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

You can get bash from your container with this command:

docker-compose exec freqtrade bash

and then:

pip install finta

OR run only one command:

docker-compose exec freqtrade pip install finta

If the above solutions didn't work, You can run docker ps command and get container id of your container. Then

docker exec -it CONTAINER_ID bash
pip install finta

To answer the first question Where is the conda environment? we just need to execute in console $ docker my_containers_name ls /opt/conda.

Second question has two options:

• We can open the containers console by executing the command

  $ docker exec -it my_containers_name /bin/bash

  and install the package like a normal conda package

  conda install --channel https://conda.anaconda.org/conda-forge folium

• We can modify the Dockerfile of the Docker image or create a new one extending the previous one. To create a new Dockerfile and add the lines

  FROM jupyter/minimal-notebook
  USER jovyan
  RUN conda install --quiet --yes --channel https://conda.anaconda.org/conda-forge folium && conda clean -tipsy
  

  And build our new image. If we want to modify the original Dockerfile we must skip the first line.

I create my own Dockerfile by forking the original project.

Thanks warmoverflow and ShanShan for your comments