Data processing Programming III course for the master Data Science for Life Science. See also Time Series and Streaming Data.
This repo has the following directories:
assessment: In this folder you find all the Notebooks that you need to work on in preperation for the lessons(formative) and the final assignment (summative).demos: Lots of notebooks that we are using during the module, or not. Feel free to open one that seems to offer what you are interested in.exercises: Notebooks with some extra exercises (hence the name).scripts: Demo scripts such client server communication scripts. All the on-the-fly-scripts that we will work on during the lectures will also be put into this directory.
Login the linux grid. Open the terminal. Choose a path and a name for your virtual environment, for instance .venv/dsls. Have a look at the file requirements.txt to see what we are using.
#create a new environment
python3 -m venv {path/to/new/virtual/environment} {name}
#activate the virtualenv
source {path/to/new/virtual/environment}{name}/bin/activate
#install the necessary requirements
python -m pip install -r requirements.txt
#create jupyter notebook kernel for venv
python -m ipykernel install --user --name={name}
Make sure that you use the created kernel in your jupyter notebook or visual studio code (you should be able to do that by now).
contact information: f.feenstra@pl.hanze.nl