install Python (only Python version 3.2 or greater is supported).

Suitable for using conda programmatically.

Output, Prompt, and Flow Control Options -json Report all output as json. p, -prefix Full path to environment location (i.e. Target Environment Specification -n, -name Name of environment. install the Chrono API with C++ source code and build it, -no-pip Do not include pip-only installed packages.This is the preferred way to have the most updated P圜hrono, but it is more complicated. conda list torch packages in environment at C. The recommended way of activating an environment is now conda activate myenv instead of source activate myenv.To enable the new syntax, you should modify your. Until we modify the P圜hrono conda package to automatically install all required dependencies of the necessary version and in the proper order, it is the user's responsibility to ensure version compatibility by following the steps above as listed.Īdvanced users that use the entire Chrono::Engine C++ API can build P圜hrono from scratch. All we need to do is select a version of CUDA if we have a supported Nvidia GPU on our system. Note that the command for activating an environment has changed in Conda version 4.4.

If installed first, the Numpy package would install MKL as its own dependency and, by default, Numpy version 1.24.0 installs MKL version 2022. As such, the P圜hrono conda packages are linked against this specific version of MKL. 7.4 and that the pythonocc-core version 7.4.1 hardcodes a requirement for MKL version 2020.

The reason for the specific dependency versions and order of installation of dependency conda packages is related to the fact that Chrono::Cascade uses the API from OpenCascade v.

Conda python version list