PrintIf you worked or read through the exercises we worked through for packaging our application in the optional parts of this section, you might have gotten the impression that pip is easier to use than conda, and, since they both facilitate software packaging and distribution, why bother packaging your applications with conda? Here are a number of reasons:
- Conda has a built-in virtual environment functionality
- Conda further aids in package installs as it not only checks for dependencies but installs any dependent packages
- Conda is closely bound with Anaconda and Anaconda Cloud, which is set up to use different channels, providing a finer-grained package organization. For example, if you are interested in packages ESRI has published, you can go to the company’s channel - https://anaconda.org/esri.
- While pip can only be used with Python, conda can be used with other languages as well – so if you decided to develop something with R, conda can work with it too.
If you are interested in a more detailed comparison of the two tools, a great article to reference is Conda Myths and Misconceptions.