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There are many ways to optimize both the Docker build process and the resulting Docker images. Cet article explique comment fonctionne le processus de génération Docker et comment créer des images optimales pour les conteneurs Windows. This article explains how the Docker build process works and how to optimally create images for Windows containers. Before you can optimize your Docker build, you'll need to know how Docker build works. During the Docker build process, a Dockerfile is consumed, and each actionable instruction is run, one-by-one, in its own temporary container. The result is a new image layer for each actionable instruction.

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There are many ways to optimize both the Docker build process and the resulting Docker images. Cet article explique comment fonctionne le processus de génération Docker et comment créer des images optimales pour les conteneurs Windows.

This article explains how the Docker build process works and how to optimally create images for Windows containers. Before you can optimize your Docker build, you'll need to know how Docker build works. During the Docker build process, a Dockerfile is consumed, and each actionable instruction is run, one-by-one, in its own temporary container. The result is a new image layer for each actionable instruction. For example, the following sample Dockerfile uses the mcr.

You might expect that this Dockerfile will produce an image with two layers, one for the container OS image, and a second that includes IIS and the website. However, the actual image has many layers, and each layer depends upon the one before it.

To make this clearer, let's run the docker history command against the image our sample Dockerfile made. The output shows us that this image has four layers: the base layer and three additional layers that are mapped to each instruction in the Dockerfile. The bottom layer dfda5 in this example represents the base OS image. One layer up is the IIS installation. La couche suivante inclut le nouveau site web, etc. The next layer includes the new website, and so on. Dockerfiles can be written to minimize image layers, optimize build performance, and optimize accessibility through readability.

Ultimately, there are many ways to complete the same image build task. Understanding how the Dockerfile's format affects build time and the image it creates improves the automation experience.

Depending on your space requirements, image size can be an important factor when building Docker container images. Container images are moved between registries and host, exported and imported, and ultimately consume space.

This section will tell you how to minimize image size during the Docker build process for Windows containers. For additional information about Dockerfile best practices, see Best practices for writing Dockerfiles on Docker. Because each RUN instruction creates a new layer in the container image, grouping actions into one RUN instruction can reduce the number of layers in a Dockerfile. Cela sera présenté dans des exemples ultérieurs. While minimizing layers may not affect image size much, grouping related actions can, which will be seen in subsequent examples.

Dans cette section, nous allons comparer deux exemples de fichiers Dockerfile effectuant les mêmes opérations. In this section, we'll compare two example Dockerfiles that do the same things.

À cette différence près, un fichier Dockerfile dispose d'une instruction par action et l'autre de ses propres actions connexes regroupées. However, one Dockerfile has one instruction per action, while the other had its related actions grouped together. The following ungrouped example Dockerfile downloads Python for Windows, installs it, and removes the downloaded setup file once installation is done. Dans ce fichier Dockerfile, chaque action reçoit sa propre instruction RUN.

In this Dockerfile, each action is given its own RUN instruction. FROM mcr. The resulting image consists of three additional layers, one for each RUN instruction. The second example is a Dockerfile that performs the exact same operation.

Toutefois, toutes les actions connexes ont été regroupées sous une seule instruction RUN. However, all related actions have been grouped under a single RUN instruction. The resulting image has only one additional layer for the RUN instruction. If there's a file in your Dockerfile, such as an installer, that you don't need after it's been used, you can remove it to reduce image size.

This needs to occur in the same step in which the file was copied into the image layer. Doing so prevents the file from persisting in a lower-level image layer. In the following example Dockerfile, the Python package is downloaded, executed, then removed.

This is all completed in one RUN operation and results in a single image layer. You can split operations into multiple individual instructions to optimize Docker build speed. Multiple RUN operations increase caching effectiveness because individual layers are created for each RUN instruction.

If an identical instruction was already run in a different Docker Build operation, this cached operation image layer is reused, resulting in decreased Docker build runtime. In the following example, both Apache and the Visual Studio Redistribute packages are downloaded, installed, and then cleaned up by removing files that are no longer needed. Tout cela se fait à l'aide d'une seule instruction RUN. This is all done with a single RUN instruction. If any of these actions are updated, all actions will rerun.

The resulting image has two layers, one for the base OS image, and one that contains all operations from the single RUN instruction. By comparison, here are the same actions split into three RUN instructions. In this case, each RUN instruction is cached in a container image layer, and only those that have changed need to be rerun on subsequent Dockerfile builds.

The resulting image consists of four layers; one layer for the base OS image and each of the three RUN instructions. Because each RUN instruction ran in its own layer, any subsequent runs of this Dockerfile or identical set of instructions in a different Dockerfile will use cached image layers, reducing build time. How you order the instructions is important when working with image caches, as you'll see in the next section.

Classement des instructionsOrdering instructions Un fichier Dockerfile est traité de haut en bas, chaque Instruction étant comparée aux couches mises en cache. A Dockerfile is processed from top to the bottom, each Instruction compared against cached layers.

When an instruction is found without a cached layer, this instruction and all subsequent instructions are processed in new container image layers. Because of this, the order in which instructions are placed is important. Placez les instructions qui resteront constantes en haut du fichier Dockerfile.

Place instructions that will remain constant towards the top of the Dockerfile. Placez les instructions qui peuvent changer en bas du fichier Dockerfile. Place instructions that may change towards the bottom of the Dockerfile. Doing so reduces the likelihood of negating existing cache.

The following examples show how Dockerfile instruction ordering can affect caching effectiveness. Cet exemple Dockerfile simple présente quatre dossiers numérotés.

This simple example Dockerfile has four numbered folders. This next Dockerfile has now been slightly modified, with the third RUN instruction changed to a new file. When Docker build is run against this Dockerfile, the first three instructions, which are identical to those in the last example, use the cached image layers. However, because the changed RUN instruction isn't cached, a new layer is created for the changed instruction and all subsequent instructions.

When you compare the image IDs of the new image to that in this section's first example, you'll notice that the first three layers from bottom to top are shared, but the fourth and fifth are unique.

Dockerfile instructions are not case-sensitive, but the convention is to use upper case. This improves readability by differentiating between the Instruction call and instruction operation. Les deux exemples suivants comparent un fichier Dockerfile sans majuscules et avec majuscules. The following two examples compare an uncapitalized and capitalized Dockerfile. The following Dockerfile installs the Visual Studio Redistributable package, removes the installer files, and then creates a configuration file.

Ces trois opérations sont toutes spécifiées sur une seule ligne. These three operations are all specified on one line. The command can be broken up with backslashes so that each operation from the one RUN instruction is specified on its own line.

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Yeni Başlayanlar İçin Python: Python 3.5.1 Sürümü İle Uyumlu

Utilisation[ modifier modifier le code ] Python est un langage qui peut s'utiliser dans de nombreux contextes et s'adapter à tout type d'utilisation grâce à des bibliothèques spécialisées. Il est cependant particulièrement utilisé comme langage de script pour automatiser des tâches simples mais fastidieuses, comme un script qui récupérerait la météo sur Internet ou qui s'intégrerait dans un logiciel de conception assistée par ordinateur afin d'automatiser certains enchaînements d'actions répétitives voir la section Adoption. On l'utilise également comme langage de développement de prototype lorsqu'on a besoin d'une application fonctionnelle avant de l'optimiser avec un langage de plus bas niveau. Il est particulièrement répandu dans le monde scientifique, et possède de nombreuses bibliothèques optimisées destinées au calcul numérique. Fan de la série télévisée Monty Python's Flying Circus , il décide de baptiser ce projet Python [12]. En février , la première version publique, numérotée 0.

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