Installation#

PyWAsP is distributed via DTU Wind Energy’s WAsP Conda Channel and requires a license to run. It supports Python 3.12, 3.13 and 3.14.

Platform Support#

Platform

Status

Notes

Linux / WSL

Supported

Recommended platform

Windows

Supported

macOS (Apple Silicon)

Experimental

osx-arm64 packages are new; please report any problems

macOS (Intel)

Not supported

Prerequisites#

Before installing, ensure you have:

License & Credentials

You need a PyWAsP license and access credentials (username and token) from DTU Wind Energy. These are provided in your license email.

Order PyWAsP

Network Access

PyWAsP requires network access to the DTU license server for license validation. Ensure outbound HTTPS connections are allowed.

Quick Install#

For experienced users, here are the essential commands:

pixi auth login conda.windenergy.dtu.dk --username <user> --password <token>
pixi init && pixi project channel add https://conda.windenergy.dtu.dk/channel/wasp
pixi add pywasp

mamba auth login conda.windenergy.dtu.dk --username <user> --password <token>
mamba create -n pywasp -c https://conda.windenergy.dtu.dk/channel/wasp -c conda-forge pywasp
mamba activate pywasp

Replace <user> and <token> with your credentials from the license email. The auth login command stores them once; later installs and updates reuse them.

Detailed Installation#

Pixi is a modern, fast package manager for project-based dependency management.

Step 1: Install pixi

Follow the instructions at pixi.sh.

Step 2: Store your channel credentials

pixi auth login conda.windenergy.dtu.dk --username <user> --password <token>

Pixi stores the credentials and uses them for every channel on that host from now on.

Step 3: Create a project

mkdir my-pywasp-project
cd my-pywasp-project
pixi init

Step 4: Add the WAsP channel and install PyWAsP

pixi project channel add https://conda.windenergy.dtu.dk/channel/wasp
pixi add pywasp

Because the channel URL carries no credentials, pixi.toml is safe to commit and share.

Step 5: Verify installation

pixi run python -c "import pywasp; print(pywasp.__version__)"

To work interactively, use pixi shell to enter the environment.

Step 1: Install a package manager

We recommend Miniforge, which provides mamba version 2 or newer. The mamba auth command used below requires mamba 2; check with mamba --version.

Linux:

wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh
bash Miniforge3-Linux-x86_64.sh

macOS (Apple Silicon):

curl -LO https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh
bash Miniforge3-MacOSX-arm64.sh

Follow the prompts and restart your terminal.

Note

Windows users

Download and run the latest Windows installer from Miniforge releases. Use the default options, then open Miniforge Prompt from the Start menu. To use PowerShell instead, run conda init powershell and restart PowerShell.

Step 2: Store your channel credentials

mamba auth login conda.windenergy.dtu.dk --username <user> --password <token>

Mamba stores the credentials and uses them for every channel on that host from now on.

Step 3: Create environment and install PyWAsP

mamba create -n pywasp -c https://conda.windenergy.dtu.dk/channel/wasp -c conda-forge pywasp

Step 4: Activate and verify

mamba activate pywasp
python -c "import pywasp; print(pywasp.__version__)"

Post-Installation Setup#

Run these commands from an activated pywasp environment.

Configure your license

The interactive configuration sets up your license and your download preferences:

pywasp configure

Download the global mesoclimate files

The air density, baroclinicity and stability functions need the global mesoclimate: long-term mean atmospheric fields from the ERA5 and CFSR reanalyses, shipped as a few NetCDF files. Fetch them now:

pywasp mesoclimate download

Importing PyWAsP never downloads anything. If you skip this step, the files are fetched the first time a function needs them, following the download settings in your configuration: with download_prompt on, a y/n prompt when there is a terminal to ask in; otherwise, including with the settings pywasp configure suggests, an automatic download. Running pywasp mesoclimate download up front avoids that first-use pause, and is the way to prepare a container image or a machine without a terminal. pywasp mesoclimate status lists the files and pywasp mesoclimate path prints where they live. See Download options for the details and Manually downloading the mesoclimate files if you have no internet access.

Check license status

To view your license status and remaining runs:

pywasp status

See User Config for more details.

Updating PyWAsP#

pixi update

We recommend creating a new environment for major updates:

mamba create -n pywasp_new -c https://conda.windenergy.dtu.dk/channel/wasp -c conda-forge pywasp

Troubleshooting#

Import errors

ModuleNotFoundError: No module named ‘pywasp’

Ensure your environment is activated:

mamba activate pywasp  # or: pixi shell

ImportError: DLL load failed (Windows)

Try reinstalling in a fresh environment:

mamba create -n pywasp_fresh -c https://conda.windenergy.dtu.dk/channel/wasp -c conda-forge pywasp
License errors

LicenseError: No valid license found

  1. Configure PyWAsP with your license:

    pywasp configure

  2. Check remaining runs:

    pywasp status

  3. Verify network access to the license server.

LicenseError: License server connection failed

Check firewall settings and ensure outbound HTTPS is allowed.

Channel authentication errors

HTTP 401 Unauthorized when fetching from conda.windenergy.dtu.dk

The stored credentials are missing or wrong. Remove them and log in again with the username and token from your license email:

pixi auth logout conda.windenergy.dtu.dk
pixi auth login conda.windenergy.dtu.dk --username <user> --password <token>

mamba auth logout conda.windenergy.dtu.dk
mamba auth login conda.windenergy.dtu.dk --username <user> --password <token>

Use the same two commands to rotate to a new token.

auth command not found

mamba auth login requires mamba 2 or newer; check with mamba --version. The reliable upgrade is a fresh install of the latest Miniforge. Alternatively, update mamba in place from your base environment using classic conda, since mamba 1.x cannot always replace itself while running:

conda update -n base mamba
Solver error “python … does not exist (perhaps a missing channel)”

The WAsP channel only hosts PyWAsP and WindKit; everything else comes from conda-forge. A mamba install with no default channel configuration sees only the WAsP channel and cannot find Python. Add conda-forge explicitly, as in the install commands above:

mamba create -n pywasp -c https://conda.windenergy.dtu.dk/channel/wasp -c conda-forge pywasp
SSL certificate errors (corporate networks)

If you see SSL: CERTIFICATE_VERIFY_FAILED or license server trust errors, your network may use a custom Certificate Authority.

  1. Get the CA certificate (.pem file) from your IT administrator

  2. Find your PyWAsP config file:

    import pywasp
pywasp.user_config.get_config_filepath()

  3. Add to the [licensing] section:

    root_ca_filepath = /path/to/your/ca-certificate.pem

See User Config for more details. You can also run pywasp configure and set the root_ca_filepath when prompted.

Downloading the global mesoclimate files fails

The global mesoclimate files for baroclinicity, stability and air density calculations are fetched by pywasp mesoclimate download, or on first use of a function that needs them. If the download fails (e.g., firewall restrictions, no internet), PyWAsP raises MesoclimateMissingError and you can download and install the files manually.

Get the files from Zenodo and place them in the directory printed by pywasp mesoclimate path. See Manually downloading the mesoclimate files for download links and file locations.

Dependencies#

PyWAsP depends on WindKit and includes all WindKit dependencies plus additional packages for WAsP modelling.

Required dependencies

  • geopandas (1.0+) - Spatial data handling

  • lxml (5.2+) - XML processing

  • matplotlib (3.9+) - Plotting

  • netcdf4 (1.7+) - NetCDF file I/O

  • numba (0.59+) - JIT compilation for faster functions

  • numpy (2.0+) - Numerical arrays

  • pandas (2.3+) - Data structures

  • platformdirs (4.3+) - Platform directories

  • py-wake (2.6.10 - 2.6.12) - Wake modelling

  • pydantic (2.7+) - Data validation

  • pydantic-settings (2.3+) - Settings management

  • pyproj (3.7+) - Coordinate transforms

  • pyyaml (6+) - YAML parsing

  • rasterio (1.4+) - Raster I/O

  • requests - HTTP client

  • scipy (1.13+) - Scientific computing

  • shapely (2.0+) - Geometric operations

  • toml - TOML parsing

  • tqdm (4+) - Progress bars

  • windkit (2.2+) - Wind data I/O, spatial operations and plotting (brings rioxarray, h5netcdf, packaging, …)

  • xarray (2024.9+) - Labeled arrays

Need Help?#

If you encounter issues not covered here:

See also