Find a document (Python)

Finds a single document in a collection using filter and sort clauses, including vector search.

Ready to write code? See the examples for this method to get started. If you are new to the Data API, check out the quickstart.

Result

Returns a dictionary representation of a document that matches the specified filter and sort clauses, or returns None if no document was found.

The fields included in the returned document depend on the subset of fields that were requested in the projection. If requested and applicable, the document will also include a $similarity key with a numeric similarity score that represents the closeness of the sort vector and the document’s vector.

Example response:

{'_id': 101, 'name': 'John Doe', '$vector': [0.12, 0.52, 0.32]}

Parameters

Use the find_one method, which belongs to the astrapy.Collection class.

Method signature

find_one(
  filter: Dict[str, Any],
  *,
  projection: Dict[str, bool],
  include_similarity: bool,
  sort: Dict[str, Any],
  general_method_timeout_ms: int,
  request_timeout_ms: int,
  timeout_ms: int,
) -> Dict[str, Any]

Name Type Summary

Name	Type	Summary
`filter`	`Dict[str, Any]`	Optional. An object that defines filter criteria using the Data API filter syntax. The method only finds documents that match the filter criteria. Filters can improve performance by reducing the number of documents that the Data API processes. You must use `&` to escape any `.` or `&` in field names in the filter clause. You cannot use `&` to escape any other characters. For more information, see Work with `.` and `&` in field names (Python). For a list of available filter operators and more examples, see Filter operators for collections (Python). Filters can use only indexed fields. If you apply selective indexing when you create a collection, you cannot reference non-indexed fields in a filter. For an example, see Use filters to find a document.
`projection`	`Dict[str, bool]`	Optional. Controls which fields are included or excluded in the returned document. You must use `&` to escape any `.` or `&` in field names in the projection clause. You cannot use `&` to escape any other characters. For more information, see Work with `.` and `&` in field names (Python). For more information, see Projections for collections (Python). Default: The default projection for the collection. All fields prefixed with `$` are excluded by default and will only be returned if you include them in the projection. `_id` is included by default and will always be returned unless you exclude it from the projection. For examples, see Include only specific fields in the response and Exclude specific fields from the response.
`include_similarity`	`bool`	Optional. Whether to include a `$similarity` property in the response. The `$similarity` value represents the closeness of the sort vector and the document’s vector. This parameter only applies if you use a vector search. For an example, see Include the similarity score with the result. Default: False
`sort`	`Dict[str, Any]`	Optional. Sorts documents by one or more fields, or performs a vector search. You must use `&` to escape any `.` or `&` in field names in the sort clause. You cannot use `&` to escape any other characters. For more information, see Work with `.` and `&` in field names (Python). For more information, see Sort clauses for collections (Python). Sort clauses can use only indexed fields. If you apply selective indexing when you create a collection, you cannot reference non-indexed fields in sort queries. For vector searches, this parameter can use either `$vector` or `$vectorize`. For examples, see Use sorting to find a document, Use vector search to find a document, and Use vector search and vectorize to find a document.
`general_method_timeout_ms`	`int`	Optional. The maximum time, in milliseconds, that the client should wait for the underlying HTTP request. Default: The default value for the collection. This default is 30 seconds unless you specified a different default when you initialized the `Collection` or `DataAPIClient` object. For more information, see Timeout options.
`request_timeout_ms`	`int`	Optional. An alias for `general_method_timeout_ms`. Since this method issues a single HTTP request, `general_method_timeout_ms` and `request_timeout_ms` are equivalent.
`timeout_ms`	`int`	Optional. An alias for `general_method_timeout_ms`.

filter

Dict[str, Any]

Optional. An object that defines filter criteria using the Data API filter syntax. The method only finds documents that match the filter criteria. Filters can improve performance by reducing the number of documents that the Data API processes.

You must use & to escape any . or & in field names in the filter clause. You cannot use & to escape any other characters. For more information, see Work with . and & in field names (Python).

For a list of available filter operators and more examples, see Filter operators for collections (Python).

Filters can use only indexed fields. If you apply selective indexing when you create a collection, you cannot reference non-indexed fields in a filter.

For an example, see Use filters to find a document.

projection

Dict[str, bool]

Optional. Controls which fields are included or excluded in the returned document.

You must use & to escape any . or & in field names in the projection clause. You cannot use & to escape any other characters. For more information, see Work with . and & in field names (Python).

For more information, see Projections for collections (Python).

Default: The default projection for the collection. All fields prefixed with $ are excluded by default and will only be returned if you include them in the projection. _id is included by default and will always be returned unless you exclude it from the projection.

For examples, see Include only specific fields in the response and Exclude specific fields from the response.

include_similarity

bool

Optional. Whether to include a $similarity property in the response. The $similarity value represents the closeness of the sort vector and the document’s vector.

This parameter only applies if you use a vector search.

For an example, see Include the similarity score with the result.

Default: False

sort

Dict[str, Any]

Optional. Sorts documents by one or more fields, or performs a vector search.

You must use & to escape any . or & in field names in the sort clause. You cannot use & to escape any other characters. For more information, see Work with . and & in field names (Python).

For more information, see Sort clauses for collections (Python).

Sort clauses can use only indexed fields. If you apply selective indexing when you create a collection, you cannot reference non-indexed fields in sort queries.

For vector searches, this parameter can use either $vector or $vectorize.

For examples, see Use sorting to find a document, Use vector search to find a document, and Use vector search and vectorize to find a document.

general_method_timeout_ms

int

Optional. The maximum time, in milliseconds, that the client should wait for the underlying HTTP request.

Default: The default value for the collection. This default is 30 seconds unless you specified a different default when you initialized the Collection or DataAPIClient object. For more information, see Timeout options.

request_timeout_ms

int

Optional. An alias for general_method_timeout_ms. Since this method issues a single HTTP request, general_method_timeout_ms and request_timeout_ms are equivalent.

timeout_ms

int

Optional. An alias for general_method_timeout_ms.

Examples

The following examples demonstrate how to find a document in a collection.

Use a document’s ID to find a document

All documents have a unique _id property. You can use a filter to find a document with a specific _id.

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one({"_id": "101"})

print(result)

Use filters to find a document

You can use a filter to find a document that matches specific criteria. For example, you can find a document with an is_checked_out value of false and a number_of_pages value less than 300.

For a list of available filter operators and more examples, see Filter operators for collections (Python).

Filters can use only indexed fields. If you apply selective indexing when you create a collection, you cannot reference non-indexed fields in a filter.

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one(
    {
        "$and": [
            {"is_checked_out": False},
            {"number_of_pages": {"$lt": 300}},
        ]
    }
)

print(result)

Use vector search to find a document

To find the document whose $vector value is most similar to a given vector, use a sort with the vector embeddings that you want to match. For more information, see Find data with vector search.

Vector search is only available for vector-enabled collections. For more information, see Create a collection that can store vector embeddings and $vector in collections (Python).

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one({}, sort={"$vector": [0.08, -0.62, 0.39]})

print(result)

Use vector search and vectorize to find a document

To find the document whose $vector value is most similar to the $vector value of a given search string, use a sort with the search string that you want to vectorize and match. For more information, see Find data with vector search.

Vector search with vectorize is only available for collections that have vectorize enabled. For more information, see Create a collection that can automatically generate vector embeddings and $vectorize in collections (Python).

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one({}, sort={"$vectorize": "Text to vectorize"})

print(result)

Use lexicographical matching to find a document

Lexicographical matching is currently in public preview. Development is ongoing, and the features and functionality are subject to change. Astra DB Serverless, and the use of such, is subject to the DataStax Preview Terms.

There are two ways to use lexicographical matching to find documents with the Data API:

Sort on the $lexical field to find the documents whose $lexical field value is most relevant to a given string of space-separated keywords or terms
Filter on the $lexical field with the $match operator to find the documents whose $lexical field value is a lexicographical match to the specified string of space-separated keywords or terms

You can use these strategies together or separately.

You can only use lexicographical matching on collections that have lexical enabled. For more information, see Create a collection that supports lexicographical matching.

Documents must have the $lexical field populated to be included in lexicographical matching. For examples, see Insert a document for retrieval with lexicographical matching and Insert documents for retrieval with lexicographical matching.

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one(
    {"$lexical": {"$match": "tree hill"}},
    sort={"$lexical": "tree hill grassy"},
)

print(result)

Use sorting to find a document

You can use a sort clause to sort documents by one or more fields.

For more information, see Sort clauses for collections (Python).

Sort clauses can use only indexed fields. If you apply selective indexing when you create a collection, you cannot reference non-indexed fields in sort queries.

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient
from astrapy.constants import SortMode

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one(
    {"metadata.language": "English"},
    sort={
        "rating": SortMode.ASCENDING,
        "title": SortMode.DESCENDING,
    },
)

print(result)

Include the similarity score with the result

If you use a vector search to find a document, you can also include a $similarity property in the result. The $similarity value represents the closeness of the sort vector and the document’s vector.

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one(
    {}, sort={"$vectorize": "Text to vectorize"}, include_similarity=True
)

if result:
    print(result["$similarity"])

Include only specific fields in the response

To specify which fields to include or exclude in the returned document, use a projection.

All fields prefixed with $ are excluded by default and will only be returned if you include them in the projection. _id is included by default and will always be returned unless you exclude it from the projection.

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one(
    {"metadata.language": "English"},
    projection={"is_checked_out": True, "title": True},
)

print(result)

Exclude specific fields from the response

To specify which fields to include or exclude in the returned document, use a projection.

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one(
    {"metadata.language": "English"},
    projection={"is_checked_out": False, "title": False},
)

print(result)

Use filter, sort, and projection together

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient
from astrapy.constants import SortMode

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one(
    {
        "$and": [
            {"is_checked_out": False},
            {"number_of_pages": {"$lt": 300}},
        ]
    },
    sort={
        "rating": SortMode.ASCENDING,
        "title": SortMode.DESCENDING,
    },
    projection={"is_checked_out": True, "title": True},
)

print(result)

Work with `.` and `&` in field names

You must use & to escape any . or & in field names when the field is used in a filter, sort, projection, update, or indexing clause. Dot notation, which is used to reference nested fields, should not be escaped. For more information, see Work with . and & in field names (Python).

For example, in the following document, you would use escaping like this: areas.r&&d, costs.price&.usd, and costs.price&.cad.

{
  "areas": {
    "r&d": true,
    "design": false
  },
  "costs": {
    "price.usd": 100,
    "price.cad": 90
  }
}

The following example uses untyped documents or rows, but you can define a client-side type for your collection to help statically catch errors. For examples, see Typing support.

from astrapy import DataAPIClient
from astrapy.constants import SortMode

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one(
    {
        "$and": [
            {"areas.r&&d": False},
            {"costs.price&.usd": {"$lt": 300}},
        ]
    },
    sort={"costs.price&.usd": SortMode.ASCENDING},
    projection={"areas.r&&d": True, "costs.price&.cad": True},
)

print(result)

You can also use the escape_field_names function provided by the client:

from astrapy import DataAPIClient
from astrapy.constants import SortMode
from astrapy.utils.document_paths import escape_field_names

# Get an existing collection
client = DataAPIClient()
database = client.get_database(
    "API_ENDPOINT", token="APPLICATION_TOKEN"
)
collection = database.get_collection("COLLECTION_NAME")

# Find a document
result = collection.find_one(
    {
        "$and": [
            {escape_field_names("areas", "r&d"): False},
            {escape_field_names("costs", "price.usd"): {"$lt": 300}},
        ]
    },
    sort={escape_field_names("costs", "price.usd"): SortMode.ASCENDING},
    projection={
        escape_field_names("areas", "r&d"): True,
        escape_field_names("costs", "price.cad"): True,
    },
)

print(result)

Client reference

For more information, see the client reference.

Find a document (Python)

Result

Parameters

Examples

Use a document’s ID to find a document

Use filters to find a document

Use vector search to find a document

Use vector search and vectorize to find a document

Use lexicographical matching to find a document

Use sorting to find a document

Include the similarity score with the result

Include only specific fields in the response

Exclude specific fields from the response

Use filter, sort, and projection together

Work with `.` and `&` in field names

Client reference

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