- #Conda install package list how to#
- #Conda install package list install#
- #Conda install package list update#
The difference between the two pre-set installation locations is:
#Conda install package list install#
The purpose of the install scripts' options is to store data according to its importance and prevent using up your quota. When the script ends it prints out information about the installation, commands to initialize conda immediately or every time you log in and a command to completely remove your conda installation.Ĭhoose your preferred method of initializing conda as recommended by the script and note down the deletion command. Then run the script again with the option of your choosing to start the installation. install_conda.shĪnd run the script to show options for choosing storage locations by issuing. Save this script as install_conda.sh, make it executable with chmod +x. #!/bin/bash SPACE_MINIMUM_REQUIRED= '5' if [[ -z " $ /.conda " To provide conda, the minimal anaconda distribution miniconda can be installed and configured for the D-ITET infrastructure with the following bash script: The infrastructure is driven by the conda packet manager which accesses the Anaconda repositories to install software.Īfter familiarizing yourself with conda, read this collection of hints and explanations about available platforms on which to use your infrastructure and particularities of the software packages involved. Some examples for software installation in the field of data sciences are provided.
#Conda install package list how to#
This page shows how to set up a personal python development infrastructure, how to use it, how to maintain it and make backups of your project environments. Setting up a personal python development infrastructure
![conda install package list conda install package list](https://i.ytimg.com/vi/Z_Kxg-EYvxM/maxresdefault.jpg)
#Conda install package list update#
![conda install package list conda install package list](https://angus.readthedocs.io/en/2019/_static/conda5.png)
Create an environment called "my_env" with packages "package1" and "package2" installed.Creating an environment with the GPU version of tensorflow and CUDA toolkit 10.Creating an environment with the GPU version of pytorch and CUDA toolkit 10.Creating an environment with a specific python version.Setting up a personal python development infrastructure.