WSL 2 Ubuntu installation environment setup and daily workflow
Purpose. This guide prepares a Windows computer for the flood forecasting workshop. It installs WSL 2 and Ubuntu, installs Micromamba inside Ubuntu, creates the cpc_id_env Python environment, installs TensorFlow, and verifies the required AI libraries.
System requirement. Windows 11 or Windows 10 version 2004 or later. An internet connection and administrator access are required.
Open the Start menu, search for PowerShell, right-click Windows PowerShell, and select Run as administrator.
Run in Administrator PowerShell
wsl --installRestart the computer when Windows requests it. The standard installation enables WSL and installs Ubuntu.
If Ubuntu was not installed
Return to Administrator PowerShell and run these commands to view and install available distributions.
Run in Administrator PowerShell
wsl --list --online
wsl --install -d UbuntuOpen the Start menu, search for Ubuntu, and launch it. On the first launch, wait for setup to finish, then create a Linux username and password.
Password note. Nothing appears on the screen while typing the Linux password. This is normal. Type it carefully and press Enter.
Run the following commands inside the Ubuntu window. Enter the Linux password if prompted.
Run in Ubuntu
sudo apt update
sudo apt install -y curl bzip2Copy the complete command into Ubuntu and press Enter.
Run in Ubuntu
curl -L https://micro.mamba.pm/install.sh | bashInstallation responses
| Prompt | Response |
|---|---|
| Micromamba binary folder [~/.local/bin] | Press Enter |
| Init shell bash [Y/n] | Type Y, then press Enter |
| Configure conda forge [Y/n] | Type Y, then press Enter |
| Prefix location [~/micromamba] | Press Enter - do not type Y |
Load the updated Bash configuration and confirm that Micromamba returns a version number.
Run in Ubuntu
source ~/.bashrc
micromamba --versionCreate the Python 3.10 environment and install the required scientific, geospatial, plotting, and machine learning packages.
Run in Ubuntu
micromamba create -n cpc_id_env -c conda-forge python=3.10 numpy pandas geopandas shapely jupyter scipy matplotlib scikit-learn netcdf4 h5py cartopy xarray seaborn pip -yActivate the environment. The Ubuntu prompt should begin with (cpc_id_env).
Run in Ubuntu
micromamba activate cpc_id_envKeep cpc_id_env activated, then upgrade pip and install TensorFlow.
Run in Ubuntu
python -m pip install --upgrade pip
python -m pip install tensorflowRun this single command after TensorFlow finishes installing.
Run in Ubuntu
python -c "import numpy as np; import pandas as pd; from sklearn.preprocessing import MinMaxScaler; from keras.models import Sequential; from keras.layers import LSTM, Dense; print('Everything works!')"Successful result. If Ubuntu prints Everything works!, the AI environment is ready.
Use these steps each time you return to the flood forecasting project.
1 Open Ubuntu
Open Ubuntu from the Windows Start menu.
2 Activate the environment
Run in Ubuntu
micromamba activate cpc_id_env3 Go to the project folder
Run in Ubuntu
cd /mnt/c/Users/ehsan/Downloads/flood/flood4 Check the files
Run in Ubuntu
ls5 Run the model
Run in Ubuntu
python flood_forecast_realtime_multiple.pyCheck WSL status in PowerShell
wsl --statusCheck installed Linux distributions in PowerShell
wsl --list --verboseList Micromamba environments in Ubuntu
micromamba env listExit the active environment in Ubuntu
micromamba deactivate