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Conda install jupyter lab11/27/2023 ![]() You can use these conda environments for different purposes, they can be program-specific (for running specific tools) or project-specific (for storing dependencies for a whole pipeline).įirst, we can check the virtual environments that have been created by typing: conda info -envsĪll the conda environments have been created on the server should be listed. Most importantly, it can also create compartmentalised computational environments to avoid messing up your computer/server when you want to test some new tools or scripts. Basically, Anaconda is a software package manager that helps us to install programs and packages. Running R and Python within Jupyter Lab remotelyĬreating conda environment for R and Pythonīefore we begin, please make sure you have conda or miniconda installed in the remote server/HPC/clusters.Creating conda environment for R and Python. ![]() As denoted in the title, there are two parts in this article: Here, I want to share some tricks when I am using Jupyter Lab on server. I believe if you end up reading this article, you must be a fan of it and want to take full use of it. This is the tool I really enjoy using for data analysis. During the learning process, I learned about Jupyter Lab and impressed by its clean and simple design. I could fully utilise the computing power from remote servers by running Python on them. Recently, I started converting from R to Python as I found out that more and more my daily data analysis could be smoothly handled by Python, especially when the data size is getting huge and requiring considerable computing power.
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