For Python, developers now can run Python tests with coverage and get rich results in the editor, Microsoft said. To run tests with coverage, users must select the coverage run icon in Test Explorer or “Run with coverage” from any menu that triggers test runs. The Python extension will run coverage by using the pytest-cov plugin if developers are using pytest, or by using coverage.py if using unittest. Once the coverage is complete, lines are highlighted in the editor for line-level coverage. The Python extension also has added a default problem matcher, simplifying issue tracking in Python code and providing more contextual feedback.

The Source Control Graph in Visual Studio Code 1.94 features a new history item reference picker in the view title, allowing developers to use the reference picker to filter the history items shown in the graph to a different branch or to view multiple branches. The Source Control Graph also expands the list of actions available in the context menu for source control history items. Actions have been added to create a new branch/tag from a history item, cherry-pick a history item, and check out an item.

Elsewhere in Visual Studio Code 1.94:

Business reputation and trust are always vulnerable; companies recognize that a security breach can instantly damage both. Indeed, you’ll get yourself on the morning news and watch your stock drop by 50%. By prioritizing security, businesses aim to safeguard their reputation and customer relationships.

Long-term cost implications mean that focusing initially on cost and scalability might seem feasible, but the long-term financial impact of security incidents can be severe. Most people in the cybersecurity space understand that risk equals money. The more risk, the less your systems are worth, considering the potential for a breach. Prioritizing security can prevent costly breaches and downtime.

Innovation and agility mean that to remain competitive, businesses need to innovate rapidly. A secure cloud infrastructure enables this by providing a reliable foundation for building and deploying new services without compromising data integrity or security.

For Python, developers now can run Python tests with coverage and get rich results in the editor, Microsoft said. To run tests with coverage, users must select the coverage run icon in Test Explorer or “Run with coverage” from any menu that triggers test runs. The Python extension will run coverage by using the pytest-cov plugin if developers are using pytest, or by using coverage.py if using unittest. Once the coverage is complete, lines are highlighted in the editor for line-level coverage. The Python extension also has added a default problem matcher, simplifying issue tracking in Python code and providing more contextual feedback.

The Source Control Graph in Visual Studio Code 1.94 features a new history item reference picker in the view title, allowing developers to use the reference picker to filter the history items shown in the graph to a different branch or to view multiple branches. The Source Control Graph also expands the list of actions available in the context menu for source control history items. Actions have been added to create a new branch/tag from a history item, cherry-pick a history item, and check out an item.

Elsewhere in Visual Studio Code 1.94:

Additionally, it also has a separate tool, SAP Data Lake Builder, that can be used to ingest data from SAP. Other specific data ingesting tools on offer include BryteFlow for Oracle, BryteFlow for SQL, BryteFLow for SQL Server, BryteFlow for PostgreSQL, and integrations with Databricks, Teradata, Google BigQuery, and Apache Kafka.

What effect will the acquisition have?

BryteFLow’s existing customers may have to look elsewhere for help with data integration if they use databases other than SingleStoreDB: “Our number one priority is to integrate BryteFlow into SingleStore and bring value to our customers through SingleConnect. We have no plan to sell BryteFlow independently at this time, apart from some special cases,” SingleStore CEO Raj Verma said via email.

But there will be opportunities for SingleStore customers, said Duncan Van Kouteren, research analyst at Nucleus Research. “The acquisition will enable customers to integrate data from various sources while maintaining real-time data analytics functionalities by utilizing BryteFlow’s capabilities such as change data capture (CDC),” he said.

“Many developers use the same context repeatedly across multiple API calls when building AI applications, like when making edits to a codebase or having long, multi-turn conversations with a chatbot,” OpenAI explained, adding that the rationale is to reduce token consumption when sending a request to the LLM.

What that means is that when a new request comes in, the LLM checks if some parts of the request are cached. In case it is cached, it uses the cached version, otherwise it runs the full request.

OpenAI’s new prompt caching capability works on the same fundamental principle, which could help developers save on cost and time.

Putting a trusted execution environment on a PC is useful for more than securing AI. It protects sensitive data, adding a new level of protection beyond at rest and in motion: in use. While it does require more work to define and use a VBS Enclave, it’s worth it to have more security with only limited performance impact.

With Windows 11’s memory integrity tools, a VBS Enclave uses Windows’ integral hypervisor to create a new, isolated, high-privilege area of system memory: Virtual Trust Level 1. Most of your code, and Windows itself, continues to run at Virtual Trust Level 0. VTL 1 is used by a secure version of the Windows kernel, with its own isolated user mode. This is where your VBS Enclave runs, as part of an application that appears to cross the boundary between the two zones. In reality, you’re separating off the VTL 1 enclave and using secure channels to communicate with it from the rest of your application in VTL 0.

Using VBS Enclaves in your applications

So how do you build and use VBS Enclaves? First, you’ll need Windows 11 or Windows Server 2019 or later, with VBS enabled. You can do this from the Windows security tool, via a Group Policy, or with Intune to control it via MDM. It’s part of the Memory Integrity service, so you should really be enabling it on all supported devices to help reduce security risks, even if you don’t plan to use VBS Enclaves in your code.

public static class MyListExtensions
{
    public static T GetLastElement(this List list)
    {
        if(list.Count > 0)
            return list[list.Count - 1];
        return default(T);
    }
}

The GetLastElement is an extension method that returns the last element of a list. You can invoke this extension method using the following code snippet.

List integers = new List { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
int element = integers.GetLastElement();
Console.WriteLine(element);

Overloading an extension method in C#

Similar to other methods, you can also overload an extension method. The following code snippet shows how you can overload the Substring method of the string class to return a substring of a string. This overloaded Substring method takes the starting and ending index and a Boolean as parameters. The Boolean denotes if the returned string should be converted to upper case. If you pass true in this parameter when calling the extension method, the returned string will be converted to upper case.

Si vous avez récemment capturé des moments précieux avec votre caméra ou créé un contenu que vous souhaitez partager, il est parfois nécessaire de le réduire ou d’en extraire une partie spécifique. Découper une vidéo peut sembler compliqué, mais avec Windows 11, cela devient un jeu d’enfant. Dans cet article, je vais vous montrer comment découper une vidéo facilement en utilisant les outils intégrés de Windows 11.

Préparation et ouverture du fichier vidéo

Ouvrir avec l’application Photos

Tout d’abord, assurez-vous que la vidéo à couper est bien enregistrée sur votre ordinateur. Vous pouvez utiliser l’application Photos de Windows pour cette tâche. Cette application n’est pas seulement destinée aux photos, elle possède aussi des fonctionnalités pour la vidéo. Pour commencer, faites un clic droit sur la vidéo que vous souhaitez découper et sélectionnez “ouvrir avec” puis choisissez Photos.

L’application s’ouvrira alors avec votre vidéo chargée. C’est le point de départ parfait pour faire vos premières modifications. Lorsque votre vidéo est ouverte dans Photos, vous verrez plusieurs options au sommet de la fenêtre qui vous permettront de procéder à la découpe.

Utilisation de l’éditeur intégré

Lorsque vous avez ouvert votre vidéo dans Photos, cliquez sur le bouton “icône découpage vidéo“. Ce bouton se trouve généralement en haut à droite de l’écran. En cliquant dessus, l’éditeur intégré de Windows s’affiche avec toute une gamme d’outils que vous pouvez utiliser pour personnaliser votre vidéo.

Avant de commencer à découper, prenez quelques instants pour vous familiariser avec l’interface de l’éditeur. Vous verrez une barre de chronologie au bas de la fenêtre, ainsi que diverses options telles que le réglage de la longueur et de la qualité de la vidéo.

Découper la vidéo pas à pas

Sélectionner la section à découper

Afin de découper une vidéo, vous devez indiquer à l’éditeur quelles parties vous souhaitez conserver. Utilisez les poignées bleues situées à chaque extrémité de la barre de chronologie vidéo et audio. Déplacez ces poignées jusqu’à ce qu’elles encadrent précisément la section dont vous avez besoin.

Il est important d’être précis ici pour éviter de perdre des parties souhaitées ou de conserver des parties indésirables. Prenez votre temps et prévisualisez la vidéo autant de fois que nécessaire pour vous assurer que la sélection est correcte.

Raccourcis clavier et finalisation

Pour rendre le processus encore plus rapide, vous pouvez utiliser le raccourci clavier Ctrl + E pour accéder directement à l’option découpage de l’écran. Une fois les poignées bleues placées, vérifiez que la section choisie est celle que vous désirez maintenir. Ensuite, utilisez l’option découpage de la vidéo pour retirer la partie non désirée.

Après avoir découpé la vidéo, vous pouvez soit sauvegarder la nouvelle version de la vidéo en remplaçant l’originale, soit créer un nouveau fichier pour ne pas perte la vidéo originale intacte. Pour cela, allez dans le menu “Fichier” puis sélectionnez “Enregistrer sous”. Donnez un nom à votre vidéo et choisissez un emplacement où l’enregistrer.

Approfondir avec des outils tiers

Quand utiliser des logiciels additionnels  ?

Bien que l’application Photos soit très pratique pour de simples découpes, vous pourriez nécessiter des fonctionnalités avancées tel que des effets spéciaux, des transitions, ou même de l’édition audio. Dans ce cas, il existe divers logiciels libres ou payants qui peuvent offrir des capacités supplémentaires.

Certains logiciels comme DaVinci Resolve ou Adobe Premiere Pro sont parfaits si vous souhaitez engager dans des projets plus complexes. Ces programmes peuvent sembler intimidants, mais ils offrent une latitude beaucoup plus grande en termes de personnalisation.

Installation et utilisation

Parmi les logiciels populaires, DaVinci Resolve est une excellente option gratuite pour les utilisateurs cherchant à aller au-delà des outils de base fournis par Windows 11. Après téléchargement et installation, ouvrez le programme et importez votre vidéo. L’interface utilisateur est bien différente de celle de Photos, cependant, elle reste intuitive après quelques minutes d’utilisation.

Une fois votre vidéo importée, placez-la sur la chronologie principale en bas de l’écran. Identifiez et sélectionner les sections exactes que vous voulez découper en utilisant les marqueurs disponibles. Enfin, exportez la vidéo finie dans votre format choisi.

Conseils pratiques pour une découpe efficace

Planification avant la découpe

Planifier avant de commencer peut vous éviter bien des tracas. Ainsi, sachez exactement quelles parties de la vidéo doivent être conservées ou supprimées. Noter les points de début et de fin vous fera gagner du temps pendant l’édition.

N’oubliez pas d’utiliser des méthodes de sauvegardes multiples. Cela pourrait impliquer la création de copies de votre fichier vidéo afin de protéger votre travail original.

Testez et ajustez régulièrement

Enfin, il est judicieux de tester fréquemment pendant que vous éditer. Visualisez la section découpée, assurez-vous que les parties importantes ne soient pas supprimées. Cela permet également d’ajuster si nécessaire pour une coupe précise.

Ces techniques devraient faciliter votre expérience de découpage de vidéo sous Windows 11 et garantir des résultats optimaux. Que ce soit pour un projet personnel ou professionnel, maîtriser l’art du découpage vous aide toujours à produire des contenus vidéos attrayants et professionnels.

docker run -i -t --name apache_web ubuntu /bin/bash

This creates a new container with a unique ID and the name apache_web. It also gives you a root shell because you specified /bin/bash as the command to run. Now, install the Apache web server using apt-get:

apt-get install apache2

Note that you don’t need to use sudo, because you’re running as root inside the container. Note that you do need to run apt-get update, because, again, the package list inside the container is not the same as the one outside of it. (The other instructions inside the container do not require sudo unless explicitly stated.)

The normal apt-get output appears, and the Apache2 package is installed in your new container. Once the install has completed, start Apache, install curl, and test the installation, all from within your container:

service apache2 start
apt-get install curl

curl http://localhost

If you were doing this in a production environment, you’d next configure Apache to your requirements and install an application for it to serve. Docker lets directories outside a container be mapped to paths inside it, so one approach is to store your web app in a directory on the host and make it visible to the container through a mapping.

Create a startup script for a Docker container

Remember that a Docker container runs only as long as its process or processes are active. So if the process you launch when you first run a container moves into the background, like a system daemon, Docker will stop the container. Therefore, you need to run Apache in the foreground when the container launches, so that the container doesn’t exit as soon as it fires up.

Create a script, startapache.sh, in /usr/local/sbin:

apt-get install nano

nano /usr/local/sbin/startapache.sh

(You don’t have to use the nano editor to do this, but it’s convenient.)

The contents of startapache.sh:

#!/bin/bash
. /etc/apache2/envvars
/usr/sbin/apache2 -D FOREGROUND

Save the file and make it executable:

chmod +x /usr/local/sbin/startapache.sh

All this small script does is bring in the appropriate environment variables for Apache and start the Apache process in the foreground.

You’re done modifying the contents of the container, so you can leave the container by typing exit. When you exit the container, it will stop.

Commit the container to create a new Docker image

Now you need to commit the container to save the changes you’ve made:

docker commit apache_web local:apache_web

The commit will save your container as a new image and return a unique ID. The argument local:apache_web will cause the commit to be placed in a local repository named local with a tag of apache_web.

You can see this by running the command docker images:

REPOSITORY   TAG          IMAGE ID       CREATED          SIZE
local        apache_web   540faa63535d   24 seconds ago   233MB
ubuntu       latest       b1e9cef3f297   4 weeks ago      78.1MB

Note that the exact details of your image—the image ID and the size of the container—will be different from my example.

Docker networking basics

Now that you have your image, you can start your container and begin serving pages. Before you do that, let’s discuss how Docker handles networking.

Docker can create various virtual networks used by Docker containers to talk to each other and the outside world:

• bridge: This is the network that containers connect to by default. The bridge network allows containers to talk to each other directly, but not to the host system.
• host: This network lets containers be seen by the host directly, as if any apps within them were running as local network services.
• none: This is essentially a null or loopback network. A container connected to none can’t see anything but itself.

Other network drivers also exist, but these three are most crucial for starting out.

When you want to launch a container and have it communicate with both other containers and the outside world, you need to manually map ports from that container to the host. For the sake of my example, you can do this on the command line when you launch your newly created container:

docker run -d -p 8080:80 --name apache local:apache_web /usr/local/sbin/startapache.sh

The -p switch is used for port mapping. Here, it maps port 8080 on the host to port 80 inside the container.

Once you run this command, you should be able to point a web browser at the IP address of the host and see the default Apache web server page.

You can see the status of the container and the TCP port mappings by using the docker ps command:

CONTAINER ID   IMAGE               COMMAND                  CREATED          STATUS          PORTS             
     NAMES
81d8985d0197   local:apache_web   "/usr/local/sbin/sta…"   13 minutes ago   Up 12 minutes   0.0.0.0:8080->80/tcp   apache

You can also look up the network mappings by using the docker port command, in this case docker port apache

80/tcp -> 0.0.0.0:8080

Note that you could use the -P option on the docker run command to publish all open ports on the container to the host and map a random high port such as 49153 back to port 80 on the container. This can be used in scripting as necessary, but it’s generally a bad idea to do this in production.

At this point, you have a fully functional Docker container running your Apache process. When you stop the container, it will remain in the system and can be restarted at any time via the docker restart command.

Use Dockerfiles to automate Docker image builds

As educational as it is to build Docker containers manually, it is pure tedium to do this repeatedly. To make the build process easy, consistent, and repeatable, Docker provides a form of automation for creating Docker images called Dockerfiles.

Dockerfiles are text files, stored in a repository alongside Docker images. They describe how a specific container is built, letting Docker perform the build process for you automatically. Here is an example Dockerfile for a minimal container, much like the one I built in the first stages of this demo:

FROM ubuntu:latest
RUN apt-get update
RUN apt-get install -y curl
ENTRYPOINT ["/bin/bash"]

If you save this file as dftest in your local directory, you can build an image named ubuntu:testing from dftest with the following command:

docker build -t ubuntu:testing - < dftest

In PowerShell, you’d use this command:

cat .\dftest | docker build -t ubuntu:testing -

Docker will build a new image based on the ubuntu:latest image. Then, inside the container, it will perform an apt-get update and use apt-get to install curl. Finally, it will set the default command to run at container launch as /bin/bash. You could then run:

docker run -i -t ubuntu:testing

Et voilà! You have a root shell on a new container built to those specifications. Note that you can also launch the container with this command:

docker run -i -t dftest

Numerous operators are available to be used in a Dockerfile, such as mapping host directories to containers, setting environment variables, and even setting triggers to be used in future builds. See the Dockerfile reference page for a full list of Dockerfile operators.

Next steps with Docker

There’s much more to Docker than we’ve covered in this guide, but you should have a basic understanding of how Docker operates, a grasp of the key Docker concepts, and enough familiarity to build functional containers. You can find more information on the Docker website including an online tutorial that goes into more granular detail about Docker features.