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…et implemented for join queries)
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Here's an example of the metadata attributes added during a request for a TSIS (xarray) dataset: Global attributes:Variable attributes:time: tsi_1au: instrument_accuracy_1au: instrument_precision_1au: solar_standard_deviation_1au: measurement_uncertainty_1au: tsi_true_earth: instrument_accuracy_true_earth: instrument_precision_true_earth: solar_standard_deviation_true_earth: measurement_uncertainty_true_earth: avg_measurement_date: std_dev_measurement_date: provisional_flag: index: |
dlindhol
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I fought with PyCharm a while and had to tweak some imports. (Any advice would be appreciated.) Otherwise, it looks good to me!
Could you also update the README with the xarray option? Mention that it will include metadata.
| base (str): The base URL of the LaTiS instance | ||
| dataset (str): A dataset identifier string | ||
| query (str): The query parameters string used to filter dataset results | ||
| auth (HTTPBasicAuth): An authentication object used to authenticate with the LaTiS server |
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You might add "optional". Also, API keys are supported in addition to basic auth.
| model_config = pydantic.ConfigDict(extra="ignore") | ||
| # Required metadata items | ||
| id: str | ||
| # Optional metadata items |
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Did we discuss including optional title and description in the dataset metadata? Those would be handy.
Sorry for any scope creep.
This PR introduces metadata fetching for xarray dataset global and variable metadata schemas which are applied to xarray datasets before returning them from the read_data function.
This metadata functionality has not yet been implemented for join requests.
Some minor imports cleanup and docstring additions were also made in this PR.