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TLJH is a great base to build 'stacks' on top of for various use cases. These 'stacks' should be built by people who are domain experts in their fields, and easily updateable with new TLJH versions. Extension points need to be very clearly defined & evolvable, so we can modify TLJH without fear of breaking everything. [pluggy](https://pluggy.readthedocs.io/) is the plugin mechanism for pytest spun out into its own library, and fits our requirements well. There is an experimental pangeo stack in progress at https://github.com/yuvipanda/tljh-pangeo for an example of how this would work
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""" | ||
Hook specifications that pluggy plugins can override | ||
""" | ||
import pluggy | ||
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hookspec = pluggy.HookspecMarker('tljh') | ||
hookimpl = pluggy.HookimplMarker('tljh') | ||
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@hookspec | ||
def tljh_extra_user_conda_packages(): | ||
""" | ||
Return list of extra conda packages to install in user environment. | ||
""" | ||
pass | ||
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@hookspec | ||
def tljh_extra_user_pip_packages(): | ||
""" | ||
Return list of extra pip packages to install in user environment. | ||
""" | ||
pass | ||
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@hookspec | ||
def tljh_extra_apt_packages(): | ||
""" | ||
Return list of extra apt packages to install in the user environment. | ||
These will be installed before additional pip or conda packages. | ||
""" | ||
pass |
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