Python High Performance - Second Edition

Using conda environments

Most of the time, using venv is a fine choice. However, when writing high-performance code, it often happens that some high-performance libraries also require non-Python software to be installed. This typically involves additional setting up of compilers and high-performance native libraries (in C, C++, or Fortran) to which Python packages link. As venv and pip are designed to deal with Python packages only, this scenario is poorly supported by these tools.

The conda package manager was created specifically to handle such cases. Creating a virtual environment with conda can be done using the conda create command. The command takes a -n argument (-n stands for --name) that specifies an identifier for the newly created ...