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decentriq_platform.data_lab

Classes​

DataLab​

DataLab(
    client: decentriq_platform.client.Client,
    cfg: decentriq_platform.data_lab.data_lab.DataLabConfig,
    existing_data_lab: Optional[decentriq_platform.data_lab.data_lab.ExistingDataLab] = None,
)

Static methods

is_validation_passed​

def is_validation_passed(
    validation_report: Dict[str, str],
) ‑> bool

deprovision_dataset​

def deprovision_dataset(
    self,
    dataset_type: decentriq_platform.types.DataLabDatasetType,
)

get_statistics_report​

def get_statistics_report(
    self,
    timeout: Optional[int] = None,
)

Retrieve the statistics report. This function will block until the report is ready unless a timeout is specified.

Parameters:

  • timeout: Amount of time to wait (in seconds) for the statistics report to become available.

get_validation_report​

def get_validation_report(
    self,
    timeout: Optional[int] = None,
)

Retrieve the validation report. This function will block until the report is ready unless a timeout is specified.

Parameters:

  • timeout: Amount of time to wait (in seconds) for the validation report to become available.

provision_dataset​

def provision_dataset(
    self,
    manifest_hash: str,
    key: decentriq_platform.storage.Key,
    dataset_type: decentriq_platform.types.DataLabDatasetType,
)

provision_local_datasets​

def provision_local_datasets(
    self,
    key: decentriq_platform.storage.Key,
    matching_data_path: str,
    segments_data_path: Optional[str] = None,
    demographics_data_path: Optional[str] = None,
    embeddings_data_path: Optional[str] = None,
    *,
    secret_store_options: Optional[decentriq_platform.client.SecretStoreOptions] = None,
)

Upload local datasets and provision to the DataLab.

Parameters

  • key: The key used to encrypt the dataset.
  • match: The file path to the "match" dataset.
  • segments: The file path to the "segments" dataset.
  • demographics: The file path to the "demographics" dataset.
  • embeddings: The file path to the "embeddings" dataset.

provision_to_lookalike_media_data_room​

def provision_to_lookalike_media_data_room(
    self,
    data_room_id: str,
)

Provision the DataLab to the DCR with the given ID.

Parameters:

  • data_room_id: ID of the DCR to provision the DataLab to.

provision_to_media_insights_data_room​

def provision_to_media_insights_data_room(
    self,
    data_room_id: str,
)

Provision the DataLab to the DCR with the given ID.

Parameters:

  • data_room_id: ID of the DCR to provision the DataLab to.

run​

def run(
    self,
    /,
    *,
    dry_run: Optional[decentriq_platform.types.DryRunOptions] = None,
    parameters: Optional[Mapping[str, str]] = None,
)

Running the DataLab results in the validation jobs and statistics job being kicked off. This function does not block waiting for the results. Instead the user should call the get_validation_report or get_statistics_report function.

DataLabBuilder​

DataLabBuilder(
    client: decentriq_platform.client.Client,
)

A helper class to build a Data Lab.

build​

def build(
    self,
) ‑> decentriq_platform.data_lab.data_lab.DataLab

Build the DataLab.

from_existing​

def from_existing(
    self,
    data_lab_id: str,
)

Construct a new DataLab from an existing DataLab with the given ID.

Parameters:

  • data_lab_id: The ID of the existing DataLab.

with_demographics​

def with_demographics(
    self,
)

Enable demographics in the DataLab.

with_embeddings​

def with_embeddings(
    self,
    num_embeddings: int,
)

Enable embeddings in the DataLab.

Parameters:

  • num_embeddings: The number of embeddings the DataLab should use.

with_matching_id_format​

def with_matching_id_format(
    self,
    matching_id: decentriq_platform.types.MatchingId,
)

Set the matching ID format.

Parameters:

  • matching_id: The type of matching ID to use.

with_name​

def with_name(
    self,
    name: str,
)

Set the name of the DataLab.

Parameters:

  • name: Name to be used for the DataLab.

with_segments​

def with_segments(
    self,
)

DataLabDatasetType​

DataLabDatasetType(
    *args,
    **kwds,
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

  • attribute access::

Color.RED <Color.RED: 1>

  • value lookup:

Color(1) <Color.RED: 1>

  • name lookup:

Color['RED'] <Color.RED: 1>

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [<Color.RED: 1>, <Color.BLUE: 2>, <Color.GREEN: 3>]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

  • enum.Enum

MatchingId​

MatchingId(
    *args,
    **kwds,
)

The type of Matching ID to use.

Ancestors (in MRO)

  • builtins.str
  • enum.Enum

MatchingIdFormat​

MatchingIdFormat(
    *args,
    **kwds,
)

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.

Ancestors (in MRO)

  • builtins.str
  • enum.Enum