Anaconda is a popular, free, and open-source distribution of Python and R packages for scientific computing and data analysis. Many users prefer using Anaconda on the personal computer instead of manually installing individual packages not only for convenience but also for taking advantage of Anaconda’s ability to resolve version conflicts and package dependencies. On the Hoffman2 cluster, however, the environment is structurally different from that of a personal computer; there are other best practices to be considered. For example, while one can take advantage of the system-wide Anaconda base, it is sometimes preferable to compose one’s own environment(s) to have particular packages. Another common situation is to install a community Python/R code that is outside of Anaconda’s base distribution but has to work with the existing installation. Thus, in this workshop, we will address how to use conda, the package manager in Anaconda, to deal with virtual environments and the file structure of package installation. The criteria, availability, the pros and cons of using the local and system-wide installations will be also discussed.

Register in advance: Click here to register using the Zoom meeting link

If you have any further questions regarding the workshop, please contact instructor Jerry Huang.