Supported tags and respective
Where to file issues:
the Docker Community
Supported Docker versions:
the latest release (down to 1.6 on a best-effort basis)
What is Python?
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.
How to use this image
Dockerfile in your Python app project
FROM arm64v8/python:3 WORKDIR /usr/src/app COPY requirements.txt ./ RUN pip install --no-cache-dir -r requirements.txt COPY . . CMD [ "python", "./your-daemon-or-script.py" ]
or (if you need to use Python 2):
FROM arm64v8/python:2 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
Run a single Python script
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 arm64v8/python:3 python your-daemon-or-script.py
or (again, if you need to use Python 2):
$ docker run -it --rm --name my-running-script -v "$PWD":/usr/src/myapp -w /usr/src/myapp arm64v8/python:2 python your-daemon-or-script.py
arm64v8/python images come in many flavors, each designed for a specific use case.
This is the defacto image. If you are unsure about what your needs are, you probably want to use this one. It is designed to be used both as a throw away container (mount your source code and start the container to start your app), as well as the base to build other images off of. This tag is based off of
buildpack-deps is designed for the average user of docker who has many images on their system. It, by design, has a large number of extremely common Debian packages. This reduces the number of packages that images that derive from it need to install, thus reducing the overall size of all images on your system.
This image does not contain the common packages contained in the default tag and only contains the minimal packages needed to run
arm64v8/python. Unless you are working in an environment where only the
arm64v8/python image will be deployed and you have space constraints, we highly recommend using the default image of this repository.
ONBUILD image variants are deprecated, and their usage is discouraged. For more details, see docker-library/official-images#2076.
This image feeds your
requirements.txt file automatically to
pip in order to make building derivative images easier. For most use cases, creating a
Dockerfile in the base of your project directory with the line
FROM arm64v8/python:onbuild will be enough to create a stand-alone image for your project.
onbuild variant is really useful for "getting off the ground running" (zero to Dockerized in a short period of time), it's not recommended for long-term usage within a project due to the lack of control over when the
ONBUILD triggers fire (see also
Once you've got a handle on how your project functions within Docker, you'll probably want to adjust your
Dockerfile to inherit from a non-
onbuild variant and copy the commands from the
Dockerfile (moving the
ONBUILD lines to the end and removing the
ONBUILD keywords) into your own file so that you have tighter control over them and more transparency for yourself and others looking at your
Dockerfile as to what it does. This also makes it easier to add additional requirements as time goes on (such as installing more packages before performing the previously-