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Slack

zenml.integrations.slack

Slack integration for alerter components.

Attributes

SLACK = 'slack' module-attribute

SLACK_ALERTER_FLAVOR = 'slack' module-attribute

Classes

Flavor

Class for ZenML Flavors.

Attributes
config_class: Type[StackComponentConfig] abstractmethod property

Returns StackComponentConfig config class.

Returns:

Type Description
Type[StackComponentConfig]

The config class.
config_schema: Dict[str, Any] property

The config schema for a flavor.

Returns:

Type Description
Dict[str, Any]

The config schema.
docs_url: Optional[str] property

A url to point at docs explaining this flavor.

Returns:

Type Description
Optional[str]

A flavor docs url.
implementation_class: Type[StackComponent] abstractmethod property

Implementation class for this flavor.

Returns:

Type Description
Type[StackComponent]

The implementation class for this flavor.
logo_url: Optional[str] property

A url to represent the flavor in the dashboard.

Returns:

Type Description
Optional[str]

The flavor logo.
name: str abstractmethod property

The flavor name.

Returns:

Type Description
str

The flavor name.
sdk_docs_url: Optional[str] property

A url to point at SDK docs explaining this flavor.

Returns:

Type Description
Optional[str]

A flavor SDK docs url.
service_connector_requirements: Optional[ServiceConnectorRequirements] property

Service connector resource requirements for service connectors.

Specifies resource requirements that are used to filter the available service connector types that are compatible with this flavor.

Returns:

Type Description
Optional[ServiceConnectorRequirements]

Requirements for compatible service connectors, if a service
Optional[ServiceConnectorRequirements]

connector is required for this flavor.
type: StackComponentType abstractmethod property

The stack component type.

Returns:

Type Description
StackComponentType

The stack component type.
Functions
from_model(flavor_model: FlavorResponse) -> Flavor classmethod

Loads a flavor from a model.

Parameters:

Name Type Description Default
flavor_model FlavorResponse

The model to load from.

 required

Raises:

Type Description
CustomFlavorImportError

If the custom flavor can't be imported.
ImportError

If the flavor can't be imported.

Returns:

Type Description
Flavor

The loaded flavor.
Source code in src/zenml/stack/flavor.py 
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@classmethod
def from_model(cls, flavor_model: FlavorResponse) -> "Flavor":
    """Loads a flavor from a model.

    Args:
        flavor_model: The model to load from.

    Raises:
        CustomFlavorImportError: If the custom flavor can't be imported.
        ImportError: If the flavor can't be imported.

    Returns:
        The loaded flavor.
    """
    try:
        flavor = source_utils.load(flavor_model.source)()
    except (ModuleNotFoundError, ImportError, NotImplementedError) as err:
        if flavor_model.is_custom:
            flavor_module, _ = flavor_model.source.rsplit(".", maxsplit=1)
            expected_file_path = os.path.join(
                source_utils.get_source_root(),
                flavor_module.replace(".", os.path.sep),
            )
            raise CustomFlavorImportError(
                f"Couldn't import custom flavor {flavor_model.name}: "
                f"{err}. Make sure the custom flavor class "
                f"`{flavor_model.source}` is importable. If it is part of "
                "a library, make sure it is installed. If "
                "it is a local code file, make sure it exists at "
                f"`{expected_file_path}.py`."
            )
        else:
            raise ImportError(
                f"Couldn't import flavor {flavor_model.name}: {err}"
            )
    return cast(Flavor, flavor)
generate_default_docs_url() -> str

Generate the doc urls for all inbuilt and integration flavors.

Note that this method is not going to be useful for custom flavors, which do not have any docs in the main zenml docs.

Returns:

Type Description
str

The complete url to the zenml documentation
Source code in src/zenml/stack/flavor.py 
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def generate_default_docs_url(self) -> str:
    """Generate the doc urls for all inbuilt and integration flavors.

    Note that this method is not going to be useful for custom flavors,
    which do not have any docs in the main zenml docs.

    Returns:
        The complete url to the zenml documentation
    """
    from zenml import __version__

    component_type = self.type.plural.replace("_", "-")
    name = self.name.replace("_", "-")

    try:
        is_latest = is_latest_zenml_version()
    except RuntimeError:
        # We assume in error cases that we are on the latest version
        is_latest = True

    if is_latest:
        base = "https://docs.zenml.io"
    else:
        base = f"https://zenml-io.gitbook.io/zenml-legacy-documentation/v/{__version__}"
    return f"{base}/stack-components/{component_type}/{name}"
generate_default_sdk_docs_url() -> str

Generate SDK docs url for a flavor.

Returns:

Type Description
str

The complete url to the zenml SDK docs
Source code in src/zenml/stack/flavor.py 
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def generate_default_sdk_docs_url(self) -> str:
    """Generate SDK docs url for a flavor.

    Returns:
        The complete url to the zenml SDK docs
    """
    from zenml import __version__

    base = f"https://sdkdocs.zenml.io/{__version__}"

    component_type = self.type.plural

    if "zenml.integrations" in self.__module__:
        # Get integration name out of module path which will look something
        #  like this "zenml.integrations.<integration>....
        integration = self.__module__.split(
            "zenml.integrations.", maxsplit=1
        )[1].split(".")[0]

        return (
            f"{base}/integration_code_docs"
            f"/integrations-{integration}/#{self.__module__}"
        )

    else:
        return (
            f"{base}/core_code_docs/core-{component_type}/"
            f"#{self.__module__}"
        )
to_model(integration: Optional[str] = None, is_custom: bool = True) -> FlavorRequest

Converts a flavor to a model.

Parameters:

Name Type Description Default
integration Optional[str]

The integration to use for the model.

 None
is_custom bool

Whether the flavor is a custom flavor.

 True

Returns:

Type Description
FlavorRequest

The model.
Source code in src/zenml/stack/flavor.py 
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def to_model(
    self,
    integration: Optional[str] = None,
    is_custom: bool = True,
) -> FlavorRequest:
    """Converts a flavor to a model.

    Args:
        integration: The integration to use for the model.
        is_custom: Whether the flavor is a custom flavor.

    Returns:
        The model.
    """
    connector_requirements = self.service_connector_requirements
    connector_type = (
        connector_requirements.connector_type
        if connector_requirements
        else None
    )
    resource_type = (
        connector_requirements.resource_type
        if connector_requirements
        else None
    )
    resource_id_attr = (
        connector_requirements.resource_id_attr
        if connector_requirements
        else None
    )

    model = FlavorRequest(
        name=self.name,
        type=self.type,
        source=source_utils.resolve(self.__class__).import_path,
        config_schema=self.config_schema,
        connector_type=connector_type,
        connector_resource_type=resource_type,
        connector_resource_id_attr=resource_id_attr,
        integration=integration,
        logo_url=self.logo_url,
        docs_url=self.docs_url,
        sdk_docs_url=self.sdk_docs_url,
        is_custom=is_custom,
    )
    return model

Integration

Base class for integration in ZenML.

Functions
activate() -> None classmethod

Abstract method to activate the integration.

Source code in src/zenml/integrations/integration.py 
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@classmethod
def activate(cls) -> None:
    """Abstract method to activate the integration."""
check_installation() -> bool classmethod

Method to check whether the required packages are installed.

Returns:

Type Description
bool

True if all required packages are installed, False otherwise.
Source code in src/zenml/integrations/integration.py 
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@classmethod
def check_installation(cls) -> bool:
    """Method to check whether the required packages are installed.

    Returns:
        True if all required packages are installed, False otherwise.
    """
    for r in cls.get_requirements():
        try:
            # First check if the base package is installed
            dist = pkg_resources.get_distribution(r)

            # Next, check if the dependencies (including extras) are
            # installed
            deps: List[Requirement] = []

            _, extras = parse_requirement(r)
            if extras:
                extra_list = extras[1:-1].split(",")
                for extra in extra_list:
                    try:
                        requirements = dist.requires(extras=[extra])  # type: ignore[arg-type]
                    except pkg_resources.UnknownExtra as e:
                        logger.debug(f"Unknown extra: {str(e)}")
                        return False
                    deps.extend(requirements)
            else:
                deps = dist.requires()

            for ri in deps:
                try:
                    # Remove the "extra == ..." part from the requirement string
                    cleaned_req = re.sub(
                        r"; extra == \"\w+\"", "", str(ri)
                    )
                    pkg_resources.get_distribution(cleaned_req)
                except pkg_resources.DistributionNotFound as e:
                    logger.debug(
                        f"Unable to find required dependency "
                        f"'{e.req}' for requirement '{r}' "
                        f"necessary for integration '{cls.NAME}'."
                    )
                    return False
                except pkg_resources.VersionConflict as e:
                    logger.debug(
                        f"Package version '{e.dist}' does not match "
                        f"version '{e.req}' required by '{r}' "
                        f"necessary for integration '{cls.NAME}'."
                    )
                    return False

        except pkg_resources.DistributionNotFound as e:
            logger.debug(
                f"Unable to find required package '{e.req}' for "
                f"integration {cls.NAME}."
            )
            return False
        except pkg_resources.VersionConflict as e:
            logger.debug(
                f"Package version '{e.dist}' does not match version "
                f"'{e.req}' necessary for integration {cls.NAME}."
            )
            return False

    logger.debug(
        f"Integration {cls.NAME} is installed correctly with "
        f"requirements {cls.get_requirements()}."
    )
    return True
flavors() -> List[Type[Flavor]] classmethod

Abstract method to declare new stack component flavors.

Returns:

Type Description
List[Type[Flavor]]

A list of new stack component flavors.
Source code in src/zenml/integrations/integration.py 
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@classmethod
def flavors(cls) -> List[Type[Flavor]]:
    """Abstract method to declare new stack component flavors.

    Returns:
        A list of new stack component flavors.
    """
    return []
get_requirements(target_os: Optional[str] = None, python_version: Optional[str] = None) -> List[str] classmethod

Method to get the requirements for the integration.

Parameters:

Name Type Description Default
target_os Optional[str]

The target operating system to get the requirements for.

 None
python_version Optional[str]

The Python version to use for the requirements.

 None

Returns:

Type Description
List[str]

A list of requirements.
Source code in src/zenml/integrations/integration.py 
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@classmethod
def get_requirements(
    cls,
    target_os: Optional[str] = None,
    python_version: Optional[str] = None,
) -> List[str]:
    """Method to get the requirements for the integration.

    Args:
        target_os: The target operating system to get the requirements for.
        python_version: The Python version to use for the requirements.

    Returns:
        A list of requirements.
    """
    return cls.REQUIREMENTS
get_uninstall_requirements(target_os: Optional[str] = None) -> List[str] classmethod

Method to get the uninstall requirements for the integration.

Parameters:

Name Type Description Default
target_os Optional[str]

The target operating system to get the requirements for.

 None

Returns:

Type Description
List[str]

A list of requirements.
Source code in src/zenml/integrations/integration.py 
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@classmethod
def get_uninstall_requirements(
    cls, target_os: Optional[str] = None
) -> List[str]:
    """Method to get the uninstall requirements for the integration.

    Args:
        target_os: The target operating system to get the requirements for.

    Returns:
        A list of requirements.
    """
    ret = []
    for each in cls.get_requirements(target_os=target_os):
        is_ignored = False
        for ignored in cls.REQUIREMENTS_IGNORED_ON_UNINSTALL:
            if each.startswith(ignored):
                is_ignored = True
                break
        if not is_ignored:
            ret.append(each)
    return ret
plugin_flavors() -> List[Type[BasePluginFlavor]] classmethod

Abstract method to declare new plugin flavors.

Returns:

Type Description
List[Type[BasePluginFlavor]]

A list of new plugin flavors.
Source code in src/zenml/integrations/integration.py 
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@classmethod
def plugin_flavors(cls) -> List[Type["BasePluginFlavor"]]:
    """Abstract method to declare new plugin flavors.

    Returns:
        A list of new plugin flavors.
    """
    return []

SlackIntegration

Bases: Integration

Definition of a Slack integration for ZenML.

Implemented using Slack SDK.

Functions
flavors() -> List[Type[Flavor]] classmethod

Declare the stack component flavors for the Slack integration.

Returns:

Type Description
List[Type[Flavor]]

List of new flavors defined by the Slack integration.
Source code in src/zenml/integrations/slack/__init__.py 
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@classmethod
def flavors(cls) -> List[Type[Flavor]]:
    """Declare the stack component flavors for the Slack integration.

    Returns:
        List of new flavors defined by the Slack integration.
    """
    from zenml.integrations.slack.flavors import SlackAlerterFlavor

    return [SlackAlerterFlavor]

StackComponentType

Bases: StrEnum

All possible types a StackComponent can have.

Attributes
plural: str property

Returns the plural of the enum value.

Returns:

Type Description
str

The plural of the enum value.

Modules

alerters

Alerter components defined by the Slack integration.

Classes
SlackAlerter(name: str, id: UUID, config: StackComponentConfig, flavor: str, type: StackComponentType, user: Optional[UUID], created: datetime, updated: datetime, labels: Optional[Dict[str, Any]] = None, connector_requirements: Optional[ServiceConnectorRequirements] = None, connector: Optional[UUID] = None, connector_resource_id: Optional[str] = None, *args: Any, **kwargs: Any)

Bases: BaseAlerter

Send messages to Slack channels.

Source code in src/zenml/stack/stack_component.py 
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def __init__(
    self,
    name: str,
    id: UUID,
    config: StackComponentConfig,
    flavor: str,
    type: StackComponentType,
    user: Optional[UUID],
    created: datetime,
    updated: datetime,
    labels: Optional[Dict[str, Any]] = None,
    connector_requirements: Optional[ServiceConnectorRequirements] = None,
    connector: Optional[UUID] = None,
    connector_resource_id: Optional[str] = None,
    *args: Any,
    **kwargs: Any,
):
    """Initializes a StackComponent.

    Args:
        name: The name of the component.
        id: The unique ID of the component.
        config: The config of the component.
        flavor: The flavor of the component.
        type: The type of the component.
        user: The ID of the user who created the component.
        created: The creation time of the component.
        updated: The last update time of the component.
        labels: The labels of the component.
        connector_requirements: The requirements for the connector.
        connector: The ID of a connector linked to the component.
        connector_resource_id: The custom resource ID to access through
            the connector.
        *args: Additional positional arguments.
        **kwargs: Additional keyword arguments.

    Raises:
        ValueError: If a secret reference is passed as name.
    """
    if secret_utils.is_secret_reference(name):
        raise ValueError(
            "Passing the `name` attribute of a stack component as a "
            "secret reference is not allowed."
        )

    self.id = id
    self.name = name
    self._config = config
    self.flavor = flavor
    self.type = type
    self.user = user
    self.created = created
    self.updated = updated
    self.labels = labels
    self.connector_requirements = connector_requirements
    self.connector = connector
    self.connector_resource_id = connector_resource_id
    self._connector_instance: Optional[ServiceConnector] = None
Attributes
config: SlackAlerterConfig property

Returns the SlackAlerterConfig config.

Returns:

Type Description
SlackAlerterConfig

The configuration.
settings_class: Type[SlackAlerterSettings] property

Settings class for the Slack alerter.

Returns:

Type Description
Type[SlackAlerterSettings]

The settings class.
Functions
ask(question: str, params: Optional[BaseAlerterStepParameters] = None) -> bool

Post a message to a Slack channel and wait for approval.

Parameters:

Name Type Description Default
question str

Initial message to be posted.

 required
params Optional[BaseAlerterStepParameters]

Optional parameters.

 None

Returns:

Type Description
bool

True if a user approved the operation, else False
Source code in src/zenml/integrations/slack/alerters/slack_alerter.py 
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def ask(
    self, question: str, params: Optional[BaseAlerterStepParameters] = None
) -> bool:
    """Post a message to a Slack channel and wait for approval.

    Args:
        question: Initial message to be posted.
        params: Optional parameters.

    Returns:
        True if a user approved the operation, else False
    """
    slack_channel_id = self._get_channel_id(params=params)

    client = WebClient(token=self.config.slack_token)
    approve_options = self._get_approve_msg_options(params)
    disapprove_options = self._get_disapprove_msg_options(params)

    try:
        # Send message to the Slack channel
        response = client.chat_postMessage(
            channel=slack_channel_id,
            text=question,
            blocks=self._create_blocks(question, params),
        )

        if not response.get("ok", False):
            error_details = response.get("error", "Unknown error")
            logger.error(
                f"Failed to send the initial message to the Slack channel. "
                f"Error: {error_details}. Full response: {response}"
            )
            return False

        # Retrieve timestamp of sent message
        timestamp = response["ts"]

        # Wait for a response
        start_time = time.time()

        while time.time() - start_time < self._get_timeout_duration():
            history = client.conversations_history(
                channel=slack_channel_id, oldest=timestamp
            )
            for msg in history["messages"]:
                if "ts" in msg and "user" in msg:
                    user_message = msg["text"].strip().lower()
                    if user_message in [
                        opt.lower() for opt in approve_options
                    ]:
                        logger.info("User approved the operation.")
                        return True
                    elif user_message in [
                        opt.lower() for opt in disapprove_options
                    ]:
                        logger.info("User disapproved the operation.")
                        return False

            time.sleep(1)  # Polling interval

        logger.warning("No response received within the timeout period.")
        return False

    except SlackApiError as error:
        error_message = error.response.get("error", "Unknown error")
        logger.error(
            f"SlackAlerter.ask() failed with Slack API error: "
            f"{error_message}. Full response: {error.response}"
        )
        return False
    except Exception as e:
        logger.error(f"Unexpected error in SlackAlerter.ask(): {str(e)}")
        return False
post(message: Optional[str] = None, params: Optional[BaseAlerterStepParameters] = None) -> bool

Post a message to a Slack channel.

Parameters:

Name Type Description Default
message Optional[str]

Message to be posted.

 None
params Optional[BaseAlerterStepParameters]

Optional parameters.

 None

Returns:

Type Description
bool

True if operation succeeded, else False
Source code in src/zenml/integrations/slack/alerters/slack_alerter.py 
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def post(
    self,
    message: Optional[str] = None,
    params: Optional[BaseAlerterStepParameters] = None,
) -> bool:
    """Post a message to a Slack channel.

    Args:
        message: Message to be posted.
        params: Optional parameters.

    Returns:
        True if operation succeeded, else False
    """
    slack_channel_id = self._get_channel_id(params=params)
    client = WebClient(token=self.config.slack_token)
    blocks = self._create_blocks(message, params)
    try:
        response = client.chat_postMessage(
            channel=slack_channel_id, text=message, blocks=blocks
        )
        if not response.get("ok", False):
            error_details = response.get("error", "Unknown error")
            logger.error(
                f"Failed to send message to Slack channel. "
                f"Error: {error_details}. Full response: {response}"
            )
            return False
        return True
    except SlackApiError as error:
        error_message = error.response.get("error", "Unknown error")
        logger.error(
            "SlackAlerter.post() failed with Slack API error: "
            f"{error_message}. Full response: {error.response}"
        )
        return False
    except Exception as e:
        logger.error(f"Unexpected error in SlackAlerter.post(): {str(e)}")
        return False
Modules
slack_alerter

Implementation for slack flavor of alerter component.

Classes
SlackAlerter(name: str, id: UUID, config: StackComponentConfig, flavor: str, type: StackComponentType, user: Optional[UUID], created: datetime, updated: datetime, labels: Optional[Dict[str, Any]] = None, connector_requirements: Optional[ServiceConnectorRequirements] = None, connector: Optional[UUID] = None, connector_resource_id: Optional[str] = None, *args: Any, **kwargs: Any)

Bases: BaseAlerter

Send messages to Slack channels.

Source code in src/zenml/stack/stack_component.py 
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def __init__(
    self,
    name: str,
    id: UUID,
    config: StackComponentConfig,
    flavor: str,
    type: StackComponentType,
    user: Optional[UUID],
    created: datetime,
    updated: datetime,
    labels: Optional[Dict[str, Any]] = None,
    connector_requirements: Optional[ServiceConnectorRequirements] = None,
    connector: Optional[UUID] = None,
    connector_resource_id: Optional[str] = None,
    *args: Any,
    **kwargs: Any,
):
    """Initializes a StackComponent.

    Args:
        name: The name of the component.
        id: The unique ID of the component.
        config: The config of the component.
        flavor: The flavor of the component.
        type: The type of the component.
        user: The ID of the user who created the component.
        created: The creation time of the component.
        updated: The last update time of the component.
        labels: The labels of the component.
        connector_requirements: The requirements for the connector.
        connector: The ID of a connector linked to the component.
        connector_resource_id: The custom resource ID to access through
            the connector.
        *args: Additional positional arguments.
        **kwargs: Additional keyword arguments.

    Raises:
        ValueError: If a secret reference is passed as name.
    """
    if secret_utils.is_secret_reference(name):
        raise ValueError(
            "Passing the `name` attribute of a stack component as a "
            "secret reference is not allowed."
        )

    self.id = id
    self.name = name
    self._config = config
    self.flavor = flavor
    self.type = type
    self.user = user
    self.created = created
    self.updated = updated
    self.labels = labels
    self.connector_requirements = connector_requirements
    self.connector = connector
    self.connector_resource_id = connector_resource_id
    self._connector_instance: Optional[ServiceConnector] = None
Attributes
config: SlackAlerterConfig property

Returns the SlackAlerterConfig config.

Returns:

Type Description
SlackAlerterConfig

The configuration.
settings_class: Type[SlackAlerterSettings] property

Settings class for the Slack alerter.

Returns:

Type Description
Type[SlackAlerterSettings]

The settings class.
Functions
ask(question: str, params: Optional[BaseAlerterStepParameters] = None) -> bool

Post a message to a Slack channel and wait for approval.

Parameters:

Name Type Description Default
question str

Initial message to be posted.

 required
params Optional[BaseAlerterStepParameters]

Optional parameters.

 None

Returns:

Type Description
bool

True if a user approved the operation, else False
Source code in src/zenml/integrations/slack/alerters/slack_alerter.py 
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def ask(
    self, question: str, params: Optional[BaseAlerterStepParameters] = None
) -> bool:
    """Post a message to a Slack channel and wait for approval.

    Args:
        question: Initial message to be posted.
        params: Optional parameters.

    Returns:
        True if a user approved the operation, else False
    """
    slack_channel_id = self._get_channel_id(params=params)

    client = WebClient(token=self.config.slack_token)
    approve_options = self._get_approve_msg_options(params)
    disapprove_options = self._get_disapprove_msg_options(params)

    try:
        # Send message to the Slack channel
        response = client.chat_postMessage(
            channel=slack_channel_id,
            text=question,
            blocks=self._create_blocks(question, params),
        )

        if not response.get("ok", False):
            error_details = response.get("error", "Unknown error")
            logger.error(
                f"Failed to send the initial message to the Slack channel. "
                f"Error: {error_details}. Full response: {response}"
            )
            return False

        # Retrieve timestamp of sent message
        timestamp = response["ts"]

        # Wait for a response
        start_time = time.time()

        while time.time() - start_time < self._get_timeout_duration():
            history = client.conversations_history(
                channel=slack_channel_id, oldest=timestamp
            )
            for msg in history["messages"]:
                if "ts" in msg and "user" in msg:
                    user_message = msg["text"].strip().lower()
                    if user_message in [
                        opt.lower() for opt in approve_options
                    ]:
                        logger.info("User approved the operation.")
                        return True
                    elif user_message in [
                        opt.lower() for opt in disapprove_options
                    ]:
                        logger.info("User disapproved the operation.")
                        return False

            time.sleep(1)  # Polling interval

        logger.warning("No response received within the timeout period.")
        return False

    except SlackApiError as error:
        error_message = error.response.get("error", "Unknown error")
        logger.error(
            f"SlackAlerter.ask() failed with Slack API error: "
            f"{error_message}. Full response: {error.response}"
        )
        return False
    except Exception as e:
        logger.error(f"Unexpected error in SlackAlerter.ask(): {str(e)}")
        return False
post(message: Optional[str] = None, params: Optional[BaseAlerterStepParameters] = None) -> bool

Post a message to a Slack channel.

Parameters:

Name Type Description Default
message Optional[str]

Message to be posted.

 None
params Optional[BaseAlerterStepParameters]

Optional parameters.

 None

Returns:

Type Description
bool

True if operation succeeded, else False
Source code in src/zenml/integrations/slack/alerters/slack_alerter.py 
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def post(
    self,
    message: Optional[str] = None,
    params: Optional[BaseAlerterStepParameters] = None,
) -> bool:
    """Post a message to a Slack channel.

    Args:
        message: Message to be posted.
        params: Optional parameters.

    Returns:
        True if operation succeeded, else False
    """
    slack_channel_id = self._get_channel_id(params=params)
    client = WebClient(token=self.config.slack_token)
    blocks = self._create_blocks(message, params)
    try:
        response = client.chat_postMessage(
            channel=slack_channel_id, text=message, blocks=blocks
        )
        if not response.get("ok", False):
            error_details = response.get("error", "Unknown error")
            logger.error(
                f"Failed to send message to Slack channel. "
                f"Error: {error_details}. Full response: {response}"
            )
            return False
        return True
    except SlackApiError as error:
        error_message = error.response.get("error", "Unknown error")
        logger.error(
            "SlackAlerter.post() failed with Slack API error: "
            f"{error_message}. Full response: {error.response}"
        )
        return False
    except Exception as e:
        logger.error(f"Unexpected error in SlackAlerter.post(): {str(e)}")
        return False
SlackAlerterParameters

Bases: BaseAlerterStepParameters

Slack alerter parameters.

SlackAlerterPayload

Bases: BaseModel

Slack alerter payload implementation.

Functions

flavors

Slack integration flavors.

Classes
SlackAlerterConfig(warn_about_plain_text_secrets: bool = False, **kwargs: Any)

Bases: BaseAlerterConfig, SlackAlerterSettings

Slack alerter config.

Attributes:

Name Type Description
slack_token str

The Slack token tied to the Slack account to be used.
default_slack_channel_id Optional[str]

(deprecated) The ID of the default Slack channel to use for communication.
Source code in src/zenml/stack/stack_component.py 
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def __init__(
    self, warn_about_plain_text_secrets: bool = False, **kwargs: Any
) -> None:
    """Ensures that secret references don't clash with pydantic validation.

    StackComponents allow the specification of all their string attributes
    using secret references of the form `{{secret_name.key}}`. This however
    is only possible when the stack component does not perform any explicit
    validation of this attribute using pydantic validators. If this were
    the case, the validation would run on the secret reference and would
    fail or in the worst case, modify the secret reference and lead to
    unexpected behavior. This method ensures that no attributes that require
    custom pydantic validation are set as secret references.

    Args:
        warn_about_plain_text_secrets: If true, then warns about using
            plain-text secrets.
        **kwargs: Arguments to initialize this stack component.

    Raises:
        ValueError: If an attribute that requires custom pydantic validation
            is passed as a secret reference, or if the `name` attribute
            was passed as a secret reference.
    """
    for key, value in kwargs.items():
        try:
            field = self.__class__.model_fields[key]
        except KeyError:
            # Value for a private attribute or non-existing field, this
            # will fail during the upcoming pydantic validation
            continue

        if value is None:
            continue

        if not secret_utils.is_secret_reference(value):
            if (
                secret_utils.is_secret_field(field)
                and warn_about_plain_text_secrets
            ):
                logger.warning(
                    "You specified a plain-text value for the sensitive "
                    f"attribute `{key}` for a `{self.__class__.__name__}` "
                    "stack component. This is currently only a warning, "
                    "but future versions of ZenML will require you to pass "
                    "in sensitive information as secrets. Check out the "
                    "documentation on how to configure your stack "
                    "components with secrets here: "
                    "https://docs.zenml.io/getting-started/deploying-zenml/secret-management"
                )
            continue

        if pydantic_utils.has_validators(
            pydantic_class=self.__class__, field_name=key
        ):
            raise ValueError(
                f"Passing the stack component attribute `{key}` as a "
                "secret reference is not allowed as additional validation "
                "is required for this attribute."
            )

    super().__init__(**kwargs)
Attributes
is_valid: bool property

Check if the stack component is valid.

Returns:

Type Description
bool

True if the stack component is valid, False otherwise.
SlackAlerterFlavor

Bases: BaseAlerterFlavor

Slack alerter flavor.

Attributes
config_class: Type[SlackAlerterConfig] property

Returns SlackAlerterConfig config class.

Returns:

Type Description
Type[SlackAlerterConfig]

The config class.
docs_url: Optional[str] property

A URL to point at docs explaining this flavor.

Returns:

Type Description
Optional[str]

A flavor docs url.
implementation_class: Type[SlackAlerter] property

Implementation class for this flavor.

Returns:

Type Description
Type[SlackAlerter]

The implementation class.
logo_url: str property

A URL to represent the flavor in the dashboard.

Returns:

Type Description
str

The flavor logo.
name: str property

Name of the flavor.

Returns:

Type Description
str

The name of the flavor.
sdk_docs_url: Optional[str] property

A URL to point at SDK docs explaining this flavor.

Returns:

Type Description
Optional[str]

A flavor SDK docs url.
SlackAlerterSettings(warn_about_plain_text_secrets: bool = False, **kwargs: Any)

Bases: BaseSettings

Settings for the Slack alerter.

Attributes:

Name Type Description
slack_channel_id Optional[str]

The ID of the Slack channel to use for communication.
timeout int

The amount of seconds to wait for the ask method.
Source code in src/zenml/config/secret_reference_mixin.py 
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def __init__(
    self, warn_about_plain_text_secrets: bool = False, **kwargs: Any
) -> None:
    """Ensures that secret references are only passed for valid fields.

    This method ensures that secret references are not passed for fields
    that explicitly prevent them or require pydantic validation.

    Args:
        warn_about_plain_text_secrets: If true, then warns about using plain-text secrets.
        **kwargs: Arguments to initialize this object.

    Raises:
        ValueError: If an attribute that requires custom pydantic validation
            or an attribute which explicitly disallows secret references
            is passed as a secret reference.
    """
    for key, value in kwargs.items():
        try:
            field = self.__class__.model_fields[key]
        except KeyError:
            # Value for a private attribute or non-existing field, this
            # will fail during the upcoming pydantic validation
            continue

        if value is None:
            continue

        if not secret_utils.is_secret_reference(value):
            if (
                secret_utils.is_secret_field(field)
                and warn_about_plain_text_secrets
            ):
                logger.warning(
                    "You specified a plain-text value for the sensitive "
                    f"attribute `{key}`. This is currently only a warning, "
                    "but future versions of ZenML will require you to pass "
                    "in sensitive information as secrets. Check out the "
                    "documentation on how to configure values with secrets "
                    "here: https://docs.zenml.io/getting-started/deploying-zenml/secret-management"
                )
            continue

        if secret_utils.is_clear_text_field(field):
            raise ValueError(
                f"Passing the `{key}` attribute as a secret reference is "
                "not allowed."
            )

        requires_validation = has_validators(
            pydantic_class=self.__class__, field_name=key
        )
        if requires_validation:
            raise ValueError(
                f"Passing the attribute `{key}` as a secret reference is "
                "not allowed as additional validation is required for "
                "this attribute."
            )

    super().__init__(**kwargs)
Modules
slack_alerter_flavor

Slack alerter flavor.

Classes
SlackAlerterConfig(warn_about_plain_text_secrets: bool = False, **kwargs: Any)

Bases: BaseAlerterConfig, SlackAlerterSettings

Slack alerter config.

Attributes:

Name Type Description
slack_token str

The Slack token tied to the Slack account to be used.
default_slack_channel_id Optional[str]

(deprecated) The ID of the default Slack channel to use for communication.
Source code in src/zenml/stack/stack_component.py 
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def __init__(
    self, warn_about_plain_text_secrets: bool = False, **kwargs: Any
) -> None:
    """Ensures that secret references don't clash with pydantic validation.

    StackComponents allow the specification of all their string attributes
    using secret references of the form `{{secret_name.key}}`. This however
    is only possible when the stack component does not perform any explicit
    validation of this attribute using pydantic validators. If this were
    the case, the validation would run on the secret reference and would
    fail or in the worst case, modify the secret reference and lead to
    unexpected behavior. This method ensures that no attributes that require
    custom pydantic validation are set as secret references.

    Args:
        warn_about_plain_text_secrets: If true, then warns about using
            plain-text secrets.
        **kwargs: Arguments to initialize this stack component.

    Raises:
        ValueError: If an attribute that requires custom pydantic validation
            is passed as a secret reference, or if the `name` attribute
            was passed as a secret reference.
    """
    for key, value in kwargs.items():
        try:
            field = self.__class__.model_fields[key]
        except KeyError:
            # Value for a private attribute or non-existing field, this
            # will fail during the upcoming pydantic validation
            continue

        if value is None:
            continue

        if not secret_utils.is_secret_reference(value):
            if (
                secret_utils.is_secret_field(field)
                and warn_about_plain_text_secrets
            ):
                logger.warning(
                    "You specified a plain-text value for the sensitive "
                    f"attribute `{key}` for a `{self.__class__.__name__}` "
                    "stack component. This is currently only a warning, "
                    "but future versions of ZenML will require you to pass "
                    "in sensitive information as secrets. Check out the "
                    "documentation on how to configure your stack "
                    "components with secrets here: "
                    "https://docs.zenml.io/getting-started/deploying-zenml/secret-management"
                )
            continue

        if pydantic_utils.has_validators(
            pydantic_class=self.__class__, field_name=key
        ):
            raise ValueError(
                f"Passing the stack component attribute `{key}` as a "
                "secret reference is not allowed as additional validation "
                "is required for this attribute."
            )

    super().__init__(**kwargs)
Attributes
is_valid: bool property

Check if the stack component is valid.

Returns:

Type Description
bool

True if the stack component is valid, False otherwise.
SlackAlerterFlavor

Bases: BaseAlerterFlavor

Slack alerter flavor.

Attributes
config_class: Type[SlackAlerterConfig] property

Returns SlackAlerterConfig config class.

Returns:

Type Description
Type[SlackAlerterConfig]

The config class.
docs_url: Optional[str] property

A URL to point at docs explaining this flavor.

Returns:

Type Description
Optional[str]

A flavor docs url.
implementation_class: Type[SlackAlerter] property

Implementation class for this flavor.

Returns:

Type Description
Type[SlackAlerter]

The implementation class.
logo_url: str property

A URL to represent the flavor in the dashboard.

Returns:

Type Description
str

The flavor logo.
name: str property

Name of the flavor.

Returns:

Type Description
str

The name of the flavor.
sdk_docs_url: Optional[str] property

A URL to point at SDK docs explaining this flavor.

Returns:

Type Description
Optional[str]

A flavor SDK docs url.
SlackAlerterSettings(warn_about_plain_text_secrets: bool = False, **kwargs: Any)

Bases: BaseSettings

Settings for the Slack alerter.

Attributes:

Name Type Description
slack_channel_id Optional[str]

The ID of the Slack channel to use for communication.
timeout int

The amount of seconds to wait for the ask method.
Source code in src/zenml/config/secret_reference_mixin.py 
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def __init__(
    self, warn_about_plain_text_secrets: bool = False, **kwargs: Any
) -> None:
    """Ensures that secret references are only passed for valid fields.

    This method ensures that secret references are not passed for fields
    that explicitly prevent them or require pydantic validation.

    Args:
        warn_about_plain_text_secrets: If true, then warns about using plain-text secrets.
        **kwargs: Arguments to initialize this object.

    Raises:
        ValueError: If an attribute that requires custom pydantic validation
            or an attribute which explicitly disallows secret references
            is passed as a secret reference.
    """
    for key, value in kwargs.items():
        try:
            field = self.__class__.model_fields[key]
        except KeyError:
            # Value for a private attribute or non-existing field, this
            # will fail during the upcoming pydantic validation
            continue

        if value is None:
            continue

        if not secret_utils.is_secret_reference(value):
            if (
                secret_utils.is_secret_field(field)
                and warn_about_plain_text_secrets
            ):
                logger.warning(
                    "You specified a plain-text value for the sensitive "
                    f"attribute `{key}`. This is currently only a warning, "
                    "but future versions of ZenML will require you to pass "
                    "in sensitive information as secrets. Check out the "
                    "documentation on how to configure values with secrets "
                    "here: https://docs.zenml.io/getting-started/deploying-zenml/secret-management"
                )
            continue

        if secret_utils.is_clear_text_field(field):
            raise ValueError(
                f"Passing the `{key}` attribute as a secret reference is "
                "not allowed."
            )

        requires_validation = has_validators(
            pydantic_class=self.__class__, field_name=key
        )
        if requires_validation:
            raise ValueError(
                f"Passing the attribute `{key}` as a secret reference is "
                "not allowed as additional validation is required for "
                "this attribute."
            )

    super().__init__(**kwargs)
Functions

steps

Built-in steps for the Slack integration.

Modules
slack_alerter_ask_step

Step that allows you to send messages to Slack and wait for a response.

Classes Functions
slack_alerter_ask_step(message: str, params: Optional[SlackAlerterParameters] = None) -> bool

Posts a message to the Slack alerter component and waits for approval.

This can be useful, e.g. to easily get a human in the loop before deploying models.

Parameters:

Name Type Description Default
message str

Initial message to be posted.

 required
params Optional[SlackAlerterParameters]

Parameters for the Slack alerter.

 None

Returns:

Type Description
bool

True if a user approved the operation, else False.

Raises:

Type Description
RuntimeError

If currently active alerter is not a SlackAlerter.
Source code in src/zenml/integrations/slack/steps/slack_alerter_ask_step.py 
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@step
def slack_alerter_ask_step(
    message: str,
    params: Optional[SlackAlerterParameters] = None,
) -> bool:
    """Posts a message to the Slack alerter component and waits for approval.

    This can be useful, e.g. to easily get a human in the loop before
    deploying models.

    Args:
        message: Initial message to be posted.
        params: Parameters for the Slack alerter.

    Returns:
        True if a user approved the operation, else False.

    Raises:
        RuntimeError: If currently active alerter is not a `SlackAlerter`.
    """
    context = get_step_context()
    client = Client()
    active_stack = client.active_stack
    alerter = active_stack.alerter
    if not isinstance(alerter, SlackAlerter):
        # TODO: potential duplicate code for other components
        # -> generalize to `check_component_flavor()` utility function?
        raise RuntimeError(
            "Step `slack_alerter_ask_step` requires an alerter component of "
            "flavor `slack`, but the currently active alerter is of type "
            f"{type(alerter)}, which is not a subclass of `SlackAlerter`."
        )
    if (
        params
        and hasattr(params, "include_format_blocks")
        and params.include_format_blocks
    ):
        pipeline_name = context.pipeline.name
        step_name = context.step_run.name
        payload = SlackAlerterPayload(
            pipeline_name=pipeline_name,
            step_name=step_name,
            stack_name=active_stack.name,
        )
        params.payload = payload
    return alerter.ask(message, params)
slack_alerter_post_step

Step that allows you to post messages to Slack.

Classes Functions
slack_alerter_post_step(message: Optional[str] = None, params: Optional[SlackAlerterParameters] = None) -> bool

Post a message to the Slack alerter component of the active stack.

Parameters:

Name Type Description Default
message Optional[str]

Message to be posted.

 None
params Optional[SlackAlerterParameters]

Parameters for the Slack alerter.

 None

Returns:

Type Description
bool

True if operation succeeded, else False.

Raises:

Type Description
RuntimeError

If currently active alerter is not a SlackAlerter.
Source code in src/zenml/integrations/slack/steps/slack_alerter_post_step.py 
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@step
def slack_alerter_post_step(
    message: Optional[str] = None,
    params: Optional[SlackAlerterParameters] = None,
) -> bool:
    """Post a message to the Slack alerter component of the active stack.

    Args:
        message: Message to be posted.
        params: Parameters for the Slack alerter.

    Returns:
        True if operation succeeded, else False.

    Raises:
        RuntimeError: If currently active alerter is not a `SlackAlerter`.
    """
    context = get_step_context()
    client = Client()
    active_stack = client.active_stack
    alerter = active_stack.alerter
    if not isinstance(alerter, SlackAlerter):
        raise RuntimeError(
            "Step `slack_alerter_post_step` requires an alerter component of "
            "flavor `slack`, but the currently active alerter is of type "
            f"{type(alerter)}, which is not a subclass of `SlackAlerter`."
        )
    if (
        params
        and hasattr(params, "include_format_blocks")
        and params.include_format_blocks
    ):
        pipeline_name = context.pipeline.name
        step_name = context.step_run.name
        payload = SlackAlerterPayload(
            pipeline_name=pipeline_name,
            step_name=step_name,
            stack_name=active_stack.name,
        )
        params.payload = payload
    return alerter.post(message, params)