Panel🔗
Dashboard panels are the basic visualization building blocks.
Definition🔗
class Panel:
"""
Dashboard panels are the basic visualization building blocks.
"""
# The panel plugin type id. This is used to find the plugin to display the panel.
type_val: str
# Unique identifier of the panel. Generated by Grafana when creating a new panel. It must be unique within a dashboard, but not globally.
id_val: typing.Optional[int]
# The version of the plugin that is used for this panel. This is used to find the plugin to display the panel and to migrate old panel configs.
plugin_version: typing.Optional[str]
# Depends on the panel plugin. See the plugin documentation for details.
targets: typing.Optional[list[cogvariants.Dataquery]]
# Panel title.
title: typing.Optional[str]
# Panel description.
description: typing.Optional[str]
# Whether to display the panel without a background.
transparent: typing.Optional[bool]
# The datasource used in all targets.
datasource: typing.Optional[dashboard.DataSourceRef]
# Grid position.
grid_pos: typing.Optional[dashboard.GridPos]
# Panel links.
links: typing.Optional[list[dashboard.DashboardLink]]
# Name of template variable to repeat for.
repeat: typing.Optional[str]
# Direction to repeat in if 'repeat' is set.
# `h` for horizontal, `v` for vertical.
repeat_direction: typing.Optional[typing.Literal["h", "v"]]
# Option for repeated panels that controls max items per row
# Only relevant for horizontally repeated panels
max_per_row: typing.Optional[float]
# The maximum number of data points that the panel queries are retrieving.
max_data_points: typing.Optional[float]
# List of transformations that are applied to the panel data before rendering.
# When there are multiple transformations, Grafana applies them in the order they are listed.
# Each transformation creates a result set that then passes on to the next transformation in the processing pipeline.
transformations: typing.Optional[list[dashboard.DataTransformerConfig]]
# The min time interval setting defines a lower limit for the $__interval and $__interval_ms variables.
# This value must be formatted as a number followed by a valid time
# identifier like: "40s", "3d", etc.
# See: https://grafana.com/docs/grafana/latest/panels-visualizations/query-transform-data/#query-options
interval: typing.Optional[str]
# Overrides the relative time range for individual panels,
# which causes them to be different than what is selected in
# the dashboard time picker in the top-right corner of the dashboard. You can use this to show metrics from different
# time periods or days on the same dashboard.
# The value is formatted as time operation like: `now-5m` (Last 5 minutes), `now/d` (the day so far),
# `now-5d/d`(Last 5 days), `now/w` (This week so far), `now-2y/y` (Last 2 years).
# Note: Panel time overrides have no effect when the dashboard’s time range is absolute.
# See: https://grafana.com/docs/grafana/latest/panels-visualizations/query-transform-data/#query-options
time_from: typing.Optional[str]
# Overrides the time range for individual panels by shifting its start and end relative to the time picker.
# For example, you can shift the time range for the panel to be two hours earlier than the dashboard time picker setting `2h`.
# Note: Panel time overrides have no effect when the dashboard’s time range is absolute.
# See: https://grafana.com/docs/grafana/latest/panels-visualizations/query-transform-data/#query-options
time_shift: typing.Optional[str]
# Controls if the timeFrom or timeShift overrides are shown in the panel header
hide_time_override: typing.Optional[bool]
# Dynamically load the panel
library_panel: typing.Optional[dashboard.LibraryPanelRef]
# Sets panel queries cache timeout.
cache_timeout: typing.Optional[str]
# Overrides the data source configured time-to-live for a query cache item in milliseconds
query_caching_ttl: typing.Optional[float]
# It depends on the panel plugin. They are specified by the Options field in panel plugin schemas.
options: typing.Optional[object]
# Field options allow you to change how the data is displayed in your visualizations.
field_config: typing.Optional[dashboard.FieldConfigSource]
Methods🔗
to_json🔗
Converts this object into a representation that can easily be encoded to JSON.
from_json🔗
Builds this object from a JSON-decoded dict.
See also🔗
- annotationslist.Panel
- barchart.Panel
- bargauge.Panel
- candlestick.Panel
- canvas.Panel
- Panel
- dashboardlist.Panel
- datagrid.Panel
- debug.Panel
- gauge.Panel
- geomap.Panel
- heatmap.Panel
- histogram.Panel
- logs.Panel
- news.Panel
- nodegraph.Panel
- piechart.Panel
- stat.Panel
- statetimeline.Panel
- statushistory.Panel
- table.Panel
- text.Panel
- timeseries.Panel
- trend.Panel
- xychart.Panel