---
title: OptimizelyConfig for the Python SDK
slug: feature-experimentation/docs/optimizelyconfig-python
docTags: 
createdAt: 2026-08-05T20:39:52.000Z
---

Optimizely Feature Experimentation SDKs open a well-defined set of public APIs, hiding implementation details. However, you may need access to project configuration data within the [datafile](docId:3LmHm4b3kTxKBuoR93KN8). The following section extends the public APIs to define data models and access methods, which you can use to access project configuration data.

A public configuration data model (OptimizelyConfig) is defined as a structured format of static Optimizely Project data.

### Get `OptimizelyConfig`

You can access `OptimizelyConfig` through the `OptimizelyClient` (top-level) using this public API call.

```python
def get_optimizely_config(self)
```

`get_optimizely_config` returns an `OptimizelyConfig` instance, which includes the following:

- Environment key
- SDK key
- Datafile revision number
- Experiments mapped by key values
- All attributes
- All audiences
- All events
- Feature flags mapped by key values
- Function to retrieve the project configuration (the datafile)

:::hint{type="info"}
When the system updates the datafile, you can add a [OptimizelyConfigUpdate notification listener](#)  to get notified. After receiving the notification, call the method to get the updated `OptimizelyConfig` data.
:::

### Get datafile

To share the same datafile between multiple SDK instances, such as in a client and server scenario, you can pass a JSON string representation of the config (the datafile) between the instances. To get the datafile, use the `OptimizelyConfig` object's `get_datafile` method. For information, see [Sharing the datafile with multiple SDK implementations](docId\:eH-UMm_rOn_GdGDGLV6__).

### Object model

The following sample shows the object model for `OptimizelyConfig`:

```python
class OptimizelyConfig(object):
    def __init__(self, revision, experiments_map, features_map, sdk_key=None, environment_key=None, attributes=None, events=None,
                 audiences=None):
        self.revision = revision
        # This experiments_map is for experiments of legacy projects only.
  			# For flag projects, experiment keys are not guaranteed to be unique 
			  # across multiple flags, so this map may not include all experiments 
  			# when keys conflict.
        self.experiments_map = experiments_map
        self.features_map = features_map
        self.sdk_key = sdk_key or ''
        self.environment_key = environment_key or ''
        self.attributes = attributes or []
        self.events = events or []
        self.audiences = audiences or []


class OptimizelyExperiment(object):
    def __init__(self, id, key, variations_map, audiences=''):
        self.id = id
        self.key = key
        self.variations_map = variations_map
        self.audiences = audiences

class OptimizelyFeature(object):
    def __init__(self, id, key, variables_map, experiments_map):
        self.id = id
        self.key = key
        self.variables_map = variables_map
        self.delivery_rules = []
        self.experiment_rules = []
        
				# Deprecated. Use experiment_rules and delivery_rules. 
        self.experiments_map = experiments_map

class OptimizelyVariation(object):
    def __init__(self, id, key, feature_enabled, variables_map):
        self.id = id
        self.key = key
        self.feature_enabled = feature_enabled
        self.variables_map = variables_map


class OptimizelyVariable(object):
    def __init__(self, id, key, variable_type, value):
        self.id = id
        self.key = key
        self.type = variable_type
        self.value = value


class OptimizelyAttribute(object):
    def __init__(self, id, key):
        self.id = id
        self.key = key


class OptimizelyEvent(object):
    def __init__(self, id, key, experiment_ids):
        self.id = id
        self.key = key
        self.experiment_ids = experiment_ids


class OptimizelyAudience(object):
    def __init__(self, id, name, conditions):
        self.id = id
        self.name = name
        self.conditions = conditions
```

## Examples

You can access `OptimizelyConfig` from the `OptimizelyClient` (top-level) using the following code example:

```python
from optimizely import optimizely
optimizely_client = optimizely.Optimizely(sdk_key='YOUR_SDK_KEY')

config = optimizely_client.get_optimizely_config()

print('REVISION ', config.revision)
print('SDK KEY ', config.sdk_key)
print('ENV KEY ', config.environment_key)

print("[OptimizelyConfig] revision = ", config.revision)
print("[OptimizelyConfig] sdk_key = ", config.sdk_key)
print("[OptimizelyConfig] environment_key = ", config.environment_key)

print("[OptimizelyConfig] attributes:")
for attribute in config.attributes:
    print('[optimizelyConfig]  - (id, key) ', attribute.id, attribute.key)

print("[OptimizelyConfig] audiences:")
for audience in config.audiences:
    print('[OptimizelyConfig]  - (id, name, conditions) ', audience.id, audience.name, audience.conditions)

print("[OptimizelyConfig] events:")
for event in config.events:
    print("[OptimizelyConfig]  - (id, key, experimentIds) ", event.id, event.key, event.experiment_ids)

# all flags
flags = config.features_map.values()
print('[OptimizelyConfig]  - flags ', flags)

flag_keys = config.features_map.keys()
print('[OptimizelyConfig]  - flag keys ', flag_keys)

for flag_key in flag_keys:
    flag = config.features_map[flag_key]

    experiment_rules = flag.experiment_rules
    delivery_rules = flag.delivery_rules

    print(experiment_rules)
    print(delivery_rules)

    # use experiment rules and delivery rules and other flag data here...
    for experiment in experiment_rules:
        print("[OptimizelyConfig]  - experiment rule-key = ", experiment.key)
        print("[OptimizelyConfig]  - experiment audiences = ", experiment.audiences)
        print("[OptimizelyConfig]  - experiment variations map = ", experiment.variations_map)

        variations_map = experiment.variations_map
        variation_keys = variations_map.keys()

        for variation_key in variation_keys:
            print("[OptimizelyConfig]  - variation = ", variation_key)       # not the same as in swift!

            map_of_variables = variations_map[variation_key].variables_map
            variable_keys = map_of_variables.keys()

            for variable_key in variable_keys:
                variable = map_of_variables[variable_key]
                print('[OptimizelyConfig]  - variable = ', variable_key, variable.value)

    for delivery in delivery_rules:
        print("[OptimizelyConfig]  - delivery rule-key = ", delivery.key)
        print("[OptimizelyConfig]  - delivery audiences = ", delivery.audiences)

# listen to OPTIMIZELY_CONFIG_UPDATE to get updated data
def on_config_update_listener(*args):
    config = optimizely_client.get_optimizely_config()

optimizely_client.notification_center.add_notification_listener(
    enums.NotificationTypes.OPTIMIZELY_CONFIG_UPDATE, on_config_update_listener)
```