This project contains Docker files for building images with QuantLib (https://www.quantlib.org) and Miniconda (https://docs.conda.io/en/latest/miniconda.html).
My basic idea is to use these images as base images for other images. See, for instance, my approach for creating a PyTorch Docker-based environment with QuantLib in ubuntu/examples.
Furthermore, I have also included Docker files for creating new images based on development versions of QuantLib (see ubuntu/development). This is very convenient if you want to add new features to QuantLib and add them to your environment.
You can find the latest image on Docker Hub (https://hub.docker.com/repository/docker/care02/quantlib-miniconda3). Use
docker pull care02/quantlib-miniconda3
and
docker run -it care02/quantlib-miniconda3
to pull it and run it.
Once you've entered the container, you can start a Python terminal and import QuantLib. Thus,
(base) root@8b27056317c0:/# python
Python 3.7.4 (default, Aug 13 2019, 20:35:49)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import QuantLib as ql
>>> print(ql.Date.todaysDate())
December 30th, 2019
>>>
You can also use the Docker image as an "environment". For example, I use JetBrains PyCharm as my IDE and can easily configure Docker as a remote intrepreter (see https://www.jetbrains.com/help/pycharm/using-docker-as-a-remote-interpreter.html).
I have based my Docker files on work done by others: