: Getting Started with Odoo Development [Article] Introduction to Odoo [Article] Web Server Development [Article]

In this article written by Suresh Kumar Gorakala, author of the book Building Recommendation Engines we will learn how to build a basic recommender system using R. In this article we will learn about various types of recommender systems in detail. This article explains neighborhood-similarity-based recommendations, personalized recommendation engines, model-based recommender systems and hybrid recommendation engines. Following are the different subtypes of recommender systems covered in this article: Neighborhood-based recommendation engines User-based collaborative filtering Item-based collaborative filtering Personalized recommendation engines Content-based recommendation engines Context-aware recommendation engines (For more resources related to this topic, see here.) Neighborhood-based recommendation engines As the name suggests, neighborhood-based recommender systems considers the preferences or likes of other users in the neighborhood before making suggestions or recommendations to the active user. While considering the preferences or tastes of neighbors, we first calculate how similar the other users are to the active user and then new items from more similar users are recommended to the user. Here the active user is the person to whom the system is serving recommendations. Since similarity calculations are involved these recommender systems are also called similarity-based recommender systems. Also since preferences or tastes are considered collaboratively from a pool of users these recommender systems are also called as collaborative filtering recommender systems. In this type of systems the main actors are the users, products and users preference information such as rating/ranking/liking towards the products. Preceding image is an example from Amazon showing collaborative filtering The collaborative filtering systems come in two flavors, They are: User-based collaborative filtering Item-based collaborative filtering Collaborative filtering When we have only the users interaction data of the products such as ratings, like/unlike, view/not viewed and we have to recommend new products then we have to choose Collaborative filtering approach. User-based Collaborative Filtering The basic intuition behind user-based collaborative filtering systems is, people with similar tastes in the past like similar items in future as well. For example, if user A and user B have very similar purchase history and if user A buys a new book which user B has not yet seen then we can suggest this book to User B as they have similar tastes. Item-based Collaborative filtering In this type of recommender systems unlike user-based collaborative filtering, we use similarity between items instead of similarity between users. Basic intuition for item-based recommender systems is if a User likes item A in past he might like item B which is similar to item A. In this approach instead of calculating similarity between users we calculate similarity between items or products. The most common similarity measure used for this approach is cosine similarity. Like user-based collaborative approach, we project the data into vector space and similarity between items is calculated using cosine angle between items. Similar to user-based collaborative filtering approach there are two steps for item-based collaborative approach. They are: Calculating the similarity between items. Predicting the ratings for the non rated item for a active user by making use of previous ratings given to other similar items Advantages of user-based collaborative filtering Easy to implement Neither the content information of the products nor users profile information is required for building recommendations New items are recommended to users giving Surprise factor to the users Disadvantages of user-based collaborative filtering This approach is computationally expensive as all the user information, product, rating information is loaded into the memory for similarity calculations. This approach fails for new users where we do not have any information about the users. This problem is called cold-start problem. This approach performs very poor if we have little data. Since we do not have content information about users or products. We cannot generate recommendations accurately only based on rating information only. Content-based recommender systems The recommendations are generated by considering only the rating or interaction information of the products by the users, that is suggesting new items for the active user are based on the ratings given to those new items by similar users to the active user. Assume the case of a person has given 4 star rating to a movie. In a collaborative filtering approach we only consider this rating information for generating recommendations. In real, a person rates a movie based on the features or content of the movie such as its genre, actor, director, story, and screenplay. Also the person watches a movie based on his personal choices. When we are building a recommendation engine to target users at personal level, the recommendations should not be based on the tastes of other similar people but should be based on the individual users’ tastes and the contents of the products. A recommendation which is targeted at personalized level and which considers individual preferences and contents of the products for generating recommendations are called content-based recommender systems. Another motivation for building content-based recommendation engines are they solve the cold start problem which new users face in collaborative filtering approach. When a new user comes based on the preferences of the person we can suggest new items which are similar to his tastes. Building content-based recommender systems involves three main steps as follows: Generating content information for products. Generating a user profile, preferences with respect to the features of the products. Generating recommendations predicting list of items which the user might like. Let us discuss each step in detail: Content extraction: In this step, we extract the features that represent the product. Most commonly the content of the products is represented in the vector space model with products name as rows and features as columns. User Profile generation: In this step, we build the user profile or preference matrix or vector space model matching the products content. Generating Recommendations: Now that, we have the generated the product content and user profile, the next step will be to generate the recommendations. Recommender systems using machine learning or any other mathematical, statistical models to generate recommendations are called as model-based systems Cosine similarity In this approach we first represent the user profiles and product content in vector forms and then we take cosine angle between each vector. The product which forms less angle with the user profile is considered as the most preferable item for the user. This approach is a standard approach while using neighborhood approach for Content based recommendations. Empirical studies shown that this approach gives more accurate results compared to other similarity measures. Classification-based approach Classification-based approaches fall under model-based recommender systems. In this approach, first we build a machine learning model by using the historical information, with user profile similar to the product content as input and the like/dislike of the product as output response classes. Supervised classification tasks such as logistic regression, KNN-classification methods, probabilistic methods and so on can be used. Advantages Content-based recommender systems are targeting at individual level Recommendations are generated using the user preferences alone unlike from user community as in collaborative filtering This approaches can be employed at real time as recommendation model doesn’t need to load the entire data for processing or generating recommendations Accuracy is high compared to collaborative approaches as they deal with the content of the products instead of rating information alone Cold start problem can be easily handled Disadvantages As the system is more personalized and the generated recommendations will become narrowed down to only user preferences with more and more user information comes into the system As a result, no new products that are not related to the user preferences will be shown to the user The user will not be able to look at what is happening around or what’s trending around Context-aware recommender Systems Over the years there has been evolution in recommender systems from neighborhood approaches to personalized recommender systems which are targeted to the individual users. These personalized recommender systems have become a huge success as this is useful at end user level and for organizations these systems become catalysts to increase their business. The personalized recommender systems, also called as content-based recommender systems are also getting evolved into Context aware recommender systems. Though the personalized recommender systems are targeted at individual user level and caters recommendations based on the personal preferences of the users, still there was scope to improve or refine the systems. Same person at different places might have different requirements. Likewise same person has different requirements at different times. Our intelligent recommender systems should be evolved enough to cater to the needs of the users for different places, at different times. Recommender System should be robust enough to suggest cotton shirts to a person during summer and suggesting Leather Jacket in winter. Similarly based on the time of the day suggesting Good restaurants serving a person’s personal choice breakfast and dinner would be very helpful. These kinds of recommender systems which considers location, time, mood, and so on that defines the context of user and suggests personalized recommendations are called context aware recommender systems. At broad level, context aware recommender systems are content-based recommenders with the inclusion of new dimension called context. In context aware systems, recommendations are generated in two steps: Generating list of recommendations of products for each user based on users’ preferences, that is content-based recommendations. Filtering out the recommendations that are specific to a current context. For example, based on past transaction history, interaction information, browsing patterns, ratings information on e-wallet mobile app, assume that User A is a movie lover, Sports lover, fitness freak. Using this information the content-based recommender systems generate recommendations of products such as Movie Tickets, 4G data offer for watching Football matches, Discount offers at GYM. Now based on the GPS co-ordinates of the mobile if the User A found to be at a 10K RUN marathon, then my Context aware recommendation engine will take this location information as the context and filters out the offers that are relevant to the current context and recommends Discount Offers at GYM to the user A. Most common approaches for building Context Aware Recommender systems are: Post filtering Approaches Pre-filtering approaches Pre-filtering approaches In pre-filtering approach, context information is applied to the User profile and product content. This step will filter out all the non relevant features and final personalized recommendations are generated on remaining feature set. Since filtering of features are made before generating personalized recommendations, these are called pre-filtering approaches. Post filtering approaches In post-filtering, firstly personalized recommendations are generated based on the user profile and product catalogue then the context information is applied for filtering out the relevant products to the user for the current context. Advantages Context aware systems are much advanced than the personalized content-based recommenders as these systems will be constantly in sync with user movements and generate recommendations as per current context. These systems are more real-time nature. Disadvantages Serendipity or surprise factor as in other personalized recommenders will be missing in this type of recommendations as well. Summary In this article, we have learned about popular recommendation engine techniques such as, collaborative filtering, content-based recommendations, context aware systems, hybrid recommendations, model-based recommendation systems with their advantages and disadvantages. Different similarity methods such as cosine similarity, Euclidean distance, Pearson-coefficient. Sub categories within each of the recommendations are also explained. Resources for Article: Further resources on this subject: Building a Recommendation Engine with Spark [article] Machine Learning Tasks [article] Machine Learning with R [article]

This article by Aleksandar Prokopec, author of the book Learning Concurrent Programming in Scala - Second Edition, explains the concepts of asynchronous programming in Scala. Asynchronous programming helps you eliminate blocking; instead of suspending the thread whenever a resource is not available, a separate computation is scheduled to proceed once the resource becomes available. In a way, many of the concurrency patterns seen so far support asynchronous programming; thread creation and scheduling execution context tasks can be used to start executing a computation concurrent to the main program flow. Still, it is not straightforward to use these facilities directly when avoiding blocking or composing asynchronous computations. In this article, we will focus on two abstractions in Scala that are specifically tailored for this task—futures and promises. More specifically, we will study the following topics: Starting asynchronous computations and using Future objects Using Promise objects to interface Blocking threads inside asynchronous computations Alternative future frameworks (For more resources related to this topic, see here.) Futures The parallel executions in a concurrent program proceed on entities called threads. At any point, the execution of a thread can be temporarily suspended until a specific condition is fulfilled. When this happens, we say that the thread is blocked. Why do we block threads in the first place in concurrent programming? One of the reasons is that we have a finite amount of resources; so, multiple computations that share these resources sometimes need to wait. In other situations, a computation needs specific data to proceed, and if that data is not yet available, threads responsible for producing the data could be slow or the source of the data could be external to the program. A classic example is waiting for the data to arrive over the network. Let's assume that we have a getWebpage method that returns that webpage's contents when given a url string with the location of the webpage: def getWebpage(url: String): String The return type of the getWebpage method is String; the method must return a string with the webpage's contents. Upon sending an HTTP request, though, the webpage's contents are not available immediately. It takes some time for the request to travel over the network to the server and back before the program can access the document. The only way for the method to return the contents of the webpage as a string value is to wait for the HTTP response to arrive. However, this can take a relatively long period of time from the program's point of view even with a high-speed Internet connection, the getWebpage method needs to wait. Since the thread that called the getWebpage method cannot proceed without the contents of the webpage, it needs to pause its execution; therefore, the only way to correctly implement the getWebpage method is for blocking. We already know that blocking can have negative side effects, so can we change the return value of the getWebpage method to some special value that can be returned immediately? The answer is yes. In Scala, this special value is called a future. The future is a placeholder, that is, a memory location for the value. This placeholder does not need to contain a value when the future is created; the value can be placed into the future eventually by getWebpage. We can change the signature of the getWebpage method to return a future as follows: def getWebpage(url: String): Future[String] Here, the Future[String] type means that the future object can eventually contain a String value. We can now implement getWebpage without blocking—we can start the HTTP request asynchronously and place the webpage's contents into the future when they become available. When this happens, we can say that the getWebpage method completes the future. Importantly, after the future is completed with some value, that value can no longer change. The Future[T] type encodes latency in the program—use it to encode values that will become available later during execution. This removes blocking from the getWebpage method, but it is not clear how the calling thread can extract the content of the future. Polling is one non-blocking way of extracting the content. In the polling approach, the calling thread calls a special method for blocking until the value becomes available. While this approach does not eliminate blocking, it transfers the responsibility of blocking from the getWebpage method to the caller thread. Java defines its own Future type to encode values that will become available later. However, as a Scala developer, you should use Scala's futures instead; they allow additional ways of handling future values and avoid blocking, as we will soon see. When programming with futures in Scala, we need to distinguish between future values and future computations. A future value of the Future[T] type denotes some value of the T type in the program that might not be currently available, but could become available later. Usually, when we say a future, we really mean a future value. In the scala.concurrent package, futures are represented with the Future[T] trait: trait Future[T] By contrast, a future computation is an asynchronous computation that produces a future value. A future computation can be started by calling the apply method on the Future companion object. This method has the following signature in the scala.concurrent package: def apply[T](b: =>T)(implicit e: ExecutionContext): Future[T] This method takes a by-name parameter of the T type. This is the body of the asynchronous computation that results in some value of type T. It also takes an implicit ExecutionContext parameter, which abstracts over where and when the thread gets executed. Recall that Scala's implicit parameters can either be specified when calling a method, in the same way as normal parameters, or they can be left out; in this case, the Scala compiler searches for a value of the ExecutionContext type in the surrounding scope. Most Future methods take an implicit execution context. Finally, the Future.apply method returns a future of the T type. This future is completed with the value resulting from the asynchronous computation, b. Starting future computations Let's see how to start a future computation in an example. We first import the contents of the scala.concurrent package. We then import the global execution context from the Implicits object. This makes sure that the future computations execute on the global context—the default execution context you can use in most cases: import scala.concurrent._ import ExecutionContext.Implicits.global object FuturesCreate extends App { Future { log("the future is here") } log("the future is coming") Thread.sleep(1000) } The order in which the log method calls (in the future computation and the main thread) execute is nondeterministic. The Future singleton object followed by a block is syntactic sugar for calling the Future.apply method. In the following example, we can use the scala.io.Source object to read the contents of our build.sbt file in a future computation. The main thread calls the isCompleted method on the future value, buildFile, returned from the future computation. Chances are that the build file was not read so fast, so isCompleted returns false. After 250 milliseconds, the main thread calls isCompleted again, and this time, isCompleted returns true. Finally, the main thread calls the value method, which returns the contents of the build file: import scala.io.Source object FuturesDataType extends App { val buildFile: Future[String] = Future { val f = Source.fromFile("build.sbt") try f.getLines.mkString("n") finally f.close() } log(s"started reading the build file asynchronously") log(s"status: ${buildFile.isCompleted}") Thread.sleep(250) log(s"status: ${buildFile.isCompleted}") log(s"value: ${buildFile.value}") } In this example, we used polling to obtain the value of the future. The Future singleton object's polling methods are non-blocking, but they are also nondeterministic; the isCompleted method will repeatedly return false until the future is completed. Importantly, completion of the future is in a happens-before relationship with the polling calls. If the future completes before the invocation of the polling method, then its effects are visible to the thread after the polling completes. Shown graphically, polling looks as shown in the following figure: Polling diagram Polling is like calling your potential employer every five minutes to ask if you're hired. What you really want to do is hand in a job application and then apply for other jobs instead of busy-waiting for the employer's response. Once your employer decides to hire you, he will give you a call on the phone number you left him. We want futures to do the same; when they are completed, they should call a specific function that we left for them. Promises Promises are objects that can be assigned a value or an exception only once. This is why promises are sometimes also called single-assignment variables. A promise is represented with the Promise[T] type in Scala. To create a promise instance, we use the Promise.apply method on the Promise companion object: def apply[T](): Promise[T] This method returns a new promise instance. Like the Future.apply method, the Promise.apply method returns immediately; it is non-blocking. However, the Promise.apply method does not start an asynchronous computation, it just creates a fresh Promise object. When the Promise object is created, it does not contain a value or an exception. To assign a value or an exception to a promise, we use the success or failure method, respectively. Perhaps you have noticed that promises are very similar to futures. Both futures and promises are initially empty and can be completed with either a value or an exception. This is intentional—every promise object corresponds to exactly one future object. To obtain the future associated with a promise, we can call the future method on the promise. Calling this method multiple times always returns the same future object. A promise and a future represent two aspects of a single-assignment variable. The promise allows you to assign a value to the future object, whereas the future allows you to read that value. In the following code snippet, we create two promises, p and q, that can hold string values. We then install a foreach callback on the future associated with the p promise and wait for 1 second. The callback is not invoked until the p promise is completed by calling the success method. We then fail the q promise in the same way and install a failed.foreach callback: object PromisesCreate extends App { val p = Promise[String] val q = Promise[String] p.future foreach { case x => log(s"p succeeded with '$x'") } Thread.sleep(1000) p success "assigned" q failure new Exception("not kept") q.future.failed foreach { case t => log(s"q failed with $t") } Thread.sleep(1000) } Alternatively, we can use the complete method and specify a Try[T] object to complete the promise. Depending on whether the Try[T] object is a success or a failure, the promise is successfully completed or failed. Importantly, after a promise is either successfully completed or failed, it cannot be assigned an exception or a value again in any way. Trying to do so results in an exception. Note that this is true even when there are multiple threads simultaneously calling success or complete. Only one thread completes the promise, and the rest throw an exception. Assigning a value or an exception to an already completed promise is not allowed and throws an exception. We can also use the trySuccess, tryFailure, and tryComplete methods that correspond to success, failure, and complete states, respectively, but return a Boolean value to indicate whether the assignment was successful. Recall that using the Future.apply method and callback methods with referentially transparent functions results in deterministic concurrent programs. As long as we do not use the trySuccess, tryFailure, and tryComplete methods, and none of the success, failure, and complete methods ever throws an exception, we can use promises and retain determinism in our programs. We now have everything we need to implement our custom Future.apply method. We call it the myFuture method in the following example. The myFuture method takes a b by-name parameter that is the asynchronous computation. First, it creates a p promise. Then, it starts an asynchronous computation on the global execution context. This computation tries to evaluate b and complete the promise. However, if the b body throws a nonfatal exception, the asynchronous computation fails the promise with that exception. In the meanwhile, the myFuture method returns the future immediately after starting the asynchronous computation: import scala.util.control.NonFatal object PromisesCustomAsync extends App { def myFuture[T](b: =>T): Future[T] = { val p = Promise[T] global.execute(new Runnable { def run() = try { p.success(b) } catch { case NonFatal(e) => p.failure(e) } }) p.future } val f = myFuture { "naa" + "na" * 8 + " Katamari Damacy!" } f foreach { case text => log(text) } } This is a common pattern when producing futures. We create a promise, let some other computation complete that promise, and return the corresponding future. However, promises were not invented just for our custom future's myFuture computation method. In the following sections, we will study use cases in which promises are useful. Futures and blocking Futures and asynchronous computations mainly exist to avoid blocking, but in some cases, we cannot live without it. It is, therefore, valid to ask how blocking interacts with futures. There are two ways to block with futures. The first way is to wait until a future is completed. The second way is by blocking from within an asynchronous computation. We will study both the topics in this section. Awaiting futures In rare situations, we cannot use callbacks or future combinators to avoid blocking. For example, the main thread that starts multiple asynchronous computations has to wait for these computations to finish. If an execution context uses daemon threads, as is the case with the global execution context, the main thread needs to block to prevent the JVM process from terminating. In these exceptional circumstances, we use the ready and result methods on the Await object from the scala.concurrent package. The ready method blocks the caller thread until the specified future is completed. The result method also blocks the caller thread, but returns the value of the future if it was completed successfully or throws the exception in the future if the future is failed. Both the methods require specifying a timeout parameter; the longest duration that the caller should wait for the completion of the future before a TimeoutException method is thrown. To specify a timeout, we import the scala.concurrent.duration package. This allows us to write expressions such as 10.seconds: import scala.concurrent.duration._ object BlockingAwait extends App { val urlSpecSizeFuture = Future { val specUrl = "http://www.w3.org/Addressing/URL/url-spec.txt" Source.fromURL(specUrl).size } val urlSpecSize = Await.result(urlSpecSizeFuture, 10.seconds) log(s"url spec contains $urlSpecSize characters") } In this example, the main thread starts a computation that retrieves the URL specification and then awaits. By this time, the World Wide Web Consortium (W3C) is worried that a DOS attack is under way, so this is the last time we download the URL specification. Blocking in asynchronous computations Waiting for the completion of a future is not the only way to block. Some legacy APIs do not use callbacks to asynchronously return results. Instead, such APIs expose the blocking methods. After we call a blocking method, we lose control over the thread; it is up to the blocking method to unblock the thread and return the control back. Execution contexts are often implemented using thread pools. By starting future computations that block, it is possible to reduce parallelism and even cause deadlocks. This is illustrated in the following example, in which 16 separate future computations call the sleep method, and the main thread waits until they complete for an unbounded amount of time: val startTime = System.nanoTime val futures = for (_ <- 0 until 16) yield Future { Thread.sleep(1000) } for (f <- futures) Await.ready(f, Duration.Inf) val endTime = System.nanoTime log(s"Total time = ${(endTime - startTime) / 1000000} ms") log(s"Total CPUs = ${Runtime.getRuntime.availableProcessors}") Assume that you have eight cores in your processor. This program does not end in one second. Instead, a first batch of eight futures started by Future.apply will block all the worker threads for one second, and then another batch of eight futures will block for another second. As a result, none of our eight processor cores can do any useful work for one second. Avoid blocking in asynchronous computations, as it can cause thread starvation. If you absolutely must block, then the part of the code that blocks should be enclosed within the blocking call. This signals to the execution context that the worker thread is blocked and allows it to temporarily spawn additional worker threads if necessary:   val futures = for (_ <- 0 until 16) yield Future { blocking { Thread.sleep(1000) } } With the blocking call around the sleep call, the global execution context spawns additional threads when it detects that there is more work than the worker threads. All 16 future computations can execute concurrently and the program terminates after one second. The Await.ready and Await.result statements block the caller thread until the future is completed and are in most cases used outside asynchronous computations. They are blocking operations. The blocking statement is used inside asynchronous code to designate that the enclosed block of code contains a blocking call. It is not a blocking operation by itself. Alternative future frameworks Scala futures and promises API resulted from an attempt to consolidate several different APIs for asynchronous programming, among them, legacy Scala futures, Akka futures, Scalaz futures, and Twitter's Finagle futures. Legacy Scala futures and Akka futures have already converged to the futures and promises API that you've learned about so far in this article. Finagle's com.twitter.util.Future type is planned to eventually implement the same interface as scala.concurrent.Future package, while the Scalaz scalaz.concurrent.Future type implements a slightly different interface. In this section, we give a brief of Scalaz futures. To use Scalaz, we add the following dependency to the build.sbt file: libraryDependencies += "org.scalaz" %% "scalaz-concurrent" % "7.0.6" We now encode an asynchronous tombola program using Scalaz. The Future type in Scalaz does not have the foreach method. Instead, we use its runAsync method, which asynchronously runs the future computation to obtain its value and then calls the specified callback: import scalaz.concurrent._ object Scalaz extends App { val tombola = Future { scala.util.Random.shuffle((0 until 10000).toVector) } tombola.runAsync { numbers => log(s"And the winner is: ${numbers.head}") } tombola.runAsync { numbers => log(s"... ahem, winner is: ${numbers.head}") } } Unless you are terribly lucky and draw the same permutation twice, running this program reveals that the two runAsync calls print different numbers. Each runAsync call separately computes the permutation of the random numbers. This is not surprising, as Scalaz futures have the pull semantics, in which the value is computed each time some callback requests it, in contrast to Finagle and Scala futures' push semantics, in which the callback is stored, and applied if and when the asynchronously computed value becomes available. To achieve the same semantics, as we would have with Scala futures, we need to use the start combinator that runs the asynchronous computation once, and caches its result: val tombola = Future { scala.util.Random.shuffle((0 until 10000).toVector) } start With this change, the two runAsync calls use the same permutation of random numbers in the tombola variable and print the same values. We will not dive further into the internals of alternate frameworks. The fundamentals about futures and promises that you learned about in this article should be sufficient to easily familiarize yourself with other asynchronous programming libraries, should the need arise. Summary This article presented some powerful abstractions for asynchronous programming. We saw how to encode latency with the Future type. You learned that futures and promises are closely tied together and that promises allow interfacing with legacy callback-based systems. In cases, where blocking was unavoidable, you learned how to use the Await object and the blocking statement. Finally, you learned that the Scala Async library is a powerful alternative for expressing future computations more concisely. Resources for Article: Further resources on this subject: Introduction to Scala [article] Concurrency in Practice [article] Integrating Scala, Groovy, and Flex Development with Apache Maven [article]

In this article by Mike Topalovich, author of the book Salesforce Lightning Application Development Essentials, we will discuss about Salesforce. As Salesforce developers, we know since Dreamforce '15, Salesforce has been all Lightning, all the time. The flagship CRM products – Sales Cloud and Service Cloud – have been rebranded to Sales Cloud Lightning and Service Cloud Lightning. In fact, many Salesforce products have undergone the Lightning treatment, the word Lightning being added to their product names overnight with few noticeable changes to the products themselves. This has led many in the Salesforce ecosystem to step back and ask, What is Lightning? (For more resources related to this topic, see here.) Lightning changes everything Lightning is not just the new Salesforce UI—it is a complete re-imagining of the entire Salesforce application and platform. Lightning represents a grand vision of unifying the Salesforce experience for everyone who interacts with Salesforce products or the Salesforce platform, on any device. In no uncertain terms, Lightning is the most important product update in the history of Salesforce as a company. Lightning represents a completely new vision for both the flagship CRM products and the platform. Salesforce is betting the company on it. Lightning changes not only how we interact with Salesforce, but how we design and develop solutions for the platform. Developers and ISV partners now have the ability to create rich, responsive applications using the same framework and design tools that Salesforce uses internally, ensuring that the user experience maintains a consistent look and feel across all applications. While the initial overuse of the term Lightning may be a source of confusion for many in the Salesforce ecosystem, don't let the noise drown out the vision. Lightning changes everything we know about Salesforce, but to understand how, we need to focus on the three key pillars of Lightning: Lightning Experience Salesforce Lightning Design System Lightning Component framework If we think about Lightning as the unified Salesforce experience across all our devices, it makes our mission much clearer. If we think about designing and developing responsive, reusable components for this new unified experience, Lightning makes a lot more sense. A brief history of Lightning The unified Lightning vision as we know it today has been rolled out in fits and starts. To understand how we arrived at the current vision for Lightning, we can look back on prior Dreamforce events as milestones in the history of Lightning. Dreamforce 2013 With Dreamforce '13, Salesforce recognized that the world was moving to a mobile-first mindset and rebranded their mobile application as Salesforce1. With Salesforce1, they also tried to sell the vision of a unified customer experience for the first time. According to a press release for Dreamforce '13, "Salesforce1 is a new social, mobile and cloud customer platform built to transform sales, service and marketing apps for the Internet of Customers." The vision was too ambitious at the time, the messaging was too confusing, and the platform was nowhere close to being ready to support any type of unified experience. Dreamforce 2014 Lightning emerged as a platform with Dreamforce '14. Branded as Salesforce1 Lightning, Salesforce opened up the underlying Aura JavaScript UI framework to developers for the first time, enabling the development of custom components for the Salesforce1 mobile application using the same technology that Salesforce had used to develop the Salesforce1 mobile application. The press release for Dreamforce '14 hinted at what was in store for Lightning, "Now customers, developers and Salesforce partners can take advantage of the new Lightning Framework to quickly build engaging apps across every device. The same framework Salesforce's internal development team uses to build apps can now be used to build custom Lightning components and create any user experience." At this point, Salesforce was still using the Salesforce1 branding for the unified end-to-end experience across Salesforce products and platforms, but we now officially had the Lightning Framework to work with. Dreamforce 2015 Dreamforce '15 may have been the official coming out party for Lightning, but in an unprecedented move for Salesforce, the company held a special pre-Dreamforce Meet the New Salesforce event on August 25, 2015, to announce the new Lightning Experience user interface as well as a complete rebranding of the end-to-end experience of Lightning. The Dreamforce event focused on strengthening the branding and educating developers, admins, and end users on what this unified experience meant for the future of Salesforce. Since then, Salesforce has been all Lightning, all the time. Dreamforce 2016 With Dreamforce '16 and the Winter '17 release of Salesforce, Lightning had finally arrived as a stable, optimized, enterprise-ready platform. Dreamforce '16 was less about hype and more about driving Lightning adoption. Sessions focused on design patterns and best practices rather than selling the platform to developers. New tooling was introduced to make the Lightning development experience something that Salesforce developers could get excited about. With Winter '17, Lightning Experience felt like a true unified end-to-end experience instead of a patchwork of functionality. The Winter '17 release notes were packed with enhancements that would get many organizations off the fence about Lightning and shift the adoption bell curve from toward an early majority from the early adopter state that it had been lingering in while Salesforce filled in the gaps in the platform. This is the Lightning we had been waiting for. Lightning Experience If someone were to ask you what the Lightning Experience was all about, your first reaction might be, "It's the new Salesforce UI." While that is technically correct, as Lightning Experience is the brand name given to the user interface that replaces what we now refer to as Salesforce Classic, the implementation of this user interface is part of the larger vision of a unified Salesforce experience across all devices. Lightning Experience takes the old way of doing things in Salesforce Classic – long, scrolling pages – and blows it up into tiny pieces. You need to reassemble those pieces in a way that makes the most sense for your business users. You can even create your own custom pieces, called components, and include those alongside components that Salesforce gives you out of the box, or components built by third parties that you download from the AppExchange. It is all completely seamless. Focusing on getting things done While the initial release of Lightning Experience focused on making salespeople more productive, the interface is rapidly evolving to improve on all areas of CRM. The ability to seamlessly transition work between desktop and mobile devices will enable every Salesforce user to find new ways to connect with customers and increase the effectiveness of business processes across the enterprise. While the initial release of Lightning Experience wasn't quite complete, it did include over 25 new features and a total redesign of many pages. Some of the notable improvements include: Component-based record pages that focused on getting work done in the context of the Salesforce object record, rather than having to scroll to find pertinent related information Completely redesigned reports and dashboards that enable visualizing customer data in new ways, with flexible layouts and additional filtering options An opportunity workspace designed to help salespeople get to closed won faster by focusing on actions instead of raw data Kanban boards for visualizing opportunities in their various deal stages and enabling salespeople to drag and drop multiple opportunities to new stages rather than having to edit and save individual records An enhanced Notes feature that enables users to create notes with rich text and attach them to multiple records at the same time Unified Salesforce Experience Following the mobile-first mindset adopted with the launch of the Salesforce1 platform, the same component framework that is used to power Salesforce1 is what underlies Lightning Experience. The incorporation of design principles from the Salesforce Lightning Design System ensures that users get the same responsive experience whether they access Salesforce from desktop browsers, mobile devices, tablets, wearables, or anything else that comes along in the near future. Developers and ISV partners can now build custom components and applications that plug right into Lightning Experience, rather than having to build custom pages and standalone applications. Blurring the lines between clicks and code Experienced Salesforce developers know that a key consideration when designing Salesforce solutions is to find the right balance between using declarative, out-of-the-box functionality and the programmatic capabilities of the platform. In the world of Salesforce development, we lovingly refer to this dichotomy as clicks versus code. With Lightning Experience and the introduction of Lightning App Builder, the discussion shifts from clicks or code to clicks and code, as developers can now build custom components and expose them to the Lightning App Builder interface, allowing admins to drag and drop these reusable components onto a canvas and assemble new Lightning pages. While this sentiment may strike fear, uncertainty, and doubt into the hearts of developers, any time we can move from code to clicks, or enable admins to maintain Salesforce customizations, it is a good thing. Lightning Experience enables a closer relationship between admins and developers. Developers can focus on building reusable components, admins can focus on maintaining the user experience. Salesforce Lightning Design System A design system is a collection of design principles, style guides, and elements that enable developers to focus on how components and applications work, while designers can focus on how the application looks and feels. The Salesforce Lightning Design System (SLDS) is a trusted, living, platform-agnostic design system that was built from the ground up to provide developers with everything needed to implement the look and feel of Lightning Experience and the Salesforce1 mobile application. SLDS ensures consistency across all components and applications, whether they are written by Salesforce developers, ISV partners, or even Salesforce itself when designing and implementing product features. Salesforce developed SLDS with four key design principles in mind: Clarity Efficiency Consistency Beauty These principles are applied to colors, typography, layout, icons, and more, throughout the accompanying CSS framework. Developers can implement the design system by including SLDS Cascading Style Sheets (CSS) and icon libraries in components and applications, and applying the appropriate CSS classes to component markup. SLDS also includes CSS style sheets for applying the design system to Visualforce components, Heroku, and native iOS applications. When SLDS was first introduced, adding the style sheets or icon libraries to a Salesforce org required installing an unmanaged package or uploading files as static resources and manually upgrading to new versions of the design system as they were released. As of the Winter '17 release of Salesforce, SLDS is included out of the box with all Salesforce orgs and no longer requires an explicit reference to the static resources from Lightning components or applications. You simply reference the appropriate SLDS class names in your component markup and it will be applied automatically, or you can use Lightning Base Components, which apply SLDS implicitly without additional markup. Lightning Component framework Traditionally, Salesforce UI design came down to two questions: Do I want to recreate the look and feel of Salesforce with custom Visualforce pages, or do I want to install a third-party framework to create rich application interfaces? The prevailing design pattern since the fall of Adobe Flash has been to use Visualforce to simply render the output from JavaScript frameworks such as Backbone, Angular, Ember, Sencha, and others. Developers could continue to follow MVC patterns by using Apex controllers to retrieve data from the Salesforce database. While this may have enabled a rich, responsive experience for certain applications developed for Salesforce, users still had to deal with a mixed experience across all of Salesforce, especially if multiple JavaScript frameworks were in use. Lighting Experience and the Lightning Component framework solve a problem that has long been a barrier to a truly unified experience for all Salesforce users: Providing a single, integrated framework for developers that enabled the creation of rich, responsive applications that could be seamlessly plugged in anywhere in the UI rather than having to stand alone in separate pages or standalone applications. Because the Lightning Component framework is what underlies Lightning Experience and the Salesforce1 mobile applications, we no longer have to choose a JavaScript framework developed and maintained outside of Salesforce. We can now create components and applications using a rich JavaScript framework, which is provided and maintained by Salesforce. What is the Lightning Component framework? The Lightning Component framework is a client-side UI framework that was built by Salesforce using the open source Aura UI framework. The framework uses JavaScript for client-side operations and exposes an API to access Salesforce data using Apex controllers. The Lightning Component framework was initially created to support development for the Salesforce1 mobile application, but is now the standard for responsive, client-side single-page applications for the end-to-end Salesforce user and developer experience across all browsers and devices. The framework provides a number of reusable out-of-the-box components for you to get started building your own Lightning components, and the platform is fully maintained and supported by Salesforce. The problem Salesforce solved with the Lightning Component framework was to give Salesforce developers a single standardized and supported JavaScript framework to move beyond the limitations of Visualforce and build rich applications with a common design system without having to select, install, and maintain a third-party framework. Eliminating the JavaScript framework sprawl within the Salesforce development ecosystem enables developers and admins to deliver customized business solutions with a standardized look and feel without having to learn and maintain yet another framework from another vendor that wasn't built specifically for the Salesforce platform. What is JavaScript? Along with HTML and CSS, JavaScript is one of the three core languages of web development. If you do not have a background in JavaScript, don't worry. Even though it will be the most difficult thing you will have to learn when coming up to speed on Lightning component-development, JavaScript has been around for decades and there are countless resources available for learning the language. JavaScript was introduced in the mid-1990s as a scripting language for the Netscape Navigator browser, with Microsoft subsequently releasing a version for Internet Explorer. By the late 1990s, JavaScript was standardized across browsers with the introduction of what is called ECMAScript. Today, all modern browsers include JavaScript engines. JavaScript will not be completely foreign to Apex developers, or anyone with an object-oriented programming (OOP) background, as it follows object-oriented principles. What will throw you off if you have an Apex background is the fact that JavaScript is loosely typed, whereas Apex is a strongly typed language. This will take some getting used to, conceptually. At its core, JavaScript is a language that is used to read and manipulate what we call the Document Object Model (DOM). The DOM is a programmatic interface that gets built when a browser reads an HTML document and converts each HTML element into what are called node objects. These HTML nodes form a tree-like structure in the DOM, and we can use JavaScript to find nodes, add nodes, remove nodes, and modify nodes to make our web applications dynamic. The other core function that JavaScript performs is listening for and handling events that occur in the browser. HTML itself is a static markup language and was not built to be dynamic in its rendering, which is why JavaScript was created to handle events such as clicking a mouse, changing a picklist value, or putting a form element into focus. You can write JavaScript functions to handle DOM events, and your JavaScript functions can in turn manipulate the DOM by adding, removing, or modifying DOM elements. Many of us have only had to learn JavaScript at a cursory level because JavaScript libraries such as jQuery and JavaScript frameworks such as Sencha ExtJS, Angular, Node, and Backbone take care of a lot of the heavy lifting for us when it comes to actual JavaScript programming. Lightning requires more direct JavaScript programming than many frameworks do, which gives you greater control over the functions in your Lightning components and applications, but unfortunately, you're going to have to bone up on your JavaScript knowledge before you can take advantage of that level of control. What are JavaScript frameworks? JavaScript frameworks handle much of the behind-the-scenes complexity of JavaScript coding and DOM manipulation, and give developers a simplified template-based approach to building web applications. While JavaScript itself does not follow the Model-View-Controller (MVC) design pattern, many JavaScript frameworks implement MVC to provide developers with a familiar architecture for separating the data model and view of an application with a logic, or controller, layer. Each component of the MVC architecture can be maintained separately and be brought together in a cohesive application. Some frameworks, such as Sencha ExtJS, may implement MVC but are more focused on enabling rich user interfaces by giving developers pre-built UI widgets that can be configured declaratively. Other frameworks are designed for touch-driven responsive mobile applications. There are dozens of JavaScript frameworks out there, the most common examples being Backbone.js, AngularJS, Ember.js, Knockout.js, React.js, and ExtJS, among others. What is Aura? Aura is an open-source JavaScript UI framework that is maintained by Salesforce. Aura is component-based, and uses JavaScript on the client-side frontend, with Java on the server-side backend. Aura is the framework that underpins the Lightning Component framework. While the Lightning Component framework and Aura have many similarities on the surface, do not try to use Aura components or functions that are not explicitly supported in the Lightning Component framework documentation. Many developers have already found that these undocumented features may work at first, but unless they are explicitly supported by Salesforce, they can be taken away at any time. Why should I use the Lightning Component framework? Why should Salesforce developers consider moving to Lightning Component development? For starters, Lightning is the future of Salesforce development. There is no way around it: Salesforce is betting the company on Lightning. If you ignore that and simply focus on the value that Lightning can provide, you will find that there are many compelling reasons for making the jump to Lightning. Responsive design From a single code base, you can create reusable components that will give your users a unified experience across all form factors. You no longer have to maintain separate desktop applications, tablet applications and mobile applications. Reusable components You can create components that can be consumed by other Lightning components and applications, allowing your component to be reused many times in many different places. Admins can use your components in the Lightning App Builder, allowing them to declaratively create new Lightning Pages with your components. This is where the line between declarative and programmatic development starts to blur! Better performance Because Lightning components render on the client and do not require expensive round trips to a server-side controller to update data and context, you can build components that are lightning fast. Have you ever used the AJAX components in Visualforce to do something as simple as create a type-ahead function for an input field? There was always a lag between the time an event was handled and the target component was re-rendered. With Lightning components, any change to an attribute value will automatically re-render a component, giving you the ability to create high-performing client-side Salesforce applications. Rendering on the client side will reduce the need for mobile applications to make expensive calls to a server API, significantly improving performance in low bandwidth situations. JavaScript + HTML5 + CSS If you have at least a cursory knowledge of web development, Lightning follows open standards and practices that you are already familiar with. While there may be a learning curve for Visualforce developers who do not have experience with JavaScript, HTML5, or CSS, the use of web standards rather than proprietary framework means there is a wealth of information and resources available to quickly get up to speed on the basics and transition to Lightning Component development. For new developers coming onto the Salesforce platform, Lightning provides an opportunity to quickly apply existing web-application development skills to hit the ground running, without having to first learn Apex or Visualforce. Event-driven architecture With Visualforce development, we are constrained to a fairly rigid architecture, which executes server-side controller actions when user-driven events occur, such as clicking a link or a button. Granted, you can use specialized Visualforce tags or component-specific event handlers to handle supported events, but this requires a significant amount of hard-coding to server-side controller methods. With Lightning, you can listen for and handle just about any DOM event or custom component event and determine what action you want to take when that event occurs. For example, you can handle the onchange event when a picklist value is selected and immediately call a function in your client-side controller to take action based on that value changing. You even have the ability to define and raise custom events, and determine how those events should be handled within your component hierarchy. Component encapsulation Encapsulation simply means that we can wall off the inner workings of a Lightning component and not expose the secret sauce behind it to another component or application that references it. This allows us to update the code within a Lightning Component without breaking any upstream components or applications. Encapsulation enables us to write reusable and efficient code that is easily maintainable. Summary In this article we have learned about Salesforce, the history about Lightning and the need to use the Lightning Component framework. Resources for Article: Further resources on this subject: Introducing Salesforce Chatter [article] Subscribing to a report [article] Learning How to Manage Records in Visualforce [article]

In this article by, Tejaswini Mandar Jog, author of the book, Learning Spring 5.0, we will cover the following topics: Introduction to Spring framework Problems address by Spring in enterprise application development Spring architecture What's new in Spring 5.0 Container Spring the fresh new start after the winter of traditional J2EE, is what Spring framework is in actual. A complete solution to the most of the problems occurred in handling the development of numerous complex modules collaborating with each other in a Java enterprise application. Spring is not a replacement to the traditional Java Development but it is a reliable solution to the companies to withstand in today's competitive and faster growing market without forcing the developers to be tightly coupled on Spring APIs. Problems addressed by Spring Java Platform is long term, complex, scalable, aggressive, and rapidly developing platform. The application development takes place on a particular version. The applications need to keep on upgrading to the latest version in order to maintain recent standards and cope up with them. These applications have numerous classes which interact with each other, reuse the APIs to take their fullest advantage so as to make the application is running smoothly. But this leads to some very common problems of as. Scalability The growth and development of each of the technologies in market is pretty fast both in hardware as well as software. The application developed, couple of years back may get outdated because of this growth in these areas. The market is so demanding that the developers need to keep on changing the application on frequent basis. That means whatever application we develop today should be capable of handling the upcoming demands and growth without affecting the working application. The scalability of an application is handling or supporting the handling of the increased load of the work to adapt to the growing environment instead of replacing them. The application when supports handling of increased traffic of website due to increase in numbers of users is a very simple example to call the application is scalable. As the code is tightly coupled, making it scalable becomes a problem. Plumbing code Let's take an example of configuring the DataSource in the Tomcat environment. Now the developers want to use this configured DataSource in the application. What will we do? Yes, we will do the JNDI lookup to get the DataSource. In order to handle JDBC we will acquire and then release the resources in try catch. The code like try catch as we discuss here, inter computer communication, collections too necessary but are not application specific are the plumbing codes. The plumbing code increases the length of the code and makes debugging complex. Boilerplate code How do we get the connection while doing JDBC? We need to register Driver class and invoke the getConnection() method on DriverManager to obtain the connection object. Is there any alternative to these steps? Actually NO! Whenever, wherever we have to do JDBC these same steps have to repeat every time. This kind of repetitive code, block of code which developer write at many places with little or no modification to achieve some task is called as boilerplate code. The boilerplate code makes the Java development unnecessarily lengthier and complex. Unavoidable non-functional code Whenever application development happens, the developer concentrate on the business logic, look and feel and persistency to be achieved. But along with these things the developers also give a rigorous thought on how to manage the transactions, how to handle increasing load on site, how to make the application secure and many more. If we give a close look, these things are not core concerns of the application but still these are unavoidable. Such kind of code which is not handling the business logic (functional) requirement but important for maintenance, trouble shooting, managing security of an application is called as non-functional code. In most of the Java application along with core concerns the developers have to write down non-functional code quite frequently. This leads to provide biased concentration on business logic development. Unit testing of the application Let's take an example. We want to test a code which is saving the data to the table in database. Here testing the database is not our motive, we just want to be sure whether the code which we have written is working fine or not. Enterprise Java application consists of many classes, which are interdependent. As there is dependency exists in the objects it becomes difficult to carry out the testing. POJO based development The class is a very basic structure of application development. If the class is getting extended or implementing an interface of the framework, reusing it becomes difficult as they are tightly coupled with API. The Plain Old Java Object (POJO) is very famous and regularly used terminology in Java application development. Unlike Struts and EJB Spring doesn't force developers to write the code which is importing or extending Spring APIs. The best thing about Spring is that developers can write the code which generally doesn't has any dependencies on framework and for this, POJOs are the favorite choice. POJOs support loosely coupled modules which are reusable and easy to test. The Spring framework is called to be non-invasive as it doesn't force the developer to use API classes or interfaces and allows to develop loosely coupled application. Loose coupling through DI Coupling, is the degree of knowledge in class has about the other. When a class is less dependent on the design of any other class, the class will be called as loosely coupled. Loose coupling can be best achieved by interface programming. In the Spring framework, we can keep the dependencies of the class separated from the code in a separate configuration file. Using interfaces and dependency injection techniques provided by Spring, developers can write loosely coupled code (Don't worry, very soon we will discuss about Dependency Injection and how to achieve it). With the help of loose coupling one can write a code which needs a frequent change, due to the change in the dependency it has. It makes the application more flexible and maintainable. Declarative programming In declarative programming, the code states what is it going to perform but not how it will be performed. This is totally opposite of imperative programming where we need to state stepwise what we will execute. The declarative programming can be achieved using XML and annotations. Spring framework keeps all configurations in XML from where it can be used by the framework to maintain the lifecycle of a bean. As the development happened in Spring framework, the 2.0 onward version gave an alternative to XML configuration with a wide range of annotations. Boilerplate code reduction using aspects and templates We just have discussed couple of pages back that repetitive code is boilerplate code. The boiler plate code is essential and without which providing transactions, security, logging, and so on, will become difficult. The framework gives solution of writing aspect which will deal with such cross cutting concerns and no need to write them along with business logic code. The use of aspect helps in reduction of boilerplate code but the developers still can achieve the same end effect. One more thing the framework provides, is the templates for different requirements. The JDBCTemplate and HibernateTemplate are couple of more useful concepts given by Spring which does reduction of boilerplate code. But as a matter of fact, you need to wait to understand and discover the actual potential. Layered architecture Unlike Struts and Hibernate which provides web persistency solutions respectively, Spring has a wide range of modules for numerous enterprise development problems. This layered architecture helps the developer to choose any one or more of the modules to write solution for his application in a coherent way. E.g. one can choose Web MVC module to handle web request efficiently without even knowing that there are many other modules available in the framework. Spring architecture Spring provides more than 20 different modules which can be broadly summaries under 7 main modules which are as follows: Spring modules What more Spring supports underneath? The following sections covers the additional features of Spring. Security module Now a days the applications alone with basic functionalities also need to provide sound ways to handle security at different levels. Spring5 support declarative security mechanism using Spring AOP. Batch module The Java Enterprise Applications needs to perform bulk processing, handling of large amount of data in many business solutions without user interactions. To handle such things in batches is the best solution available. Spring provides integration of batch processing to develop robust application. Spring integration In the development of enterprise application, the application may need interaction with them. Spring integration is extension of the core spring framework to provide integration of other enterprise applications with the help of declarative adapters. The messaging is one of such integration which is extensively supported by Spring. Mobile module The extensive use of mobiles opens the new doors in development. This module is an extension of Spring MVC which helps in developing mobile web applications known as Spring Android Project. It also provide detection of the type of device which is making the request and accordingly renders the views. LDAP module The basic aim of Spring was to simplify the development and to reduce the boilerplate code. The Spring LDAP module supports easy LDAP integration using template based development. .NEW module The new module has been introduced to support .NET platform. The modules like ADO.NET, NHibernate, ASP.NET has been in the .NET module includes to simplify the .NET development taking the advantages of features as DI, AOP, loose coupling. Container – the heart of Spring POJO development is the backbone of Spring framework. The POJO configured in the and whose object instantiation, object assembly, object management is done by Spring IoC container is called as bean or Spring bean. We use Spring IoC as it on the pattern of Inversion of Control. Inversion of Control (IoC) In every Java application, the first important thing which each developer does is, to get an object which he can use in the application. The state of an object can be obtained at runtime or it may be at compile time. But developers creates object where he use boiler plate code at a number of times. When the same developer uses Spring instead of creating object by himself he will be dependent on the framework to obtain object from. The term inversion of control comes as Spring container inverts the responsibility of object creation from developers. Spring IoC container is just a terminology, the Spring framework provides two containers: The BeanFactory The ApplicationContext Summary So in this article, we discussed about the general problems faced in Java enterprise application development and how they have been address by Spring framework. We have seen the overall major changes happened in each version of Spring from its first introduction in market. Enabling Spring Faces support Design with Spring AOP Getting Started with Spring Security

This article by Gilles Crettenand, author of the book Functional PHP, covers some of the concepts explained in book in a concise manner. We will look at the following: Declarative programming Functions Recursion Composing functions Benefits of functional programming (For more resources related to this topic, see here.) Functional programming has gained a lot of traction in the last few years. Various big tech companies started using functional languages, for example: Twitter on Scala (http://www.artima.com/scalazine/articles/twitter_on_scala.html) WhatsApp being written in Erlang (http://www.fastcompany.com/3026758/inside-erlang-the-rare-programming-language-behind-whatsapps-success) Facebook using Haskell (https://code.facebook.com/posts/302060973291128/open-sourcing-haxl-a-library-for-haskell/1) There is some really wonderful and successful work done on functional languages that compile to JavaScript—the Elm and PureScript languages to name a few. There are efforts to create new languages that either extend or compile to some more traditional languages, such as Hy and Coconut for Python. Even Apple's new language for iOS development, Swift, has multiple concepts from functional programming integrated into its core. However, this article is not about using a new language or learning a whole new technology, it is about benefiting from functional techniques without having to change our whole stack. By just applying some principles to our everyday PHP, we can greatly improve the quality of our life and code. Declarative programming Functional programming is also sometimes called declarative programming in contrast to imperative programming. This languages are called programming paradigms. Object-oriented programming is also a paradigm, but it is the one that is strongly tied to the imperative programming. Instead of explaining the difference at length, let's demonstrate with an example. First an imperative programming using PHP: <?php function getPrices(array $products) { // let's assume the $products parameter is an array of products. $prices = []; foreach($products as $p) { if($p->stock > 0) { $prices[] = $p->price; } } return $prices; } Now let's see how you can do the same with SQL which, among other things, is a declarative language: SELECT price FROM products WHERE stock > 0; Notice the difference? In the first example, you tell the computer what to do step by step, taking care of storing intermediary results yourself. In the second example, you only describe what you want and it will then be the role of the database engine to return the results. In a way, functional programming looks a lot more like SQL than the PHP code we just saw. Functions Functional programming, as it names suggests, revolves around functions. In order to apply functional techniques effectively, a language must support functions as a first-class citizen or first functions. This means that functions are considered like any other value. They can be created and passed around as parameters to other functions and they can be used as return values. Luckily, PHP is such a language, you can create functions at will, pass them around as parameters, and even return them. Another fundamental concept is the idea of a pure function or, in other words, functions that only use their input to produce a result. This means that you cannot use any kind of external or internal state to perform your computation. Another way to look at this is from the angle of dependencies. All of the dependencies of your functions need to be clearly declared in the signature. This helps a lot when someone tries to understand how and what your function is doing. Higher-order functions PHP functions can take functions as parameters and return functions as return values. A function that does either of those is called a higher-order function. It is as simple as that. There are a few of those that are commonly used in any functional code base. Map The map, or array_map, method in PHP is a higher order function that applies a given callback to all the elements of a collection. The return value is a collection in the same order. A simple example is as follows: <?php function square(int $x): int { return $x * $x; } $squared = array_map('square', [1, 2, 3, 4]); /* $squared contains [1, 4, 9, 16] */ Filter The filter, or array_filter, method in PHP is a higher order function that keeps only certain elements of a collection based on a Boolean predicate. The return value is a collection that will only contain elements returning true for the predicate function. A simple example is as follows: <?php function odd(int $a): bool { return $a % 2 === 1; } $filtered = array_filter([1, 2, 3, 4, 5, 6], 'odd'); /* $filtered contains [1, 3, 5] */ Fold or reduce Folding refers to a process where you reduce a collection to a return value using a combining function. Depending on the language, this operation can have multiple names—fold, reduce, accumulate, aggregate, or compress. As with other functions related to arrays, the PHP version is the array_reduce function. You may be familiar with the array_sum function, which calculates the sum of all the values in an array. This is in fact a fold and can be easily written using the array_reduce function: <?php function sum(int $carry, int $i): int { return $carry + $i; } $summed = array_reduce([1, 2, 3, 4], 'sum', 0); /* $summed contains 10 */ You don't necessarily need to use the elements to produce a value. You could, for example, implement a naive replacement for the in_array method using fold: <?php function in_array2(string $needle, array $haystack): bool { $search = function(bool $contains, string $i) use ($needle) : bool { return $needle == $i ? true : $contains; }; return array_reduce($haystack, $search, false); } var_dump(in_array2('two', ['one', 'two', 'three'])); // bool(true) Recursion In the academic sense, recursion is the idea of dividing a problem into smaller instances of the same problem. For example, if you need to scan a directory recursively, you first scan the starting directory and then scan its children and grandchildren. Most programming languages support recursion by allowing a function to call itself. This idea is often what is described as being recursion. Let's see how we can scan a directory using recursion: <?php function searchDirectory($dir, $accumulator = []) { foreach (scandir($dir) as $path) { // Ignore hidden files, current directory and parent directory if(strpos($path, '.') === 0) { continue; } $fullPath = $dir.DIRECTORY_SEPARATOR.$path; if(is_dir($fullPath)) { $accumulator = searchDirectory($path, $accumulator); } else { $accumulator[] = $fullPath; } } return $accumulator; } We start by using the scandir method to obtain all files and directories. Then, if we encounter a child directory, we call the function on it again. Otherwise, we simply add the file to the accumulator. This function is recursive because it calls itself. You can write this using control structures, but as you don't know in advance what the depth of your folder hierarchy is, the code will probably be a lot messier and harder to understand. Trampolines Each time you call a function, information gets added to the memory. This can be an issue when doing recursion as you only have a limited amount of memory available. Until the last recursive call, memory usage will continue growing and a stack overflow can happen. The only way we can avoid stack growth is to return a value instead of calling a new function. This value can hold the information that is needed to perform a new function call, which will continue the computation. This also means that we need some cooperation from the caller of the function. This helpful caller is called a trampoline and here is how it works: The trampoline calls our f function Instead of making a recursive call, the f function returns the next call encapsulated inside a data structure with all the arguments The trampoline extracts the information and performs a new call to the f function Repeat the two last steps until the f function returns a real value The trampoline receives a value and returns those to the real caller If you want to use trampolines in your own project, I invite you to install the following library, which offers some helpers as compared to our crude implementation: composer require functional-php/trampoline Here is an example taken from the documentation: <?php use FunctionalPHPTrampoline as t; function factorial($n, $acc = 1) { return $n <= 1 ? $acc : tbounce('factorial', $n - 1, $n * $acc); }; Composing functions Previously, we discussed the idea of building blocks and small pure functions. But, so far, we haven't even hinted at how those can be used to build something bigger. What good is a building block if you cannot use it? The answer partly lies in function's composition. As it is often the case in functional programming, the concept is borrowed from mathematics. If you have two functions f and g, you can create a third function by composing them. The usual notation in mathematics is (f   g)(x), which is equivalent to calling them one after the other as f(g(x)). You can compose any two given functions really easily with PHP using a wrapper function. Say, you want to display a title in all caps and only safe HTML characters: <?php function safe_title2(string $s) { return strtoupper(htmlspecialchars($s)); } Functional libraries for PHP often come with a helper that can create new functions out of multiple subparts easily. For example, using Lars Strojny's Functional PHP library, you can write the following: <?php $titles4 = array_map(compose('htmlspecialchars', 'strtoupper', 'trim'), $titles); Partial application You might want to set some parameters of a function but leave some of them unassigned for later. For example, we might want to create a function that returns an excerpt of a blog post. The dedicated term for setting such a value is "to bind a parameter" or "bind an argument". The process itself is called partial application and the new function is set to be partially applied. The Functional PHP library also comes with helpers to partially apply a function: <?php use function Functionalpartial_right; use function Functionalpartial_left; use function Functionalpartial_any; use const Functional…; $excerpt = partial_right('substr', 0, 5); echo $excerpt('Lorem ipsum dolor si amet.'); // Lorem $fixed_string = partial_left('substr', 'Lorem ipsum dolor si amet.'); echo $fixed_string(6, 5); // ipsum $start_placeholder = partial_any('substr', 'Lorem ipsum dolor si amet.', …(), 5); echo $start_placeholder(12); // dolor Currying Currying is often used as a synonym to partial application. Although both concepts allows us to bind some parameters of a function, the core ideas are a bit different. The idea behind currying is to transform a function that takes multiple arguments into a sequence of functions that take one argument. As this might be a bit hard to grasp, let's try to curry the substr method. The result is called a curryied function. Again, a helper to create such functions is available in the Functional PHP library: <?php use function Functionalcurry; function add($a, $b, $c, $d) { return $a + $b + $c + $d; } $curryedAdd = curry('add'); $add10 = $curryedAdd(10); $add15 = $add10(5); $add42 = $add15(27); $add42(10); // -> 52 Benefits of functional programing As we just saw, the functional world is moving, adoption by the enterprise world is growing, and even new imperative languages are taking inspiration from functional languages. But why it is so? Reduce the cognitive burden on developers You've probably often read or heard that a programmer should not be interrupted because even a small interruption can lead to literally tens of minutes being lost. This is partly due to the cognitive burden or, in other words, the amount of information you have to keep in memory in order to understand the problem or function at hand. By forcing you to clearly state the dependencies of your functions and avoiding using any kind of external data, functional programming helps a lot in writing self-contained code that can be readily understood and thus reduces cognitive burden a lot. Software with fewer bugs We just saw that functional programming reduces the cognitive burden and makes your code easier to reason about. This is already a huge win when it comes to bugs because it will allow you to spot issues quickly as you will spend less time understanding how the code works to focus on what it should do. But all the benefits we've just seen have another advantage. They make testing a lot easier too! If you have a pure function and you test it with a given set of values, you have the absolute certitude that it will always return exactly the same thing in production. Easier refactoring Refactoring is never easy. However, since the only inputs of a pure function are its parameters and its sole output is the returned value, things are simpler. If you're refactored function continues to return the same output for a given input, you can have the guarantee that your software will continue to work. You cannot forget to set a few state somewhere in an object because your function are side-effect free. Enforcing good practices This article and the related book are the proof that functional programming is more about the way we do things instead of a particular language. You can use functional techniques in nearly any language that has functions. Your language still needs to have certain properties, but not that much. I like to talk about having a functional mindset. If it is so, why do companies move to functional languages? Because those languages enforce the best practice that we will learn in this book. In PHP, you will have to always remember to use functional techniques. In Haskell, you cannot do anything else, the language forces you to write pure functions. Summary This small article is by no mean a complete introduction to functional programming, this is what the Functional PHP book is for. I however hope I convinced you it is a set of techniques worth learning. We only brushed the surface here, all topics are covered more in depth in the various chapters. You will also learn about more advanced topics like the following: Functors, applicatives, and Monads Type systems Pattern matching Functional reactive programming Property-based testing Parallel execution of functional code There is also a whole chapter about using functional programming in conjunction with various frameworks like Symfony, Drupal, Laraval, and Wordpress. Resources for Article: Further resources on this subject: Understanding PHP basics [article] Developing Middleware [article] Continuous Integration [article]