table.bulk_fetch() with meta attributes?

Hi Guys,

is there any way to have meta-attributes populated using the table.bulk_fetch() function without passing all their attribute definitions?

Calling bulk_fetch() with a list of (string) names only populates the attribute values, but not the meta-attribute values. Hence, I create a list of table attribute definitions containing both attributes and meta-attributes. When this list is used for calling bulk_fetch(), also the named meta-attributes are populated.

Now, I'm working on a project in which I generally need all the meta-attributes of a set of attributes. Building this list by table attribute definitiones is quite inconvenient. Hence I'm wondering whether there is a more elegant solution for this use case.

Ideas, anyone? :-)

Thanks in advance,
Daniel

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Accepted answers

Andy_Grigg

Understood. I'll add the enhancement to the development backlog. We'll try to get to it (or something that satisfies the same use case) before the next release.

All comments

Andy_Grigg

If you call Table.bulk_fetch() without any attributes specified, the scripting toolkit will fetch data for all attributes, meta-attributes, and pseudoattributes. If you need all attributes and meta-attributes, then this might be a good option.

If not, we can look at an enhancement to be able to specify that all meta-attributes are included for the specified attributes in a bulk_fetch operation. This would probably be via an additional optional keyword argument on the bulk_fetch method.

Please let me know what you think about the two options above.

Daniel Manocchio

Hi Andy,
thanks for your quick reply. Yeah, I've already used bulk_fetch() that way. However, for tables with a huge number of attributes and/or a higher number of records being processed, this becomes quite imperformant - at least on our system. So an additional argument like a boolean "include_metas=True" would be really great in some use cases

Andy_Grigg

Understood. I'll add the enhancement to the development backlog. We'll try to get to it (or something that satisfies the same use case) before the next release.

Daniel Manocchio

Cool, thanks a lot!

Andy_Grigg

Just to follow up on this, the solution we've chosen for the next release is to document the one or two lines of code necessary to add all meta-attributes to the bulk_fetch request. I don't want to go too much into the reasons here, but essentially it would add a lot of complexity to both the Scripting Toolkit itself and the bulk_fetch interface to do this properly.

The documentation should be much clearer now though, and provides the code snippet required in a copy-and-paste-able form.

Daniel Manocchio

Hi Andy,
thanks for the update! I guess these "one or two lines of code" just extend the list of attribute definitions with the metas of each attribute? Anyway, I'm excited

Andy_Grigg

That's exactly it, here's the snippet:

table = db.get_table("MaterialUniverse")
attribute_names = ["Density", "Price", "Young's modulus"]
print("Fetch three attributes by name")
table.bulk_fetch(records, attributes=attribute_names)

attribute_definitions = [table.attributes[name] for name in attribute_names]
print("Fetch three attributes by AttributeDefinition")
table.bulk_fetch(records, attributes=attribute_definitions)

attr_and_meta_definitions = attribute_definitions + [meta_attr
                                                     for attr in attribute_definitions
                                                     for meta_attr in attr.meta_attributes.values()]
print("Fetch three attributes and their meta-attributes")
table.bulk_fetch(records, attributes=attr_and_meta_definitions)

attr_meta_and_pseudo_definitions = attr_and_meta_definitions + mpy.RecordProperties.all()
print("Fetch three attributes, their meta-attributes, and all pseudo-attributes")
table.bulk_fetch(records, attributes=attr_meta_and_pseudo_definitions)

Daniel Manocchio

Hi Andy,
ok then, seems like something that'll find its way as function in my personal toolbox

Thanks & bests,
Daniel