kedro_datasets.email.EmailMessageDataset

class kedro_datasets.email.EmailMessageDataset(*, filepath, load_args=None, save_args=None, version=None, credentials=None, fs_args=None, metadata=None)[source]

EmailMessageDataset loads/saves an email message from/to a file using an underlying filesystem (e.g.: local, S3, GCS). It uses the email package in the standard library to manage email messages.

Note that EmailMessageDataset doesn’t handle sending email messages.

Example:

from email.message import EmailMessage

from kedro_datasets.email import EmailMessageDataset

string_to_write = "what would you do if you were invisable for one day????"

# Create a text/plain message
msg = EmailMessage()
msg.set_content(string_to_write)
msg["Subject"] = "invisibility"
msg["From"] = '"sin studly17"'
msg["To"] = '"strong bad"'

dataset = EmailMessageDataset(filepath=tmp_path / "test")
dataset.save(msg)
reloaded = dataset.load()
assert msg.__dict__ == reloaded.__dict__

Attributes

DEFAULT_LOAD_ARGS

DEFAULT_SAVE_ARGS

Methods

exists()

Checks whether a data set's output already exists by calling the provided _exists() method.

from_config(name, config[, load_version, ...])

Create a data set instance using the configuration provided.

load()

Loads data by delegation to the provided load method.

release()

Release any cached data.

resolve_load_version()

Compute the version the dataset should be loaded with.

resolve_save_version()

Compute the version the dataset should be saved with.

save(data)

Saves data by delegation to the provided save method.

DEFAULT_LOAD_ARGS: dict[str, Any] = {}
DEFAULT_SAVE_ARGS: dict[str, Any] = {}
__init__(*, filepath, load_args=None, save_args=None, version=None, credentials=None, fs_args=None, metadata=None)[source]

Creates a new instance of EmailMessageDataset pointing to a concrete text file on a specific filesystem.

Parameters:
exists()

Checks whether a data set’s output already exists by calling the provided _exists() method.

Return type:

bool

Returns:

Flag indicating whether the output already exists.

Raises:

DatasetError – when underlying exists method raises error.

classmethod from_config(name, config, load_version=None, save_version=None)

Create a data set instance using the configuration provided.

Parameters:
  • name (str) – Data set name.

  • config (dict[str, Any]) – Data set config dictionary.

  • load_version (str | None) – Version string to be used for load operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.

  • save_version (str | None) – Version string to be used for save operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.

Return type:

AbstractDataset

Returns:

An instance of an AbstractDataset subclass.

Raises:

DatasetError – When the function fails to create the data set from its config.

load()

Loads data by delegation to the provided load method.

Return type:

TypeVar(_DO)

Returns:

Data returned by the provided load method.

Raises:

DatasetError – When underlying load method raises error.

release()

Release any cached data.

Raises:

DatasetError – when underlying release method raises error.

Return type:

None

resolve_load_version()

Compute the version the dataset should be loaded with.

Return type:

str | None

resolve_save_version()

Compute the version the dataset should be saved with.

Return type:

str | None

save(data)

Saves data by delegation to the provided save method.

Parameters:

data (TypeVar(_DI)) – the value to be saved by provided save method.

Raises:
  • DatasetError – when underlying save method raises error.

  • FileNotFoundError – when save method got file instead of dir, on Windows.

  • NotADirectoryError – when save method got file instead of dir, on Unix.

Return type:

None