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@MaxGamill-Sheffield : It looks like the key around this is the mapping() function where the available_steps are ordered into available_steps.
The use of functools.partial() is required so that not all arguments need explicitly provided and *args / **kwargs are used instead to pass defaults (we already leverage functools.partial() in run_topostats.run_topostats.py to handle multi-processing).
Do you have any resources and other examples that informed your Gist that might be useful?
Because of the large number of outstanding issues and current work I've marked this as Low Priorit and added it to Milestone 4.
The text was updated successfully, but these errors were encountered:
@MaxGamill-Sheffield has been looking at using functools.partial to control workflows based on
OrderedDict
dictionaries which can be derived from YAML configuration files.An example of how this can work is shown in the Gist Use the functools partial function to refactor and setup a TopoStats filters pipeline by reading in an "OrderedDict"
@MaxGamill-Sheffield : It looks like the key around this is the
mapping()
function where theavailable_steps
are ordered intoavailable_steps
.The use of
functools.partial()
is required so that not all arguments need explicitly provided and*args
/**kwargs
are used instead to pass defaults (we already leveragefunctools.partial()
inrun_topostats.run_topostats.py
to handle multi-processing).Do you have any resources and other examples that informed your Gist that might be useful?
Because of the large number of outstanding issues and current work I've marked this as Low Priorit and added it to Milestone 4.
The text was updated successfully, but these errors were encountered: