Dataquery🔗
Constructor🔗
Methods🔗
build🔗
Builds the object.
alias🔗
channel🔗
Used for live query
csv_content🔗
csv_file_name🔗
csv_wave🔗
datasource🔗
The datasource
drop_percent🔗
Drop percentage (the chance we will lose a point 0-100)
error_source🔗
Possible enum values:
"plugin"
"downstream"
error_type🔗
Possible enum values:
"frontend_exception"
"frontend_observable"
"server_panic"
def error_type(error_type: typing.Literal["frontend_exception", "frontend_observable", "server_panic"]) -> typing.Self
flamegraph_diff🔗
hide🔗
true if query is disabled (ie should not be returned to the dashboard)
NOTE: this does not always imply that the query should not be executed since
the results from a hidden query may be used as the input to other queries (SSE etc)
interval_ms🔗
Interval is the suggested duration between time points in a time series query.
NOTE: the values for intervalMs is not saved in the query model. It is typically calculated
from the interval required to fill a pixels in the visualization
labels🔗
level_column🔗
lines🔗
max_val🔗
max_data_points🔗
MaxDataPoints is the maximum number of data points that should be returned from a time series query.
NOTE: the values for maxDataPoints is not saved in the query model. It is typically calculated
from the number of pixels visible in a visualization
min_val🔗
nodes🔗
noise🔗
points🔗
pulse_wave🔗
query_type🔗
QueryType is an optional identifier for the type of query.
It can be used to distinguish different types of queries.
raw_frame_content🔗
ref_id🔗
RefID is the unique identifier of the query, set by the frontend call.
result_assertions🔗
Optionally define expected query result behavior
def result_assertions(result_assertions: cogbuilder.Builder[testdata.ResultAssertions]) -> typing.Self
scenario_id🔗
Possible enum values:
"annotations"
"arrow"
"csv_content"
"csv_file"
"csv_metric_values"
"datapoints_outside_range"
"error_with_source"
"exponential_heatmap_bucket_data"
"flame_graph"
"grafana_api"
"linear_heatmap_bucket_data"
"live"
"logs"
"manual_entry"
"no_data_points"
"node_graph"
"predictable_csv_wave"
"predictable_pulse"
"random_walk"
"random_walk_table"
"random_walk_with_error"
"raw_frame"
"server_error_500"
"simulation"
"slow_query"
"streaming_client"
"table_static"
"trace"
"usa"
"variables-query"
def scenario_id(scenario_id: typing.Literal["annotations", "arrow", "csv_content", "csv_file", "csv_metric_values", "datapoints_outside_range", "error_with_source", "exponential_heatmap_bucket_data", "flame_graph", "grafana_api", "linear_heatmap_bucket_data", "live", "logs", "manual_entry", "no_data_points", "node_graph", "predictable_csv_wave", "predictable_pulse", "random_walk", "random_walk_table", "random_walk_with_error", "raw_frame", "server_error_500", "simulation", "slow_query", "streaming_client", "table_static", "trace", "usa", "variables-query"]) -> typing.Self
series_count🔗
sim🔗
span_count🔗
spread🔗
start_value🔗
stream🔗
string_input🔗
common parameter used by many query types
time_range🔗
TimeRange represents the query range
NOTE: unlike generic /ds/query, we can now send explicit time values in each query
NOTE: the values for timeRange are not saved in a dashboard, they are constructed on the fly