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Python | Weaviate Documentation

Changes in v4.4b9​ weaviate.connect_to_x methods​

The timeout argument in now a part of the additional_config argument. It takes the class weaviate.config.AdditionalConfig as input.

Queries​

All optional arguments to methods in the query namespace now are enforced as keyword arguments.

There is now runtime logic for parsing query arguments enforcing the correct type.

Batch processing​

Introduction of three distinct algorithms using different batching styles under-the-hood:

client.batch.dynamic() as batch is a drop-in replacement for the previous client.batch as batch, which is now deprecated and will be removed on release.

with client.batch.dynamic() as batch:
  ...

is equivalent to:

with client.batch as batch:
  ...

client.batch.fixed_size() as batch is a way to configure your batching algorithm to only use a fixed size.

with client.batch.dynamic() as batch:
  ...

is equivalent to:

client.batch.configure_fixed_size()
with client.batch as batch:
  ...

client.batch.rate_limit() as batch is a new way to help avoid hitting third-party vectorization API rate limits. By specifying request_per_minute in the rate_limit() method, you can force the batching algorithm to send objects to Weaviate at the speed your third-party API is capable of processing objects.

These methods now return completely localized context managers. This means that failed_objects and failed_references of one batch won't be included in any subsequent calls.

Finally, if the background thread responsible for sending the batches raises an exception this is now re-raised in the main thread rather than silently erroring.

Filters​

The argument prop in Filter.by_property has been renamed to name

Ref counting is now achievable using Filter.by_ref_count(ref) rather than Filter([ref])

Changes in v4.4b8​ Reference filters​

Reference filters have a simplified syntax. The new syntax looks like this:

Filter.by_ref("ref").by_property("target_property")
Changes in v4.4b7​ Library imports​

Importing directly from weaviate is deprecated. Use import weaviate.classes as wvc instead.

Close client connections​

Starting in v4.4b7, you have to explicitly close your client connections. There are two ways to close client connections.

Use client.close() to explicitly close your client connections.

import weaviate
client = weaviate.connect_to_local()

print(client.is_ready())

client.close()

Use a context manager to close client connections for you.

import weaviate

with weaviate.connect_to_local() as client:
     print(client.is_ready())


Batch processing​

The v4.4b7 client introduces changes to client.batch.

Updated client.batch parameters

Old value Value in v4.4b7 from_object_uuid: UUID from_uuid: UUID from_object_collection: str from_collection: str from_property_name: str from_property: str to_object_uuid: UUID to: Union[WeaviateReference, List[UUID]] to_object_collection: Optional[str] = None tenant: Optional[str] = None tenant: Optional[str] = None Filter syntax​

Filter syntax is updated in v4.4b7.

NOTE: The filter reference syntax is simplified in 4.4b8.

Old syntax New syntax in v4.4b7 Filter(path=property) Filter.by_property(property) Filter(path=["ref", "target_class", "target_property"]) Filter.by_ref().link_on("ref").by_property("target_property") FilterMetadata.ByXX Filter.by_id()
Filter.by_creation_time()
Filter.by_update_time()

The pre-4.4b7 filter syntax is deprecated. The new, v4.4b7 syntax looks like this.

import weaviate
import datetime
import weaviate.classes as wvc

client = weaviate.connect_to_local()

jeopardy = client.collections.get("JeopardyQuestion")
response = jeopardy.query.fetch_objects(
    filters=wvc.query.Filter.by_property("round").equal("Double Jeopardy!") &
            wvc.query.Filter.by_creation_time().greater_or_equal(datetime.datetime(2005, 1, 1)) |
            wvc.query.Filter.by_creation_time().greater_or_equal(datetime.datetime(2000, 12, 31)),
            limit=3
    )


client.close()
reference_add_many updated​

The reference_add_many syntax is updated; DataReferenceOneToMany is now DataReference.

collection.data.reference_add_many(
    [
        DataReference(
            from_property="ref",
            from_uuid=uuid_from,
            to_uuid=*one or a list of UUIDs*,
        )
    ]
)
References​

Multi-target references updated. These are the new functions:

Use ReferenceToMulti for multi-target references.

Older client changes​ References​ Reorganization of classes/parameters​ Data types​

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