Commit 29b8163a authored by jonas.hoersch's avatar jonas.hoersch

Update setup and requirements (closes #3)

parent 1f208faa
# Download
You can download the tutorials with `git` with the following command (it should be public):
You can download the tutorials with `git` with the following command (it should
be public):
```
git clone https://git.scc.kit.edu/sp2668/esm_tutorials.git
```
Alternatively, you can download the tutorials as compressed folder.
Alternatively, you can download the tutorials as compressed zip-file from
https://git.scc.kit.edu/sp2668/esm_tutorials/-/archive/master/esm_tutorials-master.zip
# Installation Guide
Install `miniconda` (or Anaconda). For instructions for your operating system see
https://conda.io/docs/user-guide/install/index.html
**Make sure to follow these steps BEFORE the first tutorial (The wireless WILL
be spotty with so many heavy users and we'll loose precious tutorial time)!**
Now create a new environment from the provided `requirements.yml` file. For detailed instructions see
Install `miniconda` (or Anaconda). For instructions for your operating system
see https://conda.io/docs/user-guide/install/index.html
Now create a new environment from the provided `requirements.yml` file. For
detailed instructions see
https://conda.io/docs/user-guide/tasks/manage-environments.html#creating-an-environment-from-an-environment-yml-file
Open a terminal. Creating the environment requires the following set of commands:
Open a terminal. Creating the environment requires the following set of
commands. They take time and have to download several packages!
Windows:
```
conda env create -f requirements.yml
activate esm-tutorials
conda list
```
macOS and Linux:
```
conda env create -f requirements.yml
source activate esm-tutorials
conda list
```
Open a jupyter notebook with the following command in the tutorial folder (where your notebooks are):
......
......@@ -7,8 +7,15 @@ dependencies:
- matplotlib
- nb_conda
- numpy
- scipy
- networkx
- pandas
- python
- scikit-learn
- pyomo
- xarray
- netcdf4
- bottleneck
- glpk
- pip:
- pypsa
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