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decentriq_platform.media

Sub-modules​

  • decentriq_platform.media.audience_statistics_result
  • decentriq_platform.media.audiences
  • decentriq_platform.media.compute_job
  • decentriq_platform.media.lookalike_audience_builder
  • decentriq_platform.media.media
  • decentriq_platform.media.participant
  • decentriq_platform.media.remarketing_audience_builder
  • decentriq_platform.media.rule_based_builder
  • decentriq_platform.media.validation_reports

Classes​

AudienceCombinator​

AudienceCombinator(
    *,
    operator: decentriq_platform.media.rule_based_builder.CombineOperator,
    source_audience: Union[decentriq_platform.media.api.SeedAudience, decentriq_platform.media.api.CustomAudience],
    filters: Optional[decentriq_platform.media.rule_based_builder.AudienceFilters] = None,
)

Initialize an AudienceCombinator instance.

Parameters:

  • operator: The operator used to combine audiences
  • source_audience: The source audience to combine
  • filters: Optional filters to apply to the source audience

as_dict​

def as_dict(
    self,
) ‑> Dict[str, Any]

Convert the audience combinator to a dictionary.

Returns:

  • The dictionary representation of the audience combinator

AudienceCombinatorBuilder​

AudienceCombinatorBuilder(
    *,
    operator: decentriq_platform.media.rule_based_builder.CombineOperator,
    source_audience: Union[decentriq_platform.media.api.SeedAudience, decentriq_platform.media.api.CustomAudience],
)

Builder for constructing an AudienceCombinator.

Initialise the audience combinator builder.

Parameters:

  • operator: The operator used to combine audiences.
  • source_audience: The source audience to combine with.

build​

def build(
    self,
) ‑> decentriq_platform.media.rule_based_builder.AudienceCombinator

Build the audience combinator.

Returns:

  • The audience combinator

with_filters​

def with_filters(
    self,
    filters: decentriq_platform.media.rule_based_builder.AudienceFilters,
) ‑> typing_extensions.Self

Set the filters to be applied to the source audience.

Parameters:

  • filters: Filters to be applied to the source audience.

Returns:

  • The updated audience combinator builder

AudienceFilters​

AudienceFilters(
    *,
    filters: List[decentriq_platform.media.rule_based_builder.Filter],
    operator: decentriq_platform.media.rule_based_builder.MatchOperator,
)

Class representing the filters for an audience.

Initialize an AudienceFilters instance.

Parameters:

  • filters: The list of filters to apply
  • operator: The operator to use for the filters

as_dict​

def as_dict(
    self,
) ‑> Dict[str, Any]

Convert the filters to a dictionary.

Returns:

  • The dictionary representation of the filters

Audiences​

Audiences(
    audiences: List[Union[decentriq_platform.media.api.SeedAudience, decentriq_platform.media.api.CustomAudience]],
)

Class for managing and accessing different types of audiences.

Initialize an Audiences instance.

Parameters:

  • audiences: List of audience objects to manage

get_custom_audience​

def get_custom_audience(
    self,
    name: str,
) ‑> decentriq_platform.media.api.CustomAudience

Get a custom audience by name.

Parameters:

  • name: Name of the custom audience to retrieve

Returns:

  • Custom audience with the given name

Raises:

  • Exception: If no custom audience is found or multiple custom audiences found with the given name

get_seed_audience​

def get_seed_audience(
    self,
    audience_type: str,
) ‑> decentriq_platform.media.api.SeedAudience

Get a seed audience by type.

Parameters:

  • audience_type: Type of the seed audience to retrieve

Returns:

  • Seed audience with the given type

Raises:

  • Exception: If no seed audience is found with the given type or multiple seed audiences found with the given type

is_lookalike_audience​

def is_lookalike_audience(
    audience: Union[decentriq_platform.media.api.SeedAudience, decentriq_platform.media.api.CustomAudience],
) ‑> bool

Check if an audience is a lookalike audience.

Parameters:

  • audience: The audience to check

Returns:

  • True if the audience is a lookalike audience, False otherwise

Raises:

  • Exception: If the audience type is not supported

list​

def list(
    self,
) ‑> List[Union[decentriq_platform.media.api.SeedAudience, decentriq_platform.media.api.CustomAudience]]

List all audiences.

Returns:

  • List of all audiences

CollaborationType​

CollaborationType(
    value,
    names=None,
    *,
    module=None,
    qualname=None,
    type=None,
    start=1,
)

Represents the features supported by a DCR.

Members:

- INSIGHTS
- LOOKALIKE
- REMARKETING
- RULE_BASED

Ancestors (in MRO)

  • builtins.str
  • enum.Enum

CombineOperator​

CombineOperator(
    value,
    names=None,
    *,
    module=None,
    qualname=None,
    type=None,
    start=1,
)

Enum representing the operations for combining audiences.

Members:

- INTERSECT: Users in both audiences.
- UNION: All users.
- DIFF: Users in first audience only.

Ancestors (in MRO)

  • builtins.str
  • enum.Enum

CreateLookalikeAudienceAction​

CreateLookalikeAudienceAction(
    dcr_id: str,
    client: decentriq_platform.client.Client,
    definition: decentriq_platform.media.lookalike_audience_builder.LookalikeAudienceDefinition,
)

Initialize a CreateLookalikeAudienceAction instance.

Parameters:

  • dcr_id: The identifier for the DCR
  • client: The client instance for API communication
  • definition: The definition of the lookalike audience to create

Ancestors (in MRO)

  • decentriq_platform.media.action.Action

create​

def create(
    self,
) ‑> Union[Dict[str, Union[Dict[str, JSONType], List[JSONType], str, int, float, bool, ForwardRef(None)]], List[Union[Dict[str, JSONType], List[JSONType], str, int, float, bool, ForwardRef(None)]], str, int, float, bool, ForwardRef(None)]

Create the lookalike audience.

Returns:

  • The response from creating the lookalike audience

Filter​

Filter(
    *,
    attribute: str,
    values: List[str],
    operator: decentriq_platform.media.rule_based_builder.FilterOperator,
)

Class representing a filter.

Initialize a filter.

Parameters:

  • attribute: The attribute to filter on
  • values: The values to filter on
  • operator: The operator to use for the filter

as_dict​

def as_dict(
    self,
) ‑> Dict[str, Any]

Convert the filter to a dictionary.

Returns:

  • The dictionary representation of the filter

FilterOperator​

FilterOperator(
    value,
    names=None,
    *,
    module=None,
    qualname=None,
    type=None,
    start=1,
)

Enum representing the filter operations.

Members:

- CONTAINS_ANY: At least one of the values must be present.
- CONTAINS_NONE: None of the values can be present.
- CONTAINS_ALL: All of the values must be present.
- EMPTY: The attribute must be empty.
- NOT_EMPTY: The attribute must not be empty.

Ancestors (in MRO)

  • builtins.str
  • enum.Enum

LalAudienceStatistics​

LalAudienceStatistics(
    auc: float,
    fpr: List[float],
    tpr: List[float],
)

Class representing the statistics of a given lookalike audience.

Initialize an instance of LalAudienceStatistics.

Parameters:

  • auc: The area under the ROC curve
  • fpr: The list of false positive rates (in order of decreasing discrimination threshold)
  • tpr: The list of true positive rates (in order of decreasing discrimination threshold)

Static methods

from_dict​

def from_dict(
    d: Dict[str, Any],
) ‑> typing_extensions.Self

Create an instance from a dictionary.

Parameters:

  • d: Dictionary containing the statistics data

Returns:

  • New LalAudienceStatistics instance

model_dump​

def model_dump(
    self,
) ‑> Dict[str, Any]

Convert the instance to a dictionary following pydantic model_dump convention.

Returns:

  • Dictionary representation of the statistics

model_dump_json​

def model_dump_json(
    self,
    indent: int = None,
) ‑> str

Convert the instance to a JSON string following pydantic model_dump_json convention.

Parameters:

  • indent: Number of spaces for indentation in the JSON output

Returns:

  • JSON string representation of the statistics

LookalikeAudienceBuilder​

LookalikeAudienceBuilder(
    *,
    name: str,
    reach: int,
    source_audience: AudienceType,
)

Builder for constructing lookalike audience definitions.

Initialise the lookalike audience builder.

Parameters:

  • name: Name of the lookalike audience.
  • reach: The desired reach of the lookalike audience expressed as a percentage between 1-30.
  • source_audience_name: Name of the source audience that the lookalike audience will be built from.

build​

def build(
    self,
) ‑> decentriq_platform.media.lookalike_audience_builder.LookalikeAudienceDefinition

Build the lookalike audience definition.

Returns:

  • The lookalike audience definition

with_exclude_seed_audience​

def with_exclude_seed_audience(
    self,
) ‑> typing_extensions.Self

Exclude the seed audience from the lookalike audience.

Returns:

  • The updated lookalike audience builder

with_share_with_participants​

def with_share_with_participants(
    self,
    participants: List[Participant],
) ‑> typing_extensions.Self

Make the lookalike audience available to the given participants.

Parameters:

  • participants: The participants to share the lookalike audience with

Returns:

  • The updated lookalike audience builder

MatchOperator​

MatchOperator(
    value,
    names=None,
    *,
    module=None,
    qualname=None,
    type=None,
    start=1,
)

Enum representing the match operations.

Members:

- MATCH_ALL: All filter criteria must be satisfied.
- MATCH_ANY: Any filter criteria may be satisfied.

Ancestors (in MRO)

  • builtins.str
  • enum.Enum

MatchingId​

MatchingId(
    value,
    names=None,
    *,
    module=None,
    qualname=None,
    type=None,
    start=1,
)

The type of Matching ID to use.

Members:

- STRING
- EMAIL
- HASHED_EMAIL
- PHONE_NUMBER
- HASHED_PHONE_NUMBER

Ancestors (in MRO)

  • builtins.str
  • enum.Enum

MediaDcr​

MediaDcr(
    client: Client,
    *,
    name: Optional[str] = None,
    participants: Optional[List[Participant]] = None,
    collaboration_types: Optional[List[CollaborationType]] = None,
    matching_ids: Optional[List[MatchingId]] = None,
    hide_absolute_values: bool = False,
)

Class for managing Media Data Clean Room (DCR) operations.

Initialize a MediaDCR instance.

Can be used either to create a new DCR (when dcr_id is None) or load an existing one.

Parameters:

  • client: The client instance for API communication
  • name: Name for new DCR
  • participants: Participants for new DCR
  • collaboration_types: Collaboration types for new DCR
  • matching_ids: Matching IDs for new DCR
  • hide_absolute_values: Whether to hide absolute values from outputs
  • _existing_dcr_id: Optional ID of existing DCR to load (for internal use only)

Static methods

from_existing​

def from_existing(
    dcr_id: str,
    client: Client,
) ‑> Self

Construct a MediaDCR from an existing DCR with the given ID.

Parameters:

  • dcr_id: The id of the DCR
  • client: The client from which a session is created

Returns:

  • The MediaDCR instance

are_seed_audiences_provisioned​

def are_seed_audiences_provisioned(
    self,
) ‑> bool

Check if the seed audiences are provisioned.

can_other_participants_export_audience​

def can_other_participants_export_audience(
    self,
) ‑> bool

Check if other participants can export audiences.

create_lookalike_audience​

def create_lookalike_audience(
    self,
    definition: LookalikeAudienceDefinition,
) ‑> decentriq_platform.media.api.CustomAudience

Create a lookalike audience based on the provided definition.

Parameters:

  • definition: Definition of the lookalike audience to create

Returns:

  • The created lookalike audience

create_remarketing_audience​

def create_remarketing_audience(
    self,
    definition: RemarketingAudienceDefinition,
) ‑> decentriq_platform.media.api.CustomAudience

Create a remarketing audience based on the provided definition.

Parameters:

  • definition: Definition of the remarketing audience to create

Returns:

  • The created remarketing audience

create_rule_based_audience​

def create_rule_based_audience(
    self,
    definition: RuleBasedAudienceDefinition,
) ‑> decentriq_platform.media.api.CustomAudience

Create a rule-based audience based on the provided definition.

Parameters:

  • definition: Definition of the rule-based audience to create

Returns:

  • The created rule-based audience

delete_audiences​

def delete_audiences(
    self,
    audiences: List[CustomAudience],
    *,
    delete_dependent_audiences: bool = False,
) ‑> None

Delete audiences.

Parameters:

  • audiences: The audiences to delete
  • delete_dependent_audiences: If true, the supplied audiences and all dependent audiences will be deleted. If false, the supplied audiences will only be deleted if they have no dependents.

deprovision_base_audience​

def deprovision_base_audience(
    self,
) ‑> None

Deprovision a base audience from the DCR.

Removes all datasets associated with the base audience from the DCR by deprovisioning each dataset type.

deprovision_seed_audiences​

def deprovision_seed_audiences(
    self,
) ‑> None

Deprovision seed audiences dataset from the DCR.

get_audience_size​

def get_audience_size(
    self,
    audience: Union[SeedAudience, CustomAudience],
) ‑> decentriq_platform.media.compute_job.MediaEstimateAudienceSizeJob

Get the size of an audience.

Parameters:

  • audience: The audience to estimate the size of

Returns:

  • The job to get the size of the audience

get_audience_user_list​

def get_audience_user_list(
    self,
    audience: Union[SeedAudience, CustomAudience],
) ‑> decentriq_platform.media.compute_job.MediaAudienceUserListJob

Get the user list for an audience.

Parameters:

  • audience: The audience to get the user list for

Returns:

  • The job to get the user list for the audience

get_audiences​

def get_audiences(
    self,
) ‑> decentriq_platform.media.compute_job.MediaGetAudiencesJob

Get audiences for a specific user.

Returns:

  • The job to get the audiences for the specified user

get_audit_log​

def get_audit_log(
    self,
) ‑> List[decentriq_platform.archv2.client.DataRoomAuditLog]

Get the audit log for the data room.

Returns:

  • Audit log

get_base_audience_validation_reports​

def get_base_audience_validation_reports(
    self,
) ‑> decentriq_platform.media.compute_job.MediaBaseAudienceValidationReportsJob

Get the validation reports for the DCR.

Returns:

  • The job to compute the validation reports

get_configuration​

def get_configuration(
    self,
) ‑> decentriq_platform.media.media.DcrConfiguration

Get the configuration of the DCR.

Returns:

  • The configuration of the DCR

get_data_attributes​

def get_data_attributes(
    self,
) ‑> decentriq_platform.media.compute_job.MediaDataAttributesJob

Get data attributes.

Returns:

  • The job to get the data attributes

get_insights​

def get_insights(
    self,
) ‑> decentriq_platform.media.compute_job.MediaInsightsJob

Compute insights from the data room.

Returns:

  • The job to compute insights

get_lookalike_audience_statistics​

def get_lookalike_audience_statistics(
    self,
    audience: AudienceType,
) ‑> decentriq_platform.media.compute_job.MediaLookalikeAudienceStatisticsJob

Get statistics for lookalike audiences.

Returns:

  • The job to get the lookalike audience statistics

get_overlap_statistics​

def get_overlap_statistics(
    self,
) ‑> decentriq_platform.media.compute_job.MediaOverlapStatisticsJob

Compute overlap statistics.

Returns:

  • The job to compute the overlap statistics

get_owner_email​

def get_owner_email(
    self,
) ‑> str

Get the email of the owner of the DCR.

get_participants​

def get_participants(
    self,
) ‑> List[decentriq_platform.media.participant.Participant]

Get the participants of the DCR.

Returns:

  • The list of participants in the DCR

get_seed_audiences_validation_report​

def get_seed_audiences_validation_report(
    self,
) ‑> decentriq_platform.media.compute_job.MediaAudiencesValidationReportJob

Get the validation report for seed audiences data.

Returns:

  • The job to compute the seed audiences validation report

is_base_audience_provisioned​

def is_base_audience_provisioned(
    self,
) ‑> bool

Check if the base audience is provisioned.

provision_base_audience​

def provision_base_audience(
    self,
    data_lab_id: str,
) ‑> None

Provision a base audience to the DCR.

Parameters:

  • data_lab_id: The identifier of the DataLab from which to provision the base audience

Raises:

  • Exception: If the DataLab is not validated or if provisioning fails

provision_seed_audiences​

def provision_seed_audiences(
    self,
    manifest_hash: str,
) ‑> None

Provision seed audiences dataset to the DCR.

Parameters:

  • manifest_hash: Hash of the seed audience dataset to provision

share_audiences​

def share_audiences(
    self,
    audiences: List[CustomAudience],
    participants: List[Participant],
)

Share the audiences with the participant group.

Parameters:

  • audiences: The audiences to share
  • participants: The participants to share the audiences with

Participant​

Participant(
    emails: List[str],
    permissions: List[decentriq_dcr_compiler._schemas.create_media_dcr.Permission],
    role: str,
    id: Optional[str] = None,
    organization_id: Optional[str] = None,
)

A participant in a Data Clean Room.

Initialize a participant.

Parameters:

  • emails: The emails of the participant
  • permissions: The permissions of the participant
  • role: The role of the participant
  • id: The id of the participant
  • organization_id: The organization id of the participant

as_dict​

def as_dict(
    self,
) ‑> Dict[str, Any]

Return the participant as a dictionary.

Returns:

  • The participant as a dictionary

can_export_audience​

def can_export_audience(
    self,
) ‑> bool

Check if the participant has the export audience permission.

Returns:

  • True if the participant has the export audience permission, False otherwise

Permission​

Permission(
    value,
    names=None,
    *,
    module=None,
    qualname=None,
    type=None,
    start=1,
)

An enumeration.

Ancestors (in MRO)

  • enum.Enum

RemarketingAudienceBuilder​

RemarketingAudienceBuilder(
    *,
    name: str,
    source_audience_type: str,
)

Builder for constructing remarketing audience definitions.

Initialise the remarketing audience builder.

Parameters:

  • name: Name of the remarketing audience.
  • source_audience_type: The audience type of the seed audience that the remarketing audience will be built from.

build​

def build(
    self,
) ‑> decentriq_platform.media.remarketing_audience_builder.RemarketingAudienceDefinition

Build the remarketing audience definition.

Returns:

  • The remarketing audience definition

with_share_with_participants​

def with_share_with_participants(
    self,
    participants: List[Participant],
) ‑> typing_extensions.Self

Make the remarketing audience available to the given participants.

Parameters:

  • participants: The participants to share the remarketing audience with

Returns:

  • The updated remarketing audience builder

RemarketingAudienceDefinition​

RemarketingAudienceDefinition(
    *,
    name: str,
    source_audience_type: str,
    shared_with: List[Participant],
)

Class representing the definition of a remarketing audience.

Initialize a remarketing audience definition.

Parameters:

  • name: Name of the remarketing audience
  • source_audience_type: The audience type of the seed audience to build from
  • shared_with: List of participant groups to share with

RuleBasedAudienceBuilder​

RuleBasedAudienceBuilder(
    *,
    name: str,
    source_audience: Union[decentriq_platform.media.api.SeedAudience, decentriq_platform.media.api.CustomAudience],
)

Builder for constructing rule-based audience definitions.

Initialise the rule-based audience builder.

Parameters:

  • name: Name of the rule-based audience.
  • source_audience: The source audience that the rule-based audience will be built from.

build​

def build(
    self,
) ‑> decentriq_platform.media.rule_based_builder.RuleBasedAudienceDefinition

Build the rule-based audience definition.

Returns:

  • The rule-based audience definition

with_combinator​

def with_combinator(
    self,
    combinators: List[decentriq_platform.media.rule_based_builder.AudienceCombinator],
) ‑> typing_extensions.Self

Set the combinators to be applied to the audiences. This defines how multiple audiences can be combined.

Parameters:

  • combinators: The list of combinators used to combine audiences.

Returns:

  • The updated rule-based audience builder

with_filters​

def with_filters(
    self,
    filters: decentriq_platform.media.rule_based_builder.AudienceFilters,
) ‑> typing_extensions.Self

Set the filters to be applied to the source audience.

Parameters:

  • filters: Filters to be applied to the source audience.

Returns:

  • The updated rule-based audience builder

with_share_with_participants​

def with_share_with_participants(
    self,
    participants: List[decentriq_platform.media.participant.Participant],
) ‑> typing_extensions.Self

Make the rule-based audience available to the given participants.

Parameters:

  • participants: The participants to share the rule-based audience with

Returns:

  • The updated rule-based audience builder

RuleBasedAudienceDefinition​

RuleBasedAudienceDefinition(
    *,
    name: str,
    source_audience: Union[decentriq_platform.media.api.SeedAudience, decentriq_platform.media.api.CustomAudience],
    filters: Optional[decentriq_platform.media.rule_based_builder.AudienceFilters] = None,
    combinators: Optional[List[decentriq_platform.media.rule_based_builder.AudienceCombinator]] = None,
    shared_with: Optional[List[decentriq_platform.media.participant.Participant]] = None,
)

Class representing the definition of a rule-based audience.

Initialize a rule-based audience definition.

Parameters:

  • name: Name of the rule-based audience
  • source_audience: The source audience to build from
  • filters: Optional filters to apply to the audience
  • combinators: Optional combinators for combining multiple audiences
  • shared_with: Optional list of participant groups to share with

ValidationReports​

ValidationReports(
    matching: decentriq_platform.media.api.ValidationReport,
    segments: decentriq_platform.media.api.ValidationReport,
    demographics: decentriq_platform.media.api.ValidationReport,
)

A class to represent the validation reports for a DCR.

Initialize a ValidationReports instance.

Parameters:

  • matching: The matching validation report
  • segments: The segments validation report
  • demographics: The demographics validation report

model_dump_json​

def model_dump_json(
    self,
)

Return a JSON string representation of the validation reports.