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Overview

matchbox.server

Matchbox server.

Includes the API, and database adapters for various backends.

Modules:

  • api –

    Matchbox API.

  • base –

    Base classes and utilities for Matchbox database adapters.

  • postgresql –

    PostgreSQL adapter for Matchbox server.

Classes:

MatchboxDBAdapter

Bases: ABC

An abstract base class for Matchbox database adapters.

Methods:

Attributes:

settings instance-attribute 

settings: MatchboxSettings

datasets instance-attribute 

datasets: ListableAndCountable

models instance-attribute 

models: Countable

data instance-attribute 

data: Countable

clusters instance-attribute 

clusters: Countable

creates instance-attribute 

creates: Countable

merges instance-attribute 

merges: Countable

proposes instance-attribute 

proposes: Countable

source_resolutions instance-attribute 

source_resolutions: Countable

query abstractmethod 

query(
    source_address: SourceAddress,
    resolution_name: str | None = None,
    threshold: int | None = None,
    limit: int = None,
) -> Table

Queries the database from an optional point of truth.

Parameters:

  • source_address
    (SourceAddress) –

    the SourceAddress object identifying the source to query

  • resolution_name
    (optional, default: None ) –

    the resolution to use for filtering results If not specified, will use the dataset resolution for the queried source

  • threshold
    (optional, default: None ) –

    the threshold to use for creating clusters If None, uses the models’ default threshold If an integer, uses that threshold for the specified model, and the model’s cached thresholds for its ancestors

  • limit
    (optional, default: None ) –

    the number to use in a limit clause. Useful for testing

Returns:

  • Table –

    The resulting matchbox IDs in Arrow format

match abstractmethod 

match(
    source_pk: str,
    source: SourceAddress,
    targets: list[SourceAddress],
    resolution_name: str,
    threshold: int | None = None,
) -> list[Match]

Matches an ID in a source dataset and returns the keys in the targets.

Parameters:

  • source_pk
    (str) –

    The primary key to match from the source.

  • source
    (SourceAddress) –

    The address of the source dataset.

  • targets
    (list[SourceAddress]) –

    The addresses of the target datasets.

  • resolution_name
    (str) –

    The name of the resolution to use for matching.

  • threshold
    (optional, default: None ) –

    the threshold to use for creating clusters If None, uses the resolutions’ default threshold If an integer, uses that threshold for the specified resolution, and the resolution’s cached thresholds for its ancestors Will use these threshold values instead of the cached thresholds

index abstractmethod 

index(source: Source, data_hashes: Table) -> None

Indexes to Matchbox a source dataset in your warehouse.

Parameters:

  • source
    (Source) –

    The source dataset to index.

  • data_hashes
    (Table) –

    The Arrow table with the hash of each data row

get_source abstractmethod 

get_source(address: SourceAddress) -> Source

Get a source from its name address.

Parameters:

  • address
    (SourceAddress) –

    The name address for the source

Returns:

  • Source –

    A Source object

validate_ids abstractmethod 

validate_ids(ids: list[int]) -> bool

Validates a list of IDs exist in the database.

Parameters:

  • ids
    (list[int]) –

    A list of IDs to validate.

Raises:

  • MatchboxDataNotFound –

    If some items don’t exist in the target table.

validate_hashes abstractmethod 

validate_hashes(hashes: list[bytes]) -> bool

Validates a list of hashes exist in the database.

Parameters:

  • hashes
    (list[bytes]) –

    A list of hashes to validate.

Raises:

  • MatchboxDataNotFound –

    If some items don’t exist in the target table.

cluster_id_to_hash abstractmethod 

cluster_id_to_hash(
    ids: list[int],
) -> dict[int, bytes | None]

Get a lookup of Cluster hashes from a list of IDs.

Parameters:

  • ids
    (list[int]) –

    A list of IDs to get hashes for.

Returns:

  • dict[int, bytes | None] –

    A dictionary mapping IDs to hashes.

get_resolution_graph abstractmethod 

get_resolution_graph() -> ResolutionGraph

Get the full resolution graph.

dump abstractmethod 

dump() -> MatchboxSnapshot

Dumps the entire database to a snapshot.

Returns:

  • MatchboxSnapshot –

    A MatchboxSnapshot object of type “postgres” with the database’s current state.

clear abstractmethod 

clear(certain: bool) -> None

Clears all data from the database.

Parameters:

  • certain
    (bool) –

    Whether to clear the database without confirmation.

restore abstractmethod 

restore(snapshot: MatchboxSnapshot, clear: bool) -> None

Restores the database from a snapshot.

Parameters:

  • snapshot
    (MatchboxSnapshot) –

    A MatchboxSnapshot object of type “postgres” with the database’s state

  • clear
    (bool) –

    Whether to clear the database before restoration

Raises:

  • TypeError –

    If the snapshot is not compatible with PostgreSQL

insert_model abstractmethod 

insert_model(model: ModelMetadata) -> None

Writes a model to Matchbox.

Parameters:

  • model
    (ModelMetadata) –

    ModelMetadata object with the model’s metadata

Raises:

  • MatchboxDataNotFound –

    If, for a linker, the source models weren’t found in the database

get_model abstractmethod 

get_model(model: str) -> ModelMetadata

Get a model from the database.

set_model_results abstractmethod 

set_model_results(model: str, results: Table) -> None

Set the results for a model.

get_model_results abstractmethod 

get_model_results(model: str) -> Table

Get the results for a model.

set_model_truth abstractmethod 

set_model_truth(model: str, truth: float) -> None

Sets the truth threshold for this model, changing the default clusters.

get_model_truth abstractmethod 

get_model_truth(model: str) -> float

Gets the current truth threshold for this model.

get_model_ancestors abstractmethod 

get_model_ancestors(model: str) -> list[ModelAncestor]

Gets the current truth values of all ancestors.

Returns a list of ModelAncestor objects mapping model names to their current truth thresholds.

Unlike ancestors_cache which returns cached values, this property returns the current truth values of all ancestor models.

set_model_ancestors_cache abstractmethod 

set_model_ancestors_cache(
    model: str, ancestors_cache: list[ModelAncestor]
) -> None

Updates the cached ancestor thresholds.

Parameters:

  • model
    (str) –

    The name of the model to update

  • ancestors_cache
    (list[ModelAncestor]) –

    List of ModelAncestor objects mapping model names to their truth thresholds

get_model_ancestors_cache abstractmethod 

get_model_ancestors_cache(
    model: str,
) -> list[ModelAncestor]

Gets the cached ancestor thresholds, converting hashes to model names.

Returns a list of ModelAncestor objects mapping model names to their cached truth thresholds.

This is required because each point of truth needs to be stable, so we choose when to update it, caching the ancestor’s values in the model itself.

delete_model abstractmethod 

delete_model(model: str, certain: bool) -> None

Delete a model from the database.

Parameters:

  • model
    (str) –

    The name of the model to delete.

  • certain
    (bool) –

    Whether to delete the model without confirmation.

MatchboxSettings

Bases: BaseSettings

Settings for the Matchbox application.

Attributes:

batch_size class-attribute instance-attribute 

batch_size: int = Field(default=250000)

backend_type instance-attribute 

backend_type: MatchboxBackends

datastore instance-attribute 

datastore: MatchboxDatastoreSettings

matchbox.server.base

Base classes and utilities for Matchbox database adapters.

Classes:

Functions:

MatchboxBackends

Bases: StrEnum

The available backends for Matchbox.

Attributes:

POSTGRES class-attribute instance-attribute 

POSTGRES = 'postgres'

MatchboxSnapshot

Bases: BaseModel

A snapshot of the Matchbox database.

Methods:

Attributes:

backend_type instance-attribute 

backend_type: MatchboxBackends

data instance-attribute 

data: Any

check_serialisable classmethod 

check_serialisable(value: Any) -> Any

Validate that the value can be serialised to JSON.

MatchboxDatastoreSettings

Bases: BaseSettings

Settings specific to the datastore configuration.

Methods:

  • get_client –

    Returns an S3 client for the datastore.

Attributes:

host class-attribute instance-attribute 

host: str | None = None

port class-attribute instance-attribute 

port: int | None = None

access_key_id class-attribute instance-attribute 

access_key_id: SecretStr | None = None

secret_access_key class-attribute instance-attribute 

secret_access_key: SecretStr | None = None

default_region class-attribute instance-attribute 

default_region: str | None = None

cache_bucket_name instance-attribute 

cache_bucket_name: str

get_client 

get_client() -> S3Client

Returns an S3 client for the datastore.

Creates S3 buckets if they don’t exist.

MatchboxSettings

Bases: BaseSettings

Settings for the Matchbox application.

Attributes:

batch_size class-attribute instance-attribute 

batch_size: int = Field(default=250000)

backend_type instance-attribute 

backend_type: MatchboxBackends

datastore instance-attribute 

datastore: MatchboxDatastoreSettings

APISettings

Bases: BaseSettings

Settings for the Matchbox API.

Attributes:

api_key class-attribute instance-attribute 

api_key: str | None = None

BackendManager

Manages the Matchbox backend instance and settings.

Methods:

initialise classmethod 

initialise(settings: MatchboxSettings)

Initialise the backend with the given settings.

get_backend classmethod 

get_backend() -> MatchboxDBAdapter

Get the backend instance.

get_settings classmethod 

get_settings() -> MatchboxSettings

Get the backend settings.

Countable

Bases: Protocol

A protocol for objects that can be counted.

Methods:

  • count –

    Counts the number of items in the object.

count 

count() -> int

Counts the number of items in the object.

Listable

Bases: Protocol

A protocol for objects that can be listed.

Methods:

  • list –

    Lists the items in the object.

list 

list() -> list[str]

Lists the items in the object.

ListableAndCountable

Bases: Countable, Listable

A protocol for objects that can be counted and listed.

Methods:

  • list –

    Lists the items in the object.

  • count –

    Counts the number of items in the object.

list 

list() -> list[str]

Lists the items in the object.

count 

count() -> int

Counts the number of items in the object.

MatchboxDBAdapter

Bases: ABC

An abstract base class for Matchbox database adapters.

Methods:

Attributes:

settings instance-attribute 

settings: MatchboxSettings

datasets instance-attribute 

datasets: ListableAndCountable

models instance-attribute 

models: Countable

data instance-attribute 

data: Countable

clusters instance-attribute 

clusters: Countable

creates instance-attribute 

creates: Countable

merges instance-attribute 

merges: Countable

proposes instance-attribute 

proposes: Countable

source_resolutions instance-attribute 

source_resolutions: Countable

query abstractmethod 

query(
    source_address: SourceAddress,
    resolution_name: str | None = None,
    threshold: int | None = None,
    limit: int = None,
) -> Table

Queries the database from an optional point of truth.

Parameters:

  • source_address
    (SourceAddress) –

    the SourceAddress object identifying the source to query

  • resolution_name
    (optional, default: None ) –

    the resolution to use for filtering results If not specified, will use the dataset resolution for the queried source

  • threshold
    (optional, default: None ) –

    the threshold to use for creating clusters If None, uses the models’ default threshold If an integer, uses that threshold for the specified model, and the model’s cached thresholds for its ancestors

  • limit
    (optional, default: None ) –

    the number to use in a limit clause. Useful for testing

Returns:

  • Table –

    The resulting matchbox IDs in Arrow format

match abstractmethod 

match(
    source_pk: str,
    source: SourceAddress,
    targets: list[SourceAddress],
    resolution_name: str,
    threshold: int | None = None,
) -> list[Match]

Matches an ID in a source dataset and returns the keys in the targets.

Parameters:

  • source_pk
    (str) –

    The primary key to match from the source.

  • source
    (SourceAddress) –

    The address of the source dataset.

  • targets
    (list[SourceAddress]) –

    The addresses of the target datasets.

  • resolution_name
    (str) –

    The name of the resolution to use for matching.

  • threshold
    (optional, default: None ) –

    the threshold to use for creating clusters If None, uses the resolutions’ default threshold If an integer, uses that threshold for the specified resolution, and the resolution’s cached thresholds for its ancestors Will use these threshold values instead of the cached thresholds

index abstractmethod 

index(source: Source, data_hashes: Table) -> None

Indexes to Matchbox a source dataset in your warehouse.

Parameters:

  • source
    (Source) –

    The source dataset to index.

  • data_hashes
    (Table) –

    The Arrow table with the hash of each data row

get_source abstractmethod 

get_source(address: SourceAddress) -> Source

Get a source from its name address.

Parameters:

  • address
    (SourceAddress) –

    The name address for the source

Returns:

  • Source –

    A Source object

validate_ids abstractmethod 

validate_ids(ids: list[int]) -> bool

Validates a list of IDs exist in the database.

Parameters:

  • ids
    (list[int]) –

    A list of IDs to validate.

Raises:

  • MatchboxDataNotFound –

    If some items don’t exist in the target table.

validate_hashes abstractmethod 

validate_hashes(hashes: list[bytes]) -> bool

Validates a list of hashes exist in the database.

Parameters:

  • hashes
    (list[bytes]) –

    A list of hashes to validate.

Raises:

  • MatchboxDataNotFound –

    If some items don’t exist in the target table.

cluster_id_to_hash abstractmethod 

cluster_id_to_hash(
    ids: list[int],
) -> dict[int, bytes | None]

Get a lookup of Cluster hashes from a list of IDs.

Parameters:

  • ids
    (list[int]) –

    A list of IDs to get hashes for.

Returns:

  • dict[int, bytes | None] –

    A dictionary mapping IDs to hashes.

get_resolution_graph abstractmethod 

get_resolution_graph() -> ResolutionGraph

Get the full resolution graph.

dump abstractmethod 

dump() -> MatchboxSnapshot

Dumps the entire database to a snapshot.

Returns:

  • MatchboxSnapshot –

    A MatchboxSnapshot object of type “postgres” with the database’s current state.

clear abstractmethod 

clear(certain: bool) -> None

Clears all data from the database.

Parameters:

  • certain
    (bool) –

    Whether to clear the database without confirmation.

restore abstractmethod 

restore(snapshot: MatchboxSnapshot, clear: bool) -> None

Restores the database from a snapshot.

Parameters:

  • snapshot
    (MatchboxSnapshot) –

    A MatchboxSnapshot object of type “postgres” with the database’s state

  • clear
    (bool) –

    Whether to clear the database before restoration

Raises:

  • TypeError –

    If the snapshot is not compatible with PostgreSQL

insert_model abstractmethod 

insert_model(model: ModelMetadata) -> None

Writes a model to Matchbox.

Parameters:

  • model
    (ModelMetadata) –

    ModelMetadata object with the model’s metadata

Raises:

  • MatchboxDataNotFound –

    If, for a linker, the source models weren’t found in the database

get_model abstractmethod 

get_model(model: str) -> ModelMetadata

Get a model from the database.

set_model_results abstractmethod 

set_model_results(model: str, results: Table) -> None

Set the results for a model.

get_model_results abstractmethod 

get_model_results(model: str) -> Table

Get the results for a model.

set_model_truth abstractmethod 

set_model_truth(model: str, truth: float) -> None

Sets the truth threshold for this model, changing the default clusters.

get_model_truth abstractmethod 

get_model_truth(model: str) -> float

Gets the current truth threshold for this model.

get_model_ancestors abstractmethod 

get_model_ancestors(model: str) -> list[ModelAncestor]

Gets the current truth values of all ancestors.

Returns a list of ModelAncestor objects mapping model names to their current truth thresholds.

Unlike ancestors_cache which returns cached values, this property returns the current truth values of all ancestor models.

set_model_ancestors_cache abstractmethod 

set_model_ancestors_cache(
    model: str, ancestors_cache: list[ModelAncestor]
) -> None

Updates the cached ancestor thresholds.

Parameters:

  • model
    (str) –

    The name of the model to update

  • ancestors_cache
    (list[ModelAncestor]) –

    List of ModelAncestor objects mapping model names to their truth thresholds

get_model_ancestors_cache abstractmethod 

get_model_ancestors_cache(
    model: str,
) -> list[ModelAncestor]

Gets the cached ancestor thresholds, converting hashes to model names.

Returns a list of ModelAncestor objects mapping model names to their cached truth thresholds.

This is required because each point of truth needs to be stable, so we choose when to update it, caching the ancestor’s values in the model itself.

delete_model abstractmethod 

delete_model(model: str, certain: bool) -> None

Delete a model from the database.

Parameters:

  • model
    (str) –

    The name of the model to delete.

  • certain
    (bool) –

    Whether to delete the model without confirmation.

get_backend_settings 

get_backend_settings(
    backend_type: MatchboxBackends,
) -> type[MatchboxSettings]

Get the appropriate settings class based on the backend type.

get_backend_class 

get_backend_class(
    backend_type: MatchboxBackends,
) -> type[MatchboxDBAdapter]

Get the appropriate backend class based on the backend type.

initialise_backend 

initialise_backend(settings: MatchboxSettings) -> None

Utility function to initialise the Matchbox backend based on settings.

initialise_matchbox 

initialise_matchbox() -> None

Initialise the Matchbox backend based on environment variables.