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Filters

Filters let you include, or exclude, particular objects from your result set based on provided conditions.
For a list of filter operators, see the API reference page.

Filter with one condition​

Add a filter to your query, to limit the result set.

from weaviate.classes.query import Filter

jeopardy = client.collections.get("JeopardyQuestion")
response = jeopardy.query.fetch_objects(
    filters=Filter.by_property("round").equal("Double Jeopardy!"),
    limit=3
)

for o in response.objects:
    print(o.properties)
python docs  API docs
Example response

The output is like this:

{
  "data": {
    "Get": {
      "JeopardyQuestion": [
        {
          "answer": "garage",
          "question": "This French word originally meant \"a place where one docks\" a boat, not a car",
          "round": "Double Jeopardy!"
        },
        {
          "answer": "Mexico",
          "question": "The Colorado River provides much of the border between this country's Baja California Norte & Sonora",
          "round": "Double Jeopardy!"
        },
        {
          "answer": "Amy Carter",
          "question": "On September 1, 1996 this former first daughter married Jim Wentzel at the Pond House near Plains",
          "round": "Double Jeopardy!"
        }
      ]
    }
  }
}

Filter with multiple conditions​

To filter with two or more conditions, use And or Or to define the relationship between the conditions.

The v4 Python client API provides filtering by any_of, or all_of, as well as using & or | operators.


  • Use any_of or all_of for filtering by any, or all of a list of provided filters.
  • Use & or | for filtering by pairs of provided filters.

Filter with & or |​

from weaviate.classes.query import Filter

jeopardy = client.collections.get("JeopardyQuestion")
response = jeopardy.query.fetch_objects(
    # Use & as AND
    #     | as OR
    filters=(
        Filter.by_property("round").equal("Double Jeopardy!") &
        Filter.by_property("points").less_than(600)
    ),
    limit=3
)

for o in response.objects:
    print(o.properties)
python docs  API docs

Filter with any of​

from weaviate.classes.query import Filter

jeopardy = client.collections.get("JeopardyQuestion")
response = jeopardy.query.fetch_objects(
    filters=(
        Filter.any_of([  # Combines the below with `|`
            Filter.by_property("points").greater_or_equal(700),
            Filter.by_property("points").less_than(500),
            Filter.by_property("round").equal("Double Jeopardy!"),
        ])
    ),
    limit=5
)

for o in response.objects:
    print(o.properties)
python docs  API docs

Filter with all of​

from weaviate.classes.query import Filter

jeopardy = client.collections.get("JeopardyQuestion")
response = jeopardy.query.fetch_objects(
    filters=(
        Filter.all_of([  # Combines the below with `&`
            Filter.by_property("points").greater_than(300),
            Filter.by_property("points").less_than(700),
            Filter.by_property("round").equal("Double Jeopardy!"),
        ])
    ),
    limit=5
)

for o in response.objects:
    print(o.properties)
python docs  API docs
Example response

The output is like this:

{
  "data": {
    "Get": {
      "JeopardyQuestion": [
        {
          "answer": "Mexico",
          "points": 200,
          "question": "The Colorado River provides much of the border between this country's Baja California Norte & Sonora",
          "round": "Double Jeopardy!"
        },
        {
          "answer": "Amy Carter",
          "points": 200,
          "question": "On September 1, 1996 this former first daughter married Jim Wentzel at the Pond House near Plains",
          "round": "Double Jeopardy!"
        },
        {
          "answer": "Greek",
          "points": 400,
          "question": "Athenians speak the Attic dialect of this language",
          "round": "Double Jeopardy!"
        }
      ]
    }
  }
}

Nested filters​

You can group and nest filters.

from weaviate.classes.query import Filter

jeopardy = client.collections.get("JeopardyQuestion")
response = jeopardy.query.fetch_objects(
    filters=Filter.by_property("answer").like("*bird*") &
            (Filter.by_property("points").greater_than(700) | Filter.by_property("points").less_than(300)),
    limit=3
)

for o in response.objects:
    print(o.properties)
python docs  API docs
Example response

The output is like this:

{
  "data": {
    "Get": {
      "JeopardyQuestion": [
        {
          "answer": "The Firebird",
          "points": 1000,
          "question": "This title character has the face & arms of a woman & a body of feathers that tapers off in flames",
          "round": "Double Jeopardy!"
        },
        {
          "answer": "the Firebird",
          "points": 800,
          "question": "This Stravinsky character first played by Tamara Karsavina has the face & arms of a girl & a body of feathers",
          "round": "Double Jeopardy!"
        }
      ]
    }
  }
}
Additional information

To create a nested filter, follow these steps.

  • Set the outer operator equal to And or Or.
  • Add operands.
  • Inside an operand expression, set operator equal to And or Or to add the nested group.
  • Add operands to the nested group as needed.

Combine filters and search operators​

Filters work with search operators like nearXXX, hybrid, and bm25.

from weaviate.classes.query import Filter

jeopardy = client.collections.get("JeopardyQuestion")
response = jeopardy.query.near_text(
    query="fashion icons",
    filters=Filter.by_property("points").greater_than(200),
    limit=3
)

for o in response.objects:
    print(o.properties)
python docs  API docs
Example response

The output is like this:

{
  "data": {
    "Get": {
      "JeopardyQuestion": [
        {
          "answer": "fashion designers",
          "points": 400,
          "question": "Ted Lapidus, Guy Laroche, Christian Lacroix",
          "round": "Jeopardy!"
        },
        {
          "answer": "Dapper Flapper",
          "points": 400,
          "question": "A stylish young woman of the 1920s",
          "round": "Double Jeopardy!"
        },
        {
          "answer": "Women's Wear Daily",
          "points": 800,
          "question": "This daily chronicler of the fashion industry launched \"W\", a bi-weekly, in 1972",
          "round": "Jeopardy!"
        }
      ]
    }
  }
}

ContainsAny Filter​

The ContainsAny operator works on text properties and take an array of values as input. It will match objects where the property contains any (i.e. one or more) of the values in the array.

from weaviate.classes.query import Filter

jeopardy = client.collections.get("JeopardyQuestion")

token_list = ["australia", "india"]
response = jeopardy.query.fetch_objects(
    # Find objects where the `answer` property contains any of the strings in `token_list`
    filters=Filter.by_property("answer").contains_any(token_list),
    limit=3
)

for o in response.objects:
    print(o.properties)
python docs  API docs
Example response

The output is like this:

{
  "data": {
    "Get": {
      "JeopardyQuestion": [
        {
          "answer": "India",
          "points": 100,
          "question": "Country that is home to Parsis & Sikhs",
          "round": "Jeopardy!"
        },
        {
          "answer": "Australia",
          "points": 400,
          "question": "The redundant-sounding Townsville, in this country's Queensland state, was named for Robert Towns",
          "round": "Double Jeopardy!"
        },
        {
          "answer": "Australia",
          "points": 100,
          "question": "Broken Hill, this country's largest company, took its name from a small town in New South Wales",
          "round": "Jeopardy!"
        }
      ]
    }
  }
}

ContainsAll Filter​

The ContainsAll operator works on text properties and take an array of values as input. It will match objects where the property contains all of the values in the array.

from weaviate.classes.query import Filter

jeopardy = client.collections.get("JeopardyQuestion")

token_list = ["blue", "red"]

response = jeopardy.query.fetch_objects(
    # Find objects where the `question` property contains all of the strings in `token_list`
    filters=Filter.by_property("question").contains_all(token_list),
    limit=3
)

for o in response.objects:
    print(o.properties)
python docs  API docs
Example response

The output is like this:

{
  "data": {
    "Get": {
      "JeopardyQuestion": [
        {
          "answer": "James Patterson",
          "points": 1000,
          "question": "His Alex Cross thrillers include \"Roses are Red\" & \"Violets are Blue\"",
          "round": "Jeopardy!"
        },
        {
          "answer": "a chevron",
          "points": 800,
          "question": "Chevron's red & blue logo is this heraldic shape, meant to convey rank & service",
          "round": "Jeopardy!"
        },
        {
          "answer": "litmus",
          "points": 400,
          "question": "Vegetable dye that turns red in acid solutions & blue in alkaline solutions",
          "round": "Double Jeopardy!"
        }
      ]
    }
  }
}

ContainsAny and ContainsAll with batch delete​

If you want to do a batch delete, see Delete objects.

Filter text on partial matches​

If the object property is a text, or text-like data type such as object ID, use Like to filter on partial text matches.

from weaviate.classes.query import Filter

jeopardy = client.collections.get("JeopardyQuestion")
response = jeopardy.query.fetch_objects(
    filters=Filter.by_property("answer").like("*inter*"),
    limit=3
)

for o in response.objects:
    print(o.properties)
python docs  API docs
Example response

The output is like this:

{
  "data": {
    "Get": {
      "JeopardyQuestion": [
        {
          "answer": "interglacial",
          "question": "This term refers to the warm periods within ice ages; we're in one of those periods now",
          "round": "Jeopardy!"
        },
        {
          "answer": "the Interior",
          "question": "In 1849, Thomas Ewing, \"The Logician of the West\", became the USA's first Secy. of this Cabinet Dept.",
          "round": "Jeopardy!"
        },
        {
          "answer": "Interlaken, Switzerland",
          "question": "You can view the Jungfrau Peak from the main street of this town between the Brienz & Thun Lakes",
          "round": "Final Jeopardy!"
        }
      ]
    }
  }
}
Additional information

The * wildcard operator matches zero or more characters. The ? operator matches exactly one character.


Currently, the Like filter is not able to match wildcard characters (? and *) as literal characters (read more).

Filter using cross-references​

To filter on properties from a cross-referenced object, add the collection name to the filter.

from weaviate.classes.query import Filter, QueryReference

jeopardy = client.collections.get("JeopardyQuestion")
response = jeopardy.query.fetch_objects(
    filters=Filter.by_ref(link_on="hasCategory").by_property("title").like("*Sport*"),
    return_references=QueryReference(link_on="hasCategory", return_properties=["title"]),
    limit=3
)

for o in response.objects:
    print(o.properties)
    print(o.references["hasCategory"].objects[0].properties["title"])
python docs  API docs
Example response

The output is like this:

{
  "data": {
    "Get": {
      "JeopardyQuestion": [
        {
          "answer": "Sampan",
          "hasCategory": [
            {
              "title": "TRANSPORTATION"
            }
          ],
          "question": "Smaller than a junk, this Oriental boat usually has a cabin with a roof made of mats",
          "round": "Jeopardy!"
        },
        {
          "answer": "Emmitt Smith",
          "hasCategory": [
            {
              "title": "SPORTS"
            }
          ],
          "question": "In 1994 this Dallas Cowboy scored 22 touchdowns; in 1995 he topped that with 25",
          "round": "Jeopardy!"
        },
        {
          "answer": "Lee Iacocca",
          "hasCategory": [
            {
              "title": "TRANSPORTATION"
            }
          ],
          "question": "Chrysler executive who developed the Ford Mustang",
          "round": "Jeopardy!"
        }
      ]
    }
  }
}

By geo-coordinates​

Limitations

Currently, geo-coordinate filtering is limited to the nearest 800 results from the source location, which will be further reduced by any other filter conditions and search parameters.

If you plan on a densely populated dataset, consider using another strategy such as geo-hashing into a text datatype, and filtering further, such as with a ContainsAny filter.

from weaviate.classes.query import Filter
from weaviate.classes.query import GeoCoordinate

response = publications.query.fetch_objects(
    filters=(
        Filter
        .by_property("headquartersGeoLocation")
        .within_geo_range(
            coordinate=GeoCoordinate(
                latitude=52.39,
                longitude=4.84
            ),
            distance=1000  # In meters
        )
    )
)

for o in response.objects:
    print(o.properties)  # Inspect returned objects
python docs  API docs

By DATE datatype​

To filter by a DATE datatype property, specify the date/time as an RFC 3339 timestamp, or a client library-compatible type such as a Python datetime object.

from datetime import datetime, timezone
from weaviate.classes.query import Filter, MetadataQuery

# Set the timezone for avoidance of doubt
filter_time = datetime(2022, 6, 10).replace(tzinfo=timezone.utc)
# The filter threshold could also be an RFC 3339 timestamp, e.g.:
# filter_time = "2022-06-10T00:00:00.00Z"

response = collection.query.fetch_objects(
    limit=3,
    # This property (`some_date`) is a `DATE` datatype
    filters=Filter.by_property("some_date").greater_than(filter_time),
)

for o in response.objects:
    print(o.properties)  # Inspect returned objects
python docs  API docs

Filter by metadata​

Filters also work with metadata properties such as object id, property length, and timestamp.

For the full list, see API references: Filters.

By object id​

from weaviate.classes.query import Filter

collection = client.collections.get("Article")

target_id = "00037775-1432-35e5-bc59-443baaef7d80"
response = collection.query.fetch_objects(
    filters=Filter.by_id().equal(target_id)
)

for o in response.objects:
    print(o.properties)  # Inspect returned objects
    print(o.uuid)
python docs  API docs

By object timestamp​

This filter requires the property timestamp to be indexed.

from datetime import datetime, timezone
from weaviate.classes.query import Filter, MetadataQuery

collection = client.collections.get("Article")

# Set the timezone for avoidance of doubt (otherwise the client will emit a warning)
filter_time = datetime(2020, 1, 1).replace(tzinfo=timezone.utc)

response = collection.query.fetch_objects(
    limit=3,
    filters=Filter.by_creation_time().greater_than(filter_time),
    return_metadata=MetadataQuery(creation_time=True)
)

for o in response.objects:
    print(o.properties)  # Inspect returned objects
    print(o.metadata.creation_time)  # Inspect object creation time
python docs  API docs

By object property length​

This filter requires the property length to be indexed.

from weaviate.classes.query import Filter

collection = client.collections.get("JeopardyQuestion")

response = collection.query.fetch_objects(
    limit=3,
    filters=Filter.by_property("answer", length=True).greater_than(length_threshold),
)

for o in response.objects:
    print(o.properties)  # Inspect returned objects
    print(len(o.properties["answer"]))  # Inspect property length
python docs  API docs

By object null state​

This filter requires the property null state to be indexed.

from weaviate.classes.query import Filter

collection = client.collections.get("WineReview")

response = collection.query.fetch_objects(
    limit=3,
    # This requires the `country` property to be configured with `index_null_state=True``
    filters=Filter.by_property("country").is_none(True)  # Find objects where the `country` property is null
)

for o in response.objects:
    print(o.properties)  # Inspect returned objects
python docs  API docs

Filter considerations​

Tokenization​

Weaviate converts filter terms into tokens. The default tokenization is word. The word tokenizer keeps alphanumeric characters, lowercase them and splits on whitespace. It converts a string like "Test_domain_weaviate" into "test", "domain", and "weaviate".

For details and additional tokenization methods, see Tokenization.

Improve filter performance​

If you encounter slow filter performance, consider adding a limit parameter or additional where operators to restrict the size of your data set.

List of filter operators​

For a list of filter operators, see the reference page.

Questions and feedback​

If you have any questions or feedback, let us know in the user forum.