As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

Types for Google Cloud Dataqna v1alpha API¶

class google.cloud.dataqna_v1alpha.types.AnnotatedString(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Describes string annotation from both semantic and formatting perspectives. Example:

User Query:

top countries by population in Africa

0 4 14 17 28 31 37

Table Data:

“country” - dimension
“population” - metric
“Africa” - value in the “continent” column

text_formatted = "top countries by population in Africa"

html_formatted = "top countries by population in Africa"

markups = [
  {DIMENSION, 4, 12}, // 'countries'
  {METRIC, 17, 26}, // 'population'
  {FILTER, 31, 36}  // 'Africa'
]

Note that html formattings for ‘DIMENSION’ and ‘METRIC’ are the same, while semantic markups are different.

text_formatted¶

Text version of the string.

Type: str

html_formatted¶

HTML version of the string annotation.

Type: str

markups¶

Semantic version of the string annotation.

Type: MutableSequence[google.cloud.dataqna_v1alpha.types.AnnotatedString.SemanticMarkup]

class SemanticMarkup(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Semantic markup denotes a substring (by index and length) with markup information.

type_¶

The semantic type of the markup substring.

Type: google.cloud.dataqna_v1alpha.types.AnnotatedString.SemanticMarkupType

start_char_index¶

Unicode character index of the query.

Type: int

length¶

The length (number of unicode characters) of the markup substring.

Type: int

class SemanticMarkupType(value)[source]¶

Bases: proto.enums.Enum

Semantic markup types.

Values:

MARKUP_TYPE_UNSPECIFIED (0):: No markup type was specified.
METRIC (1):: Markup for a substring denoting a metric.
DIMENSION (2):: Markup for a substring denoting a dimension.
FILTER (3):: Markup for a substring denoting a filter.
UNUSED (4):: Markup for an unused substring.
BLOCKED (5):: Markup for a substring containing blocked phrases.
ROW (6):: Markup for a substring that contains terms for row.

class google.cloud.dataqna_v1alpha.types.BigQueryJob(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

BigQuery job information. This can be used to query the BigQuery API and retrieve the current job’s status (using jobs.get).

job_id¶

The job ID.

Type: str

project_id¶

The project ID of the job.

Type: str

location¶

The location where the job is running.

Type: str

class google.cloud.dataqna_v1alpha.types.CreateQuestionRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request to create a question resource.

parent¶

Required. The name of the project this data source reference belongs to. Example: projects/foo/locations/bar

Type: str

question¶

Required. The question to create.

Type: google.cloud.dataqna_v1alpha.types.Question

class google.cloud.dataqna_v1alpha.types.DataQuery(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Representation of the data query for the backend. This is provided for informational purposes only. Clients should not use it to send it to the backend directly, but rather use the execute RPC to trigger the execution. Using the execute RPC is needed in order to track the state of a question and report on it correctly to the data administrators.

sql¶

The generated SQL query to be sent to the backend.

Type: str

class google.cloud.dataqna_v1alpha.types.DebugFlags(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Configuriation of debug flags.

include_va_query¶

Whether to include the original VAQuery.

Type: bool

include_nested_va_query¶

Whether to include the original nested VAQuery.

Type: bool

include_human_interpretation¶

Whether to include the original human interpretation strings generated by Analyza.

Type: bool

include_aqua_debug_response¶

Whether to include the Aqua debug response.

Type: bool

time_override¶

The time in milliseconds from Unix epoch to be used to process the query. This is useful for testing the queries at different time period. If not set or time_override <= 0, then the current time is used.

Type: int

is_internal_google_user¶

Set to true if request is initiated by an internal Google user.

Type: bool

ignore_cache¶

Determines whether cache needs to be ignored. If set to true, cache won’t be queried and updated.

Type: bool

include_search_entities_rpc¶

Whether to include the request/response pair from the call to the EntityIndex for SearchEntities.

Type: bool

include_list_column_annotations_rpc¶

Whether to include the request/response pair from the call to the Annotations service for ListColumnAnnotations.

Type: bool

include_virtual_analyst_entities¶

Whether to include the entity list passed to Analyza.

Type: bool

include_table_list¶

Whether to include the table list.

Type: bool

include_domain_list¶

Whether to include the domain list.

Type: bool

class google.cloud.dataqna_v1alpha.types.ExecuteQuestionRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request to execute an interpretation.

name¶

Required. The unique identifier for the question. Example: projects/foo/locations/bar/questions/1234

Type: str

interpretation_index¶

Required. Index of the interpretation to execute.

Type: int

class google.cloud.dataqna_v1alpha.types.ExecutionInfo(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Information about the backend status (such as BigQuery) of the execution.

job_creation_status¶

Status returned by the backend when the job was created.

Type: google.rpc.status_pb2.Status

job_execution_state¶

Status of the job execution.

Type: google.cloud.dataqna_v1alpha.types.ExecutionInfo.JobExecutionState

create_time¶

Time when the execution was triggered.

Type: google.protobuf.timestamp_pb2.Timestamp

bigquery_job¶

BigQuery job information. Future versions will have different backends. Hence, clients must make sure they can handle it when this field is not populated.

Type: google.cloud.dataqna_v1alpha.types.BigQueryJob

class JobExecutionState(value)[source]¶

Bases: proto.enums.Enum

Enum of possible job execution statuses.

Values:

JOB_EXECUTION_STATE_UNSPECIFIED (0):: No job execution was specified.
NOT_EXECUTED (1):: No job execution was requested, yet.
RUNNING (2):: The job is running.
SUCCEEDED (3):: The job completed successfully.
FAILED (4):: The job completed unsuccessfully.

class google.cloud.dataqna_v1alpha.types.GetQuestionRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A request to get a previously created question.

name¶

Required. The unique identifier for the question. Example: projects/foo/locations/bar/questions/1234

Type: str

read_mask¶

The list of fields to be retrieved.

Type: google.protobuf.field_mask_pb2.FieldMask

class google.cloud.dataqna_v1alpha.types.GetUserFeedbackRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request to get user feedback.

name¶

Required. The unique identifier for the user feedback. User feedback is a singleton resource on a Question. Example: projects/foo/locations/bar/questions/1234/userFeedback

Type: str

class google.cloud.dataqna_v1alpha.types.HumanReadable(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Human readable interpretation.

generated_interpretation¶

Generated query explaining the interpretation.

Type: google.cloud.dataqna_v1alpha.types.AnnotatedString

original_question¶

Annotations on the original query.

Type: google.cloud.dataqna_v1alpha.types.AnnotatedString

class google.cloud.dataqna_v1alpha.types.InterpretEntity(value)[source]¶

Bases: proto.enums.Enum

Query entities of an interpretation.

Values:

INTERPRET_ENTITY_UNSPECIFIED (0):: No interpret entity was specified.
DIMENSION (1):: A dimenstion entity.
METRIC (2):: A metric entity.

class google.cloud.dataqna_v1alpha.types.InterpretError(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details on the failure to interpret the question.

message¶

Error message explaining why this question could not be interpreted.

Type: str

code¶

The code for the error category why the interpretation failed.

Type: google.cloud.dataqna_v1alpha.types.InterpretError.InterpretErrorCode

details¶

Details on interpretation failure.

Type: google.cloud.dataqna_v1alpha.types.InterpretError.InterpretErrorDetails

class InterpretAmbiguityDetails(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details about a query that was too ambiguous. Currently, the message has no fields and its presence signals that there was ambiguity.

class InterpretErrorCode(value)[source]¶

Bases: proto.enums.Enum

The interpret error code provides an error category why the interpretation failed.

Values:

INTERPRET_ERROR_CODE_UNSPECIFIED (0):: No interpret error code was specified.
INVALID_QUERY (1):: The query is not valid.
FAILED_TO_UNDERSTAND (2):: The interpreter failed to understand the question. For example, because it was too ambiguous.
FAILED_TO_ANSWER (3):: The interpreter could understand the question, but was not able to arrive at an answer. For example, because a requested operation is not supported.

class InterpretErrorDetails(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details on interpretation failure.

unsupported_details¶

Populated if parts of the query are unsupported.

Type: google.cloud.dataqna_v1alpha.types.InterpretError.InterpretUnsupportedDetails

incomplete_query_details¶

Populated if the query is incomplete.

Type: google.cloud.dataqna_v1alpha.types.InterpretError.InterpretIncompleteQueryDetails

ambiguity_details¶

Populated if the query was too ambiguous.

Type: google.cloud.dataqna_v1alpha.types.InterpretError.InterpretAmbiguityDetails

class InterpretIncompleteQueryDetails(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details about an incomplete query.

entities¶

List of missing interpret entities.

Type: MutableSequence[google.cloud.dataqna_v1alpha.types.InterpretEntity]

class InterpretUnsupportedDetails(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details about unsupported parts in a query.

operators¶

Unsupported operators. For example: median.

Type: MutableSequence[str]

intent¶

Unsupported intents.

Type: MutableSequence[str]

class google.cloud.dataqna_v1alpha.types.Interpretation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

An interpretation of a natural language query.

data_sources¶

List of data sources used in the current understanding.

Type: MutableSequence[str]

confidence¶

The level of confidence that one of the interpretations is correct. This is a value in the range [0, 1] where a value of 0.5 or below is to be considered a low confidence.

Type: float

unused_phrases¶

A list of unused phrases. Clients should display a Did You Mean (DYM) dialog if this is non-empty, even if this is the only interpretation.

Type: MutableSequence[str]

human_readable¶

Human readable representation of the query.

Type: google.cloud.dataqna_v1alpha.types.HumanReadable

interpretation_structure¶

Information about the interpretation structure that helps to understand and visualize the response.

Type: google.cloud.dataqna_v1alpha.types.InterpretationStructure

data_query¶

Representation of the data query to be sent to the backend.

Type: google.cloud.dataqna_v1alpha.types.DataQuery

execution_info¶

Information about the backend response. This is populated only if execution of an interpretation was requested.

Type: google.cloud.dataqna_v1alpha.types.ExecutionInfo

class google.cloud.dataqna_v1alpha.types.InterpretationStructure(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Information about the interpretation structure that helps to understand and visualize the response.

visualization_types¶

List of possible visualization types to apply for this interpretation. The order has no relevance.

Type: MutableSequence[google.cloud.dataqna_v1alpha.types.InterpretationStructure.VisualizationType]

column_info¶

Information about the output columns, that is, the columns that will be returned by the backend.

Type: MutableSequence[google.cloud.dataqna_v1alpha.types.InterpretationStructure.ColumnInfo]

class ColumnInfo(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Information about a column.

output_alias¶

The alias of the output column as used by the backend. For example, the field name in the schema provided in the query response in BigQuery.

Type: str

display_name¶

Human readable name of the output column.

Type: str

class VisualizationType(value)[source]¶

Bases: proto.enums.Enum

Enumeration of visualzation types to use for query response data.

Values:

VISUALIZATION_TYPE_UNSPECIFIED (0):: No visualization type was specified.
TABLE (1):: Show a table.
BAR_CHART (2):: Show a bar chart.
COLUMN_CHART (3):: Show a column chart.
TIMELINE (4):: Show a timeline.
SCATTER_PLOT (5):: Show a scatter plot.
PIE_CHART (6):: Show a pie chart.
LINE_CHART (7):: Show a line chart.
AREA_CHART (8):: Show an area chart.
COMBO_CHART (9):: Show a combo chart.
HISTOGRAM (10):: Show a histogram.
GENERIC_CHART (11):: This denotes queries when the user has not specified the particular type of chart and has mentioned only a generic chart name such as “Chart”, “Plot”, “Graph”, etc. This will differentiate it from specific charting terms such as “Bar chart”, “Pie chart”, etc.
CHART_NOT_UNDERSTOOD (12):: The user tried to specify a chart type, but the interpreter could not understand the type. The client should display a generic chart and may give a hint to the user that the requested type was not understood.

class google.cloud.dataqna_v1alpha.types.Question(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

The question resource represents a natural language query, its settings, understanding generated by the system, and answer retrieval status. A question cannot be modified.

name¶

Output only. Immutable. The unique identifier for the Question. The ID is server-generated. Example: projects/foo/locations/bar/questions/123

Type: str

scopes¶

Required. Immutable. Scopes to be used for the question. A scope defines the relevant data set scope. It can be a reference to a specific data source or a collection of data sources. Currently, support is limited to a single BigQuery table. There must be exactly one scopes element.

Example: //bigquery.googleapis.com/projects/test-project/datasets/foo/tables/bar

Type: MutableSequence[str]

query¶

Required. Immutable. The query in natural language.

Type: str

data_source_annotations¶

A list of annotations to use instead of the default annotation of a data source (set in the data source reference resource). There must not be more than one annotation with the same data source reference.

Type: MutableSequence[str]

interpret_error¶

An error field explaining why interpretation failed. This is only populated if the interpretation failed.

Note: This is different from getting a status error on the request itself. This is not a client or server error and the Question resource is still persisted, but the service could not interpret the question. Clients should present the error to the user so the user can rephrase the question.

Type: google.cloud.dataqna_v1alpha.types.InterpretError

interpretations¶

A list of interpretations for this question.

Type: MutableSequence[google.cloud.dataqna_v1alpha.types.Interpretation]

create_time¶

Time when the question was created.

Type: google.protobuf.timestamp_pb2.Timestamp

user_email¶

Output only. The e-mail address of the user that created this question.

Type: str

debug_flags¶

Input only. Immutable. Flags to request additional information for debugging purposes.

Type: google.cloud.dataqna_v1alpha.types.DebugFlags

debug_info¶

Top level debug information. This will be stored as the type DebugInformation. Using Any so clients don’t need to pull in anything inside the debug message.

Type: google.protobuf.any_pb2.Any

class google.cloud.dataqna_v1alpha.types.SuggestQueriesRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request for query suggestions.

parent¶

Required. The parent of the suggestion query is the resource denoting the project and location.

Type: str

scopes¶

The scopes to which this search is restricted. The only supported scope pattern is //bigquery.googleapis.com/projects/{GCP-PROJECT-ID}/datasets/{DATASET-ID}/tables/{TABLE-ID}.

Type: MutableSequence[str]

query¶

User query for which to generate suggestions. If the query is empty, zero state suggestions are returned. This allows UIs to display suggestions right away, helping the user to get a sense of what a query might look like.

Type: str

suggestion_types¶

The requested suggestion type. Multiple suggestion types can be requested, but there is no guarantee that the service will return suggestions for each type. Suggestions for a requested type might rank lower than suggestions for other types and the service may decide to cut these suggestions off.

Type: MutableSequence[google.cloud.dataqna_v1alpha.types.SuggestionType]

class google.cloud.dataqna_v1alpha.types.SuggestQueriesResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Response to SuggestQueries.

suggestions¶

A list of suggestions.

Type: MutableSequence[google.cloud.dataqna_v1alpha.types.Suggestion]

class google.cloud.dataqna_v1alpha.types.Suggestion(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A suggestion for a query with a ranking score.

suggestion_info¶

Detailed information about the suggestion.

Type: google.cloud.dataqna_v1alpha.types.SuggestionInfo

ranking_score¶

The score of the suggestion. This can be used to define ordering in UI. The score represents confidence in the suggestion where higher is better. All score values must be in the range [0, 1).

Type: float

suggestion_type¶

The type of the suggestion.

Type: google.cloud.dataqna_v1alpha.types.SuggestionType

class google.cloud.dataqna_v1alpha.types.SuggestionInfo(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Detailed information about the suggestion.

annotated_suggestion¶

Annotations for the suggestion. This provides information about which part of the suggestion corresponds to what semantic meaning (e.g. a metric).

Type: google.cloud.dataqna_v1alpha.types.AnnotatedString

query_matches¶

Matches between user query and the annotated string.

Type: MutableSequence[google.cloud.dataqna_v1alpha.types.SuggestionInfo.MatchInfo]

class MatchInfo(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

MatchInfo describes which part of suggestion matched with data in user typed query. This can be used to highlight matching parts in the UI. This is different from the annotations provided in annotated_suggestion. The annotated_suggestion provides information about the semantic meaning, while this provides information about how it relates to the input.

Example: user query: top products

annotated_suggestion {
 text_formatted = "top product_group"
 html_formatted = "top <b>product_group</b>"
 markups {
  {type: TEXT, start_char_index: 0, length: 3}
  {type: DIMENSION, start_char_index: 4, length: 13}
 }
}

query_matches {
 { start_char_index: 0, length: 3 }
 { start_char_index: 4, length: 7}
}

start_char_index¶

Unicode character index of the string annotation.

Type: int

length¶

Count of unicode characters of this substring.

Type: int

class google.cloud.dataqna_v1alpha.types.SuggestionType(value)[source]¶

Bases: proto.enums.Enum

The type of suggestion.

Values:

SUGGESTION_TYPE_UNSPECIFIED (0):: No suggestiont type is specified.
ENTITY (1):: Entity suggestion type. Suggestions are for single entities.
TEMPLATE (2):: Template suggestion type. Suggestions are for full sentences.

class google.cloud.dataqna_v1alpha.types.UpdateUserFeedbackRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request to updates user feedback.

user_feedback¶

Required. The user feedback to update. This can be called even if there is no user feedback so far. The feedback’s name field is used to identify the user feedback (and the corresponding question) to update.

Type: google.cloud.dataqna_v1alpha.types.UserFeedback

update_mask¶

The list of fields to be updated.

Type: google.protobuf.field_mask_pb2.FieldMask

class google.cloud.dataqna_v1alpha.types.UserFeedback(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Feedback provided by a user.

name¶

Required. The unique identifier for the user feedback. User feedback is a singleton resource on a Question. Example: projects/foo/locations/bar/questions/1234/userFeedback

Type: str

free_form_feedback¶

Free form user feedback, such as a text box.

Type: str

rating¶

The user feedback rating

Type: google.cloud.dataqna_v1alpha.types.UserFeedback.UserFeedbackRating

class UserFeedbackRating(value)[source]¶

Bases: proto.enums.Enum

Enumeration of feedback ratings.

Values:

USER_FEEDBACK_RATING_UNSPECIFIED (0):: No rating was specified.
POSITIVE (1):: The user provided positive feedback.
NEGATIVE (2):: The user provided negative feedback.

Types for Google Cloud Dataqna v1alpha API¶

google-cloud-data-qna

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