Replace env_name with any name you want for the environment, and replace pkg1 pkg2 pg3 with the name(s) of the package(s) you want to install. Create a conda environment using one of the following commands.To load an Anaconda module, on the command line, enter:.
#INSTALL PACKAGE IN ANACONDA PROMPT INSTALL#
Within this environment, you can install and delete as many conda packages as you like without making any changes to the system-wide Anaconda module.Ĭonda will attempt to resolve any conflicting dependencies between software packages and install all dependencies in the environment. Create a conda environment and install packagesįollow the steps below to create a conda environment. Package managers are especially helpful in high-performance computer settings, because they allow users to install packages and their dependencies locally with just one command.įollowing are instructions for creating and activating a conda environment, and installing packages in your home directory space on any of the research supercomputers at Indiana University. Unlike pip, conda is also an environment manager similar to virtualenv. Activate a previously created conda environmentĬonda is an open source package manager similar to pip that makes installing packages and their dependencies easier.Create a conda environment and install packages.In few cases where a package is not in conda, then use pip.
#INSTALL PACKAGE IN ANACONDA PROMPT UPGRADE#
It will know which packages to upgrade or downgrade to avoid conflicts. Always try finding packages in conda(plus it’s channels) before using pip, becsusr conda will check for packages compatabilities before installation. While in your environment, you can use both conda and pip to install packages to that environment. To get out of your environment, conda deactivate The best thing about this is that this is separate from your other Python and packages. While in this environment(scrap), you have access to Python 3.6 and scrapy. We then activate it and install scrapy fron a conda channel forge. Here we create environment called scrap with python version 3.6.
A workflow would be as follow(Assuming you have install Anaconda, and its available on your system path): conda create -n scrap python=3.6 With Anaconda, you can use any Python version, and libraries you need for a specific task. You get to keep your environment(program dependency) organized when using Anaconda. Anaconda is loved because it simplify package management and deployment in Python(and R, Ruby, Lua, Scala, Java, JavaScript, C/ C++, FORTRAN)