This process enabled us to create a Docker image that could run GAMS and standard Python libraries in harmony. This image could be deployed seamlessly in various environments without worrying about dependencies, offering the benefits of containerization for our GAMS application.

Preparation of Entrypoint Scripts: As our application relies on several Python libraries and a specific Python environment managed by conda, we developed a shell script (setup_conda.sh) to set up this environment within the Docker container. This script activates the 'gams' conda environment, installs GAMS Python bindings, and other required Python packages. We also created another shell script (docker_entrypoint.sh) that is responsible for initiating our Python applications.

A key reason we required setup_conda.sh was because, while building the Docker image, we weren't within the context of a shell session, and thus couldn't directly activate a conda environment. This issue could potentially cause failures when trying to install Python packages or run Python scripts that rely on the specific Python environment. By creating a separate script to manage conda setup, we were able to establish the necessary environment during runtime instead of build-time, ensuring the required Python packages and configurations were correctly set up.

Entrypoint Configuration: We configured Docker to run our setup_conda.sh script upon launching a container. This script ensures the necessary conda environment and Python packages are set up and then triggers docker_entrypoint.sh to run our Python applications.