""" Base for Parameter providers """ from __future__ import annotations import os from abc import ABC, abstractmethod from datetime import datetime, timedelta from typing import TYPE_CHECKING, Any, Callable, NamedTuple, cast, overload from aws_lambda_powertools.shared import constants, user_agent from aws_lambda_powertools.shared.functions import resolve_max_age from aws_lambda_powertools.utilities.parameters.exceptions import GetParameterError, TransformParameterError if TYPE_CHECKING: from aws_lambda_powertools.utilities.parameters.types import TransformOptions from aws_lambda_powertools.utilities.parameters.constants import ( DEFAULT_MAX_AGE_SECS, DEFAULT_PROVIDERS, TRANSFORM_METHOD_MAPPING, ) class ExpirableValue(NamedTuple): value: str | bytes | dict[str, Any] ttl: datetime class BaseProvider(ABC): """ Abstract Base Class for Parameter providers """ store: dict[tuple, ExpirableValue] def __init__(self, *, client=None, resource=None): """ Initialize the base provider """ if client is not None: user_agent.register_feature_to_client(client=client, feature="parameters") if resource is not None: user_agent.register_feature_to_resource(resource=resource, feature="parameters") self.store: dict[tuple, ExpirableValue] = {} def has_not_expired_in_cache(self, key: tuple) -> bool: return key in self.store and self.store[key].ttl >= datetime.now() def get( self, name: str, max_age: int | None = None, transform: TransformOptions = None, force_fetch: bool = False, **sdk_options, ) -> str | bytes | dict | None: """ Retrieve a parameter value or return the cached value Parameters ---------- name: str Parameter name max_age: int Maximum age of the cached value transform: str Optional transformation of the parameter value. Supported values are "json" for JSON strings and "binary" for base 64 encoded values. force_fetch: bool, optional Force update even before a cached item has expired, defaults to False sdk_options: dict, optional Arguments that will be passed directly to the underlying API call Raises ------ GetParameterError When the parameter provider fails to retrieve a parameter value for a given name. TransformParameterError When the parameter provider fails to transform a parameter value. """ # If there are multiple calls to the same parameter but in a different # transform, they will be stored multiple times. This allows us to # optimize by transforming the data only once per retrieval, thus there # is no need to transform cached values multiple times. However, this # means that we need to make multiple calls to the underlying parameter # store if we need to return it in different transforms. Since the number # of supported transform is small and the probability that a given # parameter will always be used in a specific transform, this should be # an acceptable tradeoff. value: str | bytes | dict | None = None key = self._build_cache_key(name=name, transform=transform) # If max_age is not set, resolve it from the environment variable, defaulting to DEFAULT_MAX_AGE_SECS max_age = resolve_max_age(env=os.getenv(constants.PARAMETERS_MAX_AGE_ENV, DEFAULT_MAX_AGE_SECS), choice=max_age) if not force_fetch and self.has_not_expired_in_cache(key): return self.fetch_from_cache(key) try: value = self._get(name, **sdk_options) # Encapsulate all errors into a generic GetParameterError except Exception as exc: raise GetParameterError(str(exc)) if transform: value = transform_value(key=name, value=value, transform=transform, raise_on_transform_error=True) # NOTE: don't cache None, as they might've been failed transforms and may be corrected if value is not None: self.add_to_cache(key=key, value=value, max_age=max_age) return value @abstractmethod def _get(self, name: str, **sdk_options) -> str | bytes | dict[str, Any]: """ Retrieve parameter value from the underlying parameter store """ raise NotImplementedError() def set(self, name: str, value: Any, *, overwrite: bool = False, **kwargs): """ Set parameter value from the underlying parameter store """ raise NotImplementedError() def get_multiple( self, path: str, max_age: int | None = None, transform: TransformOptions = None, raise_on_transform_error: bool = False, force_fetch: bool = False, **sdk_options, ) -> dict[str, str] | dict[str, bytes] | dict[str, dict]: """ Retrieve multiple parameters based on a path prefix Parameters ---------- path: str Parameter path used to retrieve multiple parameters max_age: int, optional Maximum age of the cached value transform: str, optional Optional transformation of the parameter value. Supported values are "json" for JSON strings, "binary" for base 64 encoded values or "auto" which looks at the attribute key to determine the type. raise_on_transform_error: bool, optional Raises an exception if any transform fails, otherwise this will return a None value for each transform that failed force_fetch: bool, optional Force update even before a cached item has expired, defaults to False sdk_options: dict, optional Arguments that will be passed directly to the underlying API call Raises ------ GetParameterError When the parameter provider fails to retrieve parameter values for a given path. TransformParameterError When the parameter provider fails to transform a parameter value. """ key = self._build_cache_key(name=path, transform=transform, is_nested=True) # If max_age is not set, resolve it from the environment variable, defaulting to DEFAULT_MAX_AGE_SECS max_age = resolve_max_age(env=os.getenv(constants.PARAMETERS_MAX_AGE_ENV, DEFAULT_MAX_AGE_SECS), choice=max_age) if not force_fetch and self.has_not_expired_in_cache(key): return self.fetch_from_cache(key) try: values = self._get_multiple(path, **sdk_options) # Encapsulate all errors into a generic GetParameterError except Exception as exc: raise GetParameterError(str(exc)) if transform: values.update(transform_value(values, transform, raise_on_transform_error)) self.add_to_cache(key=key, value=values, max_age=max_age) return values @abstractmethod def _get_multiple(self, path: str, **sdk_options) -> dict[str, str]: """ Retrieve multiple parameter values from the underlying parameter store """ raise NotImplementedError() def clear_cache(self): self.store.clear() def fetch_from_cache(self, key: tuple): return self.store[key].value if key in self.store else {} def add_to_cache(self, key: tuple, value: Any, max_age: int): if max_age <= 0: return self.store[key] = ExpirableValue(value, datetime.now() + timedelta(seconds=max_age)) def _build_cache_key( self, name: str, transform: TransformOptions = None, is_nested: bool = False, ): """Creates cache key for parameters Parameters ---------- name : str Name of parameter, secret or config transform : TransformOptions, optional Transform method used, by default None is_nested : bool, optional Whether it's a single parameter or multiple nested parameters, by default False Returns ------- tuple[str, TransformOptions, bool] Cache key """ return (name, transform, is_nested) def get_transform_method(value: str, transform: TransformOptions = None) -> Callable[..., Any]: """ Determine the transform method Examples ------- >>> get_transform_method("key","any_other_value") 'any_other_value' >>> get_transform_method("key.json","auto") 'json' >>> get_transform_method("key.binary","auto") 'binary' >>> get_transform_method("key","auto") None >>> get_transform_method("key",None) None Parameters --------- value: str Only used when the transform is "auto". transform: str, optional Original transform method, only "auto" will try to detect the transform method by the key Returns ------ Callable: Transform function could be json.loads, base64.b64decode, or a lambda that echo the str value """ transform_method = TRANSFORM_METHOD_MAPPING.get(transform) if transform == "auto": key_suffix = value.rsplit(".")[-1] transform_method = TRANSFORM_METHOD_MAPPING.get(key_suffix, TRANSFORM_METHOD_MAPPING[None]) return cast(Callable, transform_method) # https://github.com/python/mypy/issues/10740 @overload def transform_value( value: dict[str, Any], transform: TransformOptions, raise_on_transform_error: bool = False, key: str = "", ) -> dict[str, Any]: ... @overload def transform_value( value: str | bytes | dict[str, Any], transform: TransformOptions, raise_on_transform_error: bool = False, key: str = "", ) -> str | bytes | dict[str, Any] | None: ... def transform_value( value: str | bytes | dict[str, Any], transform: TransformOptions, raise_on_transform_error: bool = True, key: str = "", ) -> str | bytes | dict[str, Any] | None: """ Transform a value using one of the available options. Parameters --------- value: str Parameter value to transform transform: str Type of transform, supported values are "json", "binary", and "auto" based on suffix (.json, .binary) key: str Parameter key when transform is auto to infer its transform method raise_on_transform_error: bool, optional Raises an exception if any transform fails, otherwise this will return a None value for each transform that failed Raises ------ TransformParameterError: When the parameter value could not be transformed """ # Maintenance: For v3, we should consider returning the original value for soft transform failures. err_msg = "Unable to transform value using '{transform}' transform: {exc}" if isinstance(value, bytes): value = value.decode("utf-8") if isinstance(value, dict): # NOTE: We must handle partial failures when receiving multiple values # where one of the keys might fail during transform, e.g. `{"a": "valid", "b": "{"}` # expected: `{"a": "valid", "b": None}` transformed_values: dict[str, Any] = {} for dict_key, dict_value in value.items(): transform_method = get_transform_method(value=dict_key, transform=transform) try: transformed_values[dict_key] = transform_method(dict_value) except Exception as exc: if raise_on_transform_error: raise TransformParameterError(err_msg.format(transform=transform, exc=exc)) from exc transformed_values[dict_key] = None return transformed_values if transform == "auto": # key="a.json", value='{"a": "b"}', or key="a.binary", value="b64_encoded" transform_method = get_transform_method(value=key, transform=transform) else: # value='{"key": "value"} transform_method = get_transform_method(value=value, transform=transform) try: return transform_method(value) except Exception as exc: if raise_on_transform_error: raise TransformParameterError(err_msg.format(transform=transform, exc=exc)) from exc return None def clear_caches(): """Clear cached parameter values from all providers""" DEFAULT_PROVIDERS.clear()