Extending the SDK

ldclient.interfaces module

This submodule contains interfaces for various components of the SDK.

They may be useful in writing new implementations of these components, or for testing.

class ldclient.interfaces.BackgroundOperation

Bases: object

is_alive()

Returns whether the operation is alive or not

Return type

bool

start()

Starts an operation in the background. Should return immediately and not block.

stop()

Stops an operation running in the background. May return before the operation is actually stopped.

class ldclient.interfaces.BigSegmentStore

Bases: object

Interface for a read-only data store that allows querying of user membership in Big Segments.

Big Segments are a specific type of user segments. For more information, read the LaunchDarkly documentation: https://docs.launchdarkly.com/home/users/big-segments

abstract get_membership(user_hash)

Queries the store for a snapshot of the current segment state for a specific user.

The user_hash is a base64-encoded string produced by hashing the user key as defined by the Big Segments specification; the store implementation does not need to know the details of how this is done, because it deals only with already-hashed keys, but the string can be assumed to only contain characters that are valid in base64.

The return value should be either a dict, or None if the user is not referenced in any big segments. Each key in the dictionary is a “segment reference”, which is how segments are identified in Big Segment data. This string is not identical to the segment key– the SDK will add other information. The store implementation should not be concerned with the format of the string. Each value in the dictionary is True if the user is explicitly included in the segment, False if the user is explicitly excluded from the segment– and is not also explicitly included (that is, if both an include and an exclude existed in the data, the include would take precedence). If the user’s status in a particular segment is undefined, there should be no key or value for that segment.

This dictionary may be cached by the SDK, so it should not be modified after it is created. It is a snapshot of the segment membership state at one point in time.

Parameters

user_hash (str) – the hashed user key

Return type

Optional[dict]

Returns

True/False values for Big Segments that reference this user

abstract get_metadata()

Returns information about the overall state of the store. This method will be called only when the SDK needs the latest state, so it should not be cached.

Return type

BigSegmentStoreMetadata

Returns

the store metadata

abstract stop()

Shuts down the store component and releases and resources it is using.

class ldclient.interfaces.BigSegmentStoreMetadata(last_up_to_date)

Bases: object

Values returned by BigSegmentStore.get_metadata().

__init__(last_up_to_date)

Initialize self. See help(type(self)) for accurate signature.

property last_up_to_date

The Unix epoch millisecond timestamp of the last update to the BigSegmentStore. It is None if the store has never been updated.

Return type

Optional[int]

class ldclient.interfaces.BigSegmentStoreStatus(available, stale)

Bases: object

Information about the state of a Big Segment store, provided by BigSegmentStoreStatusProvider.

Big Segments are a specific type of user segments. For more information, read the LaunchDarkly documentation: https://docs.launchdarkly.com/home/users/big-segments

__init__(available, stale)

Initialize self. See help(type(self)) for accurate signature.

property available

True if the Big Segment store is able to respond to queries, so that the SDK can evaluate whether a user is in a segment or not.

If this property is False, the store is not able to make queries (for instance, it may not have a valid database connection). In this case, the SDK will treat any reference to a Big Segment as if no users are included in that segment. Also, the ldclient.flag.EvaluationDetail.reason() associated with with any flag evaluation that references a Big Segment when the store is not available will have a bigSegmentsStatus of “STORE_ERROR”.

Return type

bool

property stale

True if the Big Segment store is available, but has not been updated within the amount of time specified by {BigSegmentsConfig#stale_after}.

This may indicate that the LaunchDarkly Relay Proxy, which populates the store, has stopped running or has become unable to receive fresh data from LaunchDarkly. Any feature flag evaluations that reference a Big Segment will be using the last known data, which may be out of date. Also, the ldclient.flag.EvaluationDetail.reason() associated with those evaluations will have a bigSegmentsStatus of “STALE”.

Return type

bool

class ldclient.interfaces.BigSegmentStoreStatusProvider

Bases: object

An interface for querying the status of a Big Segment store.

The Big Segment store is the component that receives information about Big Segments, normally from a database populated by the LaunchDarkly Relay Proxy. Big Segments are a specific type of user segments. For more information, read the LaunchDarkly documentation: https://docs.launchdarkly.com/home/users/big-segments

An implementation of this abstract class is returned by ldclient.client.LDClient.big_segment_store_status_provider(). Application code never needs to implement this interface.

There are two ways to interact with the status. One is to simply get the current status; if its available property is true, then the SDK is able to evaluate user membership in Big Segments, and the stale` property indicates whether the data might be out of date.

The other way is to subscribe to status change notifications. Applications may wish to know if there is an outage in the Big Segment store, or if it has become stale (the Relay Proxy has stopped updating it with new data), since then flag evaluations that reference a Big Segment might return incorrect values. Use add_listener to register a callback for notifications.

abstract add_listener(listener)

Subscribes for notifications of status changes.

The listener is a function or method that will be called with a single parameter: the new BigSegmentStoreStatus.

Parameters

listener (Callable[[BigSegmentStoreStatus], None]) – the listener to add

Return type

None

abstract remove_listener(listener)

Unsubscribes from notifications of status changes.

Parameters

listener (Callable[[BigSegmentStoreStatus], None]) – a listener that was previously added with add_listener; if it was not, this method does nothing

Return type

None

abstract property status

Gets the current status of the store.

Return type

BigSegmentStoreStatus

Returns

the status

class ldclient.interfaces.DiagnosticDescription

Bases: object

Optional interface for components to describe their own configuration.

abstract describe_configuration(config)

Used internally by the SDK to inspect the configuration. :param config: the full configuration, in case this component depends on properties outside itself :rtype: str :return: a string describing the type of the component, or None

class ldclient.interfaces.EventProcessor

Bases: object

Interface for the component that buffers analytics events and sends them to LaunchDarkly. The default implementation can be replaced for testing purposes.

abstract flush()

Specifies that any buffered events should be sent as soon as possible, rather than waiting for the next flush interval. This method is asynchronous, so events still may not be sent until a later time. However, calling stop() will synchronously deliver any events that were not yet delivered prior to shutting down.

abstract send_event(event)

Processes an event to be sent at some point.

abstract stop()

Shuts down the event processor after first delivering all pending events.

class ldclient.interfaces.FeatureRequester

Bases: object

Interface for the component that acquires feature flag data in polling mode. The default implementation can be replaced for testing purposes.

get_all()

Gets all feature flags.

class ldclient.interfaces.FeatureStore

Bases: object

Interface for a versioned store for feature flags and related objects received from LaunchDarkly. Implementations should permit concurrent access and updates.

An “object”, for FeatureStore, is simply a dict of arbitrary data which must have at least three properties: key (its unique key), version (the version number provided by LaunchDarkly), and deleted (True if this is a placeholder for a deleted object).

Delete and upsert requests are versioned: if the version number in the request is less than the currently stored version of the object, the request should be ignored.

These semantics support the primary use case for the store, which synchronizes a collection of objects based on update messages that may be received out-of-order.

abstract all(kind, callback=<function FeatureStore.<lambda>>)

Retrieves a dictionary of all associated objects of a given kind. The retrieved dict of keys to objects can be transformed by the specified callback.

Parameters

• kind (VersionedDataKind) – The kind of objects to get

• callback (Callable[[Any], Any]) – A function that accepts the retrieved data and returns a transformed value

Return type

Any

abstract delete(kind, key, version)

Deletes the object associated with the specified key, if it exists and its version is less than the specified version. The object should be replaced in the data store by a placeholder with the specified version and a “deleted” property of TErue.

Parameters

• kind (VersionedDataKind) – The kind of object to delete

• key (str) – The key of the object to be deleted

• version (int) – The version for the delete operation

abstract get(kind, key, callback=<function FeatureStore.<lambda>>)

Retrieves the object to which the specified key is mapped, or None if the key is not found or the associated object has a deleted property of True. The retrieved object, if any (a dict) can be transformed by the specified callback.

Parameters

• kind (VersionedDataKind) – The kind of object to get

• key (str) – The key whose associated object is to be returned

• callback (Callable[[Any], Any]) – A function that accepts the retrieved data and returns a transformed value

Return type

Any

Returns

The result of executing callback

abstract init(all_data)

Initializes (or re-initializes) the store with the specified set of objects. Any existing entries will be removed. Implementations can assume that this set of objects is up to date– there is no need to perform individual version comparisons between the existing objects and the supplied data.

Parameters

all_data (Mapping[VersionedDataKind, Mapping[str, dict]]) – All objects to be stored

abstract property initialized

Returns whether the store has been initialized yet or not

Return type

bool

abstract upsert(kind, item)

Updates or inserts the object associated with the specified key. If an item with the same key already exists, it should update it only if the new item’s version property is greater than the old one.

Parameters

• kind (VersionedDataKind) – The kind of object to update

• item (dict) – The object to update or insert

class ldclient.interfaces.FeatureStoreCore

Bases: object

Interface for a simplified subset of the functionality of FeatureStore, to be used in conjunction with ldclient.feature_store_helpers.CachingStoreWrapper. This allows developers of custom FeatureStore implementations to avoid repeating logic that would commonly be needed in any such implementation, such as caching. Instead, they can implement only FeatureStoreCore and then create a CachingStoreWrapper.

abstract get_all_internal(callback)

Returns a dictionary of all associated objects of a given kind. The method should not attempt to filter out any items based on their deleted property, nor to cache any items.

Parameters

kind – The kind of objects to get

Return type

Mapping[str, dict]

Returns

A dictionary of keys to items

abstract get_internal(kind, key)

Returns the object to which the specified key is mapped, or None if no such item exists. The method should not attempt to filter out any items based on their deleted property, nor to cache any items.

Parameters

• kind (VersionedDataKind) – The kind of object to get

• key (str) – The key of the object

Return type

dict

Returns

The object to which the specified key is mapped, or None

abstract init_internal(all_data)

Initializes (or re-initializes) the store with the specified set of objects. Any existing entries will be removed. Implementations can assume that this set of objects is up to date– there is no need to perform individual version comparisons between the existing objects and the supplied data.

Parameters

all_data (Mapping[VersionedDataKind, Mapping[str, dict]]) – A dictionary of data kinds to item collections

abstract initialized_internal()

Returns true if this store has been initialized. In a shared data store, it should be able to detect this even if initInternal was called in a different process, i.e. the test should be based on looking at what is in the data store. The method does not need to worry about caching this value; CachingStoreWrapper will only call it when necessary.

Return type

bool

abstract upsert_internal(kind, item)

Updates or inserts the object associated with the specified key. If an item with the same key already exists, it should update it only if the new item’s version property is greater than the old one. It should return the final state of the item, i.e. if the update succeeded then it returns the item that was passed in, and if the update failed due to the version check then it returns the item that is currently in the data store (this ensures that CachingStoreWrapper will update the cache correctly).

Parameters

• kind (VersionedDataKind) – The kind of object to update

• item (dict) – The object to update or insert

Return type

dict

Returns

The state of the object after the update

class ldclient.interfaces.UpdateProcessor

Bases: ldclient.interfaces.BackgroundOperation

Interface for the component that obtains feature flag data in some way and passes it to a FeatureStore. The built-in implementations of this are the client’s standard streaming or polling behavior. For testing purposes, there is also ldclient.integrations.Files.new_data_source().

initialized()

Returns whether the update processor has received feature flags and has initialized its feature store.

Return type

bool

ldclient.feature_store_helpers module

This submodule contains support code for writing feature store implementations.

class ldclient.feature_store_helpers.CachingStoreWrapper(core, cache_config)

Bases: ldclient.interfaces.DiagnosticDescription, ldclient.interfaces.FeatureStore

A partial implementation of ldclient.interfaces.FeatureStore.

This class delegates the basic functionality to an implementation of ldclient.interfaces.FeatureStoreCore - while adding optional caching behavior and other logic that would otherwise be repeated in every feature store implementation. This makes it easier to create new database integrations by implementing only the database-specific logic.

__init__(core, cache_config)

Constructs an instance by wrapping a core implementation object.

Parameters

• core (FeatureStoreCore) – the implementation object

• cache_config (CacheConfig) – the caching parameters

all(kind, callback=<function CachingStoreWrapper.<lambda>>)

delete(kind, key, version)

describe_configuration(config)

Used internally by the SDK to inspect the configuration. :param config: the full configuration, in case this component depends on properties outside itself :return: a string describing the type of the component, or None

get(kind, key, callback=<function CachingStoreWrapper.<lambda>>)

init(all_data)

property initialized

Return type

bool

upsert(kind, item)

ldclient.versioned_data_kind module

This submodule is used only by the internals of the feature flag storage mechanism.

If you are writing your own implementation of ldclient.integrations.FeatureStore, the VersionedDataKind tuple type will be passed to the kind parameter of the feature store methods; its namespace property tells the feature store which collection of objects is being referenced (“features”, “segments”, etc.). The intention is for the feature store to treat storable objects as completely generic JSON dictionaries, rather than having any special logic for features or segments.

class ldclient.versioned_data_kind.VersionedDataKind(namespace, request_api_path, stream_api_path)

Bases: object

property namespace

Return type

str

property request_api_path

Return type

str

property stream_api_path

Return type

str

class ldclient.versioned_data_kind.VersionedDataKindWithOrdering(namespace, request_api_path, stream_api_path, priority, get_dependency_keys)

Bases: ldclient.versioned_data_kind.VersionedDataKind

property get_dependency_keys

Return type

Optional[Callable[[dict], Iterable[str]]]

property priority

Return type

int