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# Styling
from IPython.core.display import HTML
def css_styling():
sheet = './css/custom.css'
styles = open(sheet, "r").read()
return HTML(styles)
css_styling()
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Choose one option of the following that applies to you, then follow the Starting the Material Instructions:
The recommended way to obtain the prerequisites for this course is by installing the latest Python 3 Anaconda python distribution (currently 3.5). This will download all the necessary material to open the material as a jupyter notebook and run examples and exercises.
conda Python UsersCurrent Python 2.7 users with access to the conda package manager who do not wish to interfere with their installation can create a minimal working 'conda environment' by entering the following command into a terminal/command prompt:
conda create -n py3_oop python=3.5 jupyter numpy matplotlib
And switching to this environment with
source activate py3_oop # Linux/Mac
activate py3_oop # Windows
(closing the terminal or using source deactivate will return to the default python version)
conda UsersAdvanced Python users not using conda should install the aforementioned packages with their preferred package manager. See Jupyter installation instructions for more detail.
A test script is provided to ensure you have installed the requirements correctly. Either save This file and run python installation_test_2.py from a terminal, or if you have curl (might not work with Windows), simply enter the following one-liner:
curl -L https://raw.githubusercontent.com/p-chambers/Python_OOP_Workshop/master/installation_test_2.py | python
The slides and exercises should be followed as live Jupyter notebooks so that you can run and develop your own code. The instructions and terminal commands of how to do this are provided on the Github repository, but for convenience this is repeated here:
Clone the repository with
git clone https://github.com/p-chambers/Python_OOP_Workshop.git
OR if you don't have/want git, download as a .zip (you'll need to extract the files), then navigate to the directory with
cd Python_OOP_Workshop
and view the 'index.ipynb' as a jupyter notebook with
jupyter notebook index.ipynb
You should also remove output by clicking (in the notebook)
Kernel > Restart > Clear all outputs and restart
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