aarch64/python
Python is an interpreted, interactive, object-oriented, open-source programming language.
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The aarch64
organization is deprecated in favor of the more-specific arm64v8
organization, as per https://github.com/docker-library/official-images#architectures-other-than-amd64. Please adjust your usages accordingly.
Dockerfile
links** THESE IMAGES ARE VERY EXPERIMENTAL; THEY ARE PROVIDED ON A BEST-EFFORT BASIS WHILE docker-library/official-images#2289 IS STILL IN-PROGRESS (which is the first step towards proper multiarch images) **
** PLEASE DO NOT USE THEM FOR IMPORTANT THINGS **
This image is built from the source of the official image of the same name (python
). Please see that image's description for links to the relevant Dockerfile
s.
If you are curious about specifically how this image differs, see the Jenkins Groovy DSL scripts in the tianon/jenkins-groovy
GitHub repository, which are responsible for creating the Jenkins jobs which build them.
Where to get help:
the Docker Community Forums, the Docker Community Slack, or Stack Overflow
Where to file issues:
https://github.com/docker-library/python/issues
Maintained by:
the Docker Community
Published image artifact details:
repo-info repo's repos/python/
directory (history)
(image metadata, transfer size, etc)
Image updates:
official-images PRs with label library/python
official-images repo's library/python
file (history)
Source of this description:
docs repo's python/
directory (history)
Supported Docker versions:
the latest release (down to 1.6 on a best-effort basis)
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.
Dockerfile
in your Python app projectFROM 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 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
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 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 python:2 python your-daemon-or-script.py
The python
images come in many flavors, each designed for a specific use case.
python:<version>
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
. 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.
python:slim
This image does not contain the common packages contained in the default tag and only contains the minimal packages needed to run python
. Unless you are working in an environment where only the python
image will be deployed and you have space constraints, we highly recommend using the default image of this repository.
python:alpine
This image is based on the popular Alpine Linux project, available in the alpine
official image. Alpine Linux is much smaller than most distribution base images (~5MB), and thus leads to much slimmer images in general.
This variant is highly recommended when final image size being as small as possible is desired. The main caveat to note is that it does use musl libc instead of glibc and friends, so certain software might run into issues depending on the depth of their libc requirements. However, most software doesn't have an issue with this, so this variant is usually a very safe choice. See this Hacker News comment thread for more discussion of the issues that might arise and some pro/con comparisons of using Alpine-based images.
To minimize image size, it's uncommon for additional related tools (such as git
or bash
) to be included in Alpine-based images. Using this image as a base, add the things you need in your own Dockerfile (see the alpine
image description for examples of how to install packages if you are unfamiliar).
python:onbuild
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 python:onbuild
will be enough to create a stand-alone image for your project.
While the 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 docker/docker#5714
, docker/docker#8240
, docker/docker#11917
).
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 onbuild
variant 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-ONBUILD
steps).
python:windowsservercore
This image is based on Windows Server Core (microsoft/windowsservercore
). As such, it only works in places which that image does, such as Windows 10 Professional/Enterprise (Anniversary Edition) or Windows Server 2016.
For information about how to get Docker running on Windows, please see the relevant "Quick Start" guide provided by Microsoft:
docker pull aarch64/python