Create Virtual Environment

3. Create Virtual Environment

The following steps create a virtual Python environment to ensure the model is run with the correct Python libraries. These steps are identical regardless of operating system.

Create a virtual Python environment.
```
 python3 -m venv .
```
Activate the virtual environment.
```
 source bin/activate
```
- If this worked successfully, you should see the directory name in parentheses before your terminal input.
Add Python libraries to the new virtual environment using the requirements file that was downloaded when the GitHub repo was cloned.
```
 python3 -m pip install -r requirements.txt
```
- You may be prompted to say Y or N. Respond Y to all prompts.
- Note: your requirements may differ on a supercomputing cluster such as UC Berkeley’s Savio cluster. A copy of the requirements.txt file that works on Savio is linked below.
To confirm that the libraries are installed properly, run the following code. If you get a help message, the installation has worked properly.
```
 python3 run_echo_air.py -h
```
- An example of the help message is shown here:

→ Next Step: Copy Data

Requirements for Savio

If you are using UC Berkeley’s Savio supercomputer, copy the following into your requirements.txt before step 3 above:

```text attrs==22.2.0 certifi==2021.10.8 click==8.0.3 click-plugins==1.1.1 cligj==0.7.2 cycler==0.11.0 DateTime==4.5 Fiona==1.8.21 fonttools==4.27.1 geopandas==0.9.0 importlib-metadata==4.8.3 kiwisolver==1.3.1 matplotlib==3.3.4 munch==2.5.0 numpy==1.19.5 packaging==21.3 pandas==1.1.5 pathlib==1.0.1 Pillow==8.4.0 pyarrow==6.0.1 pyparsing==3.0.8 pyproj==3.0.1 python-dateutil==2.8.2 pytz==2022.1 Rtree==0.9.7 scipy==1.5.4 seaborn==0.11.2 Shapely==1.8.1.post1 six==1.16.0