optimizely-sdk 5.4.0
Python SDK for Optimizely Feature Experimentation, Optimizely Full Stack (legacy), and Optimizely Rollouts.

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 at https://www.optimizely.com/products/experiment/feature-experimentation/ or see our documentation at https://docs.developers.optimizely.com/experimentation/v4.0.0-full-stack/docs/welcome. # Optimizely Python SDK

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This 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 at [Optimizely.com](https://www.optimizely.com/products/experiment/feature-experimentation/), or see the [developer documentation](https://docs.developers.optimizely.com/experimentation/v4.0.0-full-stack/docs/welcome).

Optimizely Rollouts is [free feature flags](https://www.optimizely.com/free-feature-flagging/) for 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 Started

Refer to the [Python SDK's developer documentation](https://docs.developers.optimizely.com/experimentation/v4.0.0-full-stack/docs/python-sdk) for detailed instructions on getting started with using the SDK.

### Requirements

Version `5.0+`: Python 3.8+, PyPy 3.8+

Version `4.0+`: Python 3.7+, PyPy 3.7+

Version `3.0+`: Python 2.7+, PyPy 3.4+

### Install the SDK

The SDK is available through [PyPi](https://pypi.python.org/pypi?name=optimizely-sdk&:action=display).

To install:

    pip install optimizely-sdk

### Feature Management Access

To access the Feature Management configuration in the Optimizely
dashboard, please contact your Optimizely customer success manager.

## Use the Python SDK

### Initialization

You can initialize the Optimizely instance in three ways: with a datafile, by providing an sdk_key, or by providing an implementation of
[BaseConfigManager](https://github.com/optimizely/python-sdk/tree/master/optimizely/config_manager.py#L32).
Each method is described below.

1.  Initialize Optimizely with a datafile. This datafile will be used as
    the source of ProjectConfig throughout the life of Optimizely instance:

        optimizely.Optimizely(
          datafile
        )

2.  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'
        )

3.  Initialize Optimizely by providing a ConfigManager that implements
    [BaseConfigManager](https://github.com/optimizely/python-sdk/tree/master/optimizely/config_manager.py#L34).
    You may use our [PollingConfigManager](https://github.com/optimizely/python-sdk/blob/master/optimizely/config_manager.py#L150) or
    [AuthDatafilePollingConfigManager](https://github.com/optimizely/python-sdk/blob/master/optimizely/config_manager.py#L375) as needed:

        optimizely.Optimizely(
          config_manager=custom_config_manager
        )

### PollingConfigManager

The [PollingConfigManager](https://github.com/optimizely/python-sdk/blob/master/optimizely/config_manager.py#L150) asynchronously 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_key** The sdk_key is used to compose the outbound
HTTP request to the default datafile location on the Optimizely CDN.

**datafile** You can provide an initial datafile to bootstrap the
`ProjectConfigManager` so 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_interval** The update_interval is used to specify a fixed
delay in seconds between consecutive HTTP requests for the datafile.

**url** The target URL from which to request the datafile.

**url_template** A 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.

### AuthDatafilePollingConfigManager

The [AuthDatafilePollingConfigManager](https://github.com/optimizely/python-sdk/blob/master/optimizely/config_manager.py#L375)
implements `PollingConfigManager` and 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 use [AuthDatafilePollingConfigManager](#authdatafilepollingconfigmanager), you must create a secure environment for
your project and generate an access token for your datafile.

**datafile_access_token** The datafile_access_token is attached to the outbound HTTP request header to authorize the request and fetch the datafile.

### Advanced configuration

The following properties can be set to override the default
configurations for [PollingConfigManager](#pollingconfigmanager) and [AuthDatafilePollingConfigManager](#authdatafilepollingconfigmanager).

| **Property Name** |                                                                                    **Default Value**                                                                                    |                        **Description**                         |
| :---------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------: |
|      sdk_key      |                                                                                          None                                                                                           |                   Optimizely project SDK key                   |
|     datafile      |                                                                                          None                                                                                           | Initial datafile, typically sourced from a local cached source |
|  update_interval  |                                                                                        5 minutes                                                                                        |          Fixed delay between fetches for the datafile          |
|        url        |                                                                                          None                                                                                           |      Custom URL location from which to fetch the datafile      |
|   url_template    | `PollingConfigManager:`<br/>https://cdn.optimizely.com/datafiles/{sdk_key}.json<br/>`AuthDatafilePollingConfigManager:`<br/>https://config.optimizely.com/datafiles/auth/{sdk_key}.json |             Parameterized datafile URL by SDK key              |

A notification signal will be triggered whenever a _new_ datafile 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 Optimizely [Feature Experimentation documentation](https://docs.developers.optimizely.com/experimentation/v4.0.0-full-stack/docs/welcome)
to learn how to set up your first Python project and use the SDK.

## SDK Development

### Building the SDK

Build and install the SDK with pip, using the following command:

    pip install -e .

### Unit Tests

#### Running all tests

To get test dependencies installed, use a modified version of the
install command:

    pip install -e '.[test]'

You can run all unit tests with:

    pytest

#### Running all tests in a file

To 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 under `test_event_builder`, the command would be:

    pytest tests/test_event_builder.py

#### Running all tests under a class

To run all tests under a particular class of tests you can use the
following command:

    pytest tests/<file_name_with_extension>::ClassName

For example, to run all tests under `test_event_builder.EventTest`, the command
would be:

    pytest tests/test_event_builder.py::EventTest

#### Running a single test

To run a single test you can use the following command:

    pytest tests/<file_name_with_extension>::ClassName::test_name

For example, to run `test_event_builder.EventTest.test_init`, the command
would be:

    pytest tests/test_event_builder.py::EventTest::test_init

### Contributing

Please see [CONTRIBUTING](https://github.com/optimizely/python-sdk/blob/master/CONTRIBUTING.md).

### Credits

This software incorporates code from the following open source projects:

requests (Apache-2.0 License: https://github.com/psf/requests/blob/master/LICENSE)

idna (BSD 3-Clause License https://github.com/kjd/idna/blob/master/LICENSE.md)

### Other Optimizely SDKs

- Agent - https://github.com/optimizely/agent

- Android - https://github.com/optimizely/android-sdk

- C# - https://github.com/optimizely/csharp-sdk

- Flutter - https://github.com/optimizely/optimizely-flutter-sdk

- Go - https://github.com/optimizely/go-sdk

- Java - https://github.com/optimizely/java-sdk

- JavaScript - https://github.com/optimizely/javascript-sdk

- PHP - https://github.com/optimizely/php-sdk

- Python - https://github.com/optimizely/python-sdk

- React - https://github.com/optimizely/react-sdk

- Ruby - https://github.com/optimizely/ruby-sdk

- Swift - https://github.com/optimizely/swift-sdk
# Optimizely Python SDK Changelog

## 5.4.0
December 19th, 2025

### New Features

Holdout features:

- Added support for Holdouts in Feature Experimentation, enabling global traffic exclusion from experiments for statistical confidence validation. ([#469](https://github.com/optimizely/python-sdk/pull/469))
- Added holdout support for default decision service ([#467](https://github.com/optimizely/python-sdk/pull/467))
- Project Config updated for Holdout ([#464](https://github.com/optimizely/python-sdk/pull/464))

---

### Bug Fixes
- Resolved issues with Holdout impression event handling and notification delivery. ([#471](https://github.com/optimizely/python-sdk/pull/471))

---


## 5.3.0
November 13th, 2025

This release introduces **Contextual Multi-Armed Bandit (CMAB)** support in the Optimizely Python SDK along with several enhancements, bug fixes, and infrastructure improvements.

---

### New Features

#### **CMAB Support**

A major addition in this release is support for **Contextual Multi-Armed Bandit (CMAB)**, enabling adaptive experimentation based on contextual user data.

The CMAB feature includes:

- CMAB Client and Service implementations to communicate with CMAB APIs ([#453](https://github.com/optimizely/python-sdk/pull/453), [#455](https://github.com/optimizely/python-sdk/pull/455))
- Decision Service updates to handle CMAB-based decisioning ([#457](https://github.com/optimizely/python-sdk/pull/457))
- Impression event updates to include CMAB UUID ([#458](https://github.com/optimizely/python-sdk/pull/458))
- Cache system enhancements including a new `remove()` method for CMAB cache ([#454](https://github.com/optimizely/python-sdk/pull/454))
- Configuration options to customize CMAB cache parameters ([#463](https://github.com/optimizely/python-sdk/pull/463))
- Exposure of CMAB prediction endpoint for programmatic access ([#466](https://github.com/optimizely/python-sdk/pull/466))

These updates collectively enable Python SDK users to leverage machine learning–driven bandit optimization strategies within Optimizely Feature Experimentation.

---

#### **Multi-Region Data Hosting**

- Added SDK support for multi-region data hosting, allowing projects to specify their data residency region ([#459](https://github.com/optimizely/python-sdk/pull/459)).

---

### Security Fixes

- Addressed a CSRF security warning by properly importing and registering `CSRFProtect`  
  ([#448](https://github.com/optimizely/python-sdk/pull/448), [#450](https://github.com/optimizely/python-sdk/pull/450), [#452](https://github.com/optimizely/python-sdk/pull/452)).

---

### Enhancements

- Updated project configuration to track CMAB properties ([#451](https://github.com/optimizely/python-sdk/pull/451)).
- Removed unused `testapp` folder from tests as part of maintenance cleanup ([#461](https://github.com/optimizely/python-sdk/pull/461)).

---

### Bug Fixes

- Fixed concurrency issues in CMAB service to ensure thread-safe cache and decision logic ([#462](https://github.com/optimizely/python-sdk/pull/462)).

---

### New Contributors

- [@esrakartalOpt](https://github.com/esrakartalOpt) made their first contribution in [#459](https://github.com/optimizely/python-sdk/pull/459).

---


## 5.2.0
February 26, 2025

Python threads have been named.

`PollingConfigManager` now has another optional parameter `retries` that will control how many times the SDK will attempt to get the datafile if the connection fails. Previously, the SDK would only try once. Now it defaults to maximum of three attempts. When sending event data, the SDK will attempt to send event data up to three times, where as before it would only attempt once.

## 5.1.0
November 27th, 2024

Added support for batch processing in DecideAll and DecideForKeys, enabling more efficient handling of multiple decisions in the User Profile Service.([#440](https://github.com/optimizely/python-sdk/pull/440))

## 5.0.1
June 26th, 2024

We removed redundant dependencies pyOpenSSL and cryptography ([#435](https://github.com/optimizely/python-sdk/pull/435), [#436](https://github.com/optimizely/python-sdk/pull/436)).

## 5.0.0
January 18th, 2024

### New Features

The 5.0.0 release introduces a new primary feature, [Advanced Audience Targeting]( https://docs.developers.optimizely.com/feature-experimentation/docs/optimizely-data-platform-advanced-audience-targeting) enabled through integration with [Optimizely Data Platform (ODP)](https://docs.developers.optimizely.com/optimizely-data-platform/docs) ([#395](https://github.com/optimizely/python-sdk/pull/395), [#398](https://github.com/optimizely/python-sdk/pull/398), [#402](https://github.com/optimizely/python-sdk/pull/402), [#403](https://github.com/optimizely/python-sdk/pull/403), [#405](https://github.com/optimizely/python-sdk/pull/405)).

You can use ODP, a high-performance [Customer Data Platform (CDP)]( https://www.optimizely.com/optimization-glossary/customer-data-platform/), 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 to `OptimizelyUserContext`:

  * `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 an `OptimizelyUserContext` is created, the SDK will automatically send an identify request to the ODP server to facilitate observing user activities.

* New APIs added to `OptimizelyClient`:

  * `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 Targeting](https://docs.developers.optimizely.com/feature-experimentation/docs/optimizely-data-platform-advanced-audience-targeting)
* [Server SDK Support](https://docs.developers.optimizely.com/feature-experimentation/v1.0/docs/advanced-audience-targeting-for-server-side-sdks)
* [Initialize Python SDK](https://docs.developers.optimizely.com/feature-experimentation/docs/initialize-sdk-python)
* [OptimizelyUserContext Python SDK](https://docs.developers.optimizely.com/feature-experimentation/docs/wip-fsodp-optimizelyusercontext-python)
* [Advanced Audience Targeting segment qualification methods](https://docs.developers.optimizely.com/feature-experimentation/v1.0/docs/advanced-audience-targeting-segment-qualification-methods-python)
* [Send Optimizely Data Platform data using Advanced Audience Targeting](https://docs.developers.optimizely.com/feature-experimentation/v1.0/docs/send-odp-data-using-advanced-audience-targeting-python)

### Logging

* Add warning to polling intervals below 30 seconds ([#428](https://github.com/optimizely/python-sdk/pull/428))
* Add warning to duplicate experiment keys ([#430](https://github.com/optimizely/python-sdk/pull/430))

### Enhancements
* Added `py.typed` to enable external usage of mypy type annotations.

### Breaking Changes
* Updated minimum supported Python version from 3.7 -> 3.8
* `ODPManager` in the SDK is enabled by default. Unless an ODP account is integrated into the Optimizely projects, most `ODPManager` functions will be ignored. If needed, `ODPManager` can be disabled when `OptimizelyClient` is instantiated.
* `BaseConfigManager` abstract class now requires a get_sdk_key method. ([#413](https://github.com/optimizely/python-sdk/pull/413))
* `PollingConfigManager` requires either the sdk_key parameter or datafile containing an sdkKey. ([#413](https://github.com/optimizely/python-sdk/pull/413))
* Asynchronous `BatchEventProcessor` is now the default event processor. ([#378](https://github.com/optimizely/python-sdk/pull/378))

## 5.0.0-beta
Apr 28th, 2023

### New Features

The 5.0.0-beta release introduces a new primary feature, [Advanced Audience Targeting]( https://docs.developers.optimizely.com/feature-experimentation/docs/optimizely-data-platform-advanced-audience-targeting) enabled through integration with [Optimizely Data Platform (ODP)](https://docs.developers.optimizely.com/optimizely-data-platform/docs) ([#395](https://github.com/optimizely/python-sdk/pull/395), [#398](https://github.com/optimizely/python-sdk/pull/398), [#402](https://github.com/optimizely/python-sdk/pull/402), [#403](https://github.com/optimizely/python-sdk/pull/403), [#405](https://github.com/optimizely/python-sdk/pull/405)).

You can use ODP, a high-performance [Customer Data Platform (CDP)]( https://www.optimizely.com/optimization-glossary/customer-data-platform/), 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 to `OptimizelyUserContext`:

  * `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 an `OptimizelyUserContext` is created, the SDK will automatically send an identify request to the ODP server to facilitate observing user activities.

* New APIs added to `OptimizelyClient`:

  * `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 Targeting](https://docs.developers.optimizely.com/feature-experimentation/docs/optimizely-data-platform-advanced-audience-targeting)
* [Server SDK Support](https://docs.developers.optimizely.com/feature-experimentation/v1.0/docs/advanced-audience-targeting-for-server-side-sdks)
* [Initialize Python SDK](https://docs.developers.optimizely.com/feature-experimentation/docs/initialize-sdk-python)
* [OptimizelyUserContext Python SDK](https://docs.developers.optimizely.com/feature-experimentation/docs/wip-fsodp-optimizelyusercontext-python)
* [Advanced Audience Targeting segment qualification methods](https://docs.developers.optimizely.com/feature-experimentation/v1.0/docs/advanced-audience-targeting-segment-qualification-methods-python)
* [Send Optimizely Data Platform data using Advanced Audience Targeting](https://docs.developers.optimizely.com/feature-experimentation/v1.0/docs/send-odp-data-using-advanced-audience-targeting-python)

### Breaking Changes

* `ODPManager` in the SDK is enabled by default. Unless an ODP account is integrated into the Optimizely projects, most `ODPManager` functions will be ignored. If needed, `ODPManager` can be disabled when `OptimizelyClient` is instantiated.
* `BaseConfigManager` abstract class now requires a get_sdk_key method. ([#413](https://github.com/optimizely/python-sdk/pull/413))
* `PollingConfigManager` requires either the sdk_key parameter or datafile containing an sdkKey. ([#413](https://github.com/optimizely/python-sdk/pull/413))
* Asynchronous `BatchEventProcessor` is now the default event processor. ([#378](https://github.com/optimizely/python-sdk/pull/378))

## 4.1.1
March 10th, 2023

We updated our README.md and other non-functional code to reflect that this SDK supports both Optimizely Feature Experimentation and Optimizely Full Stack. ([#420](https://github.com/optimizely/python-sdk/pull/420))

## 4.1.0
July 7th, 2022

### Bug Fixes
* Fix invalid datafile returned from `ProjectConfig.to_datafile` and `OptimizelyConfig.get_datafile` ([#321](https://github.com/optimizely/python-sdk/pull/321), [#384](https://github.com/optimizely/python-sdk/pull/384))

## 4.0.0
January 12th, 2022

### New Features
* Add 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](https://github.com/optimizely/python-sdk/pull/361), [#365](https://github.com/optimizely/python-sdk/pull/365), [#369](https://github.com/optimizely/python-sdk/pull/369)):
	- setForcedDecision
	- getForcedDecision
	- removeForcedDecision
	- removeAllForcedDecisions

* For details, refer to our documentation pages: [OptimizelyUserContext](https://docs.developers.optimizely.com/full-stack/v4.0/docs/optimizelyusercontext-python) and [Forced Decision methods](https://docs.developers.optimizely.com/full-stack/v4.0/docs/forced-decision-methods-python).

### Breaking Changes:

* Support for `Python v3.4` has been dropped as of this release due to a security vulnerability with `PyYAML <v5.4`. ([#366](https://github.com/optimizely/python-sdk/pull/366))
* We no longer support `Python v2.7, v3.5, and v3.6` including `PyPy` as of this release. ([#377](https://github.com/optimizely/python-sdk/pull/373))
* We now support `Python v3.7 and above` including `PyPy3`.

## 3.10.0
September 16th, 2021

### New Features
* Added 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 Fixes
* Fix event processor negative timeout interval when retrieving events from queue. [#356] (https://github.com/optimizely/python-sdk/pull/356)

## 3.9.1
July 14th, 2021

### Bug 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)

## 3.9.0
June 1st, 2021

### New Features
* Added support for multiple concurrent prioritized experiments per flag. [#322](https://github.com/optimizely/python-sdk/pull/322)

## 3.8.0
February 12th, 2021

### New Features
* New Features
Introducing a new primary interface for retrieving feature flag status, configuration and associated experiment decisions for users ([#309](https://github.com/optimizely/python-sdk/pull/309)). The new `OptimizelyUserContext` class is instantiated with `create_user_context` and exposes the following APIs to get `OptimizelyDecision`:

    - set_attribute
    - decide
    - decide_all
    - decide_for_keys
    - track_event

For details, refer to our documentation page: https://docs.developers.optimizely.com/full-stack/v4.0/docs/python-sdk.

## 3.7.1
November 19th, 2020

### Bug Fixes:
* Added "enabled" field to decision metadata structure. [#306](https://github.com/optimizely/python-sdk/pull/306)

## 3.7.0
November 2nd, 2020

### New Features
* Added support for upcoming application-controlled introduction of tracking for non-experiment Flag decisions. [#300](https://github.com/optimizely/python-sdk/pull/300)

## 3.6.0
October 1st, 2020

### New Features:
* Version targeting using semantic version syntax. [#293](https://github.com/optimizely/python-sdk/pull/293)
* Datafile accessor API added to access current config as a JSON string. [#283](https://github.com/optimizely/python-sdk/pull/283)

### Bug Fixes:
* Fixed package installation for Python 3.4 and pypy. [#298](https://github.com/optimizely/python-sdk/pull/298)

## 3.5.2
July 14th, 2020

### Bug Fixes:
* Fixed handling of network and no status code errors when polling for datafile in `PollingConfigManager` and `AuthDatafilePollingConfigManager`. ([#287](https://github.com/optimizely/python-sdk/pull/287))

## 3.5.1
July 10th, 2020

### Bug Fixes:
* Fixed HTTP request exception handling in `PollingConfigManager`. ([#285](https://github.com/optimizely/python-sdk/pull/285))

## 3.5.0
July 9th, 2020

### New Features:
* Introduced 2 APIs to interact with feature variables:
  * `get_feature_variable_json` allows you to get value for JSON variables related to a feature.
  * `get_all_feature_variables` gets values for all variables under a feature.
* Added support for fetching authenticated datafiles. `AuthDatafilePollingConfigManager` is a new config manager that allows you to poll for a datafile belonging to a secure environment. You can create a client by setting the `datafile_access_token`.

### Bug Fixes:
* Fixed log messages for targeted rollouts evaluation. ([#268](https://github.com/optimizely/python-sdk/pull/268))

## 3.4.2
June 11th, 2020

### Bug Fixes:
* Adjusted log level for audience evaluation logs. ([#267](https://github.com/optimizely/python-sdk/pull/267))

## 3.4.1
March 19th, 2020

### Bug Fixes:
* Updated `jsonschema` to address [installation issue](https://github.com/optimizely/python-sdk/issues/232).

## 3.4.0
January 27th, 2020

### New Features:
* Added a new API to get project configuration static data.
  * Call `get_optimizely_config()` to get a snapshot of project configuration static data.
  * It returns an `OptimizelyConfig` instance which includes a datafile revision number, all experiments, and feature flags mapped by their key values.
  * Added caching for `get_optimizely_config()` - `OptimizelyConfig` object 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](https://docs.developers.optimizely.com/full-stack/docs/optimizelyconfig-python).


## 3.3.1
December 16th, 2019

### Bug Fixes:
* Fixed [installation issue](https://github.com/optimizely/python-sdk/issues/220) on Windows. ([#224](https://github.com/optimizely/python-sdk/pull/224))
* Fixed batch event processor deadline reset issue. ([#227](https://github.com/optimizely/python-sdk/pull/227))
* Added more batch event processor debug messages. ([#227](https://github.com/optimizely/python-sdk/pull/227))

## 3.3.0
October 28th, 2019

### New Features:
* Added support for event batching via the event processor.
  * Events generated by methods like `activate`, `track`, and `is_feature_enabled` will 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 the `batch_size` and `flush_interval` properties when initializing instance of [BatchEventProcessor](https://github.com/optimizely/python-sdk/blob/3.3.x/optimizely/event/event_processor.py#L45).
  * Event batching is disabled by default. You can pass in instance of `BatchEventProcessor` when creating `Optimizely` instance to enable event batching.
  * Users can subscribe to `LogEvent` notification 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 in `PollingConfigManager`. By default, calls to `get_config` will block for maximum of 10 seconds until config is available.

### Bug Fixes:
* Fixed incorrect log message when numeric metric is not used. ([#217](https://github.com/optimizely/python-sdk/pull/217))

## 3.2.0
August 27th, 2019

### New Features:
* Added support for automatic datafile management via [PollingConfigManager](https://github.com/optimizely/python-sdk/blob/3.2.x/optimizely/config_manager.py#L151):
  * The [PollingConfigManager](https://github.com/optimizely/python-sdk/blob/3.2.x/optimizely/config_manager.py#L151) is an implementation of the [BaseConfigManager](https://github.com/optimizely/python-sdk/blob/3.2.x/optimizely/config_manager.py#L32).
  * Users may provide one of datafile or SDK key (sdk_key) or both to `optimizely.Optimizely`. Based on that, the SDK will use the [StaticConfigManager](https://github.com/optimizely/python-sdk/blob/3.2.x/optimizely/config_manager.py#L73) or the [PollingConfigManager](https://github.com/optimizely/python-sdk/blob/3.2.x/optimizely/config_manager.py#L151). Refer to the [README](README.md) for more instructions.
  * An initial datafile can be provided to the `PollingConfigManager` to 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.
* Introduced `Optimizely.get_feature_variable` API.  ([#191](https://github.com/optimizely/python-sdk/pull/191))

### Deprecated:

* `NotificationCenter.clear_notifications` is deprecated as of this release. Please use `NotificationCenter.clear_notification_listeners`.  ([#182](https://github.com/optimizely/python-sdk/pull/182))
* `NotificationCenter.clear_all_notifications` is deprecated as of this release. Please use `NotificationCenter.clear_all_notification_listeners`.  ([#182](https://github.com/optimizely/python-sdk/pull/182))

## 3.2.0b1
July 26th, 2019

### New Features:
* Added support for automatic datafile management via [PollingConfigManager](https://github.com/optimizely/python-sdk/blob/3.2.x/optimizely/config_manager.py#L151):
  * The [PollingConfigManager](https://github.com/optimizely/python-sdk/blob/3.2.x/optimizely/config_manager.py#L151) is an implementation of the [BaseConfigManager](https://github.com/optimizely/python-sdk/blob/3.2.x/optimizely/config_manager.py#L32).
  * Users may provide one of datafile or SDK key (sdk_key) or both to `optimizely.Optimizely`. Based on that, the SDK will use the [StaticConfigManager](https://github.com/optimizely/python-sdk/blob/3.2.x/optimizely/config_manager.py#L73) or the [PollingConfigManager](https://github.com/optimizely/python-sdk/blob/3.2.x/optimizely/config_manager.py#L151). Refer to the [README](README.md) for more instructions.
  * An initial datafile can be provided to the `PollingConfigManager` to 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.
* Introduced `Optimizely.get_feature_variable` API.  ([#191](https://github.com/optimizely/python-sdk/pull/191))

### Deprecated:

* `NotificationCenter.clear_notifications` is deprecated as of this release. Please use `NotificationCenter.clear_notification_listeners`.  ([#182](https://github.com/optimizely/python-sdk/pull/182))
* `NotificationCenter.clear_all_notifications` is deprecated as of this release. Please use `NotificationCenter.clear_all_notification_listeners`.  ([#182](https://github.com/optimizely/python-sdk/pull/182))

## 3.1.0
May 3rd, 2019

### New 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](https://github.com/optimizely/python-sdk/pull/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.

## 3.0.0
March 1st, 2019

The 3.0 release improves event tracking and supports additional audience
targeting functionality.

### New Features:
* Event tracking:
  * The `track` method now dispatches its conversion event *unconditionally*, 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:
  * An `exists` matcher that passes if the user has a non-null value for the targeted user attribute and fails otherwise.
  * A `substring` matcher that resolves if the user has a string value for the targeted attribute.
    * `gt` (greater than) and `lt` (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 templ