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These days, many app developers are looking into building their mobile apps to cater to multiple platforms. It is essential to create an app that will be able to operate on multiple platforms like Android, iOS, Windows and so on. Creating cross platform apps can be a very challenging process, especially for mobile devices, but it can bring many advantages. Despite the challenges, picking the right software development platform, especially one which has a low code ideology such as RAD Studio Delphi, is not an insurmountable hill to climb. The right IDE software mitigates a lot of the difficulty and helps you create apps with the minimum of required effort from you and with the maximum efficiency. Using a highly capable tool such as RAD Studio and the Firemonkey FMX framework for cross platform apps means you can focus on one code base for your app even if it’s going to run on multiple mobile targets such as iOS and Android. This guide will give you some pointers in creating a cross-platform app that will be able to run on multiple platforms. You will also learn how to make your app highly efficient, which is an essential part of mobile app development. Working smarter, not harder is the whole philosophy behind RAD Studio Delphi. Let’s start by discussing what building cross platform apps actually entail. What do we mean by development of cross platform apps? Cross-platform development is a process that will allow you to create an app that will be able to run on multiple platforms. The most common examples of cross-platform apps are mobile apps, which are basically software applications designed to run on mobile devices. This is a direct opposition to proprietary app development which is developed specifically to only run on a single platform. These kinds of apps often use a technology which is supplied by the hardware manufacturer and can lock the developer into that mobile hardware vendor’s ‘ecosystem’ where they provide the development tools, the hardware on which you must develop and even the app store through which you must distribute your app. These vertical development solutions can seem attractive since the vendor often streamlines the process to market – as long as that market is the one they exclusively control. Going down that route can often mean inadvertently creating cross platform apps which cannot actually work on another hardware platform without substantial rewrites, sometimes total re-engineering of the solution. Meanwhile, the idea behind genuine cross-platform development is to save developers a lot of time and effort while providing them with the most options for expansion across different hardware vendors. It will also allow developers to market their apps in a more efficient way, as they can reach out to a wider pool of potential users. Ideally, you can minimize the effort it takes to manage code while simultaneously cutting back on costs, since you’d only need one development team. Picking a tool which maximizes the idea of a single code base for the app, with minimal changes required to target another platform, is the smart choice. What is the secret to efficiently targeting multiple device types with mobile cross platform apps? What’s the secret? Choosing the right cross platform development frameworks. These are the building blocks that will help you develop your app […]

Machine Learning is one of the hottest software development topics right now. The algorithms and techniques which enable machine learning have begun to really mature and have graduated from ‘interesting ideas’ into providing genuine power and permitting capabilities in our apps which can sometimes seem magical just as much as they are useful. Python has very quickly emerged as a de facto language for machine learning. There is rich set of machine learning libraries available for Python providing the ability to do everything from image recognition to complicated scientific analyses. How to use machine learning libraries to Delphi Did you know that it’s simple to use some truly excellent Python libraries to boost your Delphi app development on Windows? All that wonderful array of Python machine learning goodness is also easily available to you as a Delphi programmer. Adding Python to your Delphi code toolbox can enhance your app development by bringing in new capabilities that allow you to provide innovative and powerful solutions to your app’s users, combining the best of Python with the supreme low-code and unparalleled power of native Windows development that Delphi provides. Are you looking for how to build a GUI for a powerful Unsupervised Machine Learning library?  You can build a state-of-the-art unsupervised learning solution with scikit-learn on Delphi. This article will demonstrate how to create a Delphi GUI app dedicated to the scikit-learn library. Watch this video by Jim McKeeth for a thorough explanation of why you can love both Delphi and Python at the same time: What is the scikit-learn machine learning library? scikit-learn logo (source: scikit-learn.org). scikit-learn is an open-source Python machine learning library. scikit-learn has simple and efficient tools for predictive data analysis that are built on top of SciPy, NumPy, and Matplotlib. Support vector machines, random forests, gradient boosting, k-means, and DBSCAN are among the algorithms available in scikit-learn for classification, regression, and clustering. In this article, we will specifically talk about clustering algorithms. What is unsupervised machine learning? Unsupervised learning, also known as unsupervised machine learning, analyzes and clusters unlabeled datasets using machine learning algorithms. Without human intervention, these algorithms uncover hidden patterns or data groupings. Its ability to detect similarities and differences in data makes it an ideal solution for exploratory data analysis, cross-selling strategies, customer segmentation, and image recognition (source: IBM Cloud Education, 2020). What is clustering and how does it relate to machine learning? Clustering is a type of unsupervised learning problem. Cluster analysis is another name for this technique. It is frequently used as a data analysis technique for discovering interesting patterns in data, such as customer groups based on their behavior. There are numerous clustering algorithms available, and there is no single best clustering algorithm for all cases. Instead, it is a good idea to experiment with various clustering algorithms and different configurations for each algorithm. A cluster is frequently a dense area in the feature space where examples from the domain (observations or rows of data) are closer to the cluster than to other clusters. The cluster may have a sample or point feature space as its center (the centroid), as well as a boundary or extent (source: Brownlee, machinelearningmastery.com, 2020). A comparison of the clustering algorithms in scikit-learn (source: scikit-learn.org). What is the difference between supervised and unsupervised machine learning? The following infographic created by AltexSoft may […]

Text is everywhere! Text is not always where we want it, or in the format we need. We often find ourselves needing the text from images. You might have a scanned document containing financial information like an invoice you want to input into an accounts system, or maybe you are building an archive of photographs that you want to index against any text detected? Whatever your use case, if you need to get some text from an image, you can achieve this with ease in Delphi programming software using Amazon Textract using the latest version of Appercept AWS SDK for Delphi. What is Amazon Textract and what does it do? Amazon Textract provides text detection and analysis for image documents. Textract can analyse the relationships between detected text objects and provide information relating to forms, financial, and identity documents. Let’s detect some text… program DetectText; {$APPTYPE CONSOLE} implementation uses AWS.Textract; var Client: ITextractClient; Request: ITextractDetectDocumentTextRequest; Response: ITextractDetectDocumentTextResponse; begin Request := TTextractDetectDocumentTextRequest.Create; Request.Document := TTextractDocument.FromFile(‘C:image.png’); Client := TTextractClient.Create; Response := Client.DetectDocumentText(Request); if Response.IsSuccessful then begin for var LBlock in Response.Blocks do WriteLn(Format(‘Detected %s: %s’, [LBlock.BlockType, LBlock.Text])); end; end. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 program DetectText;   {$APPTYPE CONSOLE}   implementation   uses   AWS.Textract;   var   Client: ITextractClient;   Request: ITextractDetectDocumentTextRequest;   Response: ITextractDetectDocumentTextResponse;   begin   Request := TTextractDetectDocumentTextRequest.Create;   Request.Document := TTextractDocument.FromFile(‘C:image.png’);     Client := TTextractClient.Create;   Response := Client.DetectDocumentText(Request);   if Response.IsSuccessful then   begin     for var LBlock in Response.Blocks do       WriteLn(Format(‘Detected %s: %s’, [LBlock.BlockType, LBlock.Text]));   end; end. Is there an example of using Amazon Textract? To help you experiment and get started, check out the Textract demo in the AWS SDK for Delphi Samples repository. About Appercept AWS SDK for Delphi Appercept AWS SDK for Delphi is available exclusively on GetIt with active Enterprise or Architect subscriptions for Embarcadero Delphi or RAD Studio. You can install the SDK through the GetIt Package Manager within Delphi or RAD Studio if you have an active subscription.

Which target platforms do Delphi and Electron support? The “Discovering The Best Cross-Platform Framework Through Benchmarking” whitepaper evaluates two frameworks supporting multi-platform desktop application development: Delphi and Electron. Delphi Delphi, encapsulated in the Rapid Application Development (RAD) Studio IDE, is Embarcadero Technologies’ flagship product. A proprietary version of the Object Pascal language, Delphi features graphical application development with “drag and drop” components, a WYSIWYG viewer for most mobile platforms, and robust style options including platform-standard and unique palettes that provide a fully customized look and feel. Among other features, included libraries provide GUI controls, database access managers, and direct access target platform hardware and platform operating systems. The Delphi FireMonkey (FMX) framework will compile projects to native code for 32-bit and 64-bit Windows, macOS, Android, iOS, and Linux, allowing users to develop and maintain one codebase reaching most of the market. Delphi has been available for over 25 years. Electron Electron is an open-source (MIT License), Chromium-based framework that utilizes web technologies to build desktop applications on Windows, macOS, and Linux. It is developed and maintained by GitHub, a subsidiary of Microsoft. Electron combines the Chromium-based rendering engine with a Node.js server environment. As such, the user interface for an Electron application is available via HTML5 and CSS. Generally, Electron works with most Javascript frameworks such as Angular, Vue.js, and React. The HTML5, CSS, and Javascript-based technologies found in Chromium provide a rich ecosystem of user customization familiar to any web developer. Despite its relatively young age of five years, its community boasts open source packages for database access, operating system interactions, and other common tasks. Benchmark Metrics This post is part of a series of blog posts that look more closely at each of the individual metrics used in the study, and how Delphi and Electron each fared on these metrics. The first can be found here. Download the complete whitepaper here Benchmark Category: Flexibility Framework flexibility was examined qualitatively through research and conversation with experts in Delphi and Electron and sought to analyze the application of each framework to business problems and requirements. Delphi’s major advantage in the flexibility category is its ability to deploy one body of source code to any major desktop or mobile platform as a native binary executable, maximizing application market reach while minimizing maintenance/upgrade headaches due to code duplication. The framework supports projects of every scale from logic controllers for industrial automation to world-wide inventory management and functions within every tier from database-heavy back-ends to client-side services. Finally, Delphi’s standard libraries provide simplified access to most database products , fully support Unicode and other modern standards, and broaden access to operating system functionality on every platform as well as I/O devices and sensors. Electron is an open-source framework targeting all desktop operating systems through its Chromium base. It typically focuses on web-centric, client-side applications but can accomplish middle-tier and database services using runtimes and libraries like node.js and node-postgres. Hardware access and limited operating system interactions are provided by node.js libraries and Electron’s Chromium core ensures compliance with modern Unicode standards. After reviewing both frameworks, Delphi holds the lead in the flexibility category due to its flexible and automated deployment to all major platforms, scalability to every level of development, and visual design system. Electron enjoys a lower barrier-to-entry and more development tool options but requires manual […]

Bookmarks and Navigator, originally known as the Parnassus plugins, are some of our most-requested IDE addons. We’re very glad to let you know they are now available in GetIt for RAD Studio 11. To install, go to the Tools menu in the IDE, GetIt Package Manager, and select the IDE Plugins section in the category selector on the left: Bookmarks is a developer-favourite addon that replaces the editor’s inbuilt bookmarks, with an unlimited number of bookmarks, a handy shortcut (Ctrl+B), avoids overwriting bookmarks accidentally, caret bookmarks for quick toggling of location and reverse/stack navigation, a docked window showing bookmark context, and more. Navigator is a related plugin that helps you quickly navigate anywhere in your code: press Ctrl+G, and type to filter to show all useful elements in the current unit. You can type, for example, ‘prop Foo’ (or even shorter, ‘p f’ or even ‘f’ if you have few enough items to make this useful: it filters more as you type more) to find properties with Foo in their name, or find property read/write fields or methods related to that property… or to navigate to classes, records, enums and other types; unit sections like uses clauses; methods; variables, and more. Anything useful in your unit is shown in Navigator and is quickly accessible. It also adds a minimap to the IDE editor showing where you are in your code. RAD Studio 11 showing the Bookmarks and Navigator plugins both in use: bookmarks are shown in the editor and the docked window on the bottom right, while the Navigator plugin is providing the minimap on the right side of the editor and the floating navigation window where I’m searching for a method Bookmarks and Navigator are usually available immediately with the release, and that did not happen for RAD Studio 11. However, we have configured our internal build so that these plugins will always be available in future: that is, you can feel assured we have internal setup to not repeat the delay. The third Parnassus plugin, Debugger, should also come within a few days. The plugins are available for both RAD Studio 11.0 and 11.1; in fact, the screenshot above is taken with RAD Studio 11.0. Thankyou for your patience waiting for these plugins, and we hope you find the Delphi and C++Builder IDE even more productive and pleasant to use with these extensions! Don’t forget — they’re available right now in GetIt. Happy coding!

There is a new patch (or hotfix) available for RAD Studio 11.1. The patch addresses an issue specific to debugging Win32 apps on Windows 11, where the IDE sometimes appears to freeze. Typical situations where you could observe the freeze include evaluating watches with side effects, opening the Threads view to switch threads, attaching to a process, and other common debugging actions. The issue is caused by getting the thread wait chain (GetThreadWaitChain()), which sometimes takes up to a minute. It is resolved by disabling the thread wait chain feature in the debugger. The exact cause of the thread wait chain delay is unknown but it appears to be related to a thread having a socket open, possibly where the thread is waiting to finish network IO. Thread wait chain information is disabled for Win32 on both Windows 10 and Windows 11. There is an environment variable to re-enable it if you need the feature: set DBK_ENABLE_WAITCHAIN=1 on a command prompt, and run RAD Studio (alternatively, set that environment variable globally for Windows.) Only Windows 11 is affected by the issue, so you only need to install the patch on Windows 11. Installation You can download this in GetIt (our recommended technique; also it will show as available on the Welcome Page when you start the IDE) or install manually after downloading from my.embarcadero.com (the zip file contains a batch file installer.) The RAD Studio 11.1 Welcome screen showing the ‘Patch available’ button. Click this to install patches, including this one. Remote Debugging Because this patches the debugger, if you do remote debugging you will also need to update PAServer on the remote machine. The patch installer replaces the (your RAD Studio install location)PAServersetup_paserver.exe file, but you’ll need to copy that over to the remote machine and install it. There are full details in the patch readme.