Mxnet_p36 /home/ec2-user/anaconda3/envs/mxnet_p36 Mxnet_p27 /home/ec2-user/anaconda3/envs/mxnet_p27 JupyterSystemEnv * /home/ec2-user/anaconda3/envs/JupyterSystemEnvĪmazonei_mxnet_p27 /home/ec2-user/anaconda3/envs/amazonei_mxnet_p27Īmazonei_mxnet_p36 /home/ec2-user/anaconda3/envs/amazonei_mxnet_p36Īmazonei_tensorflow_p27 /home/ec2-user/anaconda3/envs/amazonei_tensorflow_p27Īmazonei_tensorflow_p36 /home/ec2-user/anaconda3/envs/amazonei_tensorflow_p36Ĭhainer_p27 /home/ec2-user/anaconda3/envs/chainer_p27Ĭhainer_p36 /home/ec2-user/anaconda3/envs/chainer_p36 To see the pre-built Conda environment, run either of the following commands in the notebook instance terminal: $ conda env list $ conda info -envs For more information, see Understanding Conda and Pip in the Conda documentation. Conda verifies that all required components are satisfied before installing the packages. When this happens, use Conda to install packages instead of pip. Sometimes, pip might fail to install some of the package's dependencies. Otherwise, the command hangs and waits for user confirmation. To install packages in a notebook cell using Conda, you must explicitly pass -y. Note: When you run conda install in a notebook cell, you can't enter an interactive response. This forces the command to run as a shell command from the notebook and assures that the package is installed in the current Jupyter kernel. To run this command in a notebook cell, add an exclamation point ("!") at the beginning of the command. To install the Python packages in the correct Conda environment, first activate the environment before running pip install or conda install from the terminal.įor example: sh-4.2$ source activate python3 This is because you're not installing the Python packages in the correct Conda environment. If you use pip or Conda to install Python libraries on the terminal without specifying the correct Conda environment, you get a ModuleNotFoundError when importing that Python package to your running notebook. To read more about installing and managing environments with Anaconda, please see the conda documentation.Resolution Install Python packages to a specific Conda environment Once you're done installing and using your Anaconda packages, you may return to the default environment by typing: Likewise, the directory system for any libraries installed with conda can be found at: For example, if you would like to install the "scipy" package, type the following:Īfter the package has been installed, any associated executable files will be placed within a bin folder in your environment directory (this is automatically added to your path): Once you've created a custom environment, you need to "activate" it with the following:īy doing this, the environmental variables associated with your custom Anaconda environment (including the path to executable files) will become active.įrom here, you may install packages using the "conda install" command. If you wish to save in another directory:Ĭonda create -prefix /path-to-env/env-name Note: You can't combine the -prefix and -name flags, you may only choose one. In order to ensure that there is no conflict between the software you'd like to install and existing programs (e.g., dependency version conflicts), it's best to create a custom Anaconda environment. First load the appropriate module (either Anaconda2 or Anaconda3, depending on which version of Python is desired): The easiest way to install many software packages is by using the Anaconda package manager. Alternatively, you may install the program locally in your home or project directory. This may be preferable if the program is widely used and likely to be of interest to multiple users.Ģ. You are welcome to submit a ticket and ask the HPC support staff to install the software package. When HPC users have need of software that is not currently installed on SeaWulf, there are two basic approaches that can be taken to get the programs installed:ġ.
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