import pandas as pd

collection.ingest(pd.DataFrame({
    "time": [
      "2023-05-01T12:00:00Z",
      "2023-05-02T12:00:00Z",
    ],
    "value": [1, 2],
    "sensor": ["A", "B"],
}))

def Collection.ingest(
    data: IngestionData,
    allow_existing: bool = True
) -> list[UUID]

Ingest data into a collection.

You need to have write permission on the collection to be able to delete datapoints.

​
Parameters

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data
IngestionData

The data to ingest.

Supported IngestionData data types are:

  • A pandas.DataFrame, mapping the column names to dataset fields.
  • An xarray.Dataset, mapping variables and coordinates to dataset fields.
  • Iterable, dict or nd-array: Ingest any object that can be converted to a pandas.DataFrame using it’s constructor, equivalent to ingest(pd.DataFrame(data)).
​
allow_existing
bool

Datapoint fields are used to generate a deterministic unique UUID for each datapoint in a collection. Duplicate datapoints result in the same ID being generated. If allow_existing is True, ingest will skip those datapoints, since they already exist. If allow_existing is False, ingest will raise an error if any of the generated datapoint IDs already exist. Defaults to True.

​
Returns

List of datapoint ids that were ingested, including the IDs of already existing datapoints in case of duplicates and allow_existing=True.

​
Errors

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ArgumentError
found existing datapoints with same id

If allow_existing is False and any of the datapoints attempting to ingest already exist.

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