Config checker
Taipy provides a checking mechanism to validate if your configuration is correct.
You can trigger the check by calling:
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The Config.check()
method returns a collector of issues. Each issue corresponds to an inconsistency in
the configuration attached to an issue level (INFO
, WARNING
, ERROR
). Config.check()
raises an
exception if at least one issue collected has the ERROR
level.
Here is the list of the possible issues that could be returned by the checker:
- An
ERROR
issue is created if theclean_entities_enabled
property is populated in theGlobalAppConfig
with a non-Boolean value. - An
ERROR
issue is created if thestorage_type
and thescope
properties of anyDataNodeConfig
have not been provided with a correct value. - Depending on the
storage_type
value of aDataNodeConfig
, anERROR
issue is created if a specific required property is missing. - An
ERROR
issue is created if one of theinputs
andoutputs
parameters of aTaskConfig
does not correspond to aDataNodeConfig
. - A
WARNING
issue is created if aTaskConfig
has no input and no output. - An
ERROR
issue is created if thefunction
parameter of aTaskConfig
is not a callable function. - An
ERROR
issue is created if one of thetask
parameters of aPipelineConfig
does not correspond to aTaskConfig
. - A
WARNING
issue is created if aPipelineConfig
has no task configuration defined. - An
ERROR
issue is created if one of thepipeline
parameters of aScenarioConfig
does not correspond to aPipelineConfig
. - A
WARNING
issue is created if aScenarioConfig
has no pipeline configuration defined. - An
ERROR
issue is created if thefrequency
parameter of aScenarioConfig
has an incorrectFrequency
value. - An
INFO
issue is created if aScenarioConfig
has nocomparator
defined. - If the
JobConfig
has been configured with multiple workers, anERROR
issue is created if an "in_memory"DataNodeConfig
is defined.