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We can see new links to our external directories: | |
And now we can get to them: |
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Getting information about packages?
What’s Installed - How to find out:
In our notebook, we can see which modules are available by opening a new cell with the + button. In our cell box, set as “code” use the python Hitting tab after |
New Cell in our Notebook
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Since we appear to have a large number of packages available in this environment, we’ll import one we expect to be there.
In our bottom-most cell, add to the import command by typing an import for a common package used in mathematic and multi dimensional matrix computations - numpy.
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What’s Installed - Can we get a list in Python?
Yes. By running |
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What’s installed and how to use it: Python - help()
Generally,
help ('modules <module_name>')
will give us information on how to use the specific python library we’re importing as long as that library is installed.Similar in functionality to the
--help
andman
commands for shell.
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What’s Installed - Can we get a list in R?
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What’s Installed - Query a specific package in R?
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What’s Installed and how to use it: In R - help()
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We’ve confirmed the package we need is unavailable:
Our output results in an error: |
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Option 1: Load a different kernel
Depending on the HPC’s native environment, you may have other kernels available. | |
Or not ---> MedBow currently has a minimal number of global kernels (purposefully). |
To load a different kernel, we go to the Kernel option in our drop down menu then navigate to “Change kernel”.
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If this were an option, we’d see it in our dropdown list of kernels and could select a different one:
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No available kernels have all the software I need - Now what?
Partially covered in python and conda materials, but short answer:
Best practice - Do NOT install the software directly from your jupyter kernel
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Doing so can and frequently does eventually result in:
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Next Steps
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