• 2-5.0.1, 2-5.0, 2-5, 2 (2/Dockerfile)
• 2-5.0.1-onbuild, 2-5.0-onbuild, 2-5-onbuild, 2-onbuild (2/onbuild/Dockerfile)
• 2-5.0.1-slim, 2-5.0-slim, 2-5-slim, 2-slim (2/slim/Dockerfile)
• 3-2.4.0, 3-2.4, 3-2, 3, latest (3/Dockerfile)
• 3-2.4.0-onbuild, 3-2.4-onbuild, 3-2-onbuild, 3-onbuild, onbuild (3/onbuild/Dockerfile)
• 3-2.4.0-slim, 3-2.4-slim, 3-2-slim, 3-slim, slim (3/slim/Dockerfile)

For more information about this image and its history, please see the relevant manifest file (library/pypy). This image is updated via pull requests to the docker-library/official-images GitHub repo.

For detailed information about the virtual/transfer sizes and individual layers of each of the above supported tags, please see the pypy/tag-details.md file in the docker-library/docs GitHub repo.

PyPy is a Python interpreter and just-in-time compiler. PyPy focuses on speed, efficiency and compatibility with the original CPython interpreter.

PyPy started out as a Python interpreter written in the Python language itself. Current PyPy versions are translated from RPython to C code and compiled. The PyPy JIT (short for "Just In Time") compiler is capable of turning Python code into machine code at run time.

wikipedia.org/wiki/PyPy

FROM pypy:3-onbuild
CMD [ "pypy3", "./your-daemon-or-script.py" ]

or (if you need to use PyPy 2):

FROM pypy:2-onbuild
CMD [ "pypy", "./your-daemon-or-script.py" ]

These images include multiple ONBUILD triggers, which should be all you need to bootstrap most applications. The build will COPY a requirements.txt file,RUN pip install on said file, and then copy the current directory into/usr/src/app.

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 pypy:3 pypy3 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 pypy:2 pypy your-daemon-or-script.py

The pypy 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. 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 makes building derivative images easier. For most use cases, creating a Dockerfile in the base of your project directory with the line FROM pypy: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).

This image does not contain the common packages contained in the default tag and only contains the minimal packages needed to run pypy. Unless you are working in an environment where only the pypy image will be deployed and you have space constraints, we highly recommend using the default image of this repository.

View license information for software contained in this image.

This image is officially supported on Docker version 1.10.3.

Support for older versions (down to 1.6) is provided on a best-effort basis.

Please see the Docker installation documentation for details on how to upgrade your Docker daemon.

Documentation for this image is stored in the pypy/ directory of the docker-library/docs GitHub repo. Be sure to familiarize yourself with the repository's README.md file before attempting a pull request.

If you have any problems with or questions about this image, please contact us through a GitHub issue. If the issue is related to a CVE, please check for a cve-tracker issue on the official-images repository first.

You can also reach many of the official image maintainers via the #docker-library IRC channel on Freenode.

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.