Python SDK - Kameleoon Documentation

With the Python SDK, you can run experiments and activate feature flags on your back-end Python server. Integrating our SDK into your web-application is easy, and its footprint (memory and network usage) is low. Getting started: For help getting started, see the developer guide. Changelog: Latest version of the Python SDK: 3.20.0 Changelog. SDK methods: For the full reference documentation of the Python SDK, see the reference section.

Developer guide

This guide is designed to help you integrate our SDK in a few minutes and start running experiments in your Python applications. This tutorial will explain the setup of a simple A/B test to change the number of recommended products based on different variations.

Getting started

Installing the Python client

You can install the SDK using a Python pip package. Our package is hosted on the official pip repository, so you just have to run the following command:

pip install kameleoon-client-python

Additional configuration

You should provide credentials for the Python SDK via a configuration file, which you can also use to customize the SDK’s behavior. A sample configuration file can be obtained here. We suggest installing this file to the default path /etc/kameleoon/client-python.yaml, but you can put it in another location and pass the path as an argument to the KameleoonClient() constructor method. With the current version of the Python SDK, these are the available keys:

Key	Description	Default value
`client_id` required	Required for authentication to the Kameleoon service. To find your client id, see the API credentials documentation.
`client_secret` required	Required for authentication to the Kameleoon service. To find your client secret, see the API credentials documentation.
`session_duration_minute` optional	Designates the predefined time interval that Kameleoon stores the visitor and their associated data in memory (RAM). Note that increasing the session duration increases the amount of RAM that needs to be allocated to store visitor data.	`30` minutes
`refresh_interval_minute` optional	Specifies the refresh interval, in minutes, that the SDK fetches the configuration for the active experiments and feature flags. The value determines the maximum time it takes to propagate changes, such as activating or deactivating feature flags or launching experiments, to your production servers. Additionally, we offer a streaming mode that uses server-sent events (SSE) to push new configurations to the SDK automatically and apply new configurations in real-time, without any delays.	`60` minutes
`default_timeout_millisecond` optional	Specifies the timeout, in milliseconds, for network requests from the SDK. Set the value to 30 seconds or more if you do not have a stable connection. Some methods have an additional parameter that you can use to override the default timeout for that particular method. If you do not specify the timeout for a method explicitly, the SDK uses this default value.	`10000` milliseconds
`tracking_interval_millisecond` optional	Specifies the interval for tracking requests in milliseconds. All visitors who Kameleoon evaluated for any feature flag or had data flushed are included in this tracking request, which the SDK performs once per interval. The minimum value is `1000` ms, which is also the default, and the maximum value is `5000` ms.	`1000` milliseconds
`environment` optional	Environment from which the feature flag’s configuration is to be used. The value can be `production`, `staging`, `development`. See the managing environments article for details.	`production`
`top_level_domain` (required in hybrid mode)	The current top-level domain for your website . Use the format: `example.com`. Don’t include `https://`, `www`, or other subdomains. Kameleoon uses this information to set the corresponding cookie on the top-level domain.	`""`
`network_domain` optional	Custom domain used by SDKs for outgoing requests, often for proxying. Must be a valid domain (e.g., example.com or sub.example.com). Invalid formats default to Kameleoon’s value.	`None`
`logger` (deprecated)	Allows overriding the default Python logger. This field is deprecated and will be removed in SDK version `4.0.0`. Use `KameleoonLogger.set_logger()` instead.	`logging.Logger`
`multi_threading` (deprecated)	An option of type `bool` indicating whether threads can be used for network requests. By default everything is executed in one thread to avoid performance issues with GIL if (C)Python interpreter is being used. Possible values: `True`, `False`.	`None`

Alternatively, you can use configuration_object of type KameleoonClientConfig as a parameter during initialization. It has the same list of arguments as a config file. configuration_object takes precedence over the configuration file and overwrites its settings.

Initializing the Kameleoon client

After installing the SDK into your application, configuring the correct credentials (in /etc/kameleoon/client-python.yaml), and setting up a server-side experiment in Kameleoon’s back-office, the next step is creating the Kameleoon client in your application code. The code on the right gives a clear example. A KameleoonClient is a singleton object that acts as a bridge between your application and the Kameleoon platform. It includes all the methods and properties you will need to run an experiment.

Developers are responsible for ensuring the correct logic of their application code when implementing A/B testing with Kameleoon. A best practice is to always assume that a visitor may be excluded from the experiment if it has not yet been launched. This practice is simple to implement, as it aligns with the default or reference variation logic, which should always be in place. The code samples in the next section demonstrate this approach.

from kameleoon import KameleoonClient, KameleoonClientConfig, KameleoonClientFactory

SITE_CODE = 'a8st4f59bj'

# Option 1
kameleoon_client = KameleoonClientFactory.create(SITE_CODE, config_path='/etc/kameleoon/client-python.yaml')

# Option 2
configuration_object = KameleoonClientConfig.read_from_yaml('/etc/kameleoon/client-python.yaml')
configuration_object.set_top_level_domain("example.com")
kameleoon_client = KameleoonClientFactory.create(SITE_CODE, configuration_object)

# Option 3
configuration_object = KameleoonClientConfig(
    "client_id",  # required
    "client_secret",  # required
    refresh_interval_minute=60,  # (in minutes) optional, default: 60 minutes
    session_duration_minute=30,  # (in minutes) optional, default: 30 minutes
    default_timeout_millisecond=10000,  # (in milliseconds) optional, default: 10000 milliseconds
    tracking_interval_millisecond=1000,  # (in milliseconds) optional, default: 1000 milliseconds
    environment="production",  # optional, possible values: "production" / "staging" / "development" / "staging", default: None
    top_level_domain="example.com",
    multi_threading=False,  # optional, default: False
    logger=my_logger,  # optional, default: standard kameleoon logger. This field is deprecated and will be removed in SDK version `4.0.0`. Use `KameleoonLogger.set_logger` instead.
    network_domain="example.com",  # optional
)
kameleoon_client = KameleoonClientFactory.create(SITE_CODE, configuration_object)

Activating a feature flag

Assigning a unique ID to a user

To assign a unique ID to a user, you can use the get_visitor_code() method. If a visitor code doesn’t exist (from the request headers cookie), the method generates a random unique ID or uses a default_visitor_code that you would have generated. The ID is then set in a response headers cookie. If you are using Kameleoon in Hybrid mode, calling the get_visitor_code() method ensures that the unique ID (visitor code) is shared between the application file engine.js (previously named, kameleoon.js) and the SDK.

Retrieving a flag configuration

To implement a feature flag in your code, you must first create the feature flag in your Kameleoon account. To determine the status or variation of a feature flag for a specific user, you should use the get_variation() or is_feature_active() method to retrieve the configuration based on the feature_key. The get_variation() method handles both simple feature flags with ON/OFF states and more complex flags with multiple variations. The method retrieves the appropriate variation for the user by checking the feature rules, assigning the variation, and returning it based on the feature_key and visitor_code. The is_feature_active() method can be used if you want to retrieve the configuration of a simple feature flag that has only an ON or OFF state, as opposed to more complex feature flags with multiple variations or targeting options. If your feature flag has associated variables (such as specific behaviors tied to each variation) get_variation() also enables you to access the Variation object, which provides details about the assigned variation and its associated experiment. This method checks whether the user is targeted, finds the visitor’s assigned variation, and saves it to storage. When track=True, the SDK will send the exposure event to the specified experiment on the next tracking request, which is automatically triggered based on the SDK’s tracking_interval_millisecond. By default, this interval is set to 1000 milliseconds (1 second). The get_variation() method allows you to control whether tracking is done. If track=False, no exposure events will be sent by the SDK. This is useful if you prefer not to track data through the SDK and instead rely on client-side tracking managed by the Kameleoon engine, for example. Additionally, setting track=False is helpful when using the get_variations() method, where you might only need the variations for all flags without triggering any tracking events. If you want to know more about how tracking works, view this article

Adding data points to target a user or filter / breakdown visits in reports

To target a user, ensure you’ve added relevant data points to their profile before retrieving the feature variation or checking if the flag is active. Use the add_data() method to add these data points to the user’s profile. To retrieve data points collected on other devices or to access past user data (collected client-side when using Kameleoon in Hybrid mode), use the get_remote_visitor_data() method. This method asynchronously fetches data from the servers. It is important to call get_remote_visitor_data() before retrieving the variation or checking if the feature flag is active, as this data might be required to assign a user to a given variation. To learn more about available targeting conditions, see the detailed article on the subject. Additionally, the data points you add to the visitor profile will be available when analyzing your experiments, allowing you to filter and break down your results by factors like device and browser. Kameleoon Hybrid mode automatically collects a variety of data points on the client-side, making it easy to break down your results based on these pre-collected data points. See the complete list here. If you need to track additional data points beyond what’s automatically collected, you can use Kameleoon’s Custom Data feature. Custom Data allows you to capture and analyze specific information relevant to your experiments. Don’t forget to call the flush() method to send the collected data to Kameleoon servers for analysis.

To ensure your results are accurate, it’s recommended to filter out bots by using the UserAgent data type.

Tracking goal conversions

When a user completes a desired action (such as making a purchase), it is recorded as a conversion. To track conversions, use the track_conversion() method and provide the required visitor_code and goal_id parameters. The conversion tracking request will be sent along with the next scheduled tracking request, which the SDK sends at regular intervals (defined by tracking_interval_millisecond). If you prefer to send the request immediately, use the flush() method with the parameter instant=True.

Sending events to analytics solutions

To track conversions and send exposure events to your customer analytics solution, you must first implement Kameleoon in Hybrid mode. Then, use the get_engine_tracking_code() method. The get_engine_tracking_code() method retrieves the unique tracking code required to send exposure events to your analytics solution. Using this method allows you to record events and send them to your desired analytics platform.

Using the Kameleoon Python SDK in a Django environment

If you use Django, we recommend you to initialize the Kameleoon client at server start-up, in the apps.py file of your Django application. When you use python manage.py runserver, Django starts two processes: one for the actual development server, and the other to reload your application when the code changes. You can also start the server without the reload option, and you will only see one process running. The process is only executed once: python manage.py runserver --noreload You can also check the RUN_MAIN env var in the ready() method.

def ready(self):
    if os.environ.get('RUN_MAIN', None) == 'true':
        configuration_path = os.path.join(ROOT_DIR, 'path_to_config', 'config.yml')
        self.kameleoon_client = KameleoonClientFactory.create(SITE_CODE, config_path=configuration_path)

This only applies to local development when you use python manage.py runserver. In a production environment, the code in the ready() function will be executed only once when the application is initialized.

from django.apps import apps

my_application = apps.get_app_config('your_app')
client = my_application.kameleoon_client

You can then access the Kameleoon client in your application.

Another advantage of using Django is that the SDK will automaticallyo read and write the visitor_code on the HTTP request/response via a cookie. If you’re using another framework in a web environment where you would like to use a cookie mechanism to persist the visitor_code, you must provide implementations of the read_cookies() and write_cookies() methods.

Cross-device experimentation

To support visitors who access an app from multiple devices, Kameleoon allows the synchronization of previously collected visitor data across each of the visitor’s devices and reconciliation of their visit history across devices through cross-device experimentation. Case studies and detailed information on how Kameleoon handles data across devices are available in the article on cross-device experimentation.

Synchronizing custom data across devices

Although custom mapping synchronization is used to align visitor data across devices, it is not always necessary. Below are two scenarios where custom mapping sync is not required: Same user ID across devices If the same user ID is used consistently across all devices, synchronization is handled automatically without a custom mapping sync. It is enough to call the get_remote_visitor_data() method when you want to sync the data collected between multiple devices. Multi-server instances with consistent IDs In complex setups involving multiple servers (for example, distributed server instances), where the same user ID is available across servers, synchronization between servers (with get_remote_visitor_data()) is sufficient without additional custom mapping sync. Customers who need additional data can refer to the get_remote_visitor_data() method description for further guidance. In the below code, it is assumed that the same unique identifier (in this case, the visitor_code, which can also be referred to as userId) is used consistently between the two devices for accurate data retrieval.

If you want to sync collected data in real time, you need to choose the scope Visitor for your custom data.

Device A

# In this example, Custom data with index `90` was set to "Visitor" scope in Kameleoon.
VISITOR_SCOPE_CUSTOM_DATA_INDEX = 90

kameleoon_client.add_data(visitor_code, CustomData(VISITOR_SCOPE_CUSTOM_DATA_INDEX, "your data"))
kameleoon_client.flush(visitor_code)

Device B

# Before working with the data, call `get_remote_visitor_data`.
kameleoon_client.get_remote_visitor_data(visitor_code)

# After calling, the SDK on Device B will have access to CustomData of Visitor scope defined on Device A.
# So, "your data" will be available to target and track the visitor.

Using custom data for session merging

Cross-device experimentation allows for combining a visitor’s history across each of their devices (history reconciliation). History reconciliation allows merging different visitor sessions into one. To reconcile visit history, use CustomData to provide a unique identifier for the visitor. For more information, see the dedicated documentation. After cross-device reconciliation is enabled, calling get_remote_visitor_data() with the parameter userId retrieves all known data for a given user. Sessions with the same identifier will always be shown the same variation in an experiment. In the Visitor view of your experiment’s results pages, these sessions will appear as a single visitor. The SDK configuration ensures that associated sessions always see the same variation of the experiment. However, there are some limitations regarding cross-device variation allocation. These limitations are outlined here. Follow the activating cross-device history reconciliation guide to set up your custom data on the Kameleoon platform. Afterwards, you can use the SDK normally. The following methods that may be helpful in the context of session merging:

get_remote_visitor_data() with added UniqueIdentifier(True) - to retrieve data for all linked visitors.
track_conversion() or flush() with added UniqueIdentifier(True) data - to track some data for specific visitor that is associated with another visitor.

As the custom data you use as the identifier must be set to Visitor scope, you need to use cross-device custom data synchronization to retrieve the identifier with the get_remote_visitor_data() method on each device.

Here’s an example of how to use custom data for session merging.

# In this example, `91` represents the Custom Data's index configured as a unique identifier in Kameleoon.
MAPPING_INDEX = 91
FEATURE_KEY = "ff123"

# 1. Before the visitor is authenticated

# Retrieve the variation for an unauthenticated visitor.
# Assume `anonymous_visitor_code` is the randomly generated ID for that visitor.
anonymous_variation = kameleoon_client.get_variation(anonymous_visitor_code, FEATURE_KEY)

# 2. After the visitor is authenticated

# Assume `user_id` is the visitor code of the authenticated visitor.
kameleoon_client.add_data(anonymous_visitor_code, CustomData(MAPPING_INDEX, user_id))
kameleoon_client.flush(anonymous_visitor_code, instant=True)

# Indicate that `user_id` is a unique identifier.
kameleoon_client.add_data(user_id, UniqueIdentifier(True))

# 3. After the visitor has been authenticated

# Retrieve the variation for the `user_id`, which will match the anonymous visitor code's variation.
user_variation = kameleoon_client.get_variation(user_id, FEATURE_KEY)
is_same_variation = user_variation.key == anonymous_variation.key  # True

# The `user_id` and `anonymous_visitor_code` are now linked and tracked as a single visitor.
kameleoon_client.track_conversion(user_id, 123, 10.0)

# Additionally, the linked visitors will share all fetched remote visitor data.
kameleoon_client.get_remote_visitor_data(user_id)

In this example, the application has a login page. Since the user ID is unknown at the moment of login, an anonymous visitor identifier generated by the get_visitor_code() method is used. After the user logs in, the anonymous visitor is associated with the user ID and used as a unique identifier for the visitor.

Using a custom bucketing key

By default, Kameleoon uses a unique, anonymous visitor ID (visitor_code) to assign users to feature flag variations. This ID is typically generated and stored on the user’s device (in a browser cookie for client-side and server-side SDKs—in persistent storage for mobile SDKs). However, in certain scenarios you may need to ensure all users of the same organization see the same variant of a feature flag. The Custom Bucketing Key option allows you to override this default behavior by providing your own custom identifier for bucketing. This override ensures that Kameleoon’s assignment logic uses your specified key instead of the default visitor_code.

Use cases

Using a custom bucketing key is essential for maintaining consistency and accuracy in your feature flag assignments, particularly in these situations:

Account-level or organizational experiments: For B2B products or scenarios where you want to assign all users from the same organization to the same variation, you can use an identifier like an account_id. Custom bucketing keys are crucial for A/B testing features that impact an entire team or company.

By implementing a custom bucketing key, you ensure greater consistency and accuracy in your experiments, leading to more reliable results and a better user experience.

Technical details

When you configure a custom bucketing key for a feature flag, you provide Kameleoon with a specific identifier from your application’s data:

from kameleoon.data import CustomData

kameleoon_client.add_data(visitor_code, CustomData(index, "new_visitor_code"))

Providing the custom key: You provide your custom identifier to the Kameleoon SDK using the add_data() method. In this method, you will pass your chosen custom bucketing key as a CustomData object. Here, new_visitor_code refers to the identifier you wish to use for your bucketing (for example, the new user_id or account_id).

For the custom bucketing key to function correctly, it must also be defined and configured for the feature flag during the flag creation or editing process. Without this corresponding configuration, the SDK’s bucketing will not apply your custom key. For detailed instructions on how to set this up in Kameleoon, refer to this article.

Bucketing logic: Once a custom bucketing key is provided through the add_data() method, all hash calculations for assigning users to variations will use this new_visitor_code (your custom key) instead of the default visitor_code. Using the new_visitor_code means that the bucketing decision is tied to your custom identifier, ensuring consistent assignments across various contexts where that identifier is present.
Data tracking and analytics: It’s crucial to note that while the new_visitor_code (your custom key) is used for bucketing decisions, all subsequent data (tracking events and conversions, for example) is sent and associated with the original visitor_code. This separation ensures that your analytics accurately reflect individual user journeys and interactions within your experiment’s broader context, even when bucketing is performed at a higher level (like an account) or across multiple devices/sessions. Your original visitor data remains intact for comprehensive reporting.

Technical requirements

To effectively use a custom bucketing key:

The key must be a str.
It must be unique for the entity you intend to bucket (for example, if using a user_id, each user’s ID should be unique).
The key must be available to the SDK at the exact moment the feature flag decision is evaluated for that user or request.

Targeting conditions

The Kameleoon SDKs support a variety of predefined targeting conditions that you can use to target users in your campaigns. For the list of conditions this SDK supports, see use visit history to target users. You can also use your own external data to target users.

Logging

The SDK generates logs to reflect various internal processes and issues.

Log levels

The SDK supports configuring limiting logging by a log level.

from kameleoon.logging.log_level import LogLevel
from kameleoon.logging.kameleoon_logger import KameleoonLogger

# The `NONE` log level does not allow logging.
KameleoonLogger.set_log_level(LogLevel.NONE)

# The `ERROR` log level only allows logging issues that may affect the SDK's main behaviour.
KameleoonLogger.set_log_level(LogLevel.ERROR)

# The `WARNING` log level allows logging issues which may require additional attention.
# It extends the `ERROR` log level.
# The `WARNING` log level is a default log level.
KameleoonLogger.set_log_level(LogLevel.WARNING)

# The `INFO` log level allows logging general information on the SDK's internal processes.
# It extends the `WARNING` log level.
KameleoonLogger.set_log_level(LogLevel.INFO)

# The `DEBUG` level logs additional details about the SDK’s internal processes and extends the `INFO` level
# with more granular diagnostic output.
# This information is not intended for end-user interpretation but can be sent to our support team
# to assist with internal troubleshooting.
KameleoonLogger.set_log_level(LogLevel.DEBUG)

Custom handling of logs

The SDK writes its logs to the console output by default. This behaviour can be overridden.

Logging limiting by a log level is performed apart from the log handling logic.

from loguru import logger
from kameleoon.logging.log_level import LogLevel
from kameleoon.logging.logger import Logger


class CustomLogger(Logger):
    """Custom logger implementation using loguru."""

    def log(self, level: LogLevel, message: str) -> None:
        """Accepts logs from the SDK"""
        if level == LogLevel.ERROR:
            logger.error(message)
        elif level == LogLevel.WARNING:
            logger.warning(message)
        elif level == LogLevel.INFO:
            logger.info(message)
        elif level == LogLevel.DEBUG:
            logger.debug(message)


from kameleoon.logging.kameleoon_logger import KameleoonLogger

# Log level filtering is applied separately from log handling logic.
# The custom logger will only accept logs that meet or exceed the specified log level.
# Ensure the log level is set correctly.
KameleoonLogger.set_logger(CustomLogger())
KameleoonLogger.set_log_level(LogLevel.DEBUG)  # Optional, defaults to `LogLevel.WARNING`.

Reference

This is a full reference documentation of the Python SDK.

create()

To start using the SDK, you must complete the initialization. All interactions with the SDK are completed through an object called Kameleoon::KameleoonClient, so the first thing you must do is create this object.

kameleoon_config = KameleoonClientConfig("client_id", "client_secret")
kameleoon_client = KameleoonClientFactory.create("a8st4f59bj", kameleoon_config)

kameleoon_client = KameleoonClientFactory.create("a8st4f59bj", config_path="/etc/kameleoon/client-ruby.yaml")

Arguments

Name	Type	Description
site_code	str	This is a unique key of the Kameleoon project you are using with the SDK. This field is mandatory.
config	KameleoonClientConfig	Configuration SDK object that you can pass instead of using a configuration file. This field is optional.
config_path	str	Path to the SDK configuration file. This field is optional. The default value is `/etc/kameleoon/client-ruby.yaml`

Exceptions thrown

Type	Description
SiteCodeIsEmpty	Exception indicating that the specified site code is an empty string, which is an invalid value.
ConfigFileNotFound	Exception indicating that the configuration file was not found.

wait_init_async()

wait_init_async asynchronously waits for the Kameleoon client’s initialization. This method lets you check if the client has been successfully initialized before proceeding with other operations.

kameleoon_client = KameleoonClientFactory.create('a8st4f59bj')

if await kameleoon_client.wait_init_async():
    # The SDK has been initialized; you can fetch a feature flag / experiment configuration here.

Return value

Type	Description
Coroutine[Any, Any, bool]	A coroutine that returns `True` if the Kameleoon client instance was successfully initialized, otherwise `False`.

wait_init()

wait_init synchronously waits for the Kameleoon client’s initialization. This method lets you check if the client has been successfully initialized before proceeding with other operations.

kameleoon_client = KameleoonClientFactory.create('a8st4f59bj')

if kameleoon_client.wait_init():
    # The SDK has been initialized; you can fetch a feature flag / experiment configuration here.

Return value

Type	Description
`bool`	`True` if the Kameleoon client instance was successfully initialized, otherwise `False`.

Feature flags and variations

is_feature_active()

📨 Sends Tracking Data to Kameleoon (depending on the track parameter)

Previously called activate_feature—deprecated since SDK version 2.1.0 and will be removed in a future releases.

To check if feature flag is active for a visitor, call the is_feature_active() method. This method takes a visitor_code and feature_key as mandatory arguments to check if the feature will be active for a given user. If such a user has never been associated with this feature flag, the SDK returns a boolean value randomly (true if feature will be active for the user, or false if not). If a user with a given visitor_code is already registered with this feature flag, it will detect the previous feature flag value. You must ensure that proper error handling is set up in your code as shown in the example to the right to catch potential exceptions. If you specify a visitor_code, the is_feature_active() method uses the visitor_code as the unique visitor identifier, which is useful for cross-device experimentation. When you specify a visitor_code and set the is_unique_identifier parameter to true, the SDK links the flushed data to the visitor associated with the specified identifier.

The parameter is_unique_identifier is deprecated. Please use UniqueIdentifier instead.The is_unique_identifier can also be useful in other edge-case scenarios, such as when you can’t access the anonymous visitor_code that was originally assigned to the visitor, but you have access to an internal ID that is connected to the anonymous visitor using session merging capabilities.

Kameleoon uses tracking to count sessions and visitors when you call certain methods, such as is_feature_active(), get_variation() or get_variations().Use the default True value for the track parameter when you expose visitors to a variation and need to count them. Set the track parameter to False only if you call these methods before you expose visitors.For example, if you call get_variations() to retrieve all variations before you expose visitors, set the track parameter to False. This setting prevents Kameleoon from prematurely counting a session. You can then trigger tracking later when you explicitly expose the visitor.Kameleoon sends tracking data every second by default. You can configure this interval up to five seconds using the tracking interval configuration option. Kameleoon groups tracking events into a single session as long as the interval between events is less than 30 minutes. If more than 30 minutes elapse between tracking events, Kameleoon counts the events as separate sessions. A visit appears in your reports 30 minutes after the last recorded event in the session.

visitor_code = kameleoon_client.get_visitor_code(request.COOKIES)
feature_key = "new_checkout"
has_new_checkout = False

try
    has_new_checkout = kameleoon_client.is_feature_active(visitor_code, feature_key)
    # disabling tracking
    has_new_checkout = kameleoon_client.is_feature_active(visitor_code, feature_key, track=False)
except FeatureNotFound as ex:
    # The user will not be counted in the experiment,
    # but should see the reference variation.
    has_new_checkout = False
except VisitorCodeInvalid as ex:
    # The visitor code you passed to the method isn't valid and can't be accepted by SDK.
    has_new_checkout = False

if has_new_checkout
    # Implement new checkout code here

The is_feature_active() method evaluates the served variant, not the master flag state. If you exclude rules, the method uses the Then, for everyone else serve default state. If you select Off for this default state, the method always returns false even when the master feature flag is On.

Parameters

Name	Type	Description
visitor_code	str	Unique identifier of the user. This field is mandatory.
feature_key	str	ID or Key of the feature you want to expose to a user. This field is mandatory.
is_unique_identifier (Deprecated)	Optional[bool]	When set to `True`, the SDK links the flushed data to the visitor associated with the specified identifier.
track	bool	An optional parameter to enable or disable tracking of the feature evaluation (`True` by default).

Return value

Type	Description
bool	Value of the feature that is registered for a given visitor_code.

Exceptions thrown

Type	Description
FeatureNotFound	Exception indicating that the requested feature ID has not been found in the SDK’s internal configuration. This exception is usually normal and means that the feature flag has not yet been activated on Kameleoon’s side (but code implementing the feature is already deployed on the web-application’s side).
VisitorCodeInvalid	Exception indicating that the provided visitor code is not valid (empty or longer than 255 characters).

get_variation()

📨 Sends Tracking Data to Kameleoon (depending on the track parameter)

Retrieves the Variation assigned to a given visitor for a specific feature flag. This method takes a visitor_code and feature_key as mandatory arguments. The track argument is optional and defaults to True. It returns the assigned Variation for the visitor. If the visitor is not associated with any feature flag rules, the method returns the default Variation for the given feature flag. Ensure that proper error handling is implemented in your code to manage potential exceptions.

The default variation refers to the variation assigned to a visitor when they do not match any predefined delivery rules for a feature flag. In other words, it is the fallback variation applied to all users who are not targeted by specific rules. It’s represented as the variation in the “Then, for everyone else…” section in a management interface.

feature_key = "new_checkout"

try:
    variation = kameleoon_client.get_variation(visitor_code, feature_key)
    # disabling tracking
    variation = kameleoon_client.get_variation(visitor_code, feature_key, False)
except FeatureNotFound as ex:
    # The error has occurred; the feature flag isn't found in current configuration.
except FeatureEnvironmentDisabled as ex:
    # The feature flag is disabled for the environment.
except VisitoCodeNotValid as ex:
    # The visitor code you passed to the method is invalid and can't be accepted by SDK.

# Fetch a variable value for the assigned variation
title = variation.variables["title"].value

if variation.key == "on":
    # Main variation key is selected for visitorCode
elif variation.key == "alternative_variation":
    # Alternative variation key
else:
    # Default variation key

Parameters

Name	Type	Description	Default
`visitor_code` required	`str`	Unique identifier of the visitor.
`feature_key` required	`str`	Key of the feature you want to expose to a visitor.
`track` optional	`bool`	An optional parameter to enable or disable tracking of the feature evaluation.	`True`

Return value

Type	Description
`Variation`	An assigned `Variation` to a given visitor for a specific feature flag.

Exceptions thrown

Type	Description
`VisitorCodeInvalid`	Exception indicating that the provided visitor code is not valid. It is either empty or longer than 255 characters.
`FeatureNotFound`	Exception indicating that the requested feature key wasn’t found in the internal configuration of the SDK. This usually means that the feature flag is not activated in the Kameleoon app (but code implementing the feature is already deployed in the application).
`FeatureEnvironmentDisabled`	Exception indicating that feature flag is disabled for the visitor’s current environment (for example, production, staging, or development).

get_variations()

📨 Sends Tracking Data to Kameleoon (depending on the track parameter)

Retrieves a map of Variation objects assigned to a given visitor across all feature flags. This method iterates over all available feature flags and returns the assigned Variation for each flag associated with the specified visitor. It takes visitor_code as a mandatory argument, while only_active and track are optional.

If only_active is set to True, the method get_variations() will return feature flags variations provided the user is not bucketed with the off variation.
The track parameter controls whether or not the method will track the variation assignments. By default, it is set to True. If set to False, the tracking will be disabled.

The returned map consists of feature flag keys as keys and their corresponding Variation as values. If no variation is assigned for a feature flag, the method returns the default Variation for that flag. Proper error handling should be implemented to manage potential exceptions.

try:
    variations = kameleoon_client.get_variations(visitor_code)
    # only active variations
    variations = kameleoon_client.get_variations(visitor_code, only_active=True)
    # disable tracking
    variations = kameleoon_client.get_variations(visitor_code, track=False)
except VisitorCodeInvalid as ex:
    # Handle exception

Parameters

Name	Type	Description	Default
`visitor_code` required	`str`	Unique identifier of the visitor.
`only_active` optional	`bool`	An optional parameter indicating whether to return variations for active (`True`) or all (`False`) feature flags.	`False`
`track` optional	`bool`	An optional parameter to enable or disable tracking of the feature evaluation.	`True`

Return value

Type	Description
`Dict[str, Variation]`	Map that contains the assigned `Variation` objects of the feature flags using the keys of the corresponding features.

Exceptions thrown

Type	Description
`VisitorCodeInvalid`	Exception indicating that the provided visitor code is not valid. It is either empty or longer than 255 characters.

get_data_file()

To evaluate all feature flags, use get_variations(). This method is more efficient than calling DataFile and iterating through flags with get_variation().

Returns the current SDK configuration as a DataFile object.

data_file = kameleoon_client.get_data_file()
date_modified = data_file.date_modified

Return value

Type	Description
`DataFile`	The `DataFile` containing the SDK configuration

set_forced_variation()

The method allows you to programmatically assign a specific Variation to a user, bypassing the standard evaluation process. This is especially valuable for controlled experiments where the usual evaluation logic is not required or must be skipped. It can also be helpful in scenarios like debugging or custom testing. When a forced variation is set, it overrides Kameleoon’s real-time evaluation logic. Processes like segmentation, targeting conditions, and algorithmic calculations are skipped. To preserve segmentation and targeting conditions during an experiment, set force_targeting=False instead.

Simulated variations always take precedence in the execution order. If a simulated variation calculation is triggered, it will be fully processed and completed first.

A forced variation is treated the same as an evaluated variation. It is tracked in analytics and stored in the user context like any standard evaluated variation, ensuring consistency in reporting. The method may throw exceptions under certain conditions (e.g., invalid parameters, user context, or internal issues). Proper exception handling is essential to ensure that your application remains stable and resilient.

It’s important to distinguish forced variations from simulated variations:

Forced variations: Are specific to an individual experiment.
Simulated variations: Affect the overall feature flag result.

experiment_id = 9516
try:
    # Forcing the variation "on" for the experiment 9516 for the visitor
    kameleoon_client.set_forced_variation(visitor_code, experiment_id, "on")

    # Forcing the variation "on" while preserving segmentation and targeting conditions during the experiment
    kameleoon_client.set_forced_variation(visitor_code, experiment_id, "on", False)

    # Resetting the forced variation for the experiment 9516 for the visitor
    kameleoon_client.set_forced_variation(visitor_code, experiment_id, None)
except KameleoonError as e:
    # Handling the error

Parameters

Name	Type	Description	Default
`visitor_code` required	`str`	Unique identifier of the visitor.
`experiment_id` required	`int`	Experiment Id that will be targeted and selected during the evaluation process.
`variation_key` required	`Optional[str]`	Variation Key corresponding to a `Variation` that should be forced as the returned value for the experiment. If the value is `None`, the forced variation will be reset.
`force_targeting` optional	`bool`	Indicates whether targeting for the experiment should be forced and skipped (`True`) or applied as in the standard evaluation process (`False`).	`True`

Exceptions thrown

Type	Description
`VisitorCodeInvalid`	Exception indicating that the provided visitor code is not valid. It is either empty or longer than 255 characters.
`FeatureExperimentNotFound`	Exception indicating that the requested experiment id has not been found in the SDK’s internal configuration. This is usually normal and means that the rule’s corresponding experiment has not yet been activated on Kameleoon’s side.
`FeatureVariationNotFound`	Exception indicating that the requested variation key(id) has not been found in the internal configuration of the SDK. This is usually normal and means that the variation’s corresponding experiment has not yet been activated on Kameleoon’s side.

In most cases, only the basic error, KameleoonError, needs to be handled, as demonstrated in the example. However, if different types of errors require a response, handle each one separately based on specific requirements. Additionally, for enhanced reliability, general language errors can be handled by including Exception.

evaluate_audiences()

📨 Sends Tracking Data to Kameleoon

This method evaluates visitors against all available Audiences Explorer segments and tracks those who match. evaluate_audiences() should be called after all relevant visitor data has been set or updated, and just before getting a feature variation or checking a feature flag. This approach ensures that the visitor is evaluated against the most current data available, allowing for accurate audience assignment based on all criteria. After calling this method, you can perform a detailed analysis of segment performance in Audiences Explorer.

try:
    kameleoon_client.evaluate_audiences(visitor_code)
except KameleoonError as e:
    # Handling the error

Parameters

Name	Type	Description
`visitor_code` required	`str`	Unique identifier of the visitor.

Exceptions thrown

Type	Description
`VisitorCodeInvalid`	Exception indicating that the provided visitor code is not valid. It is either empty or longer than 255 characters.

Visitor data

get_visitor_code()

This method was previously called obtain_visitor_code, which was removed in SDK version 3.0.0.

The get_visitor_code() helper method should be called to obtain the current visitor’s Kameleoon visitor_code. This method is especially important when using Kameleoon in a mixed front-end and back-end environment, where user identification consistency must be guaranteed. The implementation logic is described here:

First we check if a kameleoonVisitorCode cookie or query parameter associated with the current HTTP request can be found. If so, we will use this as the visitor identifier.
If no cookie/parameter is found in the current request, we either randomly generate a new identifier, or use the default_visitor_code argument as an identifier if it is passed. This allows our customers to use their own identifiers as visitor codes, should they wish to, which has the added benefit of matching Kameleoon visitors with their own users without any additional look-ups in a matching table.
In any case, the server-side (via HTTP header) kameleoonVisitorCode cookie is set with the value. Then, this identifier value is finally returned by the method.

If you provide your own visitor_code, you must guarantee its uniqueness. The SDK doesn’t validate the value passed as an argument. Also note that the length of visitor_code is limited to 255 characters. A VisitorCodeInvalid exception is raised if this limit is exceeded.

The get_visitor_code() method allows you to set simulated variations for a visitor. When cookies (from a request or document) contain the key kameleoonSimulationFFData, the standard evaluation process is bypassed. Instead, the method directly returns a Variation based on the provided data.You can apply simulations in two ways:

Automatically (recommended): If using Kameleoon Web Experimentation or the SDK in Hybrid mode, the cookie is created automatically when simulating a variant’s display using the Simulation Panel.
Manually: Set the kameleoonSimulationFFData cookie manually.

It’s important to distinguish simulated variations from forced variations:

Simulated variations: Affect the overall feature flag result.
Forced variations: Are specific to an individual experiment.

⚙️ Manual setupPlease ensure the kameleoonSimulationFFData cookie follows this format:

kameleoonSimulationFFData={"featureKey":{"expId":10,"varId":20}}: Simulates the variation with varId of experiment expId for the given featureKey.
kameleoonSimulationFFData={"featureKey":{"expId":0}}: Simulates the default variation (defined in the Then, for everyone else in Production, serve section) for the given featureKey.

⚠️ To ensure proper functionality, the cookie value must be encoded as a URI component using a method such as encodeURIComponent.

### if you use KameleoonWSGIMiddleware service
visitor_code = kameleoon_client.get_visitor_code(cookies_readonly=request.COOKIES)
kameleoon_client.set_legal_consent(visitor_code, True)

### if you want to manage cookies manually
simple_cookies = SimpleCookie()
simple_cookies.load(cookie_header)

visitor_code = kameleoon_client.get_visitor_code(cookies=simple_cookies, default_visitor_code=default_visitor_code)

cookie_header = simple_cookies.output()

Parameters

Name	Type	Description
cookies_readonly	Optional[Dict[str, str]]	Read-only dictionary, usually `request.COOKIES`. Use this parameter if you also use the `KameleoonWSGIMiddleware` service. This field is optional.
cookies	Optinal[Dict[str, http.cookies.Morsel[str]]]	Pass cookies on the current HTTP request as a`Dict[str, http.cookies.Morsel[str]]` or `http.cookies.\|SimpleCookie[str]` object if you manage cookies manually without `KameleoonWSGIMiddleware` service. This field is optional.
default_visitor_code	str	This parameter will be used as the visitor_code if no existing kameleoonVisitorCode cookie is found in the request. This field is optional, and by default, a random visitor_code will be generated.

Return value

Type	Description
str	A visitor_code that will be associated with this particular user and should be used with most of our SDK methods.

Exceptions thrown

Type	Description
VisitorCodeInvalid	Exception indicating that the provided visitor code is invalid. It is either empty or longer than 255 characters.

add_data()

The add_data() method adds targeting data to storage so other methods can use the data to decide whether or not to target the current visitor. The add_data() method does not return any value and does not interact with Kameleoon back-end servers on its own. Instead, all the declared data is saved for future transmission using the flush() method. This approach reduces the number of server calls made, as the data is typically grouped into a single server call that is triggered by the flush(). The track_conversion() method also sends out any previously associated data, just like the flush(). The same holds true for get_variation() and get_variations() methods if an experimentation rule is triggered.

Each visitor can only have one instance of associated data for most data types. However, CustomData is an exception. Visitors can have one instance of associated CustomData per index.

require "kameleoon"
require "kameleoon/data"

# Add a single data item (tracked by default)
kameleoon_client.add_data(visitor_code, Browser(BrowserType.CHROME))

# Add multiple data items (tracked by default)
kameleoon_client.add_data(
    visitor_code,
    PageView("https://url.com", "title", [3]),
    UserAgent("UserAgent")
)

# Add multiple data items stored locally for targeting only (not sent to the Kameleoon Data API)
kameleoon_client.add_data(
    visitor_code,
    PageView("https://url.com", "title", [3]),
    UserAgent("UserAgent"),
    track=False
)

Parameters

Name	Type	Description	Default value
`visitor_code` required	`str`	Unique identifier of the visitor.
`data` required	`*Data`	Collection of Kameleoon data types.
`track` optional	`bool`	Specifies whether the added data is eligible for tracking. When set to `False`, the data is stored locally and used only for targeting evaluation; it is not sent to the Kameleoon Data API.	`True`

Exceptions

Type	Description
`VisitorCodeInvalid`	Exception indicating that the provided visitor code is not valid. It is either empty or longer than 255 characters.

flush()

📨 Sends Tracking Data to Kameleoon

flush() takes the Kameleoon data associated with the visitor and all of the data that was added previously using the add_data method, that has not yet been sent when calling one of these methods, and sends a tracking request. flush() is non-blocking, as the server call is made asynchronously. flush() lets you control when the data associated with a given visitor_code is sent to our servers. For instance, if you call add_data() a dozen times, it would be inefficient to send data to the server each time add_data() is invoked, so you only have to call flush() once at the end. If you specify a visitor_code, the flush() method uses it as the unique visitor identifier, which is useful for cross-device experimentation. When you specify a visitor_code and set the is_unique_identifier parameter to true, the SDK links the flushed data to the visitor associated with the specified identifier.

kameleoon_client.add_data(visitor_code, Browser(BrowserType.CHROME))
kameleoon_client.add_data(
    visitor_code,
    PageView("https://url.com", "title", [3]),
    CustomData(0, "value")
)
kameleoon_client.add_data(visitor_code, Conversion(32, 10, false))

kameleoon_client.flush(visitor_code)  # Interval tracking (most performant way for tracking)

kameleoon_client.flush(visitor_code, instant=True)  # Instant tracking

# If you operate with unique ID
kameleoon_client.add_data(UniqueIdentifier(True))
kameleoon_client.flush(visitor_code)

Arguments

Name	Type	Description
visitor_code	String	Unique identifier of the user. This field is mandatory.
is_unique_identifier (Deprecated)	Optional[bool]	When `True`, the SDK links the flushed data to the visitor associated with the specified identifier.
instant	bool	Boolean flag indicating whether the data should be sent instantly (`True`) or according to the scheduled tracking interval (`False`). If not provided, the default value is `False`. This field is optional.

get_remote_data()

Previously called retrieve_data_from_remote_source, which was removed in SDK version 3.0.0.
If you want to retrieve data asynchronously, use the get_remote_data_async method instead (available since version 2.3.0).

The get_remote_data method retrieves data synchronously (according to a key passed as argument) for a specified site_code (specified with KameleoonClient.__init__) stored on a remote Kameleoon server. Data is usually stored in our remote servers via our Data API. This method, along with the availability of our highly scalable servers for this purpose, provides a convenient method for storing massive amounts of data that can be retrieved for each of your visitors/users.

    kameleoon_client.get_remote_data('key1') # default timeout

    kameleoon_client.get_remote_data('key2', 1.0) # 1 second timeout

Parameters

Name	Type	Description
key	str	The key the data is associated with. This field is mandatory.
timeout	Optional[float]	Timeout (in seconds). This parameter specifies the maximum amount of time the method can block to wait for a result. This field is optional; if not provided, it will use the `default_timeout_millisecond` value from configuration file, or two seconds if it’s not specified in the file.

Return value

Type	Description
JSON object	JSON object associated with retrieving data for specific key.

get_remote_data_async()

The get_remote_data_async method lets you retrieve data asynchronously (according to a key passed as argument) for specified site_code (specified with KameleoonClient.__init__) stored in a remote Kameleoon server. Data is usually stored on our remote servers via our Data API. This method, along with the availability of our highly scalable servers for this purpose, provides a convenient method for storing massive amounts of data that can be retrieved for each of your visitors/users.

    await kameleoon_client.get_remote_data_async('key1') # default timeout

    await kameleoon_client.get_remote_data_async('key2', 1.0) # 1 second timeout

Parameters

Name	Type	Description
key	str	The key the data is associated with. This field is mandatory.
timeout	Optional[float]	Timeout (in seconds). This parameter specifies the maximum amount of time the method can block to wait for a result. This field is optional; if not provided, it will use the `default_timeout_millisecond` value from configuration file or two seconds if it’s not specified in the file.

Return value

Type	Description
JSON object	JSON object associated with retrieving data for a specific key.

get_remote_visitor_data()

get_remote_visitor_data() is an asynchronous method for retrieving Kameleoon Visits Data for the visitor_code from the Kameleoon Data API. The method adds the data to storage for other methods to use when making targeting decisions. Data obtained using this method plays an important role when you want to:

use data collected from other devices.
access a user’s history, such as visited pages during past visits.
use data that is only accessible on the client-side, like datalayer variables and goals that only convert on the front-end.

Read this article for a better understanding of possible use cases.

By default, get_remote_visitor_data() automatically retrieves the latest stored custom data with scope=visitor and attaches them to the visitor without the need to call the add_data() method. It is particularly useful for synchronizing custom data between multiple devices.

    visitor_code = 'visitorCode'

    # Visitor data will be fetched and automatically added for `visitor_code`
    data_list = kameleoon_client.get_remote_visitor_data(visitor_code)  # default timeout
    data_list = kameleoon_client.get_remote_visitor_data(visitor_code, timeout=1.0)  # 1 second timeout

    # If you only want to fetch data and add it yourself manually, set `add_data` to `False`
    data_list = kameleoon_client.get_remote_visitor_data(visitor_code, False)  # default timeout
    data_list = kameleoon_client.get_remote_visitor_data(visitor_code, False, 1.0)  # 1 second timeout

    # If you want to fetch custom list of data types
    data_filter = RemoteVisitorDataFilter(25, customData=False, conversions=True, experiments=True)
    data_list = kameleoon_client.get_remote_visitor_data(visitor_code, data_filter=data_filter)

    # If you want the SDK to link the extracted data with the visitor associated with the specified identifier.
    kameleoon_client.add_data(UniqueIdentifier(True))
    data_list = kameleoon_client.get_remote_visitor_data(visitor_code)

Parameters

Name	Type	Description
visitor_code	str	The visitor code for which you want to retrieve the assigned data. This field is mandatory.
add_data	bool	A boolean indicating whether the method should automatically add retrieved data for a visitor. If not specified, the default value is True. This field is optional.
data_filter	RemoteVisitorDataFilter	Filter that specifies what data should be retrieved from visits. By default, only `CustomData` is retrieved from the current and latest previous visit (`RemoteVisitorDataFilter(previousVisitAmount=1, currentVisit=True, customData=True)` or `RemoteVisitorDataFilter()`). Other filters parameters are set to `False`. This field is optional.
is_unique_identifier (Deprecated)	Optional[bool]	An optional parameter for specifying if the `visitorCode` is a unique identifier. If not provided, the default value is `False`. This field is optional.
timeout	Optional[float]	Timeout (in seconds). This parameter specifies the maximum amount of time the method can block to wait for a result. This field is optional; if not provided, it will use the `default_timeout_millisecond` value from configuration file or two seconds if it’s not specified in the file.

Using parameters in get_remote_visitor_data()

The get_remote_visitor_data() method offers flexibility by letting you define various parameters when retrieving data on visitors. Whether you’re targeting based on goals, experiments, or variations, the same approach applies to all data types. For example, suppose you want to retrieve data on visitors who completed the goal “Order transaction”. You can specify parameters within the get_remote_visitor_data() method to refine your targeting. For instance, if you want to target only users who converted on the goal in their last five visits, you can set the previous_visit_amount parameter to 5 and conversions to true. The flexibility shown in this example is not limited to goal data. You can use parameters within the get_remote_visitor_data() method to retrieve data on a variety of visitor behaviors.

Return value

Type	Description
List[Data]	A list of data assigned to the given visitor.

Here is the list of available Kameleoon::Configuration::RemoteVisitorDataFilter options:

Name	Type	Description	Default
previous_visit_amount optional	`int`	Number of previous visits to retrieve data from. Number between `1` and `25`	`1`
current_visit optional	`bool`	If True, current visit data will be retrieved	`True`
custom_data optional	`bool`	If True, custom data will be retrieved.	`True`
page_views optional	`bool`	If True, page data will be retrieved.	`False`
geolocation optional	`bool`	If True, geolocation data will be retrieved.	`False`
device optional	`bool`	If True, device data will be retrieved.	`False`
browser optional	`bool`	If True, browser data will be retrieved.	`False`
operating_system optional	`bool`	If True, operating system data will be retrieved.	`False`
conversions optional	`bool`	If True, conversion data will be retrieved.	`False`
experiments optional	`bool`	If True, experiment data will be retrieved.	`False`
kcs optional	`bool`	If true, Kameleoon Conversion Score (KCS) will be retrieved. Requires the AI Predictive Targeting add-on	`False`
visitor_code optional	`bool`	If true, Kameleoon will retrieve the `visitorCode` from the most recent visit and use it for the current visit. This is necessary if you want to ensure that the visitor, identified by their `visitorCode`, always receives the same variation across visits for cross-device experimentation.	`True`
cbs optional	`bool`	If true, Contextual Bandit score data will be retrieved.	`False`
personalization optional	`bool`	If True, personalization data will be retrieved. This is required for the personalization condition.	`False`

get_remote_visitor_data_async()

The get_remote_visitor_data_async method asynchronously retrieves custom data stored in remote Kameleoon servers for a visitor (specified using the visitor_code argument). If add_data is True, this method automatically adds the retrieved data to a visitor without requiring you to make a separate add_data call. You must have previously stored data in our remote servers, which you can add with any of the following tracking calls in the SDK:

flush
get_feature_variation_key
get_feature_variable
is_feature_active

Using the get_remote_visitor_data method along with the availability of our highly scalable servers provides a convenient method for accessing and synchronizing large amounts of data across all of the visitor’s devices. If you specify a visitor_code, the get_remote_visitor_data_async method uses the visitor_code as the unique visitor identifier, which is useful for cross-device experimentation. When you specify a visitor_code and set the is_unique_identifier parameter to true, the SDK links the flushed data to the visitor associated with the specified identifier.

    visitor_code = 'visitorCode'

    # Visitor data will be fetched and automatically added for `visitor_code`
    data_list = await kameleoon_client.get_remote_visitor_data_async(visitor_code)  # default timeout
    data_list = await kameleoon_client.get_remote_visitor_data_async(visitor_code, timeout=1.0)  # 1 second timeout

    # If you only want to fetch data and add it yourself manually, set `add_data` to `False`
    data_list = await kameleoon_client.get_remote_visitor_data_async(visitor_code, False)  # default timeout
    data_list = await kameleoon_client.get_remote_visitor_data_async(visitor_code, False, 1.0)  # 1 second timeout
    # If you want to fetch custom list of data types
    data_filter = RemoteVisitorDataFilter(25, customData=False, conversions=True, experiments=True)
    data_list = kameleoon_client.get_remote_visitor_data(visitor_code, data_filter=data_filter)

    # If you want the SDK to link the extracted data with the visitor associated with the specified identifier.
    kameleoon_client.add_data(UniqueIdentifier(True))
    data_list = kameleoon_client.get_remote_visitor_data(visitor_code)

Parameters

Name	Type	Description
visitor_code	str	The visitor code for which you want to retrieve the assigned data. This field is mandatory.
add_data	bool	A boolean indicating whether the method should automatically add retrieved data for a visitor. If not specified, the default value is True. This field is optional.
data_filter	RemoteVisitorDataFilter	Filter that specifies which data should be retrieved from visits. By default, only `CustomData` is retrieved from the current and latest previous visit (`RemoteVisitorDataFilter(previousVisitAmount=1, currentVisit=True, customData=True)` or `RemoteVisitorDataFilter()`). Other filters parameters are set to `False`. This field is optional.
is_unique_identifier (Deprecated)	Optional[bool]	An optional parameter for specifying if the `visitorCode` is a unique identifier. If not provided, the default value is `False`. The field is optional.
timeout	Optional[float]	Timeout (in seconds). This parameter specifies the maximum amount of time the method can block to wait for a result. This field is optional; if not provided, it will use the `default_timeout_millisecond` value from configuration file or two seconds if it’s not specified in the file.

Return value

Type	Description
List[Data]	A list of data assigned to the visitor.

Using parameters in get_remote_visitor_data_async()

The get_remote_visitor_data_async() method offers flexibility by letting you define various parameters when retrieving data on visitors. Whether you’re targeting based on goals, experiments, or variations, the same approach applies across all data types. For example, suppose you want to retrieve data on visitors who completed the goal “Order transaction”. You can specify parameters within the get_remote_visitor_data_async() method to refine your targeting. For instance, if you want to target only users who converted on the goal in their last five visits, you can set the previous_visit_amount parameter to 5 and conversions to true. The flexibility shown in this example is not limited to goal data. You can use parameters within the get_remote_visitor_data_async() method to retrieve data on a variety of visitor behaviors.

Here is the list of available Kameleoon::Configuration::RemoteVisitorDataFilter options:

Name	Type	Description	Default
previous_visit_amount optional	`int`	Number of previous visits to retrieve data from. Number between `1` and `25`	`1`
current_visit optional	`bool`	If True, current visit data will be retrieved	`True`
custom_data optional	`bool`	If True, custom data will be retrieved.	`True`
page_views optional	`bool`	If True, page data will be retrieved.	`False`
geolocation optional	`bool`	If True, geolocation data will be retrieved.	`False`
device optional	`bool`	If True, device data will be retrieved.	`False`
browser optional	`bool`	If True, browser data will be retrieved.	`False`
operating_system optional	`bool`	If True, operating system data will be retrieved.	`False`
conversions optional	`bool`	If True, conversion data will be retrieved.	`False`
experiments optional	`bool`	If True, experiment data will be retrieved.	`False`
kcs optional	`bool`	If true, Kameleoon Conversion Score (KCS) will be retrieved. Requires the AI Predictive Targeting add-on	`False`
visitor_code optional	`bool`	If true, Kameleoon will retrieve the `visitorCode` from the most recent visit and use it for the current visit. This is necessary if you want to ensure that the visitor, identified by their `visitorCode`, always receives the same variation across visits for Cross-device experimentation.	`True`
cbs optional	`bool`	If true, Contextual Bandit score data will be retrieved.	`False`

get_visitor_warehouse_audience()

Synchronously retrieves all audience data associated with the visitor in your data warehouse using the specified visitor_code and warehouse_key. The warehouse_key is typically your internal user ID. The custom_data_index parameter corresponds to the Kameleoon custom data that Kameleoon uses to target your visitors. You can refer to the warehouse targeting documentation for additional details. The method returns a CustomData object, confirming that the data has been added to the visitor and is available for targeting purposes.

If you want to retrieve the data asynchronously, use the get_visitor_warehouse_audience_async method instead.

try:
    warehouse_audience_data = kameleoon_client.\
        get_visitor_warehouse_audience(visitor_code, custom_data_index)  # default timeout
    warehouse_audience_data = kameleoon_client.\
        get_visitor_warehouse_audience(visitor_code, custom_data_index, timeout=1.0)  # 1 second timeout

    warehouse_audience_data = kameleoon_client.\
        get_visitor_warehouse_audience(visitor_code, custom_data_index, warehouse_key)  # default timeout
    warehouse_audience_data = kameleoon_client.\
        get_visitor_warehouse_audience(visitor_code, custom_data_index, warehouse_key, 1.0)  # 1 second timeout

    # Your custom code
except VisitorCodeInvalid as e:
    # Handle exception

Parameters

Name	Type	Description
visitor_code	str	A unique visitor identification string, can’t exceed 255 characters length. This field is mandatory.
custom_data_index	int	An integer representing the index of the custom data you want to use to target your BigQuery Audiences. This field is mandatory.
warehouse_key	Optional[str]	A unique key identifying the warehouse data (usually your internal user ID). This field is optional.
timeout	Optional[float]	Timeout (in seconds). This parameter specifies the maximum amount of time to wait for a result. This field is optional. If not provided, the default value is 10 seconds.

Return value

Type	Description
Optional[CustomData]	A `CustomData` instance confirming that the data has been added to the visitor.

Exceptions thrown

Type	Description
VisitorCodeInvalid	Exception indicating that the provided visitor code is not valid. It is either empty or longer than 255 characters.

get_visitor_warehouse_audience_async()

Asynchronously retrieves all audience data associated with the visitor in your data warehouse using the specified visitor_code and warehouse_key. The warehouse_key is typically your internal user ID. The custom_data_index parameter corresponds to the Kameleoon custom data that Kameleoon uses to target your visitors. You can refer to the warehouse targeting documentation for additional details. The method returns a CustomData object, confirming that the data has been added to the visitor and is available for targeting purposes.

try:
    warehouse_audience_data = await kameleoon_client.\
        get_visitor_warehouse_audience_async(visitor_code, custom_data_index)  # default timeout
    warehouse_audience_data = await kameleoon_client.\
        get_visitor_warehouse_audience_async(visitor_code, custom_data_index, timeout=1.0)  # 1 second timeout

    warehouse_audience_data = await kameleoon_client.\
        get_visitor_warehouse_audience_async(visitor_code, custom_data_index, warehouse_key)  # default timeout
    warehouse_audience_data = await kameleoon_client.\
        get_visitor_warehouse_audience_async(visitor_code, custom_data_index, warehouse_key, 1.0)  # 1 second timeout

    # Your custom code
except VisitorCodeInvalid as e:
    # Handle exception

Parameters

Name	Type	Description
visitor_code	str	A unique visitor identification string, can’t exceed 255 characters length. This field is mandatory.
custom_data_index	int	An integer representing the index of the custom data you want to use to target your BigQuery Audiences. This field is mandatory.
warehouse_key	Optional[str]	A unique key identifying the warehouse data (usually your internal user ID). This field is optional.
timeout	Optional[float]	Timeout (in seconds). This parameter specifies the maximum amount of time to wait for a result. This field is optional. If not provided, the default value is 10 seconds.

Return value

Type	Description
Optional[CustomData]	A `CustomData` instance confirming that the data has been added to the visitor.

Exceptions thrown

Type	Description
VisitorCodeInvalid	Exception indicating that the provided visitor code is invalid. It is either empty or longer than 255 characters.

set_legal_consent()

You must use this method to specify whether the visitor has given legal consent to use personal data. Setting the consent parameter to False limits the types of data that you can include in tracking requests. This method helps you adhere to legal and regulatory requirements while responsibly managing visitor data. You can find more information on personal data in our consent management policy.

### if you use KameleoonWSGIMiddleware service
visitor_code = kameleoon_client.get_visitor_code(cookies_readonly=request.COOKIES)
kameleoon_client.set_legal_consent(visitor_code, True)

### if you want to manage cookies manually
cookies = http.cookies.SimpleCookie()
cookies.load(cookie_header)

visitor_code = kameleoon_client.get_visitor_code(cookies=cookies)
kameleoon_client.set_legal_consent(visitor_code, True, cookies)

cookie_header = cookies.output()

Consent revocation behavior

When you call set_legal_consent() with consent=False, the SDK does not delete the kameleoonVisitorCode cookie. Instead, it stops extending the cookie’s expiration date, allowing the cookie to persist until it naturally expires. If your compliance requirements demand the immediate removal of the cookie file upon opt-out, you must delete it manually using your framework’s native cookie management methods. The SDK will not remove the file automatically.

Parameters

Name	Type	Description
visitor_code	str	The user’s unique identifier. This field is required.
consent	bool	A boolean value representing the legal consent status. `true` indicates the visitor has given legal consent, `false` indicates the visitor has never provided or withdrawn legal consent. This field is required.
cookies	Optional[Dict[str, http.cookies.Morsel[str]]]	The cookies to be adjusted based on the legal consent status as `Dict[str, http.cookies.Morsel[str]]` or `http.cookies.SimpleCookie[str]` object. This field is optional.

Exceptions thrown

Type	Description
VisitorCodeInvalid	Exception indicating that the provided visitor code is invalid. It is either empty or longer than 255 characters.

forget()

The forget method removes a KameleoonClient instance from the KameleoonClientFactory with the specified site_code and frees resources used by the KameleoonClient instance. The KameleoonClient instance must not be used after calling the forget method. If you specify a visitor_code, the track_conversion method uses the visitor_code as the unique visitor identifier, which is useful for cross-device experimentation. When you specify a visitor_code and set the is_unique_identifier parameter to true, the SDK links the flushed data to the visitor associated with the specified identifier.

The is_unique_identifier can also be useful in other edge-case scenarios, such as when you can’t access the anonymous visitor_code that was originally assigned to the visitor, but you have access to an internal ID that is connected to the anonymous visitor using session merging capabilities.

require "kameleoon"
require "kameleoon/data"

visitor_code = kameleoon_client.get_visitor_code(request.COOKIES)
goal_id = 83023

kameleoon_client.add_data(visitor_code, Browser(BrowserType.CHROME))
kameleoon_client.add_data(
    visitor_code,
    PageView("https://url.com", "title", [3]),
    CustomData(2, "value")
)
kameleoon_client.add_data(visitor_code, Conversion(32, 10, false))
kameleoon_client.track_conversion(visitor_code, goal_id)

Arguments

Name	Type	Description
visitor_code	String	Unique identifier of the user. This field is mandatory.
goal_id	int	ID of the goal. This field is mandatory.
revenue	float	Revenue of the conversion. This field is optional.
is_unique_identifier	bool	When `True`, the SDK links the flushed data to the visitor associated with the specified identifier.

Goals and third-party analytics

get_engine_tracking_code()

Kameleoon integrates with several analytics solutions, including Mixpanel, Google Analytics 4, and Segment. To track server-side experiments correctly, call the get_engine_tracking_code() method after the visitor triggers an experiment. The SDK returns JavaScript queue commands for the experiments that the visitor triggered during the previous five seconds. When you insert this code into the page, Engine.js processes the commands and sends the exposure events through the active analytics integration. Refer to hybrid experimentation for more information on implementing this method.

engine_tracking_code = kameleoon_client.get_engine_tracking_code(visitor_code)

To use this feature, implement both the Python SDK and Kameleoon Engine.js. Because Engine.js is used only for tracking in this flow, you can install the asynchronous tag before the closing </body> tag.
If you only want to track experiments in Kameleoon and do not need to send exposure events to third-party analytics tools, use the JavaScript / TypeScript SDK. This option works well for serverless edge compute platforms. The JavaScript / TypeScript SDK automatically tracks variations when you call getVisitorCode, as long as you add the corresponding experiment assignments to window.kameleoonQueue.
You can insert the returned tracking code directly into an HTML <script> tag.

<html lang="en">
  <body>
    <script>
      const engineTrackingCode = `
        window.kameleoonQueue = window.kameleoonQueue || [];
        window.kameleoonQueue.push(['Experiments.assignVariation', 123456, 7890, true]);
        window.kameleoonQueue.push(['Experiments.trigger', 123456, true]);
        window.kameleoonQueue.push(['Experiments.assignVariation', 234567, 8901, true]);
        window.kameleoonQueue.push(['Experiments.trigger', 234567, true]);
      `;
      const script = document.createElement('script');

      script.textContent = engineTrackingCode;
      document.body.appendChild(script);
    </script>

  </body>
</html>

In this example, 123456 and 234567 are experiment IDs, and 7890 and 8901 are variation IDs. In your implementation, the SDK generates these values in the returned tracking code.

Parameters

Name	Type	Description
`visitor_code` required	`str`	Unique identifier of the visitor.

Return value

Type	Description
`str`	JavaScript code to insert into the page.

track_conversion()

📨 Sends Tracking Data to Kameleoon

Use this method to track a conversion for a specific goal and user. This method requires visitor_code and goal_id. In addition, this method also accepts an optional revenue, negative and metadata arguments. The visitor_code is usually identical to the one that was used when triggering the experiment. The track_conversion() method doesn’t return any value. This method is non-blocking as the server call is made asynchronously.

The parameter is_unique_identifier is deprecated. Please use UniqueIdentifier instead.The is_unique_identifier can also be useful in other edge-case scenarios, such as when you can’t access the anonymous visitor_code that was originally assigned to the visitor, but you do have access to an internal ID that is connected to the anonymous visitor using session merging capabilities.

visitor_code = "visitorCode"
goal_id = 83023

kameleoon_client.add_data(visitor_code, Browser(BrowserType.CHROME))
kameleoon_client.add_data(
    visitor_code,
    PageView("https://url.com", "title", [3]),
    CustomData(2, "value")
)
kameleoon_client.add_data(visitor_code, Conversion(32, 10, False))

# Add metadata
cd = CustomData(1, "metadata")
kameleoon_client.track_conversion(visitorCode, goalId, metadata=[cd])

Parameters

Name	Type	Description	Default
`visitor_code` required	`str`	Unique identifier of the visitor.
`goal_id` required	`int`	ID of the goal.
`revenue` optional	`float`	Revenue of the conversion.	`0`
`negative` optional	`bool`	Defines if the revenue is positive or negative.	`False`
`metadata` optional	`Optional[Iterable[CustomData]]`	Lets you set specific values for custom data which have been defined as metadata for the goal in the Kameleoon App. Example: `[CustomData{id: 5, value: "Payment Type"}, CustomData{id: 6, value: "Delivery Method"}]`. In this example, `5` and `6` are the indexes of the custom data (5 = “Payment Type”, 6 = “Delivery Method”).	`None`
`is_unique_identifier` (deprecated)	`bool`	An optional parameter for specifying if the visitor_code is a unique identifier.	`False`

metadata values are accessible through raw data exports and the results page.If the metadata parameter is provided, Kameleoon will use these specified values for the current conversion instead of what was previously collected using the add_data() method. If the parameter is omitted, Kameleoon will use the last tracked values for those CustomData prior to the conversion and within the same visit.Kameleoon will only consider the metadata values that are explicitly passed as parameters to the track_conversion() method.In the example below, Kameleoon will associate the conversion only with the custom data value explicitly provided as a parameter (here: index 5 with the value ‘Amex Credit Card’).

kameleoon_client.add_data(visitor_code, CustomData(5, "Credit Card"), CustomData(9, "Express Delivery"))
kameleoon_client.track_conversion(visitor_code, 10, metadata=[CustomData(5, "Amex Credit Card")])

Exceptions

Type	Description
`VisitorCodeInvalid`	Exception indicating that the provided visitor code is not valid. It is either empty or longer than 255 characters.

Events

on_update_configuration()

The on_update_configuration() method allows you to handle the event when configuration has updated data. It takes one input parameter, handler. The handler that will be called when the configuration is updated using a real-time configuration event.

kameleoon_client.on_update_configuration(
    // configuration was updated
)

Parameters

Name	Type	Description
`handler`	`Callable[[], None]`	The handler that will be called when the configuration is updated using a real-time configuration event.

Data types

Browser

The Browser data set stored here can be used to filter experiment and personalization reports by any value associated with it.

Name	Type	Description
`browser_type` required	`BrowserType`	List of browsers: `CHROME`, `INTERNET_EXPLORER`, `FIREFOX`, `SAFARI`, `OPERA`, `OTHER`.
`version` optional	`Optional[float]`	Version of the browser, floating point number represents major and minor version of the browser

kameleoon_client.add_data(visitor_code, Browser(BrowserType.CHROME))

kameleoon_client.add_data(visitor_code, Browser(BrowserType.SAFARI, 10))

PageView

Name	Type	Description
url	str	URL of the page viewed. This field is mandatory.
title	Optional[str]	Title of the page viewed. This field is optional.
referrers	Optional[List[int]]	Referrers of viewed pages. This field is optional.

The index (ID) of the referrer is available in the Acquisition channel configuration page of our Back-Office. Be careful: this index starts at 0, so the first acquisition channel you create for a given site will have the ID 0, not 1.

kameleoon_client.add_data(visitor_code, PageView("https://url.com", "title", [3]))

Conversion

The Conversion data set stored here can be used to filter experiment and personalization reports by any goal associated with it.

Each visitor can have multiple Conversion objects.
You can find the goal_id in the Kameleoon app.

Name	Type	Description	Default
`goal_id` required	`int`	ID of the goal.
`revenue` optional	`float`	Revenue of the conversion	`0`
`negative` optional	`bool`	Defines if the revenue is positive or negative.	`False`
`metadata` optional	`Optional[Iterable[CustomData]]`	Metadata of the conversion.	`None`

kameleoon_client.add_data(visitor_code, Conversion(32, 10))

kameleoon_client.add_data(visitor_code, Conversion(33, negative=True))

kameleoon_client.add_data(
    visitor_code,
    Conversion(34, 5, metadata=[
        CustomData(3, "metadata1", "md2"),
        CustomData(5, "md3"),
    ])
)

CustomData

CustomData allows any type of data to be easily associated with each visitor. It can then be used as a targeting condition in segments or as a filter/breakdown in experiment reports. To learn more about custom data, please refer to this article.

Name	Type	Description	Default
index_or_name required	`Union[int, str]`	Index or Name of the custom data. Either `index` or `name` must be provided to identify the data.
args required	`*str`	Values of the custom data to be stored.
overwrite optional	`bool`	Flag to explicitly control how the values are stored and how they appear in reports. See more	`True`

Each visitor can only have one CustomData for each unique index. Adding another CustomData with the same index will replace the existing CustomData.
The custom data index can be found in the Custom Data dashboard under the “INDEX” column.
To prevent the SDK from sending data with the selected index to Kameleoon servers for privacy reasons, enable the Use this data only locally for targeting purposes option when creating custom data.
Adding a CustomData instance created with a name when the SDK instance configuration is not up to date or the name is not registered, will result in the data being ignored.

from kameleoon.data import CustomData

kameleoon_client.add_data(visitor_code, CustomData(1, "value"))

# With several values
kameleoon_client.add_data(visitor_code, CustomData(1, "value1", "value2"))

# To set the 'overwrite' flag to false
kameleoon_client.add_data(visitor_code, CustomData(1, "value", overwrite=False))

# To use a name instead of the index
kameleoon_client.add_data(visitor_code, CustomData("my-custom-data", "value"))

Device

Name	Type	Description
device	DeviceType	List of devices: `PHONE`, `TABLET`, `DESKTOP`. This field is mandatory.

from kameleoon import Device, DeviceType

kameleoon_client.add_data(visitor_code, Device(DeviceType.DESKTOP))

UserAgent

Store information on the visitor’s user-agent. Server-side experiments are more vulnerable to bot traffic than client-side experiments. To address this, Kameleoon uses the IAB/ABC International Spiders and Bots List to identify known bots and spiders. Kameleoon also uses the UserAgent field to filter out bots and other unwanted traffic that could otherwise skew your conversion metrics. For more details, see the help article on bot filtering. If you use internal bots, we suggest that you pass the value curl/8.0 of the userAgent to exclude them from our analytics.

Name	Type	Description
value	str	The User-Agent value that will be sent with tracking requests. This field is mandatory.

from kameleoon.data import UserAgent

kameleoon_client.add_data(visitor_code, UserAgent('userAgent'))

UniqueIdentifier

If you don’t add UniqueIdentifier for a visitor, visitor_code is used as the unique visitor identifier, which is useful for cross-device experimentation. When you add UniqueIdentifier for a visitor, the SDK links the flushed data to the visitor associated with the specified identifier. The UniqueIdentifier can also be useful in other edge-case scenarios, such as when you can’t access the anonymous visitor_code that was originally assigned to the visitor, but you have access to an internal ID that is connected to the anonymous visitor using session merging capabilities.

Name	Type	Description
value	bool	Parameter for specifying if the visitor_code is a unique identifier. This field is required.

from kameleoon.data import UniqueIdentifier

kameleoon_client.add_data(visitor_code, UniqueIdentifier(True))

OperatingSystem

OperatingSystem contains information about the operating system on the visitor’s device.

Name	Type	Description
os_type	OperatingSystemType	List of types: WINDOWS, MAC, IOS, LINUX, ANDROID, WINDOWS_PHONE. This field is mandatory.

Each visitor can only have one OperatingSystem. Adding a second OperatingSystem overwrites the first one.

from kameleoon.data import OperatingSystem, OperatingSystemType

kameleoon_client.add_data(visitor_code, OperatingSystem(OperatingSystemType.ANDROID))

Cookie contains information about the cookies stored on the visitor’s device.

Name	Type	Description
cookies	Dict[str, str]	Dict (`{cookie_name: cookie_value}`) consisting of cookie keys and values. This field is mandatory.

Each visitor can only have one Cookie. Adding a second Cookie overwrites the first one.

from kameleoon.data import Cookie

cookie = Cookie({"k1": "v1", "k2": "v2"})
kameleoon_client.add_data(visitor_code, cookie)

Geolocation

Geolocation contains the visitor’s geolocation details.

Name	Type	Description
`country` required	`str`	The country of the visitor.
`region` optional	`Optional[str]`	The region of the visitor.
`city` optional	`Optional[str]`	The city of the visitor.
`postal_code` optional	`Optional[str]`	The postal code of the visitor.
`latitude` optional	`Optional[float]`	The latitude coordinate representing the location of the visitor. Coordinate number represents decimal degrees.
`longitude` optional	`Optional[float]`	The longitude coordinate representing the location of the visitor. Coordinate number represents decimal degrees.

Each visitor can have only one Geolocation. Adding a second Geolocation overwrites the first one.

from kameleoon.data import Geolocation

kameleoon_client.add_data(visitor_code, Geolocation("France", "Île-de-France", "Paris"))

ApplicationVersion

ApplicationVersion represents the semantic version number of your application.

A visitor can have only one ApplicationVersion. Adding a second instance will overwrite the first one.

Name	Type	Description
version optional	`str`	The mobile application version. This field must follow semantic versioning. Accepted formats are `major`, `major.minor`, or `major.minor.patch`.

kameleoon_client_sdk.add_data(visitorCode, ApplicationVersion("10")) # major

kameleoon_client_sdk.add_data(visitorCode, ApplicationVersion("10.20")) # major.minor

kameleoon_client_sdk.add_data(visitorCode, ApplicationVersion("10.20.30")) # major.minor.patch

Returned Types

DataFile

The DataFile contains the SDK configuration details. It can be extended with additional information if required by clients. If you need more details, please contact your Customer Success Manager.

Name	Type	Description
`feature_flags`	`Dict[str, FeatureFlag]`	A map of `FeatureFlag` objects, keyed by feature flag keys.
`date_modified`	`int`	The timestamp (in milliseconds) indicating when the `DataFile` was last modified.

# Retrieves the dict of feature flags from the DataFile.
# The dict is keyed by feature flag identifiers, with each value being a FeatureFlag object.
feature_flags: Dict[str, FeatureFlag] = data_file.feature_flags

# Retrieves the last modification timestamp of the DataFile.
# The value is an int representing milliseconds since the Unix epoch.
date_modified: int = data_file.date_modified

FeatureFlag

The FeatureFlag represents a set of properties that define a feature flag itself — for example, its Variations, Rules, environment status, and other related details. It can be extended with additional information if required by clients. If you need more details, please contact your Customer Success Manager.

Name	Type	Description
`environment_enabled`	`bool`	Indicating whether the feature flag is enabled in the current environment.
`default_variation_key`	`str`	The key of the default variation associated with the feature flag.
`variations`	`Dict[str, Variation]`	A map of `Variation` objects, keyed by variation keys.
`rules`	`Iterable[Rule]`	A list of `Rule` objects

# Check whether the feature flag is enabled in the current environment
is_environment_enabled: bool = feature_flag.environment_enabled

# Retrieve the key of the default variation
default_variation_key: str = feature_flag.default_variation_key

# Retrieve the default variation object
default_variation: Variation = feature_flag.default_variation

# Retrieve all variations of the feature flag as a dict (key = variation key, value = Variation object)
variations: Dict[str, Variation] = feature_flag.variations

# Retrieve all targeting rules associated with the feature flag
rules: Iterable[Rule] = feature_flag.rules

Variation

Variation contains information about the assigned variation to the visitor (or the default variation, if no specific assignment exists).

Name	Type	Description
key	`str`	The unique key identifying the variation.
id_	`Optional[int]`	The ID of the assigned variation (or `None` if it’s the default variation).
experiment_id	`Optional[int]`	The ID of the experiment associated with the variation (or `None` if default).
variables	`Dict[str, Variable]`	A dict containing the variables of the assigned variation, keyed by variable names. This value could be empty if no variables are associated.

The Variation object provides details about the assigned variation and its associated experiment, while the Variable object contains specific details about each variable within a variation.
Ensure that your code handles the case where id_ or experiment_id may be None, indicating a default variation.
The variables hash might be empty if no variables are associated with the variation.

# Retrieving the variation key
variation_key: str = variation.key

# Retrieving the variation id
variation_id: Optional[int] = variation.id_

# Retrieving the experiment id
experiment_id: Optional[int] = variation.experiment_id

# Retrieving the variables map
variables: Dict[str, Variable] = variation.variables

Variable

Variable contains information about a variable associated with the assigned variation.

Name	Type	Description
key	`str`	The unique key identifying the variable.
type	`str`	The type of the variable. Possible values: BOOLEAN, NUMBER, STRING, JSON, JS, CSS
value	`Optional[Any]`	The value of the variable, which can be of the following types: bool, int, float, str, dict, list.

# Retrieving the variable key
variables: Dict[str, Variable] = variation.variables

# Variable type can be retrieved for further processing
variable_type: str = variables["isDiscount"].type

# Retrieving the variable value by key
is_discount: Optional[bool] = variables["isDiscount"].value

# Variable value can be of different types
title: Optional[str] = variables["title"].value

Deprecated methods

These methods are deprecated and will be removed in SDK version 4.0.0.

get_feature_variation_key()

📨 Sends Tracking Data to Kameleoon

Use get_variation() instead.

To get a feature variation key, call the get_feature_variation_key method. This method takes a visitor_code and feature_key as mandatory arguments to get a variation key for a given user. If such a user has never been associated with this feature flag, the SDK returns a variation key randomly (according to the feature flag rules). If a user with a given visitor_code is already registered with this feature flag, it will detect the previous variation key value. If the user does not match any of the rules, the default value will be returned, which we can define in your customer’s account. You must ensure that proper error handling is set up in your code as shown in the example to the right to catch potential exceptions. If you specify a visitor_code, the get_feature_variation_key method uses the visitor_code as the unique visitor identifier, which is useful for cross-device experimentation. When you specify a visitor_code and set the is_unique_identifier parameter to true, the SDK links the flushed data to the visitor associated with the specified identifier.

visitor_code = kameleoon_client.get_visitor_code(request.COOKIES)

feature_key = "feature_key"
variation_key = ""

try
    variation_key = kameleoon_client.get_feature_variation_key(visitor_code, feature_key)
    if variation_key == 'on':
        # main variation key is selected for visitorCode
    elif variation_key == 'alternative_variation':
        # alternative variation key
    else:
        # default variation key
except FeatureNotFound as ex:
    # The user will not be counted in the experiment, but should see the reference variation.
except VisitorCodeInvalid as ex:
    # The visitor code you passed to the method isn't valid and can't be accepted by SDK.
except FeatureEnvironmentDisabled as ex:
    # The feature flag is disabled for certain environments.

Parameters

Name	Type	Description
visitor_code	string	Unique identifier of the user. This field is mandatory.
feature_key	string	Key of the feature you want to expose to a user. This field is mandatory.
is_unique_identifier (Deprecated)	Optional[bool]	When `True`, the SDK links the flushed data to the visitor associated with the specified identifier.

Return value

Type	Description
string	Variation key of the feature flag that is registered for a given visitor_code.

Exceptions thrown

Type	Description
FeatureNotFound	Exception indicating that the requested feature ID has not been found in the SDK’s internal configuration. This exception is usually normal and means that the feature flag has not yet been activated on Kameleoon’s side (but code implementing the feature is already deployed on the web-application’s side).
VisitorCodeInvalid	Exception indicating that the provided visitor code is not valid (empty, or longer than 255 characters).
FeatureEnvironmentDisabled	Exception indicating that the feature flag is disabled for certain environments.

get_active_features()

Use get_variations() instead.

This method only takes the input parameter visitorCode. The result only contains active features for a given visitor.

try:
    active_features = kameleoon_client_sdk.get_active_features(visitor_code)
except VisitorCodeInvalid as e:
    # Handle exception

Arguments

Name	Type	Description
visitor_code	str	Unique identifier of the user. This field is optional.

Return value

Type	Description
Dict[str, Variation]	List of features with assigned variations that are active for a given visitor_code

Exceptions thrown

Type	Description
VisitorCodeInvalid	Exception indicating that the provided visitor code is not valid. It is either empty or longer than 255 characters.

get_active_feature_list_for_visitor()

Use get_variation() instead.

This method only takes the input parameter visitorCode. The result only contains the active feature flags for a given visitor.

active_feature_flag_for_visitor = kameleoonClient.get_active_feature_list_for_visitor(visitor_code)

Arguments

Name	Type	Description
visitor_code	str	Unique identifier of the user. This field is optional.

Return value

Type	Description
List[str]	List of feature flag keys that are active for a given visitor_code

get_feature_variable()

📨 Sends Tracking Data to Kameleoon

Use get_variation() instead.

Previously called obtain_feature_variable, which was removed in SDK version 3.0.0.

To get a variable of the variation key associated with a user, call the get_feature_variable method. This method takes a visitor_code, feature_key, and variable_key as mandatory arguments. If a user has never been associated with this feature flag, the SDK returns a variable value randomly (according to the feature flag rules). If a user with a given visitor_code is already registered with this feature flag, it will detect the variable value for the associated variation. If the user does not match any of the rules, the default variable will be returned. You must ensure that proper error handling is set up in your code as shown in the example to the right to catch potential exceptions. If you specify a visitor_code, the get_feature_variable method uses the visitor_code as the unique visitor identifier, which is useful for cross-device experimentation. When you specify a visitor_code and set the is_unique_identifier parameter to true, the SDK links the flushed data to the visitor associated with the specified identifier.

visitor_code = kameleoon_client.get_visitor_code(request.COOKIES)

feature_key = "feature_key"
variable_key = "variable_key"
variation_value = ""

try:
    variable_value = kameleoon_client.get_feature_variable(visitor_code, feature_key, variable_key)
except FeatureNotFound as ex:
    # The user will not be counted in the experiment, but should see the reference variation.
except FeatureVariableNotFound as ex:
    # Requested variable not defined on Kameleoon's side
except VisitorCodeInvalid as ex:
    # The visitor code you passed to the method isn't valid and can't be accepted by SDK.
except FeatureEnvironmentDisabled as ex:
    # The feature flag is disabled for certain environments.

# your custom code depending of variable_value, e.g.
if variable_value == "value-1":
    # your custom code if variable == 'value-1'
elif variable_value == "value-2":
    # your custom code if variable == 'value-2'
else:
    # ...

Parameters

Name	Type	Description
visitor_code	str	Unique identifier of the user. This field is mandatory.
feature_key	str	Key of the feature you want to expose to a user. This field is mandatory.
variable_key	str	Name of the variable you want to get a value. This field is mandatory.
is_unique_identifier (Deprecated)	Optional[bool]	When `True`, the SDK links the flushed data to the visitor associated with the specified identifier.

Return value

Type	Description
Union[bool, str, float, Dict[str, Any], List[Any], None]	Value of a variation’s variable that is registered for a given visitor_code for this feature flag. Possible types: bool, float, str, List, Dict, None

Exceptions thrown

Type	Description
FeatureNotFound	Exception indicating that the requested feature ID has not been found in the SDK’s internal configuration. This exception is usually normal and means that the feature flag has not yet been activated on Kameleoon’s side (but code implementing the feature is already deployed on the web-application’s side).
VisitorCodeInvalid	Exception indicating that the provided visitor code is not valid (empty, or longer than 255 characters).
FeatureVariableNotFound	Exception indicating that the requested variable has not been found. Check that the variable’s key matches the one in your code.
FeatureEnvironmentDisabled	Exception indicating that the feature flag is disabled in certain environments.

get_feature_variation_variables()

Use get_variation() instead.

Previously called get_feature_all_variables, which was removed in SDK version 3.0.0.

To retrieve the all feature variables, call the get_feature_variation_variables method. A feature variable can be changed easily via our web application. This method takes the feature_key input parameter. It will return data with the Dict[str,Any] type, as defined on the web interface. It will throw an exception (FeatureNotFound) if the requested feature has not been found in the SDK’s internal configuration.

feature_key = "myFeature"

try
    data = kameleoon_client.get_feature_variation_variables(feature_key)
except FeatureNotFound as ex:
    # The feature is not activated on Kameleoon's side.
except FeatureEnvironmentDisabled as ex:
    # The feature flag is disabled for certain environments.

Parameters

Name	Type	Description
feature_key	String	Key of the feature you want to obtain. This field is mandatory.

Return value

Type	Description
Dict[str, Any]	Data associated with this feature flag. The value can be int, str, bool or Dict or List (depending on the type defined on the web interface).

Exceptions thrown

Type	Description
FeatureNotFound	Exception indicating that the requested feature ID has not been found in the SDK’s internal configuration. This exception is usually normal and means that the feature flag has not yet been activated on Kameleoon’s side.
FeatureEnvironmentDisabled	Exception indicating that the feature flag is disabled in certain environments.

get_feature_list()

Previously called obtain_feature_list, which was removed in SDK version 3.0.0.

Returns a list of feature flag keys currently available for the SDK.

all_feature_list = kameleoon_client.get_feature_list()

Return value

Type	Description
`List[str]`	List of feature flag keys

​Developer guide

​Getting started

​Installing the Python client

​Additional configuration

​Initializing the Kameleoon client

​Activating a feature flag

Assigning a unique ID to a user

Retrieving a flag configuration

Adding data points to target a user or filter / breakdown visits in reports

Tracking goal conversions

Sending events to analytics solutions

​Using the Kameleoon Python SDK in a Django environment

​Cross-device experimentation

​Synchronizing custom data across devices

​Using custom data for session merging

​Using a custom bucketing key

​Use cases

​Technical details

​Technical requirements

​Targeting conditions

​Logging

​Log levels

​Custom handling of logs

​Reference

​create()

Arguments

Exceptions thrown

​wait_init_async()

Return value

​wait_init()

Return value

​Feature flags and variations

​is_feature_active()

Parameters

Return value

Exceptions thrown

​get_variation()

Parameters

Return value

Exceptions thrown

​get_variations()

Parameters

Return value

Exceptions thrown

​get_data_file()

Return value

​set_forced_variation()

Parameters

Exceptions thrown

​evaluate_audiences()

Parameters

Exceptions thrown

​Visitor data

​get_visitor_code()

Parameters

Return value

Exceptions thrown

​add_data()

Parameters

Exceptions

​flush()

Arguments

​get_remote_data()

Parameters

Return value

​get_remote_data_async()

Parameters

Return value

​get_remote_visitor_data()

Parameters

Using parameters in get_remote_visitor_data()

Return value

​get_remote_visitor_data_async()

Parameters

Return value

Using parameters in get_remote_visitor_data_async()

​get_visitor_warehouse_audience()

Parameters

Return value

Exceptions thrown

Developer guide

Getting started

Installing the Python client

Additional configuration

Initializing the Kameleoon client

Activating a feature flag

Using the Kameleoon Python SDK in a Django environment

Cross-device experimentation

Synchronizing custom data across devices

Using custom data for session merging

Using a custom bucketing key

Use cases

Technical details

Technical requirements

Targeting conditions

Logging

Log levels

Custom handling of logs

Reference

create()

wait_init_async()

wait_init()

Feature flags and variations

is_feature_active()

get_variation()

get_variations()

get_data_file()

set_forced_variation()

evaluate_audiences()

Visitor data

get_visitor_code()

add_data()

flush()

get_remote_data()

get_remote_data_async()

get_remote_visitor_data()

get_remote_visitor_data_async()

get_visitor_warehouse_audience()

get_visitor_warehouse_audience_async()

set_legal_consent()

forget()

Goals and third-party analytics

get_engine_tracking_code()

track_conversion()

Events

on_update_configuration()

Data types

Browser

PageView

Conversion

CustomData

Device

UserAgent

UniqueIdentifier

OperatingSystem

Cookie

Geolocation

ApplicationVersion

Returned Types

DataFile

FeatureFlag

Variation

Variable

Deprecated methods

get_feature_variation_key()

get_active_features()

get_active_feature_list_for_visitor()

get_feature_variable()

get_feature_variation_variables()

get_feature_list()