Package: optimizely-sdk
Optimizely Feature Experimentation is A/B testing and feature management for product development teams. Experiment in any application. Make every feature on your roadmap an opportunity to learn. Learn more athttps://www.optimizely.com/products/experiment/feature-experimentation/or see our documentation athttps://docs.developers.optimizely.com/experimentation/v4.0.0-full-stack/docs/welcome. # Optimizely Python SDKThis repository houses the Python SDK for use with Optimizely Feature Experimentation and Optimizely Full Stack (legacy).Optimizely Feature Experimentation is an A/B testing and feature management tool for product development teams that enables you to experiment at every step. Using Optimizely Feature Experimentation allows for every feature on your roadmap to be an opportunity to discover hidden insights. Learn more atOptimizely.com, or see thedeveloper documentation.Optimizely Rollouts isfree feature flagsfor development teams. You can easily roll out and roll back features in any application without code deploys, mitigating risk for every feature on your roadmap.Get StartedRefer to thePython SDK's developer documentationfor detailed instructions on getting started with using the SDK.RequirementsVersion5.0+: Python 3.8+, PyPy 3.8+Version4.0+: Python 3.7+, PyPy 3.7+Version3.0+: Python 2.7+, PyPy 3.4+Install the SDKThe SDK is available throughPyPi.To install:pip install optimizely-sdkFeature Management AccessTo access the Feature Management configuration in the Optimizely
dashboard, please contact your Optimizely customer success manager.Use the Python SDKInitializationYou can initialize the Optimizely instance in three ways: with a datafile, by providing an sdk_key, or by providing an implementation ofBaseConfigManager.
Each method is described below.Initialize Optimizely with a datafile. This datafile will be used as
the source of ProjectConfig throughout the life of Optimizely instance:optimizely.Optimizely(
  datafile
)Initialize Optimizely by providing an 'sdk_key'. This will
initialize a PollingConfigManager that makes an HTTP GET request to
the URL (formed using your provided sdk key and the
default datafile CDN URL template) to asynchronously download the
project datafile at regular intervals and update ProjectConfig when
a new datafile is received. A hard-coded datafile can also be
provided along with the sdk_key that will be used
initially before any update:optimizely.Optimizely(
  sdk_key='put_your_sdk_key_here'
)If providing a datafile, the initialization will look like:optimizely.Optimizely(
  datafile=datafile,
  sdk_key='put_your_sdk_key_here'
)Initialize Optimizely by providing a ConfigManager that implementsBaseConfigManager.
You may use ourPollingConfigManagerorAuthDatafilePollingConfigManageras needed:optimizely.Optimizely(
  config_manager=custom_config_manager
)PollingConfigManagerThePollingConfigManagerasynchronously polls for
datafiles from a specified URL at regular intervals by making HTTP requests.polling_config_manager = PollingConfigManager(
    sdk_key=None,
    datafile=None,
    update_interval=None,
    url=None,
    url_template=None,
    logger=None,
    error_handler=None,
    notification_center=None,
    skip_json_validation=False
)Note: You must provide either the sdk_key or URL. If
you provide both, the URL takes precedence.sdk_keyThe sdk_key is used to compose the outbound
HTTP request to the default datafile location on the Optimizely CDN.datafileYou can provide an initial datafile to bootstrap theProjectConfigManagerso that it can be used immediately. The initial
datafile also serves as a fallback datafile if HTTP connection cannot be
established. The initial datafile will be discarded after the first
successful datafile poll.update_intervalThe update_interval is used to specify a fixed
delay in seconds between consecutive HTTP requests for the datafile.urlThe target URL from which to request the datafile.url_templateA string with placeholder{sdk_key}can be provided
so that this template along with the provided sdk key is
used to form the target URL.You may also provide your own logger, error_handler, or
notification_center.AuthDatafilePollingConfigManagerTheAuthDatafilePollingConfigManagerimplementsPollingConfigManagerand asynchronously polls for authenticated datafiles from a specified URL at regular intervals
by making HTTP requests.auth_datafile_polling_config_manager = AuthDatafilePollingConfigManager(
    datafile_access_token,
    *args,
    **kwargs
)Note: To useAuthDatafilePollingConfigManager, you must create a secure environment for
your project and generate an access token for your datafile.datafile_access_tokenThe datafile_access_token is attached to the outbound HTTP request header to authorize the request and fetch the datafile.Advanced configurationThe following properties can be set to override the default
configurations forPollingConfigManagerandAuthDatafilePollingConfigManager.Property NameDefault ValueDescriptionsdk_keyNoneOptimizely project SDK keydatafileNoneInitial datafile, typically sourced from a local cached sourceupdate_interval5 minutesFixed delay between fetches for the datafileurlNoneCustom URL location from which to fetch the datafileurl_templatePollingConfigManager:https://cdn.optimizely.com/datafiles/{sdk_key}.jsonAuthDatafilePollingConfigManager:https://config.optimizely.com/datafiles/auth/{sdk_key}.jsonParameterized datafile URL by SDK keyA notification signal will be triggered whenever anewdatafile is
fetched and Project Config is updated. To subscribe to these
notifications, use:notification_center.add_notification_listener(NotificationTypes.OPTIMIZELY_CONFIG_UPDATE, update_callback)For Further details see the OptimizelyFeature Experimentation documentationto learn how to set up your first Python project and use the SDK.SDK DevelopmentBuilding the SDKBuild and install the SDK with pip, using the following command:pip install -e .Unit TestsRunning all testsTo get test dependencies installed, use a modified version of the
install command:pip install -e '.[test]'You can run all unit tests with:pytestRunning all tests in a fileTo run all tests under a particular test file you can use the following
command:pytest tests.<file_name_without_extension>For example, to run all tests undertest_event_builder, the command would be:pytest tests/test_event_builder.pyRunning all tests under a classTo run all tests under a particular class of tests you can use the
following command:pytest tests/<file_name_with_extension>::ClassNameFor example, to run all tests undertest_event_builder.EventTest, the command
would be:pytest tests/test_event_builder.py::EventTestRunning a single testTo run a single test you can use the following command:pytest tests/<file_name_with_extension>::ClassName::test_nameFor example, to runtest_event_builder.EventTest.test_init, the command
would be:pytest tests/test_event_builder.py::EventTest::test_initContributingPlease seeCONTRIBUTING.CreditsThis software incorporates code from the following open source projects:requests (Apache-2.0 License:https://github.com/psf/requests/blob/master/LICENSE)pyOpenSSL (Apache-2.0 Licensehttps://github.com/pyca/pyopenssl/blob/main/LICENSE)cryptography (Apache-2.0https://github.com/pyca/cryptography/blob/main/LICENSE.APACHE)idna (BSD 3-Clause Licensehttps://github.com/kjd/idna/blob/master/LICENSE.md)Other Optimizely SDKsAgent -https://github.com/optimizely/agentAndroid -https://github.com/optimizely/android-sdkC# -https://github.com/optimizely/csharp-sdkFlutter -https://github.com/optimizely/optimizely-flutter-sdkGo -https://github.com/optimizely/go-sdkJava -https://github.com/optimizely/java-sdkJavaScript -https://github.com/optimizely/javascript-sdkPHP -https://github.com/optimizely/php-sdkPython -https://github.com/optimizely/python-sdkReact -https://github.com/optimizely/react-sdkRuby -https://github.com/optimizely/ruby-sdkSwift -https://github.com/optimizely/swift-sdkOptimizely Python SDK Changelog5.0.0January 18th, 2024New FeaturesThe 5.0.0 release introduces a new primary feature,Advanced Audience Targetingenabled through integration withOptimizely Data Platform (ODP)(#395,#398,#402,#403,#405).You can use ODP, a high-performanceCustomer Data Platform (CDP), to easily create complex real-time segments (RTS) using first-party and 50+ third-party data sources out of the box. You can create custom schemas that support the user attributes important for your business, and stitch together user behavior done on different devices to better understand and target your customers for personalized user experiences. ODP can be used as a single source of truth for these segments in any Optimizely or 3rd party tool.With ODP accounts integrated into Optimizely projects, you can build audiences using segments pre-defined in ODP. The SDK will fetch the segments for given users and make decisions using the segments. For access to ODP audience targeting in your Feature Experimentation account, please contact your Optimizely Customer Success Manager.This version includes the following changes:New API added toOptimizelyUserContext:fetchQualifiedSegments(): this API will retrieve user segments from the ODP server. The fetched segments will be used for audience evaluation. The fetched data will be stored in the local cache to avoid repeated network delays.When anOptimizelyUserContextis created, the SDK will automatically send an identify request to the ODP server to facilitate observing user activities.New APIs added toOptimizelyClient:sendOdpEvent(): customers can build/send arbitrary ODP events that will bind user identifiers and data to user profiles in ODP.For details, refer to our documentation pages:Advanced Audience TargetingServer SDK SupportInitialize Python SDKOptimizelyUserContext Python SDKAdvanced Audience Targeting segment qualification methodsSend Optimizely Data Platform data using Advanced Audience TargetingLoggingAdd warning to polling intervals below 30 seconds (#428)Add warning to duplicate experiment keys (#430)EnhancementsAddedpy.typedto enable external usage of mypy type annotations.Breaking ChangesUpdated minimum supported Python version from 3.7 -> 3.8ODPManagerin the SDK is enabled by default. Unless an ODP account is integrated into the Optimizely projects, mostODPManagerfunctions will be ignored. If needed,ODPManagercan be disabled whenOptimizelyClientis instantiated.BaseConfigManagerabstract class now requires a get_sdk_key method. (#413)PollingConfigManagerrequires either the sdk_key parameter or datafile containing an sdkKey. (#413)AsynchronousBatchEventProcessoris now the default event processor. (#378)5.0.0-betaApr 28th, 2023New FeaturesThe 5.0.0-beta release introduces a new primary feature,Advanced Audience Targetingenabled through integration withOptimizely Data Platform (ODP)(#395,#398,#402,#403,#405).You can use ODP, a high-performanceCustomer Data Platform (CDP), to easily create complex real-time segments (RTS) using first-party and 50+ third-party data sources out of the box. You can create custom schemas that support the user attributes important for your business, and stitch together user behavior done on different devices to better understand and target your customers for personalized user experiences. ODP can be used as a single source of truth for these segments in any Optimizely or 3rd party tool.With ODP accounts integrated into Optimizely projects, you can build audiences using segments pre-defined in ODP. The SDK will fetch the segments for given users and make decisions using the segments. For access to ODP audience targeting in your Feature Experimentation account, please contact your Optimizely Customer Success Manager.This version includes the following changes:New API added toOptimizelyUserContext:fetchQualifiedSegments(): this API will retrieve user segments from the ODP server. The fetched segments will be used for audience evaluation. The fetched data will be stored in the local cache to avoid repeated network delays.When anOptimizelyUserContextis created, the SDK will automatically send an identify request to the ODP server to facilitate observing user activities.New APIs added toOptimizelyClient:sendOdpEvent(): customers can build/send arbitrary ODP events that will bind user identifiers and data to user profiles in ODP.For details, refer to our documentation pages:Advanced Audience TargetingServer SDK SupportInitialize Python SDKOptimizelyUserContext Python SDKAdvanced Audience Targeting segment qualification methodsSend Optimizely Data Platform data using Advanced Audience TargetingBreaking ChangesODPManagerin the SDK is enabled by default. Unless an ODP account is integrated into the Optimizely projects, mostODPManagerfunctions will be ignored. If needed,ODPManagercan be disabled whenOptimizelyClientis instantiated.BaseConfigManagerabstract class now requires a get_sdk_key method. (#413)PollingConfigManagerrequires either the sdk_key parameter or datafile containing an sdkKey. (#413)AsynchronousBatchEventProcessoris now the default event processor. (#378)4.1.1March 10th, 2023We updated our README.md and other non-functional code to reflect that this SDK supports both Optimizely Feature Experimentation and Optimizely Full Stack. (#420)4.1.0July 7th, 2022Bug FixesFix invalid datafile returned fromProjectConfig.to_datafileandOptimizelyConfig.get_datafile(#321,#384)4.0.0January 12th, 2022New FeaturesAdd a set of new APIs for overriding and managing user-level flag, experiment and delivery rule decisions. These methods can be used for QA and automated testing purposes. They are an extension of the OptimizelyUserContext interface (#361,#365,#369):setForcedDecisiongetForcedDecisionremoveForcedDecisionremoveAllForcedDecisionsFor details, refer to our documentation pages:OptimizelyUserContextandForced Decision methods.Breaking Changes:Support forPython v3.4has been dropped as of this release due to a security vulnerability withPyYAML <v5.4. (#366)We no longer supportPython v2.7, v3.5, and v3.6includingPyPyas of this release. (#377)We now supportPython v3.7 and aboveincludingPyPy3.3.10.0September 16th, 2021New FeaturesAdded new public properties to OptimizelyConfig.sdk_key and environment_key [#338] (https://github.com/optimizely/python-sdk/pull/338)attributes and events [#339] (https://github.com/optimizely/python-sdk/pull/339)experiment_rules, delivery_rules, audiences and audiences in OptimizelyExperiment[#342] (https://github.com/optimizely/python-sdk/pull/342)[#351] (https://github.com/optimizely/python-sdk/pull/351/files)For details please refer to our documentation page:Python-sdk: [https://docs.developers.optimizely.com/full-stack/docs/optimizelyconfig-python]OptimizelyFeature.experiments_map of OptimizelyConfig is now deprecated. Please use OptimizelyFeature.experiment_rules and OptimizelyFeature.delivery_rules. [#360] (https://github.com/optimizely/python-sdk/pull/360)Bug FixesFix event processor negative timeout interval when retrieving events from queue. [#356] (https://github.com/optimizely/python-sdk/pull/356)3.9.1July 14th, 2021Bug Fixes:Fixed issue with serving incorrect variation in projects containing multiple flags with duplicate keys. [#347] (https://github.com/optimizely/python-sdk/pull/347)Fixed issue with serving incorrect variation in create_impression_event in user_event_factory.py. [#350] (https://github.com/optimizely/python-sdk/pull/350)3.9.0June 1st, 2021New FeaturesAdded support for multiple concurrent prioritized experiments per flag.#3223.8.0February 12th, 2021New FeaturesNew Features
Introducing a new primary interface for retrieving feature flag status, configuration and associated experiment decisions for users (#309). The newOptimizelyUserContextclass is instantiated withcreate_user_contextand exposes the following APIs to getOptimizelyDecision:set_attributedecidedecide_alldecide_for_keystrack_eventFor details, refer to our documentation page:https://docs.developers.optimizely.com/full-stack/v4.0/docs/python-sdk.3.7.1November 19th, 2020Bug Fixes:Added "enabled" field to decision metadata structure.#3063.7.0November 2nd, 2020New FeaturesAdded support for upcoming application-controlled introduction of tracking for non-experiment Flag decisions.#3003.6.0October 1st, 2020New Features:Version targeting using semantic version syntax.#293Datafile accessor API added to access current config as a JSON string.#283Bug Fixes:Fixed package installation for Python 3.4 and pypy.#2983.5.2July 14th, 2020Bug Fixes:Fixed handling of network and no status code errors when polling for datafile inPollingConfigManagerandAuthDatafilePollingConfigManager. (#287)3.5.1July 10th, 2020Bug Fixes:Fixed HTTP request exception handling inPollingConfigManager. (#285)3.5.0July 9th, 2020New Features:Introduced 2 APIs to interact with feature variables:get_feature_variable_jsonallows you to get value for JSON variables related to a feature.get_all_feature_variablesgets values for all variables under a feature.Added support for fetching authenticated datafiles.AuthDatafilePollingConfigManageris a new config manager that allows you to poll for a datafile belonging to a secure environment. You can create a client by setting thedatafile_access_token.Bug Fixes:Fixed log messages for targeted rollouts evaluation. (#268)3.4.2June 11th, 2020Bug Fixes:Adjusted log level for audience evaluation logs. (#267)3.4.1March 19th, 2020Bug Fixes:Updatedjsonschemato addressinstallation issue.3.4.0January 27th, 2020New Features:Added a new API to get project configuration static data.Callget_optimizely_config()to get a snapshot of project configuration static data.It returns anOptimizelyConfiginstance which includes a datafile revision number, all experiments, and feature flags mapped by their key values.Added caching forget_optimizely_config()-OptimizelyConfigobject will be cached and reused for the lifetime of the datafile.For details, refer to our documentation page:https://docs.developers.optimizely.com/full-stack/docs/optimizelyconfig-python.3.3.1December 16th, 2019Bug Fixes:Fixedinstallation issueon Windows. (#224)Fixed batch event processor deadline reset issue. (#227)Added more batch event processor debug messages. (#227)3.3.0October 28th, 2019New Features:Added support for event batching via the event processor.Events generated by methods likeactivate,track, andis_feature_enabledwill be held in a queue until the configured batch size is reached, or the configured flush interval has elapsed. Then, they will be batched into a single payload and sent to the event dispatcher.To configure event batching, set thebatch_sizeandflush_intervalproperties when initializing instance ofBatchEventProcessor.Event batching is disabled by default. You can pass in instance ofBatchEventProcessorwhen creatingOptimizelyinstance to enable event batching.Users can subscribe toLogEventnotification to be notified of whenever a payload consisting of a batch of user events is handed off to the event dispatcher to send to Optimizely's backend.Introduced blocking timeout inPollingConfigManager. By default, calls toget_configwill block for maximum of 10 seconds until config is available.Bug Fixes:Fixed incorrect log message when numeric metric is not used. (#217)3.2.0August 27th, 2019New Features:Added support for automatic datafile management viaPollingConfigManager:ThePollingConfigManageris an implementation of theBaseConfigManager.Users may provide one of datafile or SDK key (sdk_key) or both tooptimizely.Optimizely. Based on that, the SDK will use theStaticConfigManageror thePollingConfigManager. Refer to theREADMEfor more instructions.An initial datafile can be provided to thePollingConfigManagerto bootstrap before making HTTP requests for the hosted datafile.Requests for the datafile are made in a separate thread and are scheduled with fixed delay.Configuration updates can be subscribed to by adding the OPTIMIZELY_CONFIG_UPDATE notification listener.IntroducedOptimizely.get_feature_variableAPI.  (#191)Deprecated:NotificationCenter.clear_notificationsis deprecated as of this release. Please useNotificationCenter.clear_notification_listeners.  (#182)NotificationCenter.clear_all_notificationsis deprecated as of this release. Please useNotificationCenter.clear_all_notification_listeners.  (#182)3.2.0b1July 26th, 2019New Features:Added support for automatic datafile management viaPollingConfigManager:ThePollingConfigManageris an implementation of theBaseConfigManager.Users may provide one of datafile or SDK key (sdk_key) or both tooptimizely.Optimizely. Based on that, the SDK will use theStaticConfigManageror thePollingConfigManager. Refer to theREADMEfor more instructions.An initial datafile can be provided to thePollingConfigManagerto bootstrap before making HTTP requests for the hosted datafile.Requests for the datafile are made in a separate thread and are scheduled with fixed delay.Configuration updates can be subscribed to by adding the OPTIMIZELY_CONFIG_UPDATE notification listener.IntroducedOptimizely.get_feature_variableAPI.  (#191)Deprecated:NotificationCenter.clear_notificationsis deprecated as of this release. Please useNotificationCenter.clear_notification_listeners.  (#182)NotificationCenter.clear_all_notificationsis deprecated as of this release. Please useNotificationCenter.clear_all_notification_listeners.  (#182)3.1.0May 3rd, 2019New Features:Introduced Decision notification listener to be able to record:Variation assignments for users activated in an experiment.Feature access for users.Feature variable value for users.Bug Fixes:Feature variable APIs now return default variable value when featureEnabled property is false.  (#171)Deprecated:Activate notification listener is deprecated as of this release.  Recommendation is to use the new Decision notification listener.  Activate notification listener will be removed in the next major release.3.0.0March 1st, 2019The 3.0 release improves event tracking and supports additional audience
targeting functionality.New Features:Event tracking:Thetrackmethod now dispatches its conversion eventunconditionally, without first determining whether the user is targeted by a known experiment that uses the event. This may increase outbound network traffic.In Optimizely results, conversion events sent by 3.0 SDKs don't explicitly name the experiments and variations that are currently targeted to the user. Instead, conversions are automatically attributed to variations that the user has previously seen, as long as those variations were served via 3.0 SDKs or by other clients capable of automatic attribution, and as long as our backend actually received the impression events for those variations.Altogether, this allows you to track conversion events and attribute them to variations even when you don't know all of a user's attribute values, and even if the user's attribute values or the experiment's configuration have changed such that the user is no longer affected by the experiment. As a result,you may observe an increase in the conversion rate for previously-instrumented events.If that is undesirable, you can reset the results of previously-running experiments after upgrading to the 3.0 SDK.  -   This will also allow you to attribute events to variations from other Optimizely projects in your account, even though those experiments don't appear in the same datafile.Note that for results segmentation in Optimizely results, the user attribute values from one event are automatically applied to all other events in the same session, as long as the events in question were actually received by our backend. This behavior was already in place and is not affected by the 3.0 release.Support for all types of attribute values, not just strings.All values are passed through to notification listeners.Strings, booleans, and valid numbers are passed to the event dispatcher and can be used for Optimizely results segmentation.  A valid number is a finite float or numbers.Integral in the inclusive range [-2 ^ 53, 2 ^ 53].Strings, booleans, and valid numbers are relevant for audience conditions.Support for additional matchers in audience conditions:Anexistsmatcher that passes if the user has a non-null value for the targeted user attribute and fails otherwise.Asubstringmatcher that resolves if the user has a string value for the targeted attribute.gt(greater than) andlt(less than) matchers that resolve if the user has a valid number value for the targeted attribute.  A valid number is a finite float or numbers.Integral in the inclusive range [-2 ^ 53, 2 ^ 53].The original (exact) matcher can now be used to target booleans and valid numbers, not just strings.Support for A/B tests, feature tests, and feature rollouts whose audiences are combined using"and"and"not"operators, not just the"or"operator.Datafile-version compatibility check: The SDK will remain uninitialized (i.e., will gracefully fail to activate experiments and features) if given a datafile version greater than 4.Updated Pull Request template and commit message guidelines.Breaking Changes:Conversion events sent by 3.0 SDKs don't explicitly name the experiments and variations that are currently targeted to the user, so these events are unattributed in raw events data export. You must use the newresultsexport to determine the variations to which events have been attributed.Previously, notification listeners were only given string-valued user attributes because only strings could be passed into various method calls. That is no longer the case. You may pass non-string attribute values, and if you do, you must update your notification listeners to be able to receive whatever values you pass in.Bug Fixes:Experiments and features can no longer activate when a negatively targeted attribute has a missing, null, or malformed value.Audience conditions (except for the newexistsmatcher) no longer resolve tofalsewhen they fail to find an legitimate value for the targeted user attribute. The result remainsnull(unknown). Therefore, an audience that negates such a condition (using the"not"operator) can no longer resolve totrueunless there is an unrelated branch in the condition tree that itself resolves totrue.Updated the default event dispatcher to log an error if the request resolves to HTTP 4xx or 5xx.  (#140)All methods now validate that user IDs are strings and that experiment keys, feature keys, feature variable keys, and event keys are non-empty strings.2.1.1August 21st, 2018Fix: record conversions for all experiments using an event when using track(#136).2.1.0July 2nd, 2018Introduced support for bot filtering (#121).Overhauled logging to use standard Python logging (#123).2.0.1June 19th, 2018Fix: send impression event for Feature Test when Feature is disabled (#128).2.0.0April 12th, 2018This major release introduces APIs for Feature Management. It also
introduces some breaking changes listed below.New FeaturesIntroduced theis_feature_enabledAPI to determine whether to show a feature to a user or not.is_enabled = optimizel_client.is_feature_enabled('my_feature_key', 'my_user', user_attributes)All enabled features for the user can be retrieved by calling:enabled_features = optimizely_client.get_enabled_features('my_user', user_attributes)Introduced Feature Variables to configure or parameterize a feature.  There are four variable types:String,Integer,Double,Boolean.string_variable = optimizely_client.get_feature_variable_string('my_feature_key', 'string_variable_key', 'my_user')
    integer_variable = optimizely_client.get_feature_variable_integer('my_feature_key', 'integer_variable_key', 'my_user')
    double_variable = optimizely_client.get_feature_variable_double('my_feature_key', 'double_variable_key', 'my_user')
    boolean_variable = optimizely_client.get_feature_variable_boolean('my_feature_key', 'boolean_variable_key', 'my_user')Breaking changesThetrackAPI with revenue value as a stand-alone parameter has been removed. The revenue value should be passed in as an entry in the event tags dict. The key for the revenue tag isrevenueand the passed in value will be treated by Optimizely as the value for computing results.event_tags = {
      'revenue': 1200
    }

    optimizely_client.track('event_key', 'my_user', user_attributes, event_tags)2.0.0b1March 29th, 2018This beta release introduces APIs for Feature Management. It also
introduces some breaking changes listed below.New FeaturesIntroduced theis_feature_enabledAPI to determine whether to show a feature to a user or not.is_enabled = optimizel_client.is_feature_enabled('my_feature_key', 'my_user', user_attributes)All enabled features for the user can be retrieved by calling:enabled_features = optimizely_client.get_enabled_features('my_user', user_attributes)Introduced Feature Variables to configure or parameterize a feature.  There are four variable types:String,Integer,Double,Boolean.string_variable = optimizely_client.get_feature_variable_string('my_feature_key', 'string_variable_key', 'my_user')
    integer_variable = optimizely_client.get_feature_variable_integer('my_feature_key', 'integer_variable_key', 'my_user')
    double_variable = optimizely_client.get_feature_variable_double('my_feature_key', 'double_variable_key', 'my_user')
    boolean_variable = optimizely_client.get_feature_variable_boolean('my_feature_key', 'boolean_variable_key', 'my_user')Breaking changesThetrackAPI with revenue value as a stand-alone parameter has been removed. The revenue value should be passed in as an entry in the event tags dict. The key for the revenue tag isrevenueand the passed in value will be treated by Optimizely as the value for computing results.event_tags = {
      'revenue': 1200
    }

    optimizely_client.track('event_key', 'my_user', user_attributes, event_tags)1.4.0Added support for IP anonymization.Added support for notification listeners.Added support for bucketing ID.Updated mmh3 to handle installation failures on Windows 10.1.3.0Introduced support for forced bucketing.Introduced support for numeric metrics.Updated event builder to support new endpoint.1.2.1Removed older feature flag parsing.1.2.0Added user profile service.1.1.1Updated datafile parsing to be able to handle additional fields.Deprecated Classic project support.1.1.0Included datafile revision information in log events.Added event tags to track API to allow users to pass in event metadata.Deprecated theevent_valueparameter from the track method. Should useevent_tagsto pass in event value instead.Updated event logging endpoint to logx.optimizely.com.1.0.0Introduced support for Full Stack projects in Optimizely X. No breaking changes from previous version.Introduced more graceful exception handling in instantiation and core methods.Updated whitelisting to precede audience matching.0.1.3Added support for v2 endpoint and datafile.Updated dispatch_event to consume an Event object instead of url and params. The Event object comprises of four properties: url (string representing URL to dispatch event to), params (dict representing the params to be set for the event), http_verb (one of 'GET' or 'POST') and headers (header values to be sent along).Fixed issue with tracking events for experiments in groups.0.1.2Updated requirements file.0.1.1Introduced option to skip JSON schema validation.0.1.0Beta release of the Python SDK for server-side testing.