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UI Toolkit at runtime: Get the breakdown

Let’s clarify how UI Toolkit can ensure smoother workflows while creating UI.  Creating UI in collaboration with artists can be a complex task. While the artist is editing the Canvas to add colors and material, the developer adds scripts, behaviors, and OnClick listeners. Afterward, when merging occurs, merge conflicts can arise and lead to issues that require swift resolution. UI Toolkit prevents such merge conflicts by having the artist work on the UXML and USS files while C# handles all of the logic. For example, button handling is done with C# only, which queries the button using its name, and adds logic without editing any UXML or USS files. Not only does this process ease merging, it simplifies future style changes. For instance, if all project fonts suddenly had to be changed, you wouldn’t need to go through each asset, one by one, to edit the text settings. This avoids tedious work that can lead to oversight issues – and the bigger the game, the more complicated this becomes. With UI Toolkit, Panel Settings hold all of the text settings. So to change the fonts under a UI Document, you only need to edit those Panel Settings. Although Editor scripts can similarly assist with UGUI, UI Toolkit’s framework automatically handles this process. A Visual Element is the base class of every UI Toolkit element: buttons, images, text, etc. You can think of it as the GameObject of UI Toolkit. Meanwhile, UI Builder (Window > UI Toolkit > UI Builder) is a visual tool that helps create and edit interfaces without writing code. This is useful for artists and designers alike, as it allows them to visualize the UI as it’s being built. As the premiere tool for people already familiar with web technologies, UI Toolkit also improves collaboration between artists and developers by separating logic and style to refine organization and avoid file conflicts. While UI Builder takes care of the elements’ positions, style, and design, code can be handled in a distinct section of the project to query the parts of UXML that it needs, and connect logic to it.

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Metaverse Minute: Leaving no trace with digital twins

When our team at Unity says, “We believe the world is a better place with more creators in it,” it isn’t just a catchy tagline – we mean it. To effect change at scale, we need to come up with solutions across a wide array of sectors, fueled by creative thought. And this is especially critical in the case of climate change. Climate change is a global threat that we believe real-time 3D creators can play a paramount role in combating. For Earth Day, we want to spotlight Unity’s digital twin technology and how its application is mobilizing communities and motivating change. We’re excited to showcase the way that Unity’s platform is empowering the business community to take action on climate change across three key industries: construction, fashion, and events.

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GitLab.com is moving to 15.0 with a few breaking changes

GitLab 15.0 is coming to GitLab.com. Along with the exciting new features, it also includes planned deprecations because it is our major version release for 2022. We try to minimize breaking changes, but some changes are needed to improve workflows, performance, scalability, and more. These changes will go live on GitLab.com sometime between April 23 – May 22, through our daily deployments, leading up to the official release of 15.0 on May 22. Keep reading to learn more about these important changes. GitLab 15.0 for self-managed users will also be released on May 22. Jump to the list of breaking changes in each stage by clicking below: Manage Audit events for repository push events Announced in 14.3 Audit events for repository events are now deprecated and will be removed in GitLab 15.0. These events have always been disabled by default and had to be manually enabled with a feature flag. Enabling them can cause too many events to be generated which can dramatically slow down GitLab instances. For this reason, they are being removed. External status check API breaking changes Announced in 14.8 The external status check API was originally implemented to support pass-by-default requests to mark a status check as passing. Pass-by-default requests are now deprecated. Specifically, the following are deprecated: Requests that do not contain the status field. Requests that have the status field set to approved. Beginning in GitLab 15.0, status checks will only be updated to a passing state if the status field is both present and set to passed. Requests that: Do not contain the status field will be rejected with a 422 error. For more information, see the relevant issue. Contain any value other than passed will cause the status check to fail. For more information, see the relevant issue. To align with this change, API calls to list external status checks will also return the value of passed rather than approved for status checks that have passed. OAuth implicit grant Announced in 14.0 The OAuth implicit grant authorization flow will be removed in our next major release, GitLab 15.0. Any applications that use OAuth implicit grant should switch to alternative supported OAuth flows. OAuth tokens without expiration Announced in 14.8 By default, all new applications expire access tokens after 2 hours. In GitLab 14.2 and earlier, OAuth access tokens had no expiration. In GitLab 15.0, an expiry will be automatically generated for any existing token that does not already have one. You should opt in to expiring tokens before GitLab 15.0 is released: Edit the application. Select Expire access tokens to enable them. Tokens must be revoked or they don’t expire. OmniAuth Kerberos gem Announced in 14.3 The omniauth-kerberos gem will be removed in our next major release, GitLab 15.0. This gem has not been maintained and has very little usage. We therefore plan to remove support for this authentication method and recommend using the Kerberos SPNEGO integration instead. You can follow the upgrade instructions to upgrade from the omniauth-kerberos integration to the supported one. Note that we are not deprecating the Kerberos SPNEGO integration, only the old password-based Kerberos integration. Optional enforcement of PAT expiration Announced in 14.8 The feature to disable enforcement of PAT expiration is unusual from a security perspective. We have become concerned that this unusual feature could create […]

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GitLab is now an approved SLP vendor in California

GitLab is now an approved vendor under the Software Licensing Program (SLP) with the state of California. This contract allows state and local agencies, including educational institutions in California, to purchase GitLab software licenses at an agreed-upon discount, reducing costs and streamlining the procurement process. Under the contract, agencies will have greater access to GitLab’s complete DevOps solution, which empowers organizations to deliver software faster and more efficiently. Established in 1994, California’s SLP is managed by the Procurement Division of the Department of General Services. The program provides government agencies and institutions with discounted rates for software licenses and upgrades, reducing the need for individual departments to conduct repetitive acquisitions. “There’s an exciting opportunity for public sector agencies to benefit from automated DevOps practices,” says Bob Stevens, GitLab’s area vice president for Public Sector Federal. “This contract makes it simpler and more cost-effective for agencies to adopt The DevOps Platform, and deliver more resilient and efficient applications while keeping security at the forefront.” GitLab believes that this contract, which makes The DevOps Platform more accessible and cost-effective, will expedite the broader adoption of DevOps in the public sector. GitLab’s single application will enable greater collaboration within public sector agencies, allowing teams to partner on planning, building, securing, and deploying software. To streamline the process, GitLab will work with channel partners including Acuity Technical Solutions, Launch Consulting and Veteran Enhanced Technology Solutions. “Public sector agencies are under tremendous pressure to transform and streamline their software development processes,” said Michelle Hodges, GitLab’s vice president of global channels. “We’re proud to extend the power of our platform to a new network of customers via trusted channel partners and to help evolve the ways in which they collaborate on and deliver software.” “Find out how state and local agencies in California can purchase @gitlab licenses at a discount.” – Click to tweet

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How the DORA metrics can help DevOps team performance

Accelerated adoption of the cloud requires tools that aid in faster software delivery and performance measurements. Delivering visibility across the value chain, the DORA metrics streamline alignment with business objectives, drive software velocity, and promote a collaborative culture. Software delivery, operational efficiency, quality – there is no shortage of challenges around digital transformation for business leaders. Customer satisfaction, a prominent business KPI, has paved the way for experimentation and faster analysis resulting in an increased volume of change in the software development lifecycle (SDLC). Leaders worldwide are helping drive this culture of innovation aligned with organization goals and objectives. However, it is not always about driving the culture alone; it is also about collaboration, visibility, velocity, and quality. Cloud computing and microservices are driving the cloud-first approach for software delivery, helping to scale them independently, and allowing teams to move faster. But, without DevOps, the team doesn’t have the underlying core to move fast efficiently. DevOps has the power to enable the smallest changes that can have great effects. This brings us to the question – how do you measure velocity and impact? Or how do you assess quality, and ensure that it is not hampered by velocity? The latter would be what is commonly referred to as technical debt. A continuous journey needs continuous improvement Any improvement starts with measurement. Measuring and optimizing DevOps practices improves developer efficiency, overall team performance, and business outcomes. DevOps metrics demonstrate effectiveness, shaping a culture of innovation and ultimately overall digital transformation. In the Accelerate State of DevOps 2021 report by the DevOps Research and Assessment (DORA) team at Google Cloud, which draws insights from 7 years of data collection and research, four metrics are the key to measure software delivery performance. What are these metrics? Deployment Frequency Lead time for changes Time to restore service Change failure rate Deployment Frequency Let’s start with the velocity of development. Deployment frequency measures how often the organization deploys code to production or releases it to end users. This metric borrows from lean manufacturing concepts, wherein small multiple batch sizes are the preferred approach for higher efficiency and more rapid adjustments. Lead time for changes Now comes the extent of automation in your processes. Lead time for changes measures the time needed to take a committed code to successfully run in production. This is one of the two metrics with significant variance in the data. Time to restore service This represents a business’ capacity. Time to restore service measures the time needed to restore services to the level they were previously, in case of an incident. Here too we see significant variance in the data. Change failure rate And finally, we take a look at quality. Changes which cause a failure in the system – a deployment failure, an incident, a rollback or a remedy – all contribute to measuring the change failure rate. Driving visibility into the DevOps lifecycle Recently, Zoopla used DORA metrics to boost deployments and increase automation. Understanding the root cause of their problems helped them make informed adjustments in their process workflows, automation, tools, and more. They recognized the value of using a single platform to overcome roadblocks in velocity and innovation. This brought added visibility into their system which helped improve measurement and analytics. Our 2021 Global DevSecOps Survey shows […]

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GitLab’s DevOps platform enables Tangram Vision’s engineering team to succeed at remote work

On March 14, 2020, Tangram Vision CEO Brandon Minor flew from Colorado into the Bay Area to meet with COO Adam Rodnitzky. The two had just launched Tangram Vision, the company they co-founded to make sensors simpler for robotics, drones, and autonomous vehicles. Their plan was to, each month, alternate working at each other’s location. However, that week, the Covid-19 pandemic lockdown began, forcing them to scrap that plan and figure out how to successfully collaborate from afar. “We didn’t see each other in person again for a very long time. That kicked off our remote work experience,” Minor says. The Tangram Vision engineering team started using GitLab’s DevOps platform, which enabled them to work together without missing a beat. “GitLab was a key tool that allowed us to work really fluidly in a remote context,” says Minor. “Our engineering team has placed GitLab at the core of our remote workflow because it reinforces our values and perspectives around working well remotely.” The Tangram Vision Platform takes care of complex perception tasks like sensor fusion, calibration, and diagnostics built on a scalable data backend that allows engineers to track, optimize, and analyze every sensor in their fleet. Tangram Vision’s SDK includes tools for rapid sensor integration, multi-sensor calibration, and sensor stability, saving robotics engineers months of engineering time. Supporting complex collaboration Perception systems are notoriously hard to get up and running and then maintain over time because of important lower-level activities like sensor integration and calibration. “We make sure all the sensors’ data is running smoothly, everything’s working together perfectly to basically a plug-and-play level. And then we enable the developers working on top of that to monitor and correct their system over time,” Minor says. Tangram Vision has just launched a user hub that functions as a centralized sensor data center. The user hub joins their multi-sensor calibration module, as well as a multiplexing module that maintains stream reliability for all connected sensors. Developers can access a starter set of perception development tools (Tangram Vision Platform – Basic), which will be available on an open-source hub. Much of the initial user feedback will come through and be managed within repositories hosted on GitLab, both public and private, Minor says. GitLab as a core for code The engineering team has evaluated other platforms, according to Greg Schafer, senior web architect. “We’ve looked around but we’ve been very turned off by them for one reason or another. We really haven’t swayed in wanting to use GitLab as our core for code,” Schafer says. The team uses GitLab to manage branches and merge requests (MRs), boosting efficiency and control. “We were having a bit of a struggle early on managing the short-term flow. It was hard to put down tasks to paper. So, I dove deep into GitLab to see how it could help us there. And now that’s what we use. GitLab is my product management tool,” Minor says. The alternative, siphoning MRs into tools like Notion and Slack, would have been too cumbersome. “Having code-focused discussions in those places would’ve been very awkward vs. our current orientation of having those discussions in GitLab. Having that history of MRs and threads has been very useful,” Schafer says. Doing all of the code reviews in the MR itself builds a paper trail […]

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Everything You Need To Know About Spring4D Delphi Development Framework

In this webinar from DelphiCon, Stefan Glienke introduces us to the Spring4D framework and how it can take your Delphi and Windows application development to the next level. This Delphi-based framework is packed with a number of useful modules which will be explained in this video along with their actual implementations in Delphi. Spring4D is described as a great open-source library for Delphi XE and higher. This library is freely accessible and can be used for both commercial and non-commercial projects. How can Spring4D leverage and enhance the power of Delphi? The Spring 4D framework extends the Delphi RTL and is known for its advanced use of Generics and enhanced RTTI. The framework is also under active development and is practicing the so-called “Dogfooding” which means the author of the software and the team behind it is actively using the framework for their own commercial software. Spring4D also follows the principle of “Pick and Choose” so it doesn’t dictate how you have to write your own application. You simply take the useful things for your code without being forced to do things in a certain way. Spring4D contains a number of different modules including the common types like Nullable and Event, Smart Pointers like Shared and Weak, Interface-base collection types, and reflection extensions. Aside from explaining the purpose of each module, Stefan will also demonstrate how each of these can be implemented in Delphi. To know more about Spring4D and how this framework can possibly take your Delphi development to the next level, feel free to watch the video below.

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UI Components: They Are Not As Difficult As You Think

  As a web application developer, you must have a deep understanding of UI components. You need to have a clear idea about how users interact with them. It will help you to develop user-friendly web applications. There are various JavaScript libraries and frameworks that can help you build an attractive user interface. However, which is the best one? Does it enable you to create a beautiful interface for your app easily? In this post, you will find all the details. What are UI components? UI components are the most integral parts of a web application. They consist of all the app’s styles and components, such as buttons, input fields, icons, text, etc. They are the core building blocks for all applications. UI components are responsible for interactions between the user and the application. They facilitate an effective user experience, and they allow the users to navigate through the application easily. Also, the UI components help them to efficiently perform various functions, like adding/editing information, filtering data, selecting a date on the calendar, etc. Why should you use UI components? Quickly create the user interface of your web application Reduce code duplication by using reusable components Save development time and money Easily update the UI when required How can I easily create UI components for my JavaScript application? You can easily create UI components for your JavaScript web application using Sencha Ext JS. It is the most comprehensive framework for building data-intensive apps for all modern devices. The UI of Ext JS applications is made up of widgets. They are known as components, and they are subclasses of the Ext.Component class. You can easily extend them to create a customized component for your web application. How can Sencha Ext JS help me in quickly creating UI components? Sencha Ext JS allows you to use reusable code. As a result, you can easily create UI components. Also, it doesn’t require you to get involved with a lot of coding. You can create UI components with just a few lines of code. Let’s take a look at some practical examples. How can I quickly create a calendar for scheduling events? The Ext JS calendar is a powerful UI component for creating custom calendars. It allows you to use the date and event data, just like Google Calendar. Here is an example: The calendar allows you to schedule your work and personal events easily. It comes with a minimalistic design. To create it, you have to follow these steps: 1. First, you need to define a new custom class, called KitchenSink.view.calendar.Month. Then you have to extend Ext.panel.Panel. Also, you need to define the type of UI component, which is calendar-month-view. Ext.define(‘KitchenSink.view.calendar.Month’, {    extend: ‘Ext.panel.Panel’,     xtype: ‘calendar-month-view’, 2. Then you have to add this code:    requires: [        ‘KitchenSink.data.calendar.Month’,        ‘Ext.calendar.panel.Month’,        ‘Ext.calendar.List’    ],    width: 1000,     height: 600, 3. Next, you have to create the viewModel.    viewModel: {        data: {            value: Ext.Date.getFirstDateOfMonth(new Date())        },        stores: {            calStore: {                type: ‘calendar-calendars’,                autoLoad: true,                proxy: {                    type: ‘ajax’,                    url: ‘/KitchenSink/CalendarMonth’                }            }        }     }, 4. Now, you have to specify the layout, bind, and titleAlign fields.    layout: ‘border’,    bind: {        title: ‘{value:date(“M Y”)}’    […]

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How To Make Powerful Data Visualizations With Matplotlib

Did you know it’s easy to make use of some truly excellent Python libraries to super-charge your Delphi app development on Windows? Adding Python to your toolbox of Delphi code can enhance your app development, bringing in new capabilities which help you provide innovative and powerful solutions to your app’s users, which combine the best of Python with the supreme low-code and unparalleled power of native Windows development you get with Delphi. Are you looking for how to build a GUI for powerful and visually stunning data visualizations? You can build publication-quality figures with Matplotlib on Delphi. Matplotlib can be used in Python scripts, the Python and IPython shell, web application servers, and various graphical user interface toolkits (including Delphi!). This post will show you how to build a Delphi GUI app, dedicated to the Matplotlib library. Watch this video by Jim McKeeth, as a comprehensive introduction about why you can love both Delphi and Python at the same time: What is the Matplotlib Library? Matplotlib is a comprehensive Python library for creating static, animated, and interactive visualizations. Matplotlib produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms. Matplotlib makes easy things easy and hard things possible. Create publication-quality plots. Make interactive figures that can zoom, pan, update. Customize visual style and layout. Export to many file formats. Embedded in JupyterLab and Graphical User Interfaces. Use a rich array of third-party packages built on Matplotlib. How do I get the Matplotlib library? You can easily install Matplotlib with pip: Or, you can choose conda install, to avoid complexities, as Anaconda is known as the most trusted distribution for Data Science related tasks: conda install -c conda-forge matplotlib conda install –c conda–forge matplotlib How do I build a Delphi GUI for the Matplotlib library? The following is the user interface structure for our project: User Interface Structure for our Matplotlib4D Project. Here is the list of Components used in the Matplotlib4D demo app: TPythonEngine TPythonModule TPythonType TPythonVersions TPythonGUIInputOutput TForm TMemo TOpenDialog TSaveDialog TSplitter TImage TPanel TLabel TComboBox TButton Navigate to the UnitMatplotlib4D.pas, and add the following line to the FormCreate, to load our basic matplotlibApp.py: Memo1.Lines.LoadFromFile(ExtractFilePath(ParamStr(0)) + ‘matplotlibApp.py’); Memo1.Lines.LoadFromFile(ExtractFilePath(ParamStr(0)) + ‘matplotlibApp.py’); You can Seamlessly Load the Matplotlib App Python File Inside the UnitMatplotlib4D.pas File. And make sure that the matplotlibApp.py is in the same directory as our Matplotlib4D.exe or inside your Delphi project folder. How to visualize data using Matplotlib on the Delphi app? Highly recommended practice:  1. This GUI was created by modifying Python4Delphi Demo34, which makes us possibly change the Python version in the runtime (this will save you from the seemingly complicated dll issues). 2. Add “Jpeg” to the Uses-list at the top of our UnitMatplotlib4D.pas code. We have to do that, because otherwise, Delphi can not understand the JPG format. With this correction, it should work. After that, the above change should look similar to this: Import Jpeg to Your Uses-list. And we can load JPG images into our TImage. 3. Set up these paths to your Environment Variable: C:/Users/ASUS/AppData/Local/Programs/Python/Python38 C:/Users/ASUS/AppData/Local/Programs/Python/Python38/DLLs C:/Users/ASUS/AppData/Local/Programs/Python/Python38/Lib/bin C:/Users/ASUS/AppData/Local/Programs/Python/Python38/Lib/site-packages/bin C:/Users/ASUS/AppData/Local/Programs/Python/Python38/Scripts C:/Users/ASUS/AppData/Local/Programs/Python/Python38 C:/Users/ASUS/AppData/Local/Programs/Python/Python38/DLLs C:/Users/ASUS/AppData/Local/Programs/Python/Python38/Lib/bin C:/Users/ASUS/AppData/Local/Programs/Python/Python38/Lib/site–packages/bin C:/Users/ASUS/AppData/Local/Programs/Python/Python38/Scripts 4. Creating a GUI for Matplotlib means that you will use Matplotlib outside the “normal” command-line process. You need to add these lines to all your Python code: import matplotlib import matplotlib.pyplot as […]

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Customize your memory use with Unity 2021 LTS

In summer 2020, Unity provided support for Moon Studios when they were working to port Ori and the Will of the Wisp to Nintendo Switch. You can learn more about how we worked together to scale the project for this target platform in this case study. Moon Studios and Unity Accelerate Solutions (formerly Unity Professional Services) analyzed sections of code together, finding ways to tweak the particle systems and reduce memory usage. “When you’re targeting 60 fps on Nintendo Switch, you have to make sure every single aspect is optimized, including simulation, streaming, rendering, and graphics,” says studio founder Gennadiy Korol. Ori and the Will of the Wisps pushes the Nintendo Switch very hard in terms of memory use. The Accelerate Solutions team helped Moon make sure they were getting the best from these layers, focusing on native memory allocation.  Working with the team from Moon Studios, the Unity team measured the number of allocations from the different allocators. They also looked at the amount of memory allocated from each, which showed that the game was filling up some of the bucket allocators before even reaching the start of gameplay.   Increasing the size of the bucket allocator allowed extra room for small allocations that happen when playing the game. Allocating these small blocks from the bucket allocator gives the game a performance boost, helping it to hit the 60 fps target. The small allocations no longer come from the dynamic heap allocator, so this allocator contains just large blocks of memory. The allocator is less fragmented, which keeps the game running smoothly for longer.   Following the collaboration with Moon, the Accelerate Solutions team worked with the Optimization team, who developed the memory allocator customization feature that is now available in 2021 LTS.

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