Скачать или смотреть How to Install Python in a Dockerfile Without Using a Python Base Image

Learn how to containerize your Python script with DigitalOcean tools by installing `Python`, `doctl`, and `kubectl` in a Dockerfile without a pre-defined Python base image.
---
This video is based on the question https://stackoverflow.com/q/70610919/ asked by the user 'boblerbob' ( https://stackoverflow.com/u/16614317/ ) and on the answer https://stackoverflow.com/a/70611018/ provided by the user 'Guinther Kovalski' ( https://stackoverflow.com/u/11145820/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Installing python in Dockerfile without using python image as base

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Installing Python in Dockerfile without Using a Python Image as Base

Containerization has become a vital part of modern software development, enabling developers to build, package, and deploy applications consistently across various environments. If you have a Python script that requires specific tools like DigitalOcean's doctl and kubectl, the process can be tricky—especially when you want to create your Dockerfile without relying on a predefined Python image. In this post, we'll guide you through the steps to successfully achieve this.

The Dilemma: Combining Python with Other Tools

The challenge arises when you're trying to include two separate tools within a single Dockerfile while adhering to the limitation of using only one base image. Here are the two options you might consider:

Option 1: Use a Python Base Image

If you choose to start with a Python base image (python:3), you would typically install the necessary DigitalOcean tools afterward. Your initial Dockerfile segment might look like this:

[[See Video to Reveal this Text or Code Snippet]]

Option 2: Use the Alpine/doctl Base Image

Alternatively, you could opt for the alpine/doctl base image and install Python separately:

[[See Video to Reveal this Text or Code Snippet]]

However, figuring out how to perform installations in either case can be quite daunting. Let's explore how to efficiently tackle it.

The Solution: Installing Python and DigitalOcean Tools

Using APT-GET in Debian-Based Images

If you're utilizing a Debian-based image (like the python:3 image), installing Python and the necessary tools can be done by running the following commands:

[[See Video to Reveal this Text or Code Snippet]]

apt-get update: Updates the package list for the apt package manager.

apt-get install -y: Installs Python 3.6 and pip without prompting for confirmation.

Using APK in Alpine-Based Images

If you decide to use the alpine/doctl base image, you will use the apk package manager. The installation commands look something like this:

[[See Video to Reveal this Text or Code Snippet]]

apk add: Installs Python 3 and allows version management.

ln -sf: Creates a symbolic link for the Python executable.

python3 -m ensurepip: Ensures that the pip package manager is available for installation.

pip3 install --no-cache: Upgrades both pip and setuptools without caching.

Putting It All Together

To construct a complete Dockerfile using the Alpine-based image, your final Dockerfile could appear as follows:

[[See Video to Reveal this Text or Code Snippet]]

Final Thoughts

By following the steps outlined above, you can effectively manage the installation of your required tools within a single Dockerfile. This not only consolidates your dependencies but also preserves the integrity of your containerization strategy. Don't hesitate to explore various base images and installation methods as your project requirements evolve!

With this guide, you should now feel equipped to containerize your Python script that integrates DigitalOcean tools confidently.