#Anaconda vs anaconda navigator install

Pip has no built in support for environments but rather depends on other tools like virtualenv or venv to create isolated environments. This can be extremely useful when working with data science tools as different tools may contain conflicting requirements which could prevent them all being installed into a single environment.

#Anaconda vs anaconda navigator install

Conda on the other hand can install Python packages as well as the Python interpreter directly.Īnother key difference between the two tools is that conda has the ability to create isolated environments that can contain different versions of Python and/or the packages installed in them. For example, before using pip, a Python interpreter must be installed via a system package manager or by downloading and running an installer. Pip installs Python packages whereas conda installs packages which may contain software written in any language. This highlights a key difference between conda and pip. They may also contain C or C++ libraries, R packages or any other software.

Additionally conda packages are not limited to Python software. There is never a need to have compilers available to install them. The latter may require that the system have compatible compilers, and possibly libraries, installed before invoking pip to succeed.Ĭonda is a cross platform package and environment manager that installs and manages conda packages from the Anaconda repository as well as from the Anaconda Cloud. Pip installs Python software packaged as wheels or source distributions. Pip is the Python Packaging Authority’s recommended tool for installing packages from the Python Package Index, PyPI. Although some of the functionality of these two tools overlap, they were designed and should be used for different purposes.

Conda and pip are often considered as being nearly identical.