balenalib/cl-som-imx8-ubuntu-python
This image is part of the balena.io base image series for IoT devices.
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This image is part of the balena.io base image series for IoT devices. The image is optimized for use with balena.io and balenaOS, but can be used in any Docker environment running on the appropriate architecture.
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Some notable features in balenalib
base images:
Helpful package installer script called install_packages
that abstracts away the specifics of the underlying package managers. It will install the named packages with smallest number of dependencies (ignore optional dependencies), clean up the package manager medata and retry if package install fails.
Working with dynamically plugged devices: each balenalib
base image has a default ENTRYPOINT
which is defined as ENTRYPOINT ["/usr/bin/entry.sh"]
, it checks if the UDEV
flag is set to true or not (by adding ENV UDEV=1
) and if true, it will start udevd
daemon and the relevant device nodes in the container /dev will appear.
For more details, please check the features overview in our documentation.
The balenalib
images come in many flavors, each designed for a specific use case.
:<version>
or :<version>-run
This is the defacto image. The run
variant is designed to be a slim and minimal variant with only runtime essentials packaged into it.
:<version>-build
The build variant is a heavier image that includes many of the tools required for building from source. This reduces the number of packages that you will need to manually install in your Dockerfile, thus reducing the overall size of all images on your system.
This guide can help you get started with using this base image with balena, there are also some cool example projects that will give you an idea what can be done with balena.
Python is an interpreted, interactive, object-oriented, open-source programming language. It incorporates modules, exceptions, dynamic typing, very high level dynamic data types, and classes. Python combines remarkable power with very clear syntax. It has interfaces to many system calls and libraries, as well as to various window systems, and is extensible in C or C++. It is also usable as an extension language for applications that need a programmable interface. Finally, Python is portable: it runs on many Unix variants, on the Mac, and on Windows 2000 and later.
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Dockerfile
links :`3.10.5 (latest)`,`3.9.13`, `3.8.13`, `3.7.13`, `3.6.15`
For more information about this image and its history, please see the relevant manifest file (cl-som-imx8-ubuntu-python
) in the balena-io-library/official-images
GitHub repo.
Dockerfile
in your Python app projectFROM balenalib/cl-som-imx8-ubuntu-python:latest
WORKDIR /usr/src/app
COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
CMD [ "python", "./your-daemon-or-script.py" ]
You can then build and run the Docker image:
$ docker build -t my-python-app .
$ docker run -it --rm --name my-running-app my-python-app
For many simple, single file projects, you may find it inconvenient to write a complete Dockerfile
. In such cases, you can run a Python script by using the Python Docker image directly:
$ docker run -it --rm --name my-running-script -v "$PWD":/usr/src/myapp -w /usr/src/myapp balenalib/cl-som-imx8-ubuntu-python:latest python your-daemon-or-script.py
If you have any problems with or questions about this image, please contact us through a GitHub issue.
You are invited to contribute new features, fixes, or updates, large or small; we are always thrilled to receive pull requests, and do our best to process them as fast as we can.
Before you start to code, we recommend discussing your plans through a GitHub issue, especially for more ambitious contributions. This gives other contributors a chance to point you in the right direction, give you feedback on your design, and help you find out if someone else is working on the same thing.
Documentation for this image is stored in the base images documentation. Check it out for list of all of our base images including many specialised ones for e.g. node, python, go, smaller images, etc.
You can also find more details about new features in balenalib
base images in this blog post
docker pull balenalib/cl-som-imx8-ubuntu-python