Some tools to follow the introduction course to Python
Project description
Turing Centre for living systems's "Introduction to biological data analysis" course
The website version here
This is the repository for the introduction of the CENTURI "Introduction to biological data analysis" course.
This first day is 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.
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.
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