This release could not be installed due to a packaging error, and has been removed from PyPI.
Consul in ldclient.integrations, and the reference guide for "Using a persistent feature store".DynamoDB in ldclient.integrations, and the reference guide to "Using a persistent feature store".CacheConfig (in ldclient.feature_store) encapsulates all the parameters that control local caching in database feature stores. This takes the place of the expiration and capacity parameters that are in the deprecated RedisFeatureStore constructor; it can be used with DynamoDB and any other database integrations in the future, and if more caching options are added to CacheConfig they will be automatically supported in all of the feature stores.RedisFeatureStore constructor in ldclient.redis_feature_store. The recommended way to create a Redis feature store now is to use Redis.new_feature_store in ldclient.integrations.file_data_source.py.all_flags_state method now accepts a new option, details_only_for_tracked_flags, which reduces the size of the JSON representation of the flag state by omitting some metadata. Specifically, it omits any data that is normally used for generating detailed evaluation events if a flag does not have event tracking or debugging turned on.expiringdict package. This has been changed to use the current version of that package from PyPi.all_flags_state is now slightly smaller even if you do not use the new option described above, because it omits the flag property for event tracking unless that property is true.hgetall method returned an invalid result, all_flags and all_flags_state would throw an exception. Instead, all_flags will now return an empty dict, and all_flags_state will return a state object with no flags and valid==False. (Thanks, thieman!)message property of the exception, which does not exist in Python 3. This has been fixed. (Thanks, mattbriancon!)LDClient method variation_detail allows you to evaluate a feature flag (using the same parameters as you would for variation) and receive more information about how the value was calculated. This information is returned in an EvaluationDetail object, which contains both the result value and a "reason" object which will tell you, for instance, if the user was individually targeted for the flag or was matched by one of the flag's rules, or if the flag returned the default value due to an error.LDClient method all_flags_state() should be used instead of all_flags() if you are passing flag data to the front end for use with the JavaScript SDK. It preserves some flag metadata that the front end requires in order to send analytics events correctly. Versions 2.5.0 and above of the JavaScript SDK are able to use this metadata, but the output of all_flags_state() will still work with older versions.all_flags_state() method also allows you to select only client-side-enabled flags to pass to the front end, by using the option client_side_only=True.LDClient.all_flags()ERROR level. Previously, this message included the amount of time before the next retry; since that interval is different for each attempt, that meant the ERROR-level messages were all unique, which could cause problems for monitors. This has been changed so the ERROR-level message is always the same, and is followed by an INFO-level message about the time delay. (Note that in order to suppress the default message, the LaunchDarkly client modifies the logger used by the backoff package; if you are using backoff for some other purpose and do want to see the default message, set logging.getLogger('backoff').propagate to True.) (#88)CacheControl package.urllib3 for HTTP requests, rather than the requests package. This change was made because requests has a dependency on an LGPL-licensed package, and some of our customers cannot use LGPL code. The networking behavior of the client should be unchanged.ldclient.get() will return immediately; previously it would continue waiting until a timeout. The is_initialized() method will return false in this case.AttributeError to appear in the log.pylru package, because it uses a GPL license.Config initializer to create a new instance of InMemoryFeatureStore if you omit the feature_store argument. Previously, all Config instances that were created with default parameters would share the same feature store instance.KeyError: 'default') when evaluating a prerequisite flag (and that also prevented an analytics event from being sent for that flag).enableThreads option is absent, as long as the threads option has been set to a number greater than 1. (#84)inline_users_in_events. For more details, see Analytics Data Stream Reference.Config property flush_interval.Config property events_upload_max_batch_size, which is no longer relevant in the new event flushing logic (see above).pip 10.0.0. This should work now (thanks, @theholy7!) with the latest pip as well as previous versions.all_flags method return a dictionary with byte-string keys instead of string keys when using the Redis feature store.FeatureStore interface has been changed to support user segment data as well as feature flags. Existing code that uses InMemoryFeatureStore or RedisFeatureStore should work as before, but custom feature store implementations will need to be updated.This release was broken and has been removed.