fiftyone.core.aggregations.ListSchema

Extracts the value type(s) in a specified list field across all samples in a collection.

Examples:

from datetime import datetime
import fiftyone as fo

dataset = fo.Dataset()

sample1 = fo.Sample(
    filepath="image1.png",
    ground_truth=fo.Classification(
        label="cat",
        info=[
            fo.DynamicEmbeddedDocument(
                task="initial_annotation",
                author="Alice",
                timestamp=datetime(1970, 1, 1),
                notes=["foo", "bar"],
            ),
            fo.DynamicEmbeddedDocument(
                task="editing_pass",
                author="Bob",
                timestamp=datetime.utcnow(),
            ),
        ],
    ),
)

sample2 = fo.Sample(
    filepath="image2.png",
    ground_truth=fo.Classification(
        label="dog",
        info=[
            fo.DynamicEmbeddedDocument(
                task="initial_annotation",
                author="Bob",
                timestamp=datetime(2018, 10, 18),
                notes=["spam", "eggs"],
            ),
        ],
    ),
)

dataset.add_samples([sample1, sample2])

# Determine that `ground_truth.info` contains embedded documents
aggregation = fo.ListSchema("ground_truth.info")
print(dataset.aggregate(aggregation))
# fo.EmbeddedDocumentField

# Determine the fields of the embedded documents in the list
aggregation = fo.Schema("ground_truth.info[]")
print(dataset.aggregate(aggregation))
# {'task': StringField, ..., 'notes': ListField}

# Determine the type of the values in the nested `notes` list field
# Since `ground_truth.info` is not yet declared on the dataset's
# schema, we must manually include `[]` to unwind the info lists
aggregation = fo.ListSchema("ground_truth.info[].notes")
print(dataset.aggregate(aggregation))
# fo.StringField

# Declare the `ground_truth.info` field
dataset.add_sample_field(
    "ground_truth.info",
    fo.ListField,
    subfield=fo.EmbeddedDocumentField,
    embedded_doc_type=fo.DynamicEmbeddedDocument,
)

# Now we can inspect the nested `notes` field without unwinding
aggregation = fo.ListSchema("ground_truth.info.notes")
print(dataset.aggregate(aggregation))
# fo.StringField