In order to use the OpenEye Python toolkits, a compatible version of Python must be installed. Instructions on installing Python are given in this document.

Python3 is binary compatible between minor versions on Linux and macOS, so the “python3” distribution works in for Python 3.6 and higher. On Windows, 3.7 and 3.8 are supported. Below are the different Python versions supported for various platforms.

Linux installation also requires the zlib and libcairo libraries be available. These are usually available on Desktop Linux installations by default, but may not be available on Linux server installations.


The following platforms and Python versions are supported with one single build Linux package:

RHEL7, RHEL8, Ubuntu 18.04, Ubuntu 20.04

  • 3.[6-8]


The following platforms and Python versions are supported with one single build macOS package:

  • macOS 10.13 - 10.15
    • 3.[6-8]


On Windows, packages are built for specific Python versions.

  • 3.7 (x64)
  • 3.8 (x64)


VSRUNTIME140.dll and MSVCP140.dll are dependencies of OpenEye Windows dlls. The recommended Anaconda Python provides these.

GPU Prerequisites

The following is required in order to use GPU-accelerated OpenEye toolkits and applications:

Supported Platforms

CUDA-enabled OpenEye software is only available on supported Linux platforms. For supported Linux platforms see above and/or the Platform Support Page

Supported GPUs

An NVIDIA Tesla, Quadro, or GeForce GPU with a compute capability of 3.5 or higher is required on your system. For a comprehensive table of which GPUs fall into which compute capability category please refer to the CUDA wikipedia page.

NVIDIA Drivers

  • Minimum NVIDIA Driver version: 450.x.
  • CUDA is not required to be installed.

We recommend driver 450.80.02 and we strongly advise manually downloading and installing the appropriate NVidia driver for your system as opposed to using a package manager.

To install, root privilege is required. Follow these steps:

  1. Download the driver to the machine you are installing it on.

  2. chmod +x the driver package to make it executable.

  3. Ensure you have disabled X-server by killing any running sessions. Reboot may be required if X-server is still running after this step.


    Disabling X-server requires different processes to be killed depending on your Linux distribution. See Nvidia installation guide for more details.


    The NVidia kernel module can often conflict with the open source Nouveau display drivers depending on your specific Linux distribution. The NVidia documentation is a much more complete and up-to-date source for information on how to work around this issue. See Disabling Nouveau on the NVIDIA website.

  4. Install the driver by sudo ./ and follow the step-by-step installation instructions.

For more details on driver installations see the CUDA Installation Guide


The output of the nvidia-smi command is extremely useful when debugging GPU issues. Please include the output from nvidia-smi in any request to

Performance Tuning

To get the most performance out of an NVIDIA Graphics card, use the persistence daemon to switch persistence mode on across all cards on the system (root privilege required):

sudo nvidia-persistenced --user foo

This will automatically enable persistence mode after reboot.

For full instructions on persistence daemon see the Persistence daemon section of the NVIDIA docs.