Turing Centre for living systems's "Coding for life science" course

This is the repository for the 3 first classes of the CENTURI "Coding for life science course".

These 3 half-days of course are split in 2 main parts:

0. Requirements for the course.

0.1 Recommended software

This course is made on a jupyter notebook running on Python 3.8 or newer.

To install Python and the required dependencies we strongly recommend to use conda, mamba or pipenv (the teachers will use conda)

0.2 Installing conda

Conda can be installed multiple ways. We do not have any recommendations about how to but one can read there for a likely exhaustive list on ways to install conda. That being said.

Note that we do not necessarily recommend installing Anaconda, we do have a slight preference towards Miniconda but that's just us.

Moreover, we advise to start jupyter notebooks from a shell/terminal/prompt to be able to better see the error messages.

0.3 Dependencies

While we tried to keep the dependencies as small as possible, few are still required:

Note that other libraries might be necessary for the courses after.

To install them one can for example run the following command lines in a terminal, assuming that conda is installed:

conda create --name CenTuri-Course

to create the environment for the course. Then:

conda activate CenTuri-Course

to activate the course environment. And finally:

conda install notebook numpy scipy matplotlib

All dependencies should now be installed!

Enjoy!

0.4 Troubleshooting for MacOs M1 chips.

The newly introduced M1 chips in the latest macbooks can create some difficulties for installation.

One way to solve the issue is to install Miniforge and to then use it as Miniconda.

0.5 Testing your configuration

If you would like to test your configuration, you can run the following python file: Configuration-test.py.

One way to run it is the following:

From a terminal in the folder that contains Configuration-test.py:

python Configuration-test.py

You should get an output similar to the following one:

You are using Python version (3.10.4). It is recent enough for this course

Numpy version (1.21.5) is installed

Scipy version (1.8.0) is installed

Matplotlib version (3.5.1) is installed

Everything's good

If your python version is too old or if you failed to install one of the libraries, you will get an error message.