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(2022-09-20) Lab Notebook: PyMesh installation with Conda


This is as a Lab Notebook which describes how to solve a specific problem at a specific time. Please keep this in mind as you read and use the content. Please pay close attention to the date, version information and other details.

Lab Notebook --- Installing PyMesh on HPCC using Conda (2022-09-20)

PyMesh is a code base developed by Qingnan Zhou for his PhD research at New York University. It is a rapid prototyping platform focused on geometry processing. PyMesh is written with both C++ and Python, where computational intensive functionalities are realized in C++, and Python is used for creating minimalistic and easy to use interfaces. Documentation for AntiSMASH can be found at, but you will need to follow the instruction below to install AntiSMASH in your home directory on HPCC.

If you have not installed Anaconda in you home directory, see

Installing Pymesh

# Clear modules and load Anaconda
module purge
module load Conda/3

# You need to create a conda environment with an older version of python
conda create -n pymesh python=3.6

# Activate the environment
conda activate pymesh

# Use the the 0.2.1 version because the 0.3 version on conda forge required
# GLIBC 2.18 which is incompatible with the version (2.17) on HPCC (Centos7 thing I think)
conda install pymesh2=0.2.1

# Once done, test by trying to do 'import pymesh' in python

Why not Pymesh 0.30

The version of Pymesh 0.3 on conda forge produces the following error when I try to import pymesh

ImportError: /lib64/ version `GLIBC_2.18' not found (required by /mnt/home/panchyni/anaconda3/envs/pymesh/lib/python3.6/site-packages/pymesh/lib/

As far as I understand it, the GLIBC version is tied to the OS, so its not a s simple as importing another library. If for some reason version 0.3 is required, there are a couple of options, though they may be time consuming:

  • Build PyMesh from source using the files from the github. There are a number of dependencies, so you might want to see if you can use a conda environment to install the dependencies
  • Create a conda environment within an Singularity container of Centos8