Installation#

graphlow supports a default torch backend and an optional phlower_tensor backend.

Install with `uv` (recommended)#

Install with the CPU Torch backend:

uv add graphlow[cpu]

Install with a CUDA backend (example: CUDA 12.4):

uv add graphlow[cu124]

Install with the optional phlower backend (combine as needed):

uv add graphlow[cpu,phlower]
uv add graphlow[cu124,phlower]

Install with `pip`#

If your environment does not use uv, the same package layout is available through pip:

pip install graphlow[cpu]
pip install graphlow[cu124]
pip install graphlow[cpu,phlower]

Requirements#

Python 3.12 or newer
One Torch backend extra selected: cpu, cu118, or cu124
PyVista-compatible mesh input such as .vtu, .vtp, or other VTK-based files handled by PyVista

Choosing a backend#

Use backend="torch" for PyTorch-based execution (after installing one of cpu, cu118, or cu124). Use backend="phlower" when your workflow depends on phlower_tensor semantics.

The backend is chosen when creating a mesh object:

import graphlow

mesh = graphlow.read("path/to/mesh.vtu", backend="torch")

Next step#

Continue with Quickstart to load your first mesh and inspect the object model.