This accepts a set of packages to install on all workers. You can also optionally ask for the worker to restart itself after performing this installation.
This will increase the time it takes to start up each worker. If possible, we recommend including the libraries in the worker environment or image. This is primarily intended for experimentation and debugging.
Additional issues may arise if multiple workers share the same file system. Each worker might try to install the packages simultaneously.
A list of strings to place after "pip install" command
Additional options to pass to pip.
Whether or not to restart the worker after pip installing Only functions if the worker has an attached nanny process
A Worker Plugin to pip install a set of packages
>>> from dask.distributed import PipInstallThis example is valid syntax, but we were not able to check execution
... plugin = PipInstall(packages=["scikit-learn"], pip_options=["--upgrade"])
>>> client.register_worker_plugin(plugin)See :
The following pages refer to to this document either explicitly or contain code examples using this.
distributed.diagnostics.plugin.PipInstall
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them