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In my docker file, I want to install med2image python package ( https://github.com/FNNDSC/med2image ). I use the following code:

FROM ubuntu:16.04
RUN apt-get update && apt-get install -y --no-install-recommends \
    python3.5 \
    python3-pip \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN pip install nibabel pydicom matplotlib pillow
RUN pip install med2image
But I get the following error when I want to build the image:
Downloading https://files.pythonhosted.org/packages/6f/e5/948b023c7feb72adf7dfb26d90a13c838737bbf52be704f5ddd0878e3264/med2image-1.1.2.tar.gz
Complete output from command python setup.py egg_info:
Sorry, only Python 3.5+ is supported.
----------------------------------------
Command "python setup.py egg_info" failed with error code 1 in  /tmp/pip-install-FnNb_S/med2image/
The command '/bin/sh -c pip install med2image' returned a non-zero code: 1
What should I do?!
                Try adding the following to set python3 as default askubuntu.com/questions/320996/… (in particular the update-alternatives way)
– Oleg Sklyar
                May 14, 2018 at 15:33
Recommended base image
As suggested in my comment, you could write a Dockerfile that looks like:
FROM python:3
RUN pip install --no-cache-dir --upgrade pip && \
    pip install --no-cache-dir nibabel pydicom matplotlib pillow med2image
    # Note: we had to merge the two "pip install" package lists here, otherwise
    # the last "pip install" command in the OP may break dependency resolution…
CMD ["cat", "/etc/os-release"]
And the command example above could confirm at runtime (docker build --pull -t test . && docker run --rm -it test) that this image is based on the GNU/Linux distribution "Debian stable".
Generic Dockerfile template
Finally to give a comprehensive answer, note that a good practice regarding Python dependencies consists in specifying them in a declarative way in a dedicated text file (in alphabetical order, to ease review and update) so that for your example, you may want to write the following file:
requirements.txt
matplotlib
med2image
nibabel
pillow
pydicom
and use the following generic Dockerfile
FROM python:3
WORKDIR /usr/src/app
COPY requirements.txt ./
RUN pip install --no-cache-dir --upgrade pip \
  && pip install --no-cache-dir -r requirements.txt
COPY . .
CMD ["python", "./your-daemon-or-script.py"]
To be more precise, this is the approach suggested in the documentation of the Docker official image python, §. How to use this image
                When RUN python -m pip install --upgrade pip is used, then does it re-use the same layer or does it create new layer (so effectively use upgrade)?
– variable
                May 14, 2020 at 11:15
                (maybe python -m pip install --upgrade pip is unneeded, but) I confirm that the 2 commands concatenated with a && (RUN pip install --upgrade pip && pip install --no-cache-dir -r requirements.txt) do create a single layer. See also the SO question Purpose of specifying several UNIX commands in a single RUN instruction in Dockerfile
– ErikMD
                May 14, 2020 at 11:33
                @Gaetan I guess you talk about theRUN command, but can you be more specific? which exact command would you recommend?
– ErikMD
                Sep 6, 2022 at 11:27
                BTW AFAICT, pip and dependency resolution is not very robust: (independently of this Docker context) I often stumbled on a pip install command that went through successfully, unlike a subsequent pip check…
– ErikMD
                Sep 6, 2022 at 11:28
Some of the other answers/comments are suggesting to change your base image but if you want to keep your ubuntu 16.04 you can also simply specify your version of pip/python to use pip3 or pip3.5 like shown below.
FROM ubuntu:16.04
RUN apt-get update && apt-get install -y --no-install-recommends \
    python3.5 \
    python3-pip \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*
RUN pip3 install nibabel pydicom matplotlib pillow
RUN pip3 install med2image
If you have Jupyter Notebook in your docker container, you can install any python package by running a new Terminal in Jupyter by clicking the button shown here:
and running: pip install <package-name>
The package stays in the docker container even after you exit the container.
        
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