Source code for

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This module contains Base AWS Hook.

.. seealso::
    For more information on how to use this hook, take a look at the guide:
from __future__ import annotations

import datetime
import inspect
import json
import logging
import os
import warnings
from copy import deepcopy
from functools import cached_property, wraps
from pathlib import Path
from typing import TYPE_CHECKING, Any, Callable, Generic, TypeVar, Union

import boto3
import botocore
import botocore.session
import jinja2
import requests
import tenacity
from botocore.config import Config
from botocore.waiter import Waiter, WaiterModel
from import tzlocal
from slugify import slugify

from airflow.configuration import conf
from airflow.exceptions import (
from airflow.hooks.base import BaseHook
from import AwsConnectionWrapper
from import generate_uuid
from import return_on_error
from airflow.providers_manager import ProvidersManager
from airflow.utils.helpers import exactly_one
from airflow.utils.log.logging_mixin import LoggingMixin
from airflow.utils.log.secrets_masker import mask_secret

[docs]BaseAwsConnection = TypeVar("BaseAwsConnection", bound=Union[boto3.client, boto3.resource])
if TYPE_CHECKING: from botocore.client import ClientMeta from botocore.credentials import ReadOnlyCredentials from airflow.models.connection import Connection # Avoid circular imports.
[docs]class BaseSessionFactory(LoggingMixin): """Base AWS Session Factory class. This handles synchronous and async boto session creation. It can handle most of the AWS supported authentication methods. User can also derive from this class to have full control of boto3 session creation or to support custom federation. .. note:: Not all features implemented for synchronous sessions are available for async sessions. .. seealso:: - :ref:`howto/connection:aws:session-factory` """ def __init__( self, conn: Connection | AwsConnectionWrapper | None, region_name: str | None = None, config: Config | None = None, ) -> None: super().__init__() self._conn = conn self._region_name = region_name self._config = config @cached_property
[docs] def conn(self) -> AwsConnectionWrapper: """Cached AWS Connection Wrapper.""" return AwsConnectionWrapper( conn=self._conn, region_name=self._region_name, botocore_config=self._config, )
[docs] def basic_session(self) -> boto3.session.Session: """Cached property with basic boto3.session.Session.""" return self._create_basic_session(session_kwargs=self.conn.session_kwargs)
[docs] def extra_config(self) -> dict[str, Any]: """AWS Connection extra_config.""" return self.conn.extra_config
[docs] def region_name(self) -> str | None: """AWS Region Name read-only property.""" return self.conn.region_name
[docs] def config(self) -> Config | None: """Configuration for botocore client read-only property.""" return self.conn.botocore_config
[docs] def role_arn(self) -> str | None: """Assume Role ARN from AWS Connection.""" return self.conn.role_arn
def _apply_session_kwargs(self, session): if self.conn.session_kwargs.get("profile_name", None) is not None: session.set_config_variable("profile", self.conn.session_kwargs["profile_name"]) if ( self.conn.session_kwargs.get("aws_access_key_id", None) or self.conn.session_kwargs.get("aws_secret_access_key", None) or self.conn.session_kwargs.get("aws_session_token", None) ): session.set_credentials( access_key=self.conn.session_kwargs.get("aws_access_key_id"), secret_key=self.conn.session_kwargs.get("aws_secret_access_key"), token=self.conn.session_kwargs.get("aws_session_token"), ) if self.conn.session_kwargs.get("region_name", None) is not None: session.set_config_variable("region", self.conn.session_kwargs["region_name"])
[docs] def get_async_session(self): from aiobotocore.session import get_session as async_get_session return async_get_session()
[docs] def create_session(self, deferrable: bool = False) -> boto3.session.Session: """Create boto3 or aiobotocore Session from connection config.""" if not self.conn: "No connection ID provided. Fallback on boto3 credential strategy (region_name=%r). " "See:", self.region_name, ) if deferrable: session = self.get_async_session() self._apply_session_kwargs(session) return session else: return boto3.session.Session(region_name=self.region_name) elif not self.role_arn: if deferrable: session = self.get_async_session() self._apply_session_kwargs(session) return session else: return self.basic_session # Values stored in ``AwsConnectionWrapper.session_kwargs`` are intended to be used only # to create the initial boto3 session. # If the user wants to use the 'assume_role' mechanism then only the 'region_name' needs to be # provided, otherwise other parameters might conflict with the base botocore session. # Unfortunately it is not a part of public boto3 API, see source of boto3.session.Session: # # If we provide 'aws_access_key_id' or 'aws_secret_access_key' or 'aws_session_token' # as part of session kwargs it will use them instead of assumed credentials. assume_session_kwargs = {} if self.conn.region_name: assume_session_kwargs["region_name"] = self.conn.region_name return self._create_session_with_assume_role( session_kwargs=assume_session_kwargs, deferrable=deferrable )
def _create_basic_session(self, session_kwargs: dict[str, Any]) -> boto3.session.Session: return boto3.session.Session(**session_kwargs) def _create_session_with_assume_role( self, session_kwargs: dict[str, Any], deferrable: bool = False ) -> boto3.session.Session: if self.conn.assume_role_method == "assume_role_with_web_identity": # Deferred credentials have no initial credentials credential_fetcher = self._get_web_identity_credential_fetcher() params = { "method": "assume-role-with-web-identity", "refresh_using": credential_fetcher.fetch_credentials, "time_fetcher": lambda:, } if deferrable: from aiobotocore.credentials import AioDeferredRefreshableCredentials credentials = AioDeferredRefreshableCredentials(**params) else: credentials = botocore.credentials.DeferredRefreshableCredentials(**params) else: # Refreshable credentials do have initial credentials params = { "metadata": self._refresh_credentials(), "refresh_using": self._refresh_credentials, "method": "sts-assume-role", } if deferrable: from aiobotocore.credentials import AioRefreshableCredentials credentials = AioRefreshableCredentials.create_from_metadata(**params) else: credentials = botocore.credentials.RefreshableCredentials.create_from_metadata(**params) if deferrable: from aiobotocore.session import get_session as async_get_session session = async_get_session() else: session = botocore.session.get_session() session._credentials = credentials session.set_config_variable("region", self.basic_session.region_name) return boto3.session.Session(botocore_session=session, **session_kwargs) def _refresh_credentials(self) -> dict[str, Any]: self.log.debug("Refreshing credentials") assume_role_method = self.conn.assume_role_method if assume_role_method not in ("assume_role", "assume_role_with_saml"): raise NotImplementedError(f"assume_role_method={assume_role_method} not expected") sts_client = self.basic_session.client( "sts", config=self.config, endpoint_url=self.conn.get_service_endpoint_url("sts", sts_connection_assume=True), ) if assume_role_method == "assume_role": sts_response = self._assume_role(sts_client=sts_client) else: sts_response = self._assume_role_with_saml(sts_client=sts_client) sts_response_http_status = sts_response["ResponseMetadata"]["HTTPStatusCode"] if sts_response_http_status != 200: raise RuntimeError(f"sts_response_http_status={sts_response_http_status}") credentials = sts_response["Credentials"] expiry_time = credentials.get("Expiration").isoformat() self.log.debug("New credentials expiry_time: %s", expiry_time) credentials = { "access_key": credentials.get("AccessKeyId"), "secret_key": credentials.get("SecretAccessKey"), "token": credentials.get("SessionToken"), "expiry_time": expiry_time, } return credentials def _assume_role(self, sts_client: boto3.client) -> dict: kw = { "RoleSessionName": self._strip_invalid_session_name_characters(f"Airflow_{self.conn.conn_id}"), **self.conn.assume_role_kwargs, "RoleArn": self.role_arn, } return sts_client.assume_role(**kw) def _assume_role_with_saml(self, sts_client: boto3.client) -> dict[str, Any]: saml_config = self.extra_config["assume_role_with_saml"] principal_arn = saml_config["principal_arn"] idp_auth_method = saml_config["idp_auth_method"] if idp_auth_method == "http_spegno_auth": saml_assertion = self._fetch_saml_assertion_using_http_spegno_auth(saml_config) else: raise NotImplementedError( f"idp_auth_method={idp_auth_method} in Connection {self.conn.conn_id} Extra." 'Currently only "http_spegno_auth" is supported, and must be specified.' ) self.log.debug("Doing sts_client.assume_role_with_saml to role_arn=%s", self.role_arn) return sts_client.assume_role_with_saml( RoleArn=self.role_arn, PrincipalArn=principal_arn, SAMLAssertion=saml_assertion, **self.conn.assume_role_kwargs, ) def _get_idp_response( self, saml_config: dict[str, Any], auth: requests.auth.AuthBase ) -> requests.models.Response: idp_url = saml_config["idp_url"] self.log.debug("idp_url= %s", idp_url) session = requests.Session() # Configurable Retry when querying the IDP endpoint if "idp_request_retry_kwargs" in saml_config: idp_request_retry_kwargs = saml_config["idp_request_retry_kwargs"]"idp_request_retry_kwargs= %s", idp_request_retry_kwargs) from requests.adapters import HTTPAdapter from requests.packages.urllib3.util.retry import Retry retry_strategy = Retry(**idp_request_retry_kwargs) adapter = HTTPAdapter(max_retries=retry_strategy) session.mount("https://", adapter) session.mount("http://", adapter) idp_request_kwargs = {} if "idp_request_kwargs" in saml_config: idp_request_kwargs = saml_config["idp_request_kwargs"] idp_response = session.get(idp_url, auth=auth, **idp_request_kwargs) idp_response.raise_for_status() return idp_response def _fetch_saml_assertion_using_http_spegno_auth(self, saml_config: dict[str, Any]) -> str: # requests_gssapi will need paramiko > 2.6 since you'll need # 'gssapi' not 'python-gssapi' from PyPi. # import requests_gssapi from lxml import etree auth = requests_gssapi.HTTPSPNEGOAuth() if "mutual_authentication" in saml_config: mutual_auth = saml_config["mutual_authentication"] if mutual_auth == "REQUIRED": auth = requests_gssapi.HTTPSPNEGOAuth(requests_gssapi.REQUIRED) elif mutual_auth == "OPTIONAL": auth = requests_gssapi.HTTPSPNEGOAuth(requests_gssapi.OPTIONAL) elif mutual_auth == "DISABLED": auth = requests_gssapi.HTTPSPNEGOAuth(requests_gssapi.DISABLED) else: raise NotImplementedError( f"mutual_authentication={mutual_auth} in Connection {self.conn.conn_id} Extra." 'Currently "REQUIRED", "OPTIONAL" and "DISABLED" are supported.' "(Exclude this setting will default to HTTPSPNEGOAuth() )." ) # Query the IDP idp_response = self._get_idp_response(saml_config, auth=auth) # Assist with debugging. Note: contains sensitive info! xpath = saml_config["saml_response_xpath"] log_idp_response = "log_idp_response" in saml_config and saml_config["log_idp_response"] if log_idp_response: self.log.warning( "The IDP response contains sensitive information, but log_idp_response is ON (%s).", log_idp_response, ) self.log.debug("idp_response.content= %s", idp_response.content) self.log.debug("xpath= %s", xpath) # Extract SAML Assertion from the returned HTML / XML xml = etree.fromstring(idp_response.content) saml_assertion = xml.xpath(xpath) if isinstance(saml_assertion, list): if len(saml_assertion) == 1: saml_assertion = saml_assertion[0] if not saml_assertion: raise ValueError("Invalid SAML Assertion") return saml_assertion def _get_web_identity_credential_fetcher( self, ) -> botocore.credentials.AssumeRoleWithWebIdentityCredentialFetcher: base_session = self.basic_session._session or botocore.session.get_session() client_creator = base_session.create_client federation = str(self.extra_config.get("assume_role_with_web_identity_federation")) web_identity_token_loader = { "file": self._get_file_token_loader, "google": self._get_google_identity_token_loader, }.get(federation) if not web_identity_token_loader: raise AirflowException(f"Unsupported federation: {federation}.") return botocore.credentials.AssumeRoleWithWebIdentityCredentialFetcher( client_creator=client_creator, web_identity_token_loader=web_identity_token_loader(), role_arn=self.role_arn, extra_args=self.conn.assume_role_kwargs, ) def _get_file_token_loader(self): from botocore.credentials import FileWebIdentityTokenLoader token_file = self.extra_config.get("assume_role_with_web_identity_token_file") or os.getenv( "AWS_WEB_IDENTITY_TOKEN_FILE" ) return FileWebIdentityTokenLoader(token_file) def _get_google_identity_token_loader(self): from google.auth.transport import requests as requests_transport from import ( get_default_id_token_credentials, ) audience = self.extra_config.get("assume_role_with_web_identity_federation_audience") google_id_token_credentials = get_default_id_token_credentials(target_audience=audience) def web_identity_token_loader(): if not google_id_token_credentials.valid: request_adapter = requests_transport.Request() google_id_token_credentials.refresh(request=request_adapter) return google_id_token_credentials.token return web_identity_token_loader def _strip_invalid_session_name_characters(self, role_session_name: str) -> str: return slugify(role_session_name, regex_pattern=r"[^\w+=,.@-]+")
[docs]class AwsGenericHook(BaseHook, Generic[BaseAwsConnection]): """Generic class for interact with AWS. This class provide a thin wrapper around the boto3 Python library. :param aws_conn_id: The Airflow connection used for AWS credentials. If this is None or empty then the default boto3 behaviour is used. If running Airflow in a distributed manner and aws_conn_id is None or empty, then default boto3 configuration would be used (and must be maintained on each worker node). :param verify: Whether or not to verify SSL certificates. See: :param region_name: AWS region_name. If not specified then the default boto3 behaviour is used. :param client_type: Reference to :external:py:meth:`boto3.client service_name \ <boto3.session.Session.client>`, e.g. 'emr', 'batch', 's3', etc. Mutually exclusive with ``resource_type``. :param resource_type: Reference to :external:py:meth:`boto3.resource service_name \ <boto3.session.Session.resource>`, e.g. 's3', 'ec2', 'dynamodb', etc. Mutually exclusive with ``client_type``. :param config: Configuration for botocore client. See: """
[docs] conn_name_attr = "aws_conn_id"
[docs] default_conn_name = "aws_default"
[docs] conn_type = "aws"
[docs] hook_name = "Amazon Web Services"
def __init__( self, aws_conn_id: str | None = default_conn_name, verify: bool | str | None = None, region_name: str | None = None, client_type: str | None = None, resource_type: str | None = None, config: Config | dict[str, Any] | None = None, ) -> None: super().__init__() self.aws_conn_id = aws_conn_id self.client_type = client_type self.resource_type = resource_type self._region_name = region_name if isinstance(config, dict): config = Config(**config) self._config = config self._verify = verify @classmethod @return_on_error("Unknown") def _get_provider_version(cls) -> str: """Check the Providers Manager for the package version.""" manager = ProvidersManager() hook = manager.hooks[cls.conn_type] if not hook: # This gets caught immediately, but without it MyPy complains # Item "None" of "Optional[HookInfo]" has no attribute "package_name" # on the following line and static checks fail. raise ValueError(f"Hook info for {cls.conn_type} not found in the Provider Manager.") return manager.providers[hook.package_name].version @staticmethod def _find_operator_class_name(target_function_name: str) -> str | None: """Given a frame off the stack, return the name of the class that made the call. This method may raise a ValueError or an IndexError. The caller is responsible with catching and handling those. """ stack = inspect.stack() # Find the index of the most recent frame which called the provided function name # and pull that frame off the stack. target_frames = [frame for frame in stack if frame.function == target_function_name] if target_frames: target_frame = target_frames[0][0] else: return None # Get the local variables for that frame. frame_variables = target_frame.f_locals["self"] # Get the class object for that frame. frame_class_object = frame_variables.__class__ # Return the name of the class object. return frame_class_object.__name__ @staticmethod def _find_executor_class_name() -> str | None: """Inspect the call stack looking for any executor classes and returning the first found.""" stack = inspect.stack() # Fetch class objects on all frames, looking for one containing an executor (since it # will inherit from BaseExecutor) for frame in stack: classes = [] for name, obj in frame[0].f_globals.items(): if inspect.isclass(obj): classes.append(name) if "BaseExecutor" in classes: return classes[-1] return None @return_on_error("Unknown") def _get_caller(self, target_function_name: str = "execute") -> str: """Try to determine the caller of this hook. Whether that be an AWS Operator, Sensor or Executor.""" caller = self._find_operator_class_name(target_function_name) if caller == "BaseSensorOperator": # If the result is a BaseSensorOperator, then look for whatever last called "poke". caller = self._find_operator_class_name("poke") if not caller: # Check if we can find an executor caller = self._find_executor_class_name() return caller if caller else "Unknown" @staticmethod @return_on_error("00000000-0000-0000-0000-000000000000") def _generate_dag_key() -> str: """Generate a DAG key. The Object Identifier (OID) namespace is used to salt the dag_id value. That salted value is used to generate a SHA-1 hash which, by definition, can not (reasonably) be reversed. No personal data can be inferred or extracted from the resulting UUID. """ return generate_uuid(os.environ.get("AIRFLOW_CTX_DAG_ID")) @staticmethod @return_on_error("Unknown") def _get_airflow_version() -> str: """Fetch and return the current Airflow version.""" # This can be a circular import under specific configurations. # Importing locally to either avoid or catch it if it does happen. from airflow import __version__ as airflow_version return airflow_version def _generate_user_agent_extra_field(self, existing_user_agent_extra: str) -> str: user_agent_extra_values = [ f"Airflow/{self._get_airflow_version()}", f"AmPP/{self._get_provider_version()}", f"Caller/{self._get_caller()}", f"DagRunKey/{self._generate_dag_key()}", existing_user_agent_extra or "", ] return " ".join(user_agent_extra_values).strip() @cached_property
[docs] def conn_config(self) -> AwsConnectionWrapper: """Get the Airflow Connection object and wrap it in helper (cached).""" connection = None if self.aws_conn_id: try: connection = self.get_connection(self.aws_conn_id) except AirflowNotFoundException: self.log.warning( "Unable to find AWS Connection ID '%s', switching to empty.", self.aws_conn_id ) return AwsConnectionWrapper( conn=connection, region_name=self._region_name, botocore_config=self._config, verify=self._verify )
def _resolve_service_name(self, is_resource_type: bool = False) -> str: """Resolve service name based on type or raise an error.""" if exactly_one(self.client_type, self.resource_type): # It is possible to write simple conditions, however it make mypy unhappy. if self.client_type: if is_resource_type: raise LookupError("Requested `resource_type`, but `client_type` was set instead.") return self.client_type elif self.resource_type: if not is_resource_type: raise LookupError("Requested `client_type`, but `resource_type` was set instead.") return self.resource_type raise ValueError( f"Either client_type={self.client_type!r} or " f"resource_type={self.resource_type!r} must be provided, not both." ) @property
[docs] def service_name(self) -> str: """Extracted botocore/boto3 service name from hook parameters.""" return self._resolve_service_name(is_resource_type=bool(self.resource_type))
[docs] def service_config(self) -> dict: """Config for hook-specific service from AWS Connection.""" return self.conn_config.get_service_config(service_name=self.service_name)
[docs] def region_name(self) -> str | None: """AWS Region Name read-only property.""" return self.conn_config.region_name
[docs] def config(self) -> Config: """Configuration for botocore client read-only property.""" return self.conn_config.botocore_config or botocore.config.Config()
[docs] def verify(self) -> bool | str | None: """Verify or not SSL certificates boto3 client/resource read-only property.""" return self.conn_config.verify
[docs] def get_session(self, region_name: str | None = None, deferrable: bool = False) -> boto3.session.Session: """Get the underlying boto3.session.Session(region_name=region_name).""" return SessionFactory( conn=self.conn_config, region_name=region_name, config=self.config ).create_session(deferrable=deferrable)
def _get_config(self, config: Config | None = None) -> Config: """ No AWS Operators use the config argument to this method. Keep backward compatibility with other users who might use it. """ if config is None: config = deepcopy(self.config) # ignore[union-attr] is required for this block to appease MyPy # because the user_agent_extra field is generated at runtime. user_agent_config = Config( user_agent_extra=self._generate_user_agent_extra_field( existing_user_agent_extra=config.user_agent_extra # type: ignore[union-attr] ) ) return config.merge(user_agent_config) # type: ignore[union-attr]
[docs] def get_client_type( self, region_name: str | None = None, config: Config | None = None, deferrable: bool = False, ) -> boto3.client: """Get the underlying boto3 client using boto3 session.""" service_name = self._resolve_service_name(is_resource_type=False) session = self.get_session(region_name=region_name, deferrable=deferrable) endpoint_url = self.conn_config.get_service_endpoint_url(service_name=service_name) if not isinstance(session, boto3.session.Session): return session.create_client( service_name=service_name, endpoint_url=endpoint_url, config=self._get_config(config), verify=self.verify, ) return session.client( service_name=service_name, endpoint_url=endpoint_url, config=self._get_config(config), verify=self.verify, )
[docs] def get_resource_type( self, region_name: str | None = None, config: Config | None = None, ) -> boto3.resource: """Get the underlying boto3 resource using boto3 session.""" service_name = self._resolve_service_name(is_resource_type=True) session = self.get_session(region_name=region_name) return session.resource( service_name=service_name, endpoint_url=self.conn_config.get_service_endpoint_url(service_name=service_name), config=self._get_config(config), verify=self.verify, )
[docs] def conn(self) -> BaseAwsConnection: """ Get the underlying boto3 client/resource (cached). :return: boto3.client or boto3.resource """ if self.client_type: return self.get_client_type(region_name=self.region_name) return self.get_resource_type(region_name=self.region_name)
[docs] def async_conn(self): """Get an aiobotocore client to use for async operations.""" if not self.client_type: raise ValueError("client_type must be specified.") return self.get_client_type(region_name=self.region_name, deferrable=True)
@cached_property def _client(self) -> botocore.client.BaseClient: conn = self.conn if isinstance(conn, botocore.client.BaseClient): return conn return conn.meta.client @property
[docs] def conn_client_meta(self) -> ClientMeta: """Get botocore client metadata from Hook connection (cached).""" return self._client.meta
[docs] def conn_region_name(self) -> str: """Get actual AWS Region Name from Hook connection (cached).""" return self.conn_client_meta.region_name
[docs] def conn_partition(self) -> str: """Get associated AWS Region Partition from Hook connection (cached).""" return self.conn_client_meta.partition
[docs] def get_conn(self) -> BaseAwsConnection: """ Get the underlying boto3 client/resource (cached). Implemented so that caching works as intended. It exists for compatibility with subclasses that rely on a super().get_conn() method. :return: boto3.client or boto3.resource """ # Compat shim return self.conn
[docs] def get_credentials(self, region_name: str | None = None) -> ReadOnlyCredentials: """ Get the underlying `botocore.Credentials` object. This contains the following authentication attributes: access_key, secret_key and token. By use this method also secret_key and token will mask in tasks logs. """ # Credentials are refreshable, so accessing your access key and # secret key separately can lead to a race condition. # See creds = self.get_session(region_name=region_name).get_credentials().get_frozen_credentials() mask_secret(creds.secret_key) if creds.token: mask_secret(creds.token) return creds
[docs] def expand_role(self, role: str, region_name: str | None = None) -> str: """Get the Amazon Resource Name (ARN) for the role. If IAM role is already an IAM role ARN, the value is returned unchanged. :param role: IAM role name or ARN :param region_name: Optional region name to get credentials for :return: IAM role ARN """ if "/" in role: return role else: session = self.get_session(region_name=region_name) _client = session.client( service_name="iam", endpoint_url=self.conn_config.get_service_endpoint_url("iam"), config=self.config, verify=self.verify, ) return _client.get_role(RoleName=role)["Role"]["Arn"]
[docs] def retry(should_retry: Callable[[Exception], bool]): """Repeat requests in response to exceeding a temporary quote limit.""" def retry_decorator(fun: Callable): @wraps(fun) def decorator_f(self, *args, **kwargs): retry_args = getattr(self, "retry_args", None) if retry_args is None: return fun(self, *args, **kwargs) multiplier = retry_args.get("multiplier", 1) min_limit = retry_args.get("min", 1) max_limit = retry_args.get("max", 1) stop_after_delay = retry_args.get("stop_after_delay", 10) tenacity_before_logger = tenacity.before_log(self.log, logging.INFO) if self.log else None tenacity_after_logger = tenacity.after_log(self.log, logging.INFO) if self.log else None default_kwargs = { "wait": tenacity.wait_exponential(multiplier=multiplier, max=max_limit, min=min_limit), "retry": tenacity.retry_if_exception(should_retry), "stop": tenacity.stop_after_delay(stop_after_delay), "before": tenacity_before_logger, "after": tenacity_after_logger, } return tenacity.retry(**default_kwargs)(fun)(self, *args, **kwargs) return decorator_f return retry_decorator
[docs] def get_ui_field_behaviour() -> dict[str, Any]: """Return custom UI field behaviour for AWS Connection.""" return { "hidden_fields": ["host", "schema", "port"], "relabeling": { "login": "AWS Access Key ID", "password": "AWS Secret Access Key", }, "placeholders": { "login": "AKIAIOSFODNN7EXAMPLE", "password": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY", "extra": json.dumps( { "region_name": "us-east-1", "session_kwargs": {"profile_name": "default"}, "config_kwargs": {"retries": {"mode": "standard", "max_attempts": 10}}, "role_arn": "arn:aws:iam::123456789098:role/role-name", "assume_role_method": "assume_role", "assume_role_kwargs": {"RoleSessionName": "airflow"}, "aws_session_token": "AQoDYXdzEJr...EXAMPLETOKEN", "endpoint_url": "http://localhost:4566", }, indent=2, ), }, }
[docs] def test_connection(self): """Test the AWS connection by call AWS STS (Security Token Service) GetCallerIdentity API. .. seealso:: """ try: session = self.get_session() conn_info = session.client( service_name="sts", endpoint_url=self.conn_config.get_service_endpoint_url("sts", sts_test_connection=True), ).get_caller_identity() metadata = conn_info.pop("ResponseMetadata", {}) if metadata.get("HTTPStatusCode") != 200: try: return False, json.dumps(metadata) except TypeError: return False, str(metadata) conn_info["credentials_method"] = session.get_credentials().method conn_info["region_name"] = session.region_name return True, ", ".join(f"{k}={v!r}" for k, v in conn_info.items()) except Exception as e: return False, f"{type(e).__name__!r} error occurred while testing connection: {e}"
[docs] def waiter_path(self) -> os.PathLike[str] | None: filename = self.client_type if self.client_type else self.resource_type path = Path(__file__).parents[1].joinpath(f"waiters/{filename}.json").resolve() return path if path.exists() else None
[docs] def get_waiter( self, waiter_name: str, parameters: dict[str, str] | None = None, deferrable: bool = False, client=None, ) -> Waiter: """Get a waiter by name. First checks if there is a custom waiter with the provided waiter_name and uses that if it exists, otherwise it will check the service client for a waiter that matches the name and pass that through. If `deferrable` is True, the waiter will be an AIOWaiter, generated from the client that is passed as a parameter. If `deferrable` is True, `client` must be provided. :param waiter_name: The name of the waiter. The name should exactly match the name of the key in the waiter model file (typically this is CamelCase). :param parameters: will scan the waiter config for the keys of that dict, and replace them with the corresponding value. If a custom waiter has such keys to be expanded, they need to be provided here. :param deferrable: If True, the waiter is going to be an async custom waiter. An async client must be provided in that case. :param client: The client to use for the waiter's operations """ from import BaseBotoWaiter if deferrable and not client: raise ValueError("client must be provided for a deferrable waiter.") # Currently, the custom waiter doesn't work with resource_type, only client_type is supported. client = client or self._client if self.waiter_path and (waiter_name in self._list_custom_waiters()): # Technically if waiter_name is in custom_waiters then self.waiter_path must # exist but MyPy doesn't like the fact that self.waiter_path could be None. with open(self.waiter_path) as config_file: config = json.loads( config = self._apply_parameters_value(config, waiter_name, parameters) return BaseBotoWaiter(client=client, model_config=config, deferrable=deferrable).waiter( waiter_name ) # If there is no custom waiter found for the provided name, # then try checking the service's official waiters. return client.get_waiter(waiter_name)
@staticmethod def _apply_parameters_value(config: dict, waiter_name: str, parameters: dict[str, str] | None) -> dict: """Replace potential jinja templates in acceptors definition.""" # only process the waiter we're going to use to not raise errors for missing params for other waiters. acceptors = config["waiters"][waiter_name]["acceptors"] for a in acceptors: arg = a["argument"] template = jinja2.Template(arg, autoescape=False, undefined=jinja2.StrictUndefined) try: a["argument"] = template.render(parameters or {}) except jinja2.UndefinedError as e: raise AirflowException( f"Parameter was not supplied for templated waiter's acceptor '{arg}'", e ) return config
[docs] def list_waiters(self) -> list[str]: """Return a list containing the names of all waiters for the service, official and custom.""" return [*self._list_official_waiters(), *self._list_custom_waiters()]
def _list_official_waiters(self) -> list[str]: return self._client.waiter_names def _list_custom_waiters(self) -> list[str]: if not self.waiter_path: return [] with open(self.waiter_path) as config_file: model_config = json.load(config_file) return WaiterModel(model_config).waiter_names
[docs]class AwsBaseHook(AwsGenericHook[Union[boto3.client, boto3.resource]]): """Base class for interact with AWS. This class provide a thin wrapper around the boto3 Python library. :param aws_conn_id: The Airflow connection used for AWS credentials. If this is None or empty then the default boto3 behaviour is used. If running Airflow in a distributed manner and aws_conn_id is None or empty, then default boto3 configuration would be used (and must be maintained on each worker node). :param verify: Whether or not to verify SSL certificates. See: :param region_name: AWS region_name. If not specified then the default boto3 behaviour is used. :param client_type: Reference to :external:py:meth:`boto3.client service_name \ <boto3.session.Session.client>`, e.g. 'emr', 'batch', 's3', etc. Mutually exclusive with ``resource_type``. :param resource_type: Reference to :external:py:meth:`boto3.resource service_name \ <boto3.session.Session.resource>`, e.g. 's3', 'ec2', 'dynamodb', etc. Mutually exclusive with ``client_type``. :param config: Configuration for botocore client. See: """
[docs]def resolve_session_factory() -> type[BaseSessionFactory]: """Resolve custom SessionFactory class.""" clazz = conf.getimport("aws", "session_factory", fallback=None) if not clazz: return BaseSessionFactory if not issubclass(clazz, BaseSessionFactory): raise TypeError( f"Your custom AWS SessionFactory class `{clazz.__name__}` is not a subclass " f"of `{BaseSessionFactory.__name__}`." ) return clazz
[docs]SessionFactory = resolve_session_factory()
def _parse_s3_config(config_file_name: str, config_format: str | None = "boto", profile: str | None = None): """For compatibility with airflow.contrib.hooks.aws_hook.""" from import _parse_s3_config return _parse_s3_config( config_file_name=config_file_name, config_format=config_format, profile=profile, ) try: import aiobotocore.credentials from aiobotocore.session import AioSession, get_session except ImportError: pass
[docs]class BaseAsyncSessionFactory(BaseSessionFactory): """ Base AWS Session Factory class to handle aiobotocore session creation. It currently, handles ENV, AWS secret key and STS client method ``assume_role`` provided in Airflow connection """ def __init__(self, *args, **kwargs): warnings.warn( " has been deprecated and " "will be removed in future", AirflowProviderDeprecationWarning, stacklevel=2, ) super().__init__(*args, **kwargs)
[docs] async def get_role_credentials(self) -> dict: """Get the role_arn, method credentials from connection and get the role credentials.""" async with self._basic_session.create_client("sts", region_name=self.region_name) as client: response = await client.assume_role( RoleArn=self.role_arn, RoleSessionName=self._strip_invalid_session_name_characters(f"Airflow_{self.conn.conn_id}"), **self.conn.assume_role_kwargs, ) return response["Credentials"]
async def _get_refresh_credentials(self) -> dict[str, Any]: self.log.debug("Refreshing credentials") assume_role_method = self.conn.assume_role_method if assume_role_method != "assume_role": raise NotImplementedError(f"assume_role_method={assume_role_method} not expected") credentials = await self.get_role_credentials() expiry_time = credentials["Expiration"].isoformat() self.log.debug("New credentials expiry_time: %s", expiry_time) credentials = { "access_key": credentials.get("AccessKeyId"), "secret_key": credentials.get("SecretAccessKey"), "token": credentials.get("SessionToken"), "expiry_time": expiry_time, } return credentials def _get_session_with_assume_role(self) -> AioSession: assume_role_method = self.conn.assume_role_method if assume_role_method != "assume_role": raise NotImplementedError(f"assume_role_method={assume_role_method} not expected") credentials = aiobotocore.credentials.AioRefreshableCredentials.create_from_metadata( metadata=self._get_refresh_credentials(), refresh_using=self._get_refresh_credentials, method="sts-assume-role", ) session = aiobotocore.session.get_session() session._credentials = credentials return session @cached_property def _basic_session(self) -> AioSession: """Cached property with basic aiobotocore.session.AioSession.""" session_kwargs = self.conn.session_kwargs aws_access_key_id = session_kwargs.get("aws_access_key_id") aws_secret_access_key = session_kwargs.get("aws_secret_access_key") aws_session_token = session_kwargs.get("aws_session_token") region_name = session_kwargs.get("region_name") profile_name = session_kwargs.get("profile_name") aio_session = get_session() if profile_name is not None: aio_session.set_config_variable("profile", profile_name) if aws_access_key_id or aws_secret_access_key or aws_session_token: aio_session.set_credentials( access_key=aws_access_key_id, secret_key=aws_secret_access_key, token=aws_session_token, ) if region_name is not None: aio_session.set_config_variable("region", region_name) return aio_session
[docs] def create_session(self, deferrable: bool = False) -> AioSession: """Create aiobotocore Session from connection and config.""" if not self._conn:"No connection ID provided. Fallback on boto3 credential strategy") return get_session() elif not self.role_arn: return self._basic_session return self._get_session_with_assume_role()
[docs]class AwsBaseAsyncHook(AwsBaseHook): """Interacts with AWS using aiobotocore asynchronously. :param aws_conn_id: The Airflow connection used for AWS credentials. If this is None or empty then the default botocore behaviour is used. If running Airflow in a distributed manner and aws_conn_id is None or empty, then default botocore configuration would be used (and must be maintained on each worker node). :param verify: Whether to verify SSL certificates. :param region_name: AWS region_name. If not specified then the default boto3 behaviour is used. :param client_type: boto3.client client_type. Eg 's3', 'emr' etc :param resource_type: boto3.resource resource_type. Eg 'dynamodb' etc :param config: Configuration for botocore client. """ def __init__(self, *args, **kwargs): warnings.warn( " has been deprecated and " "will be removed in future", AirflowProviderDeprecationWarning, stacklevel=2, ) super().__init__(*args, **kwargs)
[docs] def get_async_session(self) -> AioSession: """Get the underlying aiobotocore.session.AioSession(...).""" return BaseAsyncSessionFactory( conn=self.conn_config, region_name=self.region_name, config=self.config ).create_session()
[docs] async def get_client_async(self): """Get the underlying aiobotocore client using aiobotocore session.""" return self.get_async_session().create_client( self.client_type, region_name=self.region_name, verify=self.verify, endpoint_url=self.conn_config.endpoint_url, config=self.config, )

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