Module aws_lambda_powertools.utilities.feature_flags

Advanced feature flags utility

"""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

aws_lambda_powertools.utilities.feature_flags.time_conditions

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] = None, logger: Union[logging.Logger, Logger, ForwardRef(None)] = 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

logger : A logging object

Used to log messages. If None is supplied, one will be created.

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,
        logger: Optional[Union[logging.Logger, Logger]] = 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
        logger: A logging object
            Used to log messages. If None is supplied, one will be created.
        """
        super().__init__()
        self.logger = logger or logging.getLogger(__name__)
        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)

    @property
    def get_raw_configuration(self) -> Dict[str, Any]:
        """Fetch feature schema configuration from AWS AppConfig"""
        try:
            # parse result conf as JSON, keep in cache for self.max_age seconds
            self.logger.debug(
                "Fetching configuration from the store", extra={"param_name": self.name, "max_age": self.cache_seconds}
            )
            return cast(
                dict,
                self._conf_store.get(
                    name=self.name,
                    transform="json",
                    max_age=self.cache_seconds,
                ),
            )
        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

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

        If envelope is set, it'll extract and return feature flags from configuration,
        otherwise it'll return the entire configuration fetched from AWS AppConfig.

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

        Returns
        -------
        Dict[str, Any]
            parsed JSON dictionary
        """
        config = self.get_raw_configuration

        if self.envelope:
            self.logger.debug("Envelope enabled; extracting data from config", extra={"envelope": self.envelope})
            config = jmespath_utils.extract_data_from_envelope(
                data=config, envelope=self.envelope, jmespath_options=self.jmespath_options
            )

        return config

Ancestors

• StoreProvider
• abc.ABC

Instance variables

var get_raw_configuration : Dict[str, Any]

Fetch feature schema configuration from AWS AppConfig

Expand source code

@property
def get_raw_configuration(self) -> Dict[str, Any]:
    """Fetch feature schema configuration from AWS AppConfig"""
    try:
        # parse result conf as JSON, keep in cache for self.max_age seconds
        self.logger.debug(
            "Fetching configuration from the store", extra={"param_name": self.name, "max_age": self.cache_seconds}
        )
        return cast(
            dict,
            self._conf_store.get(
                name=self.name,
                transform="json",
                max_age=self.cache_seconds,
            ),
        )
    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

Methods

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

Fetch feature schema configuration from AWS AppConfig

If envelope is set, it'll extract and return feature flags from configuration, otherwise it'll return the entire configuration fetched 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

    If envelope is set, it'll extract and return feature flags from configuration,
    otherwise it'll return the entire configuration fetched from AWS AppConfig.

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

    Returns
    -------
    Dict[str, Any]
        parsed JSON dictionary
    """
    config = self.get_raw_configuration

    if self.envelope:
        self.logger.debug("Envelope enabled; extracting data from config", extra={"envelope": self.envelope})
        config = jmespath_utils.extract_data_from_envelope(
            data=config, envelope=self.envelope, jmespath_options=self.jmespath_options
        )

    return config

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, logger: Union[logging.Logger, Logger, ForwardRef(None)] = None)

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.

logger : A logging object

Used to log messages. If None is supplied, one will be created.

Expand source code

class FeatureFlags:
    def __init__(self, store: StoreProvider, logger: Optional[Union[logging.Logger, Logger]] = None):
        """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.
        logger: A logging object
            Used to log messages. If None is supplied, one will be created.
        """
        self.store = store
        self.logger = logger or logging.getLogger(__name__)

    def _match_by_action(self, action: str, condition_value: Any, context_value: Any) -> bool:
        mapping_by_action = {
            schema.RuleAction.EQUALS.value: lambda a, b: a == b,
            schema.RuleAction.NOT_EQUALS.value: lambda a, b: a != b,
            schema.RuleAction.KEY_GREATER_THAN_VALUE.value: lambda a, b: a > b,
            schema.RuleAction.KEY_GREATER_THAN_OR_EQUAL_VALUE.value: lambda a, b: a >= b,
            schema.RuleAction.KEY_LESS_THAN_VALUE.value: lambda a, b: a < b,
            schema.RuleAction.KEY_LESS_THAN_OR_EQUAL_VALUE.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,
            schema.RuleAction.KEY_IN_VALUE.value: lambda a, b: a in b,
            schema.RuleAction.KEY_NOT_IN_VALUE.value: lambda a, b: a not in b,
            schema.RuleAction.VALUE_IN_KEY.value: lambda a, b: b in a,
            schema.RuleAction.VALUE_NOT_IN_KEY.value: lambda a, b: b not in a,
            schema.RuleAction.SCHEDULE_BETWEEN_TIME_RANGE.value: lambda a, b: compare_time_range(a, b),
            schema.RuleAction.SCHEDULE_BETWEEN_DATETIME_RANGE.value: lambda a, b: compare_datetime_range(a, b),
            schema.RuleAction.SCHEDULE_BETWEEN_DAYS_OF_WEEK.value: lambda a, b: compare_days_of_week(a, b),
        }

        try:
            func = mapping_by_action.get(action, lambda a, b: False)
            return func(context_value, condition_value)
        except Exception as exc:
            self.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:
            self.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(condition.get(schema.CONDITION_KEY, ""))
            cond_action = condition.get(schema.CONDITION_ACTION, "")
            cond_value = condition.get(schema.CONDITION_VALUE)

            # time based rule actions have no user context. the context is the condition key
            if cond_action in (
                schema.RuleAction.SCHEDULE_BETWEEN_TIME_RANGE.value,
                schema.RuleAction.SCHEDULE_BETWEEN_DATETIME_RANGE.value,
                schema.RuleAction.SCHEDULE_BETWEEN_DAYS_OF_WEEK.value,
            ):
                context_value = condition.get(schema.CONDITION_KEY)  # e.g., CURRENT_TIME

            if not self._match_by_action(action=cond_action, condition_value=cond_value, context_value=context_value):
                self.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

        self.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: Any,
        rules: Dict[str, Any],
        boolean_feature: bool,
    ) -> 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
            self.logger.debug(
                f"Evaluating rule matching, rule={rule_name}, feature={feature_name}, default={str(feat_default)}, boolean_feature={boolean_feature}"  # noqa: E501
            )
            if self._evaluate_conditions(rule_name=rule_name, feature_name=feature_name, rule=rule, context=context):
                # Maintenance: Revisit before going GA.
                return bool(rule_match_value) if boolean_feature else rule_match_value

        # no rule matched, return default value of feature
        self.logger.debug(
            f"no rule matched, returning feature default, default={str(feat_default)}, name={feature_name}, boolean_feature={boolean_feature}"  # noqa: E501
        )
        return feat_default

    def get_configuration(self) -> 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
        self.logger.debug(f"Fetching schema from registered store, store={self.store}")
        config: Dict = self.store.get_configuration()
        validator = schema.SchemaValidator(schema=config, logger=self.logger)
        validator.validate()

        return config

    def evaluate(self, *, name: str, context: Optional[Dict[str, Any]] = None, default: JSONType) -> JSONType:
        """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: JSONType
            default value if feature flag doesn't exist in the schema,
            or there has been an error when fetching the configuration from the store
            Can be boolean or any JSON values for non-boolean features.

        Returns
        ------
        JSONType
            whether feature should be enabled (bool flags) or JSON value when non-bool feature matches

        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:
            self.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:
            self.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)
        # Maintenance: Revisit before going GA. We might to simplify customers on-boarding by not requiring it
        # for non-boolean flags. It'll need minor implementation changes, docs changes, and maybe refactor
        # get_enabled_features. We can minimize breaking change, despite Beta label, by having a new
        # method `get_matching_features` returning Dict[feature_name, feature_value]
        boolean_feature = feature.get(
            schema.FEATURE_DEFAULT_VAL_TYPE_KEY, True
        )  # backwards compatibility, assume feature flag
        if not rules:
            self.logger.debug(
                f"no rules found, returning feature default, name={name}, default={str(feat_default)}, boolean_feature={boolean_feature}"  # noqa: E501
            )
            # Maintenance: Revisit before going GA. We might to simplify customers on-boarding by not requiring it
            # for non-boolean flags.
            return bool(feat_default) if boolean_feature else feat_default

        self.logger.debug(
            f"looking for rule match, name={name}, default={str(feat_default)}, boolean_feature={boolean_feature}"  # noqa: E501
        )
        return self._evaluate_rules(
            feature_name=name, context=context, feat_default=feat_default, rules=rules, boolean_feature=boolean_feature
        )

    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:
            self.logger.debug(f"Failed to fetch feature flags from store, returning empty list, reason={err}")
            return features_enabled

        self.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)
            boolean_feature = feature.get(
                schema.FEATURE_DEFAULT_VAL_TYPE_KEY, True
            )  # backwards compatibility, assume feature flag

            if feature_default_value and not rules:
                self.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,
                boolean_feature=boolean_feature,
            ):
                self.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: Union[str, int, float, bool, ForwardRef(None), Dict[str, Any], List[Any]]) ‑> Union[str, int, float, bool, ForwardRef(None), Dict[str, Any], List[Any]]

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 : JSONType

default value if feature flag doesn't exist in the schema, or there has been an error when fetching the configuration from the store Can be boolean or any JSON values for non-boolean features.

Returns

JSONType

whether feature should be enabled (bool flags) or JSON value when non-bool feature matches

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: JSONType) -> JSONType:
    """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: JSONType
        default value if feature flag doesn't exist in the schema,
        or there has been an error when fetching the configuration from the store
        Can be boolean or any JSON values for non-boolean features.

    Returns
    ------
    JSONType
        whether feature should be enabled (bool flags) or JSON value when non-bool feature matches

    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:
        self.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:
        self.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)
    # Maintenance: Revisit before going GA. We might to simplify customers on-boarding by not requiring it
    # for non-boolean flags. It'll need minor implementation changes, docs changes, and maybe refactor
    # get_enabled_features. We can minimize breaking change, despite Beta label, by having a new
    # method `get_matching_features` returning Dict[feature_name, feature_value]
    boolean_feature = feature.get(
        schema.FEATURE_DEFAULT_VAL_TYPE_KEY, True
    )  # backwards compatibility, assume feature flag
    if not rules:
        self.logger.debug(
            f"no rules found, returning feature default, name={name}, default={str(feat_default)}, boolean_feature={boolean_feature}"  # noqa: E501
        )
        # Maintenance: Revisit before going GA. We might to simplify customers on-boarding by not requiring it
        # for non-boolean flags.
        return bool(feat_default) if boolean_feature else feat_default

    self.logger.debug(
        f"looking for rule match, name={name}, default={str(feat_default)}, boolean_feature={boolean_feature}"  # noqa: E501
    )
    return self._evaluate_rules(
        feature_name=name, context=context, feat_default=feat_default, rules=rules, boolean_feature=boolean_feature
    )

def get_configuration(self) ‑> 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

{
    "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) -> 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
    self.logger.debug(f"Fetching schema from registered store, store={self.store}")
    config: Dict = self.store.get_configuration()
    validator = schema.SchemaValidator(schema=config, logger=self.logger)
    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:
        self.logger.debug(f"Failed to fetch feature flags from store, returning empty list, reason={err}")
        return features_enabled

    self.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)
        boolean_feature = feature.get(
            schema.FEATURE_DEFAULT_VAL_TYPE_KEY, True
        )  # backwards compatibility, assume feature flag

        if feature_default_value and not rules:
            self.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,
            boolean_feature=boolean_feature,
        ):
            self.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"
    NOT_EQUALS = "NOT_EQUALS"
    KEY_GREATER_THAN_VALUE = "KEY_GREATER_THAN_VALUE"
    KEY_GREATER_THAN_OR_EQUAL_VALUE = "KEY_GREATER_THAN_OR_EQUAL_VALUE"
    KEY_LESS_THAN_VALUE = "KEY_LESS_THAN_VALUE"
    KEY_LESS_THAN_OR_EQUAL_VALUE = "KEY_LESS_THAN_OR_EQUAL_VALUE"
    STARTSWITH = "STARTSWITH"
    ENDSWITH = "ENDSWITH"
    IN = "IN"
    NOT_IN = "NOT_IN"
    KEY_IN_VALUE = "KEY_IN_VALUE"
    KEY_NOT_IN_VALUE = "KEY_NOT_IN_VALUE"
    VALUE_IN_KEY = "VALUE_IN_KEY"
    VALUE_NOT_IN_KEY = "VALUE_NOT_IN_KEY"
    SCHEDULE_BETWEEN_TIME_RANGE = "SCHEDULE_BETWEEN_TIME_RANGE"  # hour:min 24 hours clock
    SCHEDULE_BETWEEN_DATETIME_RANGE = "SCHEDULE_BETWEEN_DATETIME_RANGE"  # full datetime format, excluding timezone
    SCHEDULE_BETWEEN_DAYS_OF_WEEK = "SCHEDULE_BETWEEN_DAYS_OF_WEEK"  # MONDAY, TUESDAY, .... see TimeValues enum

Ancestors

• builtins.str
• enum.Enum

Class variables

var ENDSWITH

var EQUALS

var IN

var KEY_GREATER_THAN_OR_EQUAL_VALUE

var KEY_GREATER_THAN_VALUE

var KEY_IN_VALUE

var KEY_LESS_THAN_OR_EQUAL_VALUE

var KEY_LESS_THAN_VALUE

var KEY_NOT_IN_VALUE

var NOT_EQUALS

var NOT_IN

var SCHEDULE_BETWEEN_DATETIME_RANGE

var SCHEDULE_BETWEEN_DAYS_OF_WEEK

var SCHEDULE_BETWEEN_TIME_RANGE

var STARTSWITH

var VALUE_IN_KEY

var VALUE_NOT_IN_KEY

class SchemaValidator (schema: Dict[str, Any], logger: Union[logging.Logger, Logger, ForwardRef(None)] = None)

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: Union[bool, JSONType]. Defines default feature value. This MUST be present
• boolean_type: bool. Defines whether feature has non-boolean value (JSONType). This MIGHT be present
• rules: Dict[str, Dict]. Rules object. This MIGHT be present

JSONType being any JSON primitive value: Union[str, int, float, bool, None, Dict[str, Any], List[Any]]

{
    "my_feature": {
        "default": true,
        "rules": {}
    },
    "my_non_boolean_feature": {
        "default": {"group": "read-only"},
        "boolean_type": false,
        "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: Union[bool, JSONType]. 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": []
            }
        }
    },
    "my_non_boolean_feature": {
        "default": {"group": "read-only"},
        "boolean_type": false,
        "rules": {
            "tenant id equals 345345435": {
                "when_match": {"group": "admin"},
                "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, KEY_IN_VALUE KEY_NOT_IN_VALUE VALUE_IN_KEY VALUE_NOT_IN_KEY

• 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**: `Union[bool, JSONType]`. Defines default feature value. This MUST be present
    * **boolean_type**: bool. Defines whether feature has non-boolean value (`JSONType`). This MIGHT be present
    * **rules**: `Dict[str, Dict]`. Rules object. This MIGHT be present

    `JSONType` being any JSON primitive value: `Union[str, int, float, bool, None, Dict[str, Any], List[Any]]`

    ```json
    {
        "my_feature": {
            "default": true,
            "rules": {}
        },
        "my_non_boolean_feature": {
            "default": {"group": "read-only"},
            "boolean_type": false,
            "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**: `Union[bool, JSONType]`. Defines value to return when context matches conditions
    * **conditions**: `List[Dict]`. Conditions object. This MUST be present

    ```json
    {
        "my_feature": {
            "default": true,
            "rules": {
                "tenant id equals 345345435": {
                    "when_match": false,
                    "conditions": []
                }
            }
        },
        "my_non_boolean_feature": {
            "default": {"group": "read-only"},
            "boolean_type": false,
            "rules": {
                "tenant id equals 345345435": {
                    "when_match": {"group": "admin"},
                    "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,
    KEY_IN_VALUE KEY_NOT_IN_VALUE VALUE_IN_KEY VALUE_NOT_IN_KEY

    * **key**: `str`. Key in given context to perform operation
    * **value**: `Any`. Value in given context that should match action operation.

    ```json
    {
        "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], logger: Optional[Union[logging.Logger, Logger]] = None):
        self.schema = schema
        self.logger = logger or logging.getLogger(__name__)

    def validate(self) -> None:
        self.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, logger=self.logger)
        features.validate()

Ancestors

• BaseValidator
• abc.ABC

Methods

def validate(self) ‑> None

Expand source code

def validate(self) -> None:
    self.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, logger=self.logger)
    features.validate()

class StoreProvider

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

Expand source code

class StoreProvider(ABC):
    @property
    @abstractmethod
    def get_raw_configuration(self) -> Dict[str, Any]:
        """Get configuration from any store and return the parsed JSON dictionary"""
        raise NotImplementedError()  # pragma: no cover

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

        If envelope is set, it'll extract and return feature flags from configuration,
        otherwise it'll return the entire configuration fetched from the store.

        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
            }
        }
        ```
        """
        raise NotImplementedError()  # pragma: no cover

Ancestors

• abc.ABC

Subclasses

• AppConfigStore

Instance variables

var get_raw_configuration : Dict[str, Any]

Get configuration from any store and return the parsed JSON dictionary

Expand source code

@property
@abstractmethod
def get_raw_configuration(self) -> Dict[str, Any]:
    """Get configuration from any store and return the parsed JSON dictionary"""
    raise NotImplementedError()  # pragma: no cover

Methods

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

Get configuration from any store and return the parsed JSON dictionary

If envelope is set, it'll extract and return feature flags from configuration, otherwise it'll return the entire configuration fetched from the store.

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

    If envelope is set, it'll extract and return feature flags from configuration,
    otherwise it'll return the entire configuration fetched from the store.

    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
        }
    }
    ```
    """
    raise NotImplementedError()  # pragma: no cover