Add Support for Batch Publishing Non-Scalar Measurement Values

[hunter-ni]

What does this Pull Request accomplish?

This set of changes updates the MDS Python API to support the batch publishing of non-scalar measurement values (e.g., AnalogWaveform). This is in addition to the pre-existing support for batch publishing scalar measurement values.

This reflects the addition of this support to the service API itself in ni/ni-apis#161.

Implementation

• Updates _grpc_conversion.py to handle an Iterable of the various supported non-scalar data types being supplied as the values object being passed into publish_measurement_batch.
  • This use of Iterable is consistent with our existing support of an Iterable of float, int, str, and bool being supplied for batch publishing scalar values.

Why should this Pull Request be merged?

This PR should be submitted to maintain feature support/consistency between the MDS Python API and the DataStoreService itself.

What testing has been done?

• Added new unit tests related to populating the PublishMeasurementBatchRequest appropriately from batched, non-scalar values supplied to publish_measurement_batch
  • Includes error cases for heterogeneous Iterables and unsupported types being supplied
• Added acceptance tests verifying that non-scalar measurement data can successfully be batch published and then read back from MDS
• Added a notebook example describing and exercising both the scalar and non-scalar data cases of publish_measurement_batch (in addition to publish_condition_batch).

[Copilot]

Pull request overview

This pull request extends the NI DataStore Python client’s batch publishing support to include non-scalar measurement value types (e.g., AnalogWaveform, Vector, XYData) in addition to the existing scalar batch support, aligning the client with updated service API capabilities.

Changes:

• Updated gRPC request population logic to accept Iterables of supported non-scalar measurement types and map them into the appropriate PublishMeasurementBatchRequest fields.
• Added extensive unit and acceptance tests validating successful conversions/publishing and error handling for heterogeneous/unsupported iterables.
• Added a notebook example demonstrating batch publishing for both scalar and non-scalar measurements (and conditions).

Reviewed changes

Copilot reviewed 6 out of 7 changed files in this pull request and generated no comments.

Show a summary per file

File	Description
tests/unit/data/test_publish_measurement.py	Updates an assertion to match the new unsupported-iterable error message format.
tests/unit/data/test_grpc_conversion.py	Adds unit tests covering batch conversion for multiple non-scalar types and error cases.
tests/acceptance/test_publish_measurement_batch_and_read_data.py	Adds acceptance tests for batch publishing/read-back of non-scalar values (e.g., AnalogWaveform, per-iteration Vector).
src/ni/datastore/data/_grpc_conversion.py	Implements iterable-of-non-scalar handling for publish_measurement_batch request construction.
pyproject.toml	Bumps ni-measurements-data-v1-client minimum prerelease version to pick up new API support.
poetry.lock	Updates locked dependency versions consistent with the updated client/proto requirements.
examples/notebooks/publish/publish_batch.ipynb	New notebook documenting and exercising scalar + non-scalar batch publishing flows.

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[papowerNI]

Note: It looks like the documentation on publish_measurement_batch might be out of date, it seems to still refer to only scalars and always has a single measurement id on output.

datastore-python/src/ni/datastore/data/_data_store_client.py

Line 306 in 96e2cea

values: The values of the (scalar) measurement being published