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#!/bin/bash

SOURCE_PATH="${BASH_SOURCE[0]:-${(%):-%x}}"

RELATIVE_PATH="$(dirname "$SOURCE_PATH")"

ABSOLUTE_PATH="$(realpath "${RELATIVE_PATH}")"

source "${ABSOLUTE_PATH}"/config.sh

echo the name is "$ENV_NAME"

echo "Setting up the python interpreter script in the following dir: " "~/.local/share/python/interpreter/${ENV_NAME}"

mkdir -p ~/.local/share/python/interpreter/"${ENV_NAME}"

echo '

#!/bin/bash

source "'"${ABSOLUTE_PATH}"'"/activate.sh  2> /dev/null > /dev/null

python "$@"

' > ~/.local/share/python/interpreter/"${ENV_NAME}"/python

chmod a+x ~/.local/share/python/interpreter/"${ENV_NAME}"/python

The script `create_kernel.sh` will create a kernel json file in the user's home directory that can be found

by Jupyter and a helper script in the virtual environment folder.

The script `create_interpreter.sh` creates a python interpreter wrapper script in the user's home directory (`~/.local/share/python/interpreter/<venv_name>/python`).

You can set this newly created wrapper script as python interpreter in your favorite IDE for remote development and debugging. See further instructions [here](https://gitlab.jsc.fz-juelich.de/niesel1/howtos-ai/-/blob/main/RemoteDebuggingWithVSCode.ipynb).

# Intended Workflow

4. Edit `setup.sh` and `activate.sh` to add extra steps for custom modules.

5. Create the environment with `bash setup.sh`.

6. Create a kernel with `bash create_kernel.sh`.

7. Create a python interpreter wrapper with `create_interpreter.sh`.