turbx 1.0.8

Extensible toolkit for analyzing turbulent flow datasets

turbx

About

turbx is a package for processing turbulent flow datasets. Primary data access classes are super()ed wrappers of h5py.File that make data & metadata access tidy and performant. Workloads requiring heavy I/O and compute are made scalable using parallelization and high-performance collective MPI-IO.

Pre-installation requirements

h5py

turbx is designed to be used with parallel-mode h5py, the python3 API for HDF5. Most basic workflows will still work transparently with the basic serial install of h5py, however data-heavy workflows will require the full API functionality. This requires:

• A parallel HDF5 installation
• h5py built with HDF5_MPI="ON"; see h5py docs

Confirm that h5py was built with MPI support:

>>> import h5py
>>> h5py.get_config().mpi
True

mpi4py

High-performance collective MPI-IO and MPI operations are handled with mpi4py. This requires:

• An MPI implementation such as OpenMPI or MPICH
• mpi4py; see mpi4py docs

Installation

TL;DR

Install binary directly from PyPI:

python3 -m pip install --upgrade turbx

---

Non-root install with --user

The --user flag can be added to install to ~/.local/lib/pythonX.Y/site-packages rather than site-packages of the python3 installation itself. This is often required for HPC environments where installing packages for the system python3 is not allowed for regular users.

Editable installs

turbx can also be installed from source in editable mode (see setuptools docs). Once the source is acquired (PyPI or GitLab), the source can be installed from the project root folder:

python3 -m pip install --upgrade -e .

Installing on systems with no outbound network access

If the restricted install environment requires devpi-server:

On a local machine with internet access:

devpi-server

On a local machine with internet access:

ssh -R <remote_port>:localhost:<local_devpi_port> [e-mail]

• <local_devpi_port> is the port on which devpi-server is running locally
• <remote_port> is an arbitrary free port on the system login node used to expose the mirror remotely
• After connecting, the PyPI mirror will be reachable on the server side at: http://localhost:<remote_port>

On the remote system:

python3 -m pip install --upgrade [--user] [--editable] --index-url http://localhost:<remote_port>/root/pypi/+simple/ <package-or-path>