Module aws_lambda_powertools.utilities.feature_flags

Advanced feature flags utility

Expand source code
"""Advanced feature flags utility"""
from .appconfig import AppConfigStore
from .base import StoreProvider
from .exceptions import ConfigurationStoreError
from .feature_flags import FeatureFlags
from .schema import RuleAction, SchemaValidator

__all__ = [
    "ConfigurationStoreError",
    "FeatureFlags",
    "RuleAction",
    "SchemaValidator",
    "AppConfigStore",
    "StoreProvider",
]

Sub-modules

aws_lambda_powertools.utilities.feature_flags.appconfig
aws_lambda_powertools.utilities.feature_flags.base
aws_lambda_powertools.utilities.feature_flags.exceptions
aws_lambda_powertools.utilities.feature_flags.feature_flags
aws_lambda_powertools.utilities.feature_flags.schema

Classes

class AppConfigStore (environment: str, application: str, name: str, max_age: int = 5, sdk_config: Optional[botocore.config.Config] = None, envelope: Optional[str] = '', jmespath_options: Optional[Dict[~KT, ~VT]] = None)

Helper class that provides a standard way to create an ABC using inheritance.

This class fetches JSON schemas from AWS AppConfig

Parameters

environment : str
Appconfig environment, e.g. 'dev/test' etc.
application : str
AppConfig application name, e.g. 'powertools'
name : str
AppConfig configuration name e.g. my_conf
max_age : int
cache expiration time in seconds, or how often to call AppConfig to fetch latest configuration
sdk_config : Optional[Config]
Botocore Config object to pass during client initialization
envelope : Optional[str]
JMESPath expression to pluck feature flags data from config
jmespath_options : Optional[Dict]
Alternative JMESPath options to be included when filtering expr
Expand source code
class AppConfigStore(StoreProvider):
    def __init__(
        self,
        environment: str,
        application: str,
        name: str,
        max_age: int = 5,
        sdk_config: Optional[Config] = None,
        envelope: Optional[str] = "",
        jmespath_options: Optional[Dict] = None,
    ):
        """This class fetches JSON schemas from AWS AppConfig

        Parameters
        ----------
        environment: str
            Appconfig environment, e.g. 'dev/test' etc.
        application: str
            AppConfig application name, e.g. 'powertools'
        name: str
            AppConfig configuration name e.g. `my_conf`
        max_age: int
            cache expiration time in seconds, or how often to call AppConfig to fetch latest configuration
        sdk_config: Optional[Config]
            Botocore Config object to pass during client initialization
        envelope : Optional[str]
            JMESPath expression to pluck feature flags data from config
        jmespath_options : Optional[Dict]
            Alternative JMESPath options to be included when filtering expr
        """
        super().__init__()
        self.environment = environment
        self.application = application
        self.name = name
        self.cache_seconds = max_age
        self.config = sdk_config
        self.envelope = envelope
        self.jmespath_options = jmespath_options
        self._conf_store = AppConfigProvider(environment=environment, application=application, config=sdk_config)

    def get_configuration(self) -> Dict[str, Any]:
        """Fetch feature schema configuration from AWS AppConfig

        Raises
        ------
        ConfigurationStoreError
            Any validation error or AppConfig error that can occur

        Returns
        -------
        Dict[str, Any]
            parsed JSON dictionary
        """
        try:
            # parse result conf as JSON, keep in cache for self.max_age seconds
            config = cast(
                dict,
                self._conf_store.get(
                    name=self.name,
                    transform=TRANSFORM_TYPE,
                    max_age=self.cache_seconds,
                ),
            )

            if self.envelope:
                config = jmespath_utils.extract_data_from_envelope(
                    data=config, envelope=self.envelope, jmespath_options=self.jmespath_options
                )

            return config
        except (GetParameterError, TransformParameterError) as exc:
            err_msg = traceback.format_exc()
            if "AccessDenied" in err_msg:
                raise StoreClientError(err_msg) from exc
            raise ConfigurationStoreError("Unable to get AWS AppConfig configuration file") from exc

Ancestors

Methods

def get_configuration(self) ‑> Dict[str, Any]

Fetch feature schema configuration from AWS AppConfig

Raises

ConfigurationStoreError
Any validation error or AppConfig error that can occur

Returns

Dict[str, Any]
parsed JSON dictionary
Expand source code
def get_configuration(self) -> Dict[str, Any]:
    """Fetch feature schema configuration from AWS AppConfig

    Raises
    ------
    ConfigurationStoreError
        Any validation error or AppConfig error that can occur

    Returns
    -------
    Dict[str, Any]
        parsed JSON dictionary
    """
    try:
        # parse result conf as JSON, keep in cache for self.max_age seconds
        config = cast(
            dict,
            self._conf_store.get(
                name=self.name,
                transform=TRANSFORM_TYPE,
                max_age=self.cache_seconds,
            ),
        )

        if self.envelope:
            config = jmespath_utils.extract_data_from_envelope(
                data=config, envelope=self.envelope, jmespath_options=self.jmespath_options
            )

        return config
    except (GetParameterError, TransformParameterError) as exc:
        err_msg = traceback.format_exc()
        if "AccessDenied" in err_msg:
            raise StoreClientError(err_msg) from exc
        raise ConfigurationStoreError("Unable to get AWS AppConfig configuration file") from exc
class ConfigurationStoreError (*args, **kwargs)

When a configuration store raises an exception on config retrieval or parsing

Expand source code
class ConfigurationStoreError(Exception):
    """When a configuration store raises an exception on config retrieval or parsing"""

Ancestors

  • builtins.Exception
  • builtins.BaseException
class FeatureFlags (store: StoreProvider)

Evaluates whether feature flags should be enabled based on a given context.

It uses the provided store to fetch feature flag rules before evaluating them.

Examples

from aws_lambda_powertools.utilities.feature_flags import FeatureFlags, AppConfigStore

app_config = AppConfigStore(
    environment="test",
    application="powertools",
    name="test_conf_name",
    max_age=300,
    envelope="features"
)

feature_flags: FeatureFlags = FeatureFlags(store=app_config)

Parameters

store : StoreProvider
Store to use to fetch feature flag schema configuration.
Expand source code
class FeatureFlags:
    def __init__(self, store: StoreProvider):
        """Evaluates whether feature flags should be enabled based on a given context.

        It uses the provided store to fetch feature flag rules before evaluating them.

        Examples
        --------

        ```python
        from aws_lambda_powertools.utilities.feature_flags import FeatureFlags, AppConfigStore

        app_config = AppConfigStore(
            environment="test",
            application="powertools",
            name="test_conf_name",
            max_age=300,
            envelope="features"
        )

        feature_flags: FeatureFlags = FeatureFlags(store=app_config)
        ```

        Parameters
        ----------
        store: StoreProvider
            Store to use to fetch feature flag schema configuration.
        """
        self._store = store

    @staticmethod
    def _match_by_action(action: str, condition_value: Any, context_value: Any) -> bool:
        if not context_value:
            return False
        mapping_by_action = {
            schema.RuleAction.EQUALS.value: lambda a, b: a == b,
            schema.RuleAction.STARTSWITH.value: lambda a, b: a.startswith(b),
            schema.RuleAction.ENDSWITH.value: lambda a, b: a.endswith(b),
            schema.RuleAction.IN.value: lambda a, b: a in b,
            schema.RuleAction.NOT_IN.value: lambda a, b: a not in b,
        }

        try:
            func = mapping_by_action.get(action, lambda a, b: False)
            return func(context_value, condition_value)
        except Exception as exc:
            logger.debug(f"caught exception while matching action: action={action}, exception={str(exc)}")
            return False

    def _evaluate_conditions(
        self, rule_name: str, feature_name: str, rule: Dict[str, Any], context: Dict[str, Any]
    ) -> bool:
        """Evaluates whether context matches conditions, return False otherwise"""
        rule_match_value = rule.get(schema.RULE_MATCH_VALUE)
        conditions = cast(List[Dict], rule.get(schema.CONDITIONS_KEY))

        if not conditions:
            logger.debug(
                f"rule did not match, no conditions to match, rule_name={rule_name}, rule_value={rule_match_value}, "
                f"name={feature_name} "
            )
            return False

        for condition in conditions:
            context_value = context.get(str(condition.get(schema.CONDITION_KEY)))
            cond_action = condition.get(schema.CONDITION_ACTION, "")
            cond_value = condition.get(schema.CONDITION_VALUE)

            if not self._match_by_action(action=cond_action, condition_value=cond_value, context_value=context_value):
                logger.debug(
                    f"rule did not match action, rule_name={rule_name}, rule_value={rule_match_value}, "
                    f"name={feature_name}, context_value={str(context_value)} "
                )
                return False  # context doesn't match condition

        logger.debug(f"rule matched, rule_name={rule_name}, rule_value={rule_match_value}, name={feature_name}")
        return True

    def _evaluate_rules(
        self, *, feature_name: str, context: Dict[str, Any], feat_default: bool, rules: Dict[str, Any]
    ) -> bool:
        """Evaluates whether context matches rules and conditions, otherwise return feature default"""
        for rule_name, rule in rules.items():
            rule_match_value = rule.get(schema.RULE_MATCH_VALUE)

            # Context might contain PII data; do not log its value
            logger.debug(f"Evaluating rule matching, rule={rule_name}, feature={feature_name}, default={feat_default}")
            if self._evaluate_conditions(rule_name=rule_name, feature_name=feature_name, rule=rule, context=context):
                return bool(rule_match_value)

            # no rule matched, return default value of feature
            logger.debug(f"no rule matched, returning feature default, default={feat_default}, name={feature_name}")
            return feat_default
        return False

    def get_configuration(self) -> Union[Dict[str, Dict], Dict]:
        """Get validated feature flag schema from configured store.

        Largely used to aid testing, since it's called by `evaluate` and `get_enabled_features` methods.

        Raises
        ------
        ConfigurationStoreError
            Any propagated error from store
        SchemaValidationError
            When schema doesn't conform with feature flag schema

        Returns
        ------
        Dict[str, Dict]
            parsed JSON dictionary

            **Example**

        ```python
        {
            "premium_features": {
                "default": False,
                "rules": {
                    "customer tier equals premium": {
                        "when_match": True,
                        "conditions": [
                            {
                                "action": "EQUALS",
                                "key": "tier",
                                "value": "premium",
                            }
                        ],
                    }
                },
            },
            "feature_two": {
                "default": False
            }
        }
        ```
        """
        # parse result conf as JSON, keep in cache for max age defined in store
        logger.debug(f"Fetching schema from registered store, store={self._store}")
        config = self._store.get_configuration()
        validator = schema.SchemaValidator(schema=config)
        validator.validate()

        return config

    def evaluate(self, *, name: str, context: Optional[Dict[str, Any]] = None, default: bool) -> bool:
        """Evaluate whether a feature flag should be enabled according to stored schema and input context

        **Logic when evaluating a feature flag**

        1. Feature exists and a rule matches, returns when_match value
        2. Feature exists but has either no rules or no match, return feature default value
        3. Feature doesn't exist in stored schema, encountered an error when fetching -> return default value provided

        Parameters
        ----------
        name: str
            feature name to evaluate
        context: Optional[Dict[str, Any]]
            Attributes that should be evaluated against the stored schema.

            for example: `{"tenant_id": "X", "username": "Y", "region": "Z"}`
        default: bool
            default value if feature flag doesn't exist in the schema,
            or there has been an error when fetching the configuration from the store

        Returns
        ------
        bool
            whether feature should be enabled or not

        Raises
        ------
        SchemaValidationError
            When schema doesn't conform with feature flag schema
        """
        if context is None:
            context = {}

        try:
            features = self.get_configuration()
        except ConfigurationStoreError as err:
            logger.debug(f"Failed to fetch feature flags from store, returning default provided, reason={err}")
            return default

        feature = features.get(name)
        if feature is None:
            logger.debug(f"Feature not found; returning default provided, name={name}, default={default}")
            return default

        rules = feature.get(schema.RULES_KEY)
        feat_default = feature.get(schema.FEATURE_DEFAULT_VAL_KEY)
        if not rules:
            logger.debug(f"no rules found, returning feature default, name={name}, default={feat_default}")
            return bool(feat_default)

        logger.debug(f"looking for rule match, name={name}, default={feat_default}")
        return self._evaluate_rules(feature_name=name, context=context, feat_default=bool(feat_default), rules=rules)

    def get_enabled_features(self, *, context: Optional[Dict[str, Any]] = None) -> List[str]:
        """Get all enabled feature flags while also taking into account context
        (when a feature has defined rules)

        Parameters
        ----------
        context: Optional[Dict[str, Any]]
            dict of attributes that you would like to match the rules
            against, can be `{'tenant_id: 'X', 'username':' 'Y', 'region': 'Z'}` etc.

        Returns
        ----------
        List[str]
            list of all feature names that either matches context or have True as default

            **Example**

        ```python
        ["premium_features", "my_feature_two", "always_true_feature"]
        ```

        Raises
        ------
        SchemaValidationError
            When schema doesn't conform with feature flag schema
        """
        if context is None:
            context = {}

        features_enabled: List[str] = []

        try:
            features: Dict[str, Any] = self.get_configuration()
        except ConfigurationStoreError as err:
            logger.debug(f"Failed to fetch feature flags from store, returning empty list, reason={err}")
            return features_enabled

        logger.debug("Evaluating all features")
        for name, feature in features.items():
            rules = feature.get(schema.RULES_KEY, {})
            feature_default_value = feature.get(schema.FEATURE_DEFAULT_VAL_KEY)
            if feature_default_value and not rules:
                logger.debug(f"feature is enabled by default and has no defined rules, name={name}")
                features_enabled.append(name)
            elif self._evaluate_rules(
                feature_name=name, context=context, feat_default=feature_default_value, rules=rules
            ):
                logger.debug(f"feature's calculated value is True, name={name}")
                features_enabled.append(name)

        return features_enabled

Methods

def evaluate(self, *, name: str, context: Optional[Dict[str, Any]] = None, default: bool) ‑> bool

Evaluate whether a feature flag should be enabled according to stored schema and input context

Logic when evaluating a feature flag

  1. Feature exists and a rule matches, returns when_match value
  2. Feature exists but has either no rules or no match, return feature default value
  3. Feature doesn't exist in stored schema, encountered an error when fetching -> return default value provided

Parameters

name : str
feature name to evaluate
context : Optional[Dict[str, Any]]

Attributes that should be evaluated against the stored schema.

for example: {"tenant_id": "X", "username": "Y", "region": "Z"}

default : bool
default value if feature flag doesn't exist in the schema, or there has been an error when fetching the configuration from the store

Returns

bool
whether feature should be enabled or not

Raises

SchemaValidationError
When schema doesn't conform with feature flag schema
Expand source code
def evaluate(self, *, name: str, context: Optional[Dict[str, Any]] = None, default: bool) -> bool:
    """Evaluate whether a feature flag should be enabled according to stored schema and input context

    **Logic when evaluating a feature flag**

    1. Feature exists and a rule matches, returns when_match value
    2. Feature exists but has either no rules or no match, return feature default value
    3. Feature doesn't exist in stored schema, encountered an error when fetching -> return default value provided

    Parameters
    ----------
    name: str
        feature name to evaluate
    context: Optional[Dict[str, Any]]
        Attributes that should be evaluated against the stored schema.

        for example: `{"tenant_id": "X", "username": "Y", "region": "Z"}`
    default: bool
        default value if feature flag doesn't exist in the schema,
        or there has been an error when fetching the configuration from the store

    Returns
    ------
    bool
        whether feature should be enabled or not

    Raises
    ------
    SchemaValidationError
        When schema doesn't conform with feature flag schema
    """
    if context is None:
        context = {}

    try:
        features = self.get_configuration()
    except ConfigurationStoreError as err:
        logger.debug(f"Failed to fetch feature flags from store, returning default provided, reason={err}")
        return default

    feature = features.get(name)
    if feature is None:
        logger.debug(f"Feature not found; returning default provided, name={name}, default={default}")
        return default

    rules = feature.get(schema.RULES_KEY)
    feat_default = feature.get(schema.FEATURE_DEFAULT_VAL_KEY)
    if not rules:
        logger.debug(f"no rules found, returning feature default, name={name}, default={feat_default}")
        return bool(feat_default)

    logger.debug(f"looking for rule match, name={name}, default={feat_default}")
    return self._evaluate_rules(feature_name=name, context=context, feat_default=bool(feat_default), rules=rules)
def get_configuration(self) ‑> Union[Dict[str, Dict[~KT, ~VT]], Dict[~KT, ~VT]]

Get validated feature flag schema from configured store.

Largely used to aid testing, since it's called by evaluate and get_enabled_features methods.

Raises

ConfigurationStoreError
Any propagated error from store
SchemaValidationError
When schema doesn't conform with feature flag schema

Returns

Dict[str, Dict]

parsed JSON dictionary

Example

{
    "premium_features": {
        "default": False,
        "rules": {
            "customer tier equals premium": {
                "when_match": True,
                "conditions": [
                    {
                        "action": "EQUALS",
                        "key": "tier",
                        "value": "premium",
                    }
                ],
            }
        },
    },
    "feature_two": {
        "default": False
    }
}
Expand source code
def get_configuration(self) -> Union[Dict[str, Dict], Dict]:
    """Get validated feature flag schema from configured store.

    Largely used to aid testing, since it's called by `evaluate` and `get_enabled_features` methods.

    Raises
    ------
    ConfigurationStoreError
        Any propagated error from store
    SchemaValidationError
        When schema doesn't conform with feature flag schema

    Returns
    ------
    Dict[str, Dict]
        parsed JSON dictionary

        **Example**

    ```python
    {
        "premium_features": {
            "default": False,
            "rules": {
                "customer tier equals premium": {
                    "when_match": True,
                    "conditions": [
                        {
                            "action": "EQUALS",
                            "key": "tier",
                            "value": "premium",
                        }
                    ],
                }
            },
        },
        "feature_two": {
            "default": False
        }
    }
    ```
    """
    # parse result conf as JSON, keep in cache for max age defined in store
    logger.debug(f"Fetching schema from registered store, store={self._store}")
    config = self._store.get_configuration()
    validator = schema.SchemaValidator(schema=config)
    validator.validate()

    return config
def get_enabled_features(self, *, context: Optional[Dict[str, Any]] = None) ‑> List[str]

Get all enabled feature flags while also taking into account context (when a feature has defined rules)

Parameters

context : Optional[Dict[str, Any]]
dict of attributes that you would like to match the rules against, can be {'tenant_id: 'X', 'username':' 'Y', 'region': 'Z'} etc.

Returns

List[str]

list of all feature names that either matches context or have True as default

Example

["premium_features", "my_feature_two", "always_true_feature"]

Raises

SchemaValidationError
When schema doesn't conform with feature flag schema
Expand source code
def get_enabled_features(self, *, context: Optional[Dict[str, Any]] = None) -> List[str]:
    """Get all enabled feature flags while also taking into account context
    (when a feature has defined rules)

    Parameters
    ----------
    context: Optional[Dict[str, Any]]
        dict of attributes that you would like to match the rules
        against, can be `{'tenant_id: 'X', 'username':' 'Y', 'region': 'Z'}` etc.

    Returns
    ----------
    List[str]
        list of all feature names that either matches context or have True as default

        **Example**

    ```python
    ["premium_features", "my_feature_two", "always_true_feature"]
    ```

    Raises
    ------
    SchemaValidationError
        When schema doesn't conform with feature flag schema
    """
    if context is None:
        context = {}

    features_enabled: List[str] = []

    try:
        features: Dict[str, Any] = self.get_configuration()
    except ConfigurationStoreError as err:
        logger.debug(f"Failed to fetch feature flags from store, returning empty list, reason={err}")
        return features_enabled

    logger.debug("Evaluating all features")
    for name, feature in features.items():
        rules = feature.get(schema.RULES_KEY, {})
        feature_default_value = feature.get(schema.FEATURE_DEFAULT_VAL_KEY)
        if feature_default_value and not rules:
            logger.debug(f"feature is enabled by default and has no defined rules, name={name}")
            features_enabled.append(name)
        elif self._evaluate_rules(
            feature_name=name, context=context, feat_default=feature_default_value, rules=rules
        ):
            logger.debug(f"feature's calculated value is True, name={name}")
            features_enabled.append(name)

    return features_enabled
class RuleAction (value, names=None, *, module=None, qualname=None, type=None, start=1)

An enumeration.

Expand source code
class RuleAction(str, Enum):
    EQUALS = "EQUALS"
    STARTSWITH = "STARTSWITH"
    ENDSWITH = "ENDSWITH"
    IN = "IN"
    NOT_IN = "NOT_IN"

Ancestors

  • builtins.str
  • enum.Enum

Class variables

var ENDSWITH
var EQUALS
var IN
var NOT_IN
var STARTSWITH
class SchemaValidator (schema: Dict[str, Any])

Validates feature flag schema configuration

Raises

SchemaValidationError
When schema doesn't conform with feature flag schema

Schema

Feature object

A dictionary containing default value and rules for matching. The value MUST be an object and MIGHT contain the following members:

  • default: bool. Defines default feature value. This MUST be present
  • rules: Dict[str, Dict]. Rules object. This MIGHT be present
{
    "my_feature": {
        "default": True,
        "rules": {}
    }
}

Rules object

A dictionary with each rule and their conditions that a feature might have. The value MIGHT be present, and when defined it MUST contain the following members:

  • when_match: bool. Defines value to return when context matches conditions
  • conditions: List[Dict]. Conditions object. This MUST be present
{
    "my_feature": {
        "default": True,
        "rules": {
            "tenant id equals 345345435": {
                "when_match": False,
                "conditions": []
            }
        }
    }
}

Conditions object

A list of dictionaries containing conditions for a given rule. The value MUST contain the following members:

  • action: str. Operation to perform to match a key and value. The value MUST be either EQUALS, STARTSWITH, ENDSWITH, IN, NOT_IN
  • key: str. Key in given context to perform operation
  • value: Any. Value in given context that should match action operation.
{
    "my_feature": {
        "default": True,
        "rules": {
            "tenant id equals 345345435": {
                "when_match": False,
                "conditions": [
                    {
                        "action": "EQUALS",
                        "key": "tenant_id",
                        "value": "345345435",
                    }
                ]
            }
        }
    }
}
Expand source code
class SchemaValidator(BaseValidator):
    """Validates feature flag schema configuration

    Raises
    ------
    SchemaValidationError
        When schema doesn't conform with feature flag schema

    Schema
    ------

    **Feature object**

    A dictionary containing default value and rules for matching.
    The value MUST be an object and MIGHT contain the following members:

    * **default**: `bool`. Defines default feature value. This MUST be present
    * **rules**: `Dict[str, Dict]`. Rules object. This MIGHT be present

    ```python
    {
        "my_feature": {
            "default": True,
            "rules": {}
        }
    }
    ```

    **Rules object**

    A dictionary with each rule and their conditions that a feature might have.
    The value MIGHT be present, and when defined it MUST contain the following members:

    * **when_match**: `bool`. Defines value to return when context matches conditions
    * **conditions**: `List[Dict]`. Conditions object. This MUST be present

    ```python
    {
        "my_feature": {
            "default": True,
            "rules": {
                "tenant id equals 345345435": {
                    "when_match": False,
                    "conditions": []
                }
            }
        }
    }
    ```

    **Conditions object**

    A list of dictionaries containing conditions for a given rule.
    The value MUST contain the following members:

    * **action**: `str`. Operation to perform to match a key and value.
    The value MUST be either EQUALS, STARTSWITH, ENDSWITH, IN, NOT_IN
    * **key**: `str`. Key in given context to perform operation
    * **value**: `Any`. Value in given context that should match action operation.

    ```python
    {
        "my_feature": {
            "default": True,
            "rules": {
                "tenant id equals 345345435": {
                    "when_match": False,
                    "conditions": [
                        {
                            "action": "EQUALS",
                            "key": "tenant_id",
                            "value": "345345435",
                        }
                    ]
                }
            }
        }
    }
    ```
    """

    def __init__(self, schema: Dict[str, Any]):
        self.schema = schema

    def validate(self) -> None:
        logger.debug("Validating schema")
        if not isinstance(self.schema, dict):
            raise SchemaValidationError(f"Features must be a dictionary, schema={str(self.schema)}")

        features = FeaturesValidator(schema=self.schema)
        features.validate()

Ancestors

Methods

def validate(self) ‑> None
Expand source code
def validate(self) -> None:
    logger.debug("Validating schema")
    if not isinstance(self.schema, dict):
        raise SchemaValidationError(f"Features must be a dictionary, schema={str(self.schema)}")

    features = FeaturesValidator(schema=self.schema)
    features.validate()
class StoreProvider

Helper class that provides a standard way to create an ABC using inheritance.

Expand source code
class StoreProvider(ABC):
    @abstractmethod
    def get_configuration(self) -> Dict[str, Any]:
        """Get configuration from any store and return the parsed JSON dictionary

        Raises
        ------
        ConfigurationStoreError
            Any error that can occur during schema fetch or JSON parse

        Returns
        -------
        Dict[str, Any]
            parsed JSON dictionary

            **Example**

        ```python
        {
            "premium_features": {
                "default": False,
                "rules": {
                    "customer tier equals premium": {
                        "when_match": True,
                        "conditions": [
                            {
                                "action": "EQUALS",
                                "key": "tier",
                                "value": "premium",
                            }
                        ],
                    }
                },
            },
            "feature_two": {
                "default": False
            }
        }
        ```
        """
        return NotImplemented  # pragma: no cover

Ancestors

  • abc.ABC

Subclasses

Methods

def get_configuration(self) ‑> Dict[str, Any]

Get configuration from any store and return the parsed JSON dictionary

Raises

ConfigurationStoreError
Any error that can occur during schema fetch or JSON parse

Returns

Dict[str, Any]

parsed JSON dictionary

Example

{
    "premium_features": {
        "default": False,
        "rules": {
            "customer tier equals premium": {
                "when_match": True,
                "conditions": [
                    {
                        "action": "EQUALS",
                        "key": "tier",
                        "value": "premium",
                    }
                ],
            }
        },
    },
    "feature_two": {
        "default": False
    }
}
Expand source code
@abstractmethod
def get_configuration(self) -> Dict[str, Any]:
    """Get configuration from any store and return the parsed JSON dictionary

    Raises
    ------
    ConfigurationStoreError
        Any error that can occur during schema fetch or JSON parse

    Returns
    -------
    Dict[str, Any]
        parsed JSON dictionary

        **Example**

    ```python
    {
        "premium_features": {
            "default": False,
            "rules": {
                "customer tier equals premium": {
                    "when_match": True,
                    "conditions": [
                        {
                            "action": "EQUALS",
                            "key": "tier",
                            "value": "premium",
                        }
                    ],
                }
            },
        },
        "feature_two": {
            "default": False
        }
    }
    ```
    """
    return NotImplemented  # pragma: no cover