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dash-api/lib/python3.11/site-packages/dash/dash_table/DataTable.py

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# AUTO GENERATED FILE - DO NOT EDIT
import typing # noqa: F401
from typing_extensions import TypedDict, NotRequired, Literal # noqa: F401
from dash.development.base_component import Component, _explicitize_args
ComponentType = typing.Union[
str,
int,
float,
Component,
None,
typing.Sequence[typing.Union[str, int, float, Component, None]],
]
NumberType = typing.Union[
typing.SupportsFloat, typing.SupportsInt, typing.SupportsComplex
]
class DataTable(Component):
"""A DataTable component.
Dash DataTable is an interactive table component designed for
viewing, editing, and exploring large datasets.
DataTable is rendered with standard, semantic HTML <table/> markup,
which makes it accessible, responsive, and easy to style. This
component was written from scratch in React.js specifically for the
Dash community. Its API was designed to be ergonomic and its behavior
is completely customizable through its properties.
Keyword arguments:
- data (list of dicts with strings as keys and values of type string | number | boolean; optional):
The contents of the table. The keys of each item in data should
match the column IDs. Each item can also have an 'id' key, whose
value is its row ID. If there is a column with ID='id' this will
display the row ID, otherwise it is just used to reference the row
for selections, filtering, etc. Example: [ {'column-1': 4.5,
'column-2': 'montreal', 'column-3': 'canada'}, {'column-1':
8, 'column-2': 'boston', 'column-3': 'america'} ].
- columns (list of dicts; optional):
Columns describes various aspects about each individual column.
`name` and `id` are the only required parameters.
`columns` is a list of dicts with keys:
- id (string; required):
The `id` of the column. The column `id` is used to match cells
in data with particular columns. The `id` is not visible in
the table.
- name (string | list of strings; required):
The `name` of the column, as it appears in the column header.
If `name` is a list of strings, then the columns will render
with multiple headers rows.
- type (a value equal to: 'any', 'numeric', 'text', 'datetime'; optional):
The data-type provides support for per column typing and
allows for data validation and coercion. 'numeric': represents
both floats and ints. 'text': represents a string. 'datetime':
a string representing a date or date-time, in the form:
'YYYY-MM-DD HH:MM:SS.ssssss' or some truncation thereof. Years
must have 4 digits, unless you use `validation.allow_YY:
True`. Also accepts 'T' or 't' between date and time, and
allows timezone info at the end. To convert these strings to
Python `datetime` objects, use `dateutil.parser.isoparse`.
In R use `parse_iso_8601` from the `parsedate` library.
WARNING: these parsers do not work with 2-digit years, if you
use `validation.allow_YY: True` and do not coerce to 4-digit
years. And parsers that do work with 2-digit years may make
a different guess about the century than we make on the
front end. 'any': represents any type of data. Defaults to
'any' if undefined.
- presentation (a value equal to: 'input', 'dropdown', 'markdown'; optional):
The `presentation` to use to display data. Markdown can be
used on columns with type 'text'. See 'dropdown' for more
info. Defaults to 'input' for ['datetime', 'numeric', 'text',
'any'].
- selectable (a value equal to: 'first', 'last' | boolean | list of booleans; optional):
If True, the user can select the column by clicking on the
checkbox or radio button in the column. If there are multiple
header rows, True will display the input on each row. If
`last`, the input will only appear on the last header row. If
`first` it will only appear on the first header row. These are
respectively shortcut equivalents to `[False, ..., False,
True]` and `[True, False, ..., False]`. If there are merged,
multi-header columns then you can choose which column header
row to display the input in by supplying an array of booleans.
For example, `[True, False]` will display the `selectable`
input on the first row, but now on the second row. If the
`selectable` input appears on a merged columns, then clicking
on that input will select *all* of the merged columns
associated with it. The table-level prop `column_selectable`
is used to determine the type of column selection to use.
- clearable (a value equal to: 'first', 'last' | boolean | list of booleans; optional):
If True, the user can clear the column by clicking on the
`clear` action button on the column. If there are multiple
header rows, True will display the action button on each row.
If `last`, the `clear` action button will only appear on the
last header row. If `first` it will only appear on the first
header row. These are respectively shortcut equivalents to
`[False, ..., False, True]` and `[True, False, ..., False]`.
If there are merged, multi-header columns then you can choose
which column header row to display the `clear` action button
in by supplying an array of booleans. For example, `[True,
False]` will display the `clear` action button on the first
row, but not the second row. If the `clear` action button
appears on a merged column, then clicking on that button will
clear *all* of the merged columns associated with it. Unlike
`column.deletable`, this action does not remove the column(s)
from the table. It only removed the associated entries from
`data`.
- deletable (a value equal to: 'first', 'last' | boolean | list of booleans; optional):
If True, the user can remove the column by clicking on the
`delete` action button on the column. If there are multiple
header rows, True will display the action button on each row.
If `last`, the `delete` action button will only appear on the
last header row. If `first` it will only appear on the first
header row. These are respectively shortcut equivalents to
`[False, ..., False, True]` and `[True, False, ..., False]`.
If there are merged, multi-header columns then you can choose
which column header row to display the `delete` action button
in by supplying an array of booleans. For example, `[True,
False]` will display the `delete` action button on the first
row, but not the second row. If the `delete` action button
appears on a merged column, then clicking on that button will
remove *all* of the merged columns associated with it.
- editable (boolean; optional):
There are two `editable` flags in the table. This is the
column-level editable flag and there is also the table-level
`editable` flag. These flags determine whether the contents of
the table are editable or not. If the column-level `editable`
flag is set it overrides the table-level `editable` flag for
that column.
- hideable (a value equal to: 'first', 'last' | boolean | list of booleans; optional):
If True, the user can hide the column by clicking on the
`hide` action button on the column. If there are multiple
header rows, True will display the action button on each row.
If `last`, the `hide` action button will only appear on the
last header row. If `first` it will only appear on the first
header row. These are respectively shortcut equivalents to
`[False, ..., False, True]` and `[True, False, ..., False]`.
If there are merged, multi-header columns then you can choose
which column header row to display the `hide` action button in
by supplying an array of booleans. For example, `[True,
False]` will display the `hide` action button on the first
row, but not the second row. If the `hide` action button
appears on a merged column, then clicking on that button will
hide *all* of the merged columns associated with it.
- renamable (a value equal to: 'first', 'last' | boolean | list of booleans; optional):
If True, the user can rename the column by clicking on the
`rename` action button on the column. If there are multiple
header rows, True will display the action button on each row.
If `last`, the `rename` action button will only appear on the
last header row. If `first` it will only appear on the first
header row. These are respectively shortcut equivalents to
`[False, ..., False, True]` and `[True, False, ..., False]`.
If there are merged, multi-header columns then you can choose
which column header row to display the `rename` action button
in by supplying an array of booleans. For example, `[True,
False]` will display the `rename` action button on the first
row, but not the second row. If the `rename` action button
appears on a merged column, then clicking on that button will
rename *all* of the merged columns associated with it.
- filter_options (dict; optional):
There are two `filter_options` props in the table. This is the
column-level filter_options prop and there is also the
table-level `filter_options` prop. If the column-level
`filter_options` prop is set it overrides the table-level
`filter_options` prop for that column.
`filter_options` is a dict with keys:
- case (a value equal to: 'sensitive', 'insensitive'; optional):
(default: 'sensitive') Determine whether the applicable
filter relational operators will default to `sensitive` or
`insensitive` comparison.
- placeholder_text (string; optional):
(default: 'filter data...') The filter cell placeholder
text.
- format (dict; optional):
The formatting applied to the column's data. This prop is
derived from the [d3-format](https://github.com/d3/d3-format)
library specification. Apart from being structured slightly
differently (under a single prop), the usage is the same. See
also dash_table.FormatTemplate. It contains helper functions
for typical number formats.
`format` is a dict with keys:
- locale (dict; optional):
Represents localization specific formatting information.
When left unspecified, will use the default value provided
by d3-format.
`locale` is a dict with keys:
- symbol (list of strings; optional):
(default: ['$', '']). A list of two strings
representing the prefix and suffix symbols. Typically
used for currency, and implemented using d3's
currency format, but you can use this for other
symbols such as measurement units.
- decimal (string; optional):
(default: '.'). The string used for the decimal
separator.
- group (string; optional):
(default: ','). The string used for the groups
separator.
- grouping (list of numbers; optional):
(default: [3]). A list of integers representing the
grouping pattern. The default is 3 for thousands.
- numerals (list of strings; optional):
A list of ten strings used as replacements for numbers
0-9.
- percent (string; optional):
(default: '%'). The string used for the percentage
symbol.
- separate_4digits (boolean; optional):
(default: True). Separates integers with 4-digits or
less.
- nully (boolean | number | string | dict | list; optional):
A value that will be used in place of the Noney value
during formatting. If the value type matches the column
type, it will be formatted normally.
- prefix (number; optional):
A number representing the SI unit to use during
formatting. See `dash_table.Format.Prefix` enumeration
for the list of valid values.
- specifier (string; optional):
(default: ''). Represents the d3 rules to apply when
formatting the number.
- on_change (dict; optional):
The `on_change` behavior of the column for user-initiated
modifications.
`on_change` is a dict with keys:
- action (a value equal to: 'coerce', 'none', 'validate'; optional):
(default 'coerce'): 'none': do not validate data;
'coerce': check if the data corresponds to the destination
type and attempts to coerce it into the destination type
if not; 'validate': check if the data corresponds to the
destination type (no coercion).
- failure (a value equal to: 'accept', 'default', 'reject'; optional):
(default 'reject'): What to do with the value if the
action fails. 'accept': use the invalid value;
'default': replace the provided value with
`validation.default`; 'reject': do not modify the
existing value.
- sort_as_null (list of string | number | booleans; optional):
An array of string, number and boolean values that are treated
as `None` (i.e. ignored and always displayed last) when
sorting. This value overrides the table-level `sort_as_None`.
- validation (dict; optional):
The `validation` options for user input processing that can
accept, reject or apply a default value.
`validation` is a dict with keys:
- allow_null (boolean; optional):
Allow the use of Noney values. (undefined, None, NaN)
(default: False).
- default (boolean | number | string | dict | list; optional):
The default value to apply with on_change.failure =
'default'. (default: None).
- allow_YY (boolean; optional):
This is for `datetime` columns only. Allow 2-digit years
(default: False). If True, we interpret years as ranging
from now-70 to now+29 - in 2019 this is 1949 to 2048 but
in 2020 it will be different. If used with `action:
'coerce'`, will convert user input to a 4-digit year.
- editable (boolean; default False):
If True, then the data in all of the cells is editable. When
`editable` is True, particular columns can be made uneditable by
setting `editable` to `False` inside the `columns` property. If
False, then the data in all of the cells is uneditable. When
`editable` is False, particular columns can be made editable by
setting `editable` to `True` inside the `columns` property.
- fixed_columns (dict; default { headers: False, data: 0}):
`fixed_columns` will \"fix\" the set of columns so that they
remain visible when scrolling horizontally across the unfixed
columns. `fixed_columns` fixes columns from left-to-right. If
`headers` is False, no columns are fixed. If `headers` is True,
all operation columns (see `row_deletable` and `row_selectable`)
are fixed. Additional data columns can be fixed by assigning a
number to `data`. Note that fixing columns introduces some
changes to the underlying markup of the table and may impact the
way that your columns are rendered or sized. View the
documentation examples to learn more.
`fixed_columns` is a dict with keys:
- data (number; optional):
Example `{'headers':False, 'data':0}` No columns are fixed
(the default).
- headers (boolean; optional)
- fixed_rows (dict; default { headers: False, data: 0}):
`fixed_rows` will \"fix\" the set of rows so that they remain
visible when scrolling vertically down the table. `fixed_rows`
fixes rows from top-to-bottom, starting from the headers. If
`headers` is False, no rows are fixed. If `headers` is True, all
header and filter rows (see `filter_action`) are fixed. Additional
data rows can be fixed by assigning a number to `data`. Note that
fixing rows introduces some changes to the underlying markup of
the table and may impact the way that your columns are rendered or
sized. View the documentation examples to learn more.
`fixed_rows` is a dict with keys:
- data (number; optional):
Example `{'headers':False, 'data':0}` No rows are fixed (the
default).
- headers (boolean; optional)
- column_selectable (a value equal to: 'single', 'multi', false; default False):
If `single`, then the user can select a single column or group of
merged columns via the radio button that will appear in the header
rows. If `multi`, then the user can select multiple columns or
groups of merged columns via the checkbox that will appear in the
header rows. If False, then the user will not be able to select
columns and no input will appear in the header rows. When a column
is selected, its id will be contained in `selected_columns` and
`derived_viewport_selected_columns`.
- cell_selectable (boolean; default True):
If True (default), then it is possible to click and navigate table
cells.
- row_selectable (a value equal to: 'single', 'multi', false; default False):
If `single`, then the user can select a single row via a radio
button that will appear next to each row. If `multi`, then the
user can select multiple rows via a checkbox that will appear next
to each row. If False, then the user will not be able to select
rows and no additional UI elements will appear. When a row is
selected, its index will be contained in `selected_rows`.
- row_deletable (boolean; optional):
If True, then a `x` will appear next to each `row` and the user
can delete the row.
- active_cell (dict; optional):
The row and column indices and IDs of the currently active cell.
`row_id` is only returned if the data rows have an `id` key.
`active_cell` is a dict with keys:
- row (number; optional)
- column (number; optional)
- row_id (string | number; optional)
- column_id (string; optional)
- selected_cells (list of dicts; optional):
`selected_cells` represents the set of cells that are selected, as
an array of objects, each item similar to `active_cell`. Multiple
cells can be selected by holding down shift and clicking on a
different cell or holding down shift and navigating with the arrow
keys.
`selected_cells` is a list of dicts with keys:
- row (number; optional)
- column (number; optional)
- row_id (string | number; optional)
- column_id (string; optional)
- selected_rows (list of numbers; optional):
`selected_rows` contains the indices of rows that are selected via
the UI elements that appear when `row_selectable` is `'single'` or
`'multi'`.
- selected_columns (list of strings; optional):
`selected_columns` contains the ids of columns that are selected
via the UI elements that appear when `column_selectable` is
`'single' or 'multi'`.
- selected_row_ids (list of string | numbers; optional):
`selected_row_ids` contains the ids of rows that are selected via
the UI elements that appear when `row_selectable` is `'single'` or
`'multi'`.
- start_cell (dict; optional):
When selecting multiple cells (via clicking on a cell and then
shift-clicking on another cell), `start_cell` represents the [row,
column] coordinates of the cell in one of the corners of the
region. `end_cell` represents the coordinates of the other corner.
`start_cell` is a dict with keys:
- row (number; optional)
- column (number; optional)
- row_id (string | number; optional)
- column_id (string; optional)
- end_cell (dict; optional):
When selecting multiple cells (via clicking on a cell and then
shift-clicking on another cell), `end_cell` represents the row /
column coordinates and IDs of the cell in one of the corners of
the region. `start_cell` represents the coordinates of the other
corner.
`end_cell` is a dict with keys:
- row (number; optional)
- column (number; optional)
- row_id (string | number; optional)
- column_id (string; optional)
- data_previous (list of dicts; optional):
The previous state of `data`. `data_previous` has the same
structure as `data` and it will be updated whenever `data`
changes, either through a callback or by editing the table. This
is a read-only property: setting this property will not have any
impact on the table.
- hidden_columns (list of strings; optional):
List of columns ids of the columns that are currently hidden. See
the associated nested prop `columns.hideable`.
- is_focused (boolean; optional):
If True, then the `active_cell` is in a focused state.
- merge_duplicate_headers (boolean; optional):
If True, then column headers that have neighbors with duplicate
names will be merged into a single cell. This will be applied for
single column headers and multi-column headers.
- data_timestamp (number; optional):
The unix timestamp when the data was last edited. Use this
property with other timestamp properties (such as
`n_clicks_timestamp` in `dash_html_components`) to determine which
property has changed within a callback.
- include_headers_on_copy_paste (boolean; default False):
If True, headers are included when copying from the table to
different tabs and elsewhere. Note that headers are ignored when
copying from the table onto itself and between two tables within
the same tab.
- export_columns (a value equal to: 'all', 'visible'; default 'visible'):
Denotes the columns that will be used in the export data file. If
`all`, all columns will be used (visible + hidden). If `visible`,
only the visible columns will be used. Defaults to `visible`.
- export_format (a value equal to: 'csv', 'xlsx', 'none'; default 'none'):
Denotes the type of the export data file, Defaults to `'none'`.
- export_headers (a value equal to: 'none', 'ids', 'names', 'display'; optional):
Denotes the format of the headers in the export data file. If
`'none'`, there will be no header. If `'display'`, then the header
of the data file will be how it is currently displayed. Note that
`'display'` is only supported for `'xlsx'` export_format and will
behave like `'names'` for `'csv'` export format. If `'ids'` or
`'names'`, then the headers of data file will be the column id or
the column names, respectively.
- page_action (a value equal to: 'custom', 'native', 'none'; default 'native'):
`page_action` refers to a mode of the table where not all of the
rows are displayed at once: only a subset are displayed (a
\"page\") and the next subset of rows can viewed by clicking
\"Next\" or \"Previous\" buttons at the bottom of the page.
Pagination is used to improve performance: instead of rendering
all of the rows at once (which can be expensive), we only display
a subset of them. With pagination, we can either page through data
that exists in the table (e.g. page through `10,000` rows in
`data` `100` rows at a time) or we can update the data on-the-fly
with callbacks when the user clicks on the \"Previous\" or
\"Next\" buttons. These modes can be toggled with this
`page_action` parameter: `'native'`: all data is passed to the
table up-front, paging logic is handled by the table; `'custom'`:
data is passed to the table one page at a time, paging logic is
handled via callbacks; `'none'`: disables paging, render all of
the data at once.
- page_current (number; default 0):
`page_current` represents which page the user is on. Use this
property to index through data in your callbacks with backend
paging.
- page_count (number; optional):
`page_count` represents the number of the pages in the paginated
table. This is really only useful when performing backend
pagination, since the front end is able to use the full size of
the table to calculate the number of pages.
- page_size (number; default 250):
`page_size` represents the number of rows that will be displayed
on a particular page when `page_action` is `'custom'` or
`'native'`.
- filter_query (string; default ''):
If `filter_action` is enabled, then the current filtering string
is represented in this `filter_query` property.
- filter_action (dict; default 'none'):
The `filter_action` property controls the behavior of the
`filtering` UI. If `'none'`, then the filtering UI is not
displayed. If `'native'`, then the filtering UI is displayed and
the filtering logic is handled by the table. That is, it is
performed on the data that exists in the `data` property. If
`'custom'`, then the filtering UI is displayed but it is the
responsibility of the developer to program the filtering through a
callback (where `filter_query` or `derived_filter_query_structure`
would be the input and `data` would be the output).
`filter_action` is a a value equal to: 'custom', 'native', 'none'
| dict with keys:
- type (a value equal to: 'custom', 'native'; required)
- operator (a value equal to: 'and', 'or'; optional)
- filter_options (dict; optional):
There are two `filter_options` props in the table. This is the
table-level filter_options prop and there is also the column-level
`filter_options` prop. If the column-level `filter_options` prop
is set it overrides the table-level `filter_options` prop for that
column.
`filter_options` is a dict with keys:
- case (a value equal to: 'sensitive', 'insensitive'; optional):
(default: 'sensitive') Determine whether the applicable filter
relational operators will default to `sensitive` or
`insensitive` comparison.
- placeholder_text (string; optional):
(default: 'filter data...') The filter cell placeholder text.
- sort_action (a value equal to: 'custom', 'native', 'none'; default 'none'):
The `sort_action` property enables data to be sorted on a
per-column basis. If `'none'`, then the sorting UI is not
displayed. If `'native'`, then the sorting UI is displayed and the
sorting logic is handled by the table. That is, it is performed on
the data that exists in the `data` property. If `'custom'`, the
sorting UI is displayed but it is the responsibility of the
developer to program the sorting through a callback (where
`sort_by` would be the input and `data` would be the output).
Clicking on the sort arrows will update the `sort_by` property.
- sort_mode (a value equal to: 'single', 'multi'; default 'single'):
Sorting can be performed across multiple columns (e.g. sort by
country, sort within each country, sort by year) or by a single
column. NOTE - With multi-column sort, it's currently not possible
to determine the order in which the columns were sorted through
the UI. See
[https://github.com/plotly/dash-table/issues/170](https://github.com/plotly/dash-table/issues/170).
- sort_by (list of dicts; optional):
`sort_by` describes the current state of the sorting UI. That is,
if the user clicked on the sort arrow of a column, then this
property will be updated with the column ID and the direction
(`asc` or `desc`) of the sort. For multi-column sorting, this will
be a list of sorting parameters, in the order in which they were
clicked.
`sort_by` is a list of dicts with keys:
- column_id (string; required)
- direction (a value equal to: 'asc', 'desc'; required)
- sort_as_null (list of string | number | booleans; optional):
An array of string, number and boolean values that are treated as
`None` (i.e. ignored and always displayed last) when sorting. This
value will be used by columns without `sort_as_None`. Defaults to
`[]`.
- dropdown (dict; optional):
`dropdown` specifies dropdown options for different columns. Each
entry refers to the column ID. The `clearable` property defines
whether the value can be deleted. The `options` property refers to
the `options` of the dropdown.
`dropdown` is a dict with strings as keys and values of type dict
with keys:
- clearable (boolean; optional)
- options (list of dicts; required)
`options` is a list of dicts with keys:
- label (string; required)
- value (number | string | boolean; required)
- dropdown_conditional (list of dicts; optional):
`dropdown_conditional` specifies dropdown options in various
columns and cells. This property allows you to specify different
dropdowns depending on certain conditions. For example, you may
render different \"city\" dropdowns in a row depending on the
current value in the \"state\" column.
`dropdown_conditional` is a list of dicts with keys:
- clearable (boolean; optional)
- if (dict; optional)
`if` is a dict with keys:
- column_id (string; optional)
- filter_query (string; optional)
- options (list of dicts; required)
`options` is a list of dicts with keys:
- label (string; required)
- value (number | string | boolean; required)
- dropdown_data (list of dicts; optional):
`dropdown_data` specifies dropdown options on a row-by-row,
column-by-column basis. Each item in the array corresponds to the
corresponding dropdowns for the `data` item at the same index.
Each entry in the item refers to the Column ID.
`dropdown_data` is a list of dicts with strings as keys and values
of type dict with keys:
- clearable (boolean; optional)
- options (list of dicts; required)
`options` is a list of dicts with keys:
- label (string; required)
- value (number | string | boolean; required)
- tooltip (dict; optional):
`tooltip` is the column based tooltip configuration applied to all
rows. The key is the column id and the value is a tooltip
configuration. Example: {i: {'value': i, 'use_with: 'both'} for i
in df.columns}.
`tooltip` is a dict with strings as keys and values of type string
| dict with keys:
- delay (number; optional):
Represents the delay in milliseconds before the tooltip is
shown when hovering a cell. This overrides the table's
`tooltip_delay` property. If set to `None`, the tooltip will
be shown immediately.
- duration (number; optional):
represents the duration in milliseconds during which the
tooltip is shown when hovering a cell. This overrides the
table's `tooltip_duration` property. If set to `None`, the
tooltip will not disappear.
- type (a value equal to: 'text', 'markdown'; optional):
refers to the type of tooltip syntax used for the tooltip
generation. Can either be `markdown` or `text`. Defaults to
`text`.
- use_with (a value equal to: 'both', 'data', 'header'; optional):
Refers to whether the tooltip will be shown only on data or
headers. Can be `both`, `data`, `header`. Defaults to `both`.
- value (string; required):
refers to the syntax-based content of the tooltip. This value
is required. Alternatively, the value of the property can also
be a plain string. The `text` syntax will be used in that
case.
- tooltip_conditional (list of dicts; optional):
`tooltip_conditional` represents the tooltip shown for different
columns and cells. This property allows you to specify different
tooltips depending on certain conditions. For example, you may
have different tooltips in the same column based on the value of a
certain data property. Priority is from first to last defined
conditional tooltip in the list. Higher priority (more specific)
conditional tooltips should be put at the beginning of the list.
`tooltip_conditional` is a list of dicts with keys:
- delay (number; optional):
The `delay` represents the delay in milliseconds before the
tooltip is shown when hovering a cell. This overrides the
table's `tooltip_delay` property. If set to `None`, the
tooltip will be shown immediately.
- duration (number; optional):
The `duration` represents the duration in milliseconds during
which the tooltip is shown when hovering a cell. This
overrides the table's `tooltip_duration` property. If set to
`None`, the tooltip will not disappear.
- if (dict; required):
The `if` refers to the condition that needs to be fulfilled in
order for the associated tooltip configuration to be used. If
multiple conditions are defined, all conditions must be met
for the tooltip to be used by a cell.
`if` is a dict with keys:
- column_id (string; optional):
`column_id` refers to the column ID that must be matched.
- filter_query (string; optional):
`filter_query` refers to the query that must evaluate to
True.
- row_index (number | a value equal to: 'odd', 'even'; optional):
`row_index` refers to the index of the row in the source
`data`.
- type (a value equal to: 'text', 'markdown'; optional):
The `type` refers to the type of tooltip syntax used for the
tooltip generation. Can either be `markdown` or `text`.
Defaults to `text`.
- value (string; required):
The `value` refers to the syntax-based content of the tooltip.
This value is required.
- tooltip_data (list of dicts; optional):
`tooltip_data` represents the tooltip shown for different columns
and cells. A list of dicts for which each key is a column id and
the value is a tooltip configuration.
`tooltip_data` is a list of dicts with strings as keys and values
of type string | dict with keys:
- delay (number; optional):
The `delay` represents the delay in milliseconds before the
tooltip is shown when hovering a cell. This overrides the
table's `tooltip_delay` property. If set to `None`, the
tooltip will be shown immediately.
- duration (number; optional):
The `duration` represents the duration in milliseconds during
which the tooltip is shown when hovering a cell. This
overrides the table's `tooltip_duration` property. If set to
`None`, the tooltip will not disappear. Alternatively, the
value of the property can also be a plain string. The `text`
syntax will be used in that case.
- type (a value equal to: 'text', 'markdown'; optional):
For each tooltip configuration, The `type` refers to the type
of tooltip syntax used for the tooltip generation. Can either
be `markdown` or `text`. Defaults to `text`.
- value (string; required):
The `value` refers to the syntax-based content of the tooltip.
This value is required.
- tooltip_header (dict; optional):
`tooltip_header` represents the tooltip shown for each header
column and optionally each header row. Example to show long column
names in a tooltip: {i: i for i in df.columns}. Example to show
different column names in a tooltip: {'Rep': 'Republican', 'Dem':
'Democrat'}. If the table has multiple rows of headers, then use a
list as the value of the `tooltip_header` items.
`tooltip_header` is a dict with strings as keys and values of type
string | dict with keys:
- delay (number; optional):
The `delay` represents the delay in milliseconds before the
tooltip is shown when hovering a cell. This overrides the
table's `tooltip_delay` property. If set to `None`, the
tooltip will be shown immediately.
- duration (number; optional):
The `duration` represents the duration in milliseconds during
which the tooltip is shown when hovering a cell. This
overrides the table's `tooltip_duration` property. If set to
`None`, the tooltip will not disappear. Alternatively, the
value of the property can also be a plain string. The `text`
syntax will be used in that case.
- type (a value equal to: 'text', 'markdown'; optional):
For each tooltip configuration, The `type` refers to the type
of tooltip syntax used for the tooltip generation. Can either
be `markdown` or `text`. Defaults to `text`.
- value (string; required):
The `value` refers to the syntax-based content of the tooltip.
This value is required.
Or list of a value equal to: null | string | dict with keys:
- delay (number; optional)
- duration (number; optional)
- type (a value equal to: 'text', 'markdown'; optional)
- value (string; required)s
- tooltip_delay (number; default 350):
`tooltip_delay` represents the table-wide delay in milliseconds
before the tooltip is shown when hovering a cell. If set to
`None`, the tooltip will be shown immediately. Defaults to 350.
- tooltip_duration (number; default 2000):
`tooltip_duration` represents the table-wide duration in
milliseconds during which the tooltip will be displayed when
hovering a cell. If set to `None`, the tooltip will not disappear.
Defaults to 2000.
- locale_format (dict; optional):
The localization specific formatting information applied to all
columns in the table. This prop is derived from the
[d3.formatLocale](https://github.com/d3/d3-format#formatLocale)
data structure specification. When left unspecified, each
individual nested prop will default to a pre-determined value.
`locale_format` is a dict with keys:
- symbol (list of strings; optional):
(default: ['$', '']). A list of two strings representing the
prefix and suffix symbols. Typically used for currency, and
implemented using d3's currency format, but you can use this
for other symbols such as measurement units.
- decimal (string; optional):
(default: '.'). The string used for the decimal separator.
- group (string; optional):
(default: ','). The string used for the groups separator.
- grouping (list of numbers; optional):
(default: [3]). A list of integers representing the grouping
pattern.
- numerals (list of strings; optional):
A list of ten strings used as replacements for numbers 0-9.
- percent (string; optional):
(default: '%'). The string used for the percentage symbol.
- separate_4digits (boolean; optional):
(default: True). Separate integers with 4-digits or less.
- style_as_list_view (boolean; default False):
If True, then the table will be styled like a list view and not
have borders between the columns.
- fill_width (boolean; default True):
`fill_width` toggles between a set of CSS for two common
behaviors: True: The table container's width will grow to fill the
available space; False: The table container's width will equal the
width of its content.
- markdown_options (dict; default { link_target: '_blank', html: False}):
The `markdown_options` property allows customization of the
markdown cells behavior.
`markdown_options` is a dict with keys:
- link_target (string | a value equal to: '_blank', '_parent', '_self', '_top'; optional):
(default: '_blank'). The link's behavior (_blank opens the
link in a new tab, _parent opens the link in the parent frame,
_self opens the link in the current tab, and _top opens the
link in the top frame) or a string.
- html (boolean; optional):
(default: False) If True, html may be used in markdown cells
Be careful enabling html if the content being rendered can
come from an untrusted user, as this may create an XSS
vulnerability.
- css (list of dicts; optional):
The `css` property is a way to embed CSS selectors and rules onto
the page. We recommend starting with the `style_*` properties
before using this `css` property. Example: [ {\"selector\":
\".dash-spreadsheet\", \"rule\": 'font-family: \"monospace\"'} ].
`css` is a list of dicts with keys:
- selector (string; required)
- rule (string; required)
- style_table (dict; optional):
CSS styles to be applied to the outer `table` container. This is
commonly used for setting properties like the width or the height
of the table.
- style_cell (dict; optional):
CSS styles to be applied to each individual cell of the table.
This includes the header cells, the `data` cells, and the filter
cells.
- style_data (dict; optional):
CSS styles to be applied to each individual data cell. That is,
unlike `style_cell`, it excludes the header and filter cells.
- style_filter (dict; optional):
CSS styles to be applied to the filter cells. Note that this may
change in the future as we build out a more complex filtering UI.
- style_header (dict; optional):
CSS styles to be applied to each individual header cell. That is,
unlike `style_cell`, it excludes the `data` and filter cells.
- style_cell_conditional (list of dicts; optional):
Conditional CSS styles for the cells. This can be used to apply
styles to cells on a per-column basis.
`style_cell_conditional` is a list of dicts with keys:
- if (dict; optional)
`if` is a dict with keys:
- column_id (string | list of strings; optional)
- column_type (a value equal to: 'any', 'numeric', 'text', 'datetime'; optional)
- style_data_conditional (list of dicts; optional):
Conditional CSS styles for the data cells. This can be used to
apply styles to data cells on a per-column basis.
`style_data_conditional` is a list of dicts with keys:
- if (dict; optional)
`if` is a dict with keys:
- column_id (string | list of strings; optional)
- column_type (a value equal to: 'any', 'numeric', 'text', 'datetime'; optional)
- filter_query (string; optional)
- state (a value equal to: 'active', 'selected'; optional)
- row_index (number | a value equal to: 'odd', 'even' | list of numbers; optional)
- column_editable (boolean; optional)
- style_filter_conditional (list of dicts; optional):
Conditional CSS styles for the filter cells. This can be used to
apply styles to filter cells on a per-column basis.
`style_filter_conditional` is a list of dicts with keys:
- if (dict; optional)
`if` is a dict with keys:
- column_id (string | list of strings; optional)
- column_type (a value equal to: 'any', 'numeric', 'text', 'datetime'; optional)
- column_editable (boolean; optional)
- style_header_conditional (list of dicts; optional):
Conditional CSS styles for the header cells. This can be used to
apply styles to header cells on a per-column basis.
`style_header_conditional` is a list of dicts with keys:
- if (dict; optional)
`if` is a dict with keys:
- column_id (string | list of strings; optional)
- column_type (a value equal to: 'any', 'numeric', 'text', 'datetime'; optional)
- header_index (number | list of numbers | a value equal to: 'odd', 'even'; optional)
- column_editable (boolean; optional)
- virtualization (boolean; default False):
This property tells the table to use virtualization when
rendering. Assumptions are that: the width of the columns is
fixed; the height of the rows is always the same; and runtime
styling changes will not affect width and height vs. first
rendering.
- derived_filter_query_structure (dict; optional):
This property represents the current structure of `filter_query`
as a tree structure. Each node of the query structure has: type
(string; required): 'open-block', 'logical-operator',
'relational-operator', 'unary-operator', or 'expression';
subType (string; optional): 'open-block': '()',
'logical-operator': '&&', '||', 'relational-operator': '=',
'>=', '>', '<=', '<', '!=', 'contains', 'unary-operator': '!',
'is bool', 'is even', 'is nil', 'is num', 'is object', 'is odd',
'is prime', 'is str', 'expression': 'value', 'field'; value
(any): 'expression, value': passed value, 'expression, field':
the field/prop name. block (nested query structure; optional).
left (nested query structure; optional). right (nested query
structure; optional). If the query is invalid or empty, the
`derived_filter_query_structure` will be `None`.
- derived_viewport_data (list of dicts; optional):
This property represents the current state of `data` on the
current page. This property will be updated on paging, sorting,
and filtering.
- derived_viewport_indices (list of numbers; optional):
`derived_viewport_indices` indicates the order in which the
original rows appear after being filtered, sorted, and/or paged.
`derived_viewport_indices` contains indices for the current page,
while `derived_virtual_indices` contains indices across all pages.
- derived_viewport_row_ids (list of string | numbers; optional):
`derived_viewport_row_ids` lists row IDs in the order they appear
after being filtered, sorted, and/or paged.
`derived_viewport_row_ids` contains IDs for the current page,
while `derived_virtual_row_ids` contains IDs across all pages.
- derived_viewport_selected_columns (list of strings; optional):
`derived_viewport_selected_columns` contains the ids of the
`selected_columns` that are not currently hidden.
- derived_viewport_selected_rows (list of numbers; optional):
`derived_viewport_selected_rows` represents the indices of the
`selected_rows` from the perspective of the
`derived_viewport_indices`.
- derived_viewport_selected_row_ids (list of string | numbers; optional):
`derived_viewport_selected_row_ids` represents the IDs of the
`selected_rows` on the currently visible page.
- derived_virtual_data (list of dicts; optional):
This property represents the visible state of `data` across all
pages after the front-end sorting and filtering as been applied.
- derived_virtual_indices (list of numbers; optional):
`derived_virtual_indices` indicates the order in which the
original rows appear after being filtered and sorted.
`derived_viewport_indices` contains indices for the current page,
while `derived_virtual_indices` contains indices across all pages.
- derived_virtual_row_ids (list of string | numbers; optional):
`derived_virtual_row_ids` indicates the row IDs in the order in
which they appear after being filtered and sorted.
`derived_viewport_row_ids` contains IDs for the current page,
while `derived_virtual_row_ids` contains IDs across all pages.
- derived_virtual_selected_rows (list of numbers; optional):
`derived_virtual_selected_rows` represents the indices of the
`selected_rows` from the perspective of the
`derived_virtual_indices`.
- derived_virtual_selected_row_ids (list of string | numbers; optional):
`derived_virtual_selected_row_ids` represents the IDs of the
`selected_rows` as they appear after filtering and sorting, across
all pages.
- id (string; optional):
The ID of the table.
- loading_state (dict; optional):
Object that holds the loading state object coming from
dash-renderer.
`loading_state` is a dict with keys:
- is_loading (boolean; optional):
Determines if the component is loading or not.
- prop_name (string; optional):
Holds which property is loading.
- component_name (string; optional):
Holds the name of the component that is loading.
- persistence (boolean | string | number; optional):
Used to allow user interactions in this component to be persisted
when the component - or the page - is refreshed. If `persisted` is
truthy and hasn't changed from its previous value, any
`persisted_props` that the user has changed while using the app
will keep those changes, as long as the new prop value also
matches what was given originally. Used in conjunction with
`persistence_type` and `persisted_props`.
- persisted_props (list of a value equal to: 'columns.name', 'data', 'filter_query', 'hidden_columns', 'page_current', 'selected_columns', 'selected_rows', 'sort_by's; default [ 'columns.name', 'filter_query', 'hidden_columns', 'page_current', 'selected_columns', 'selected_rows', 'sort_by']):
Properties whose user interactions will persist after refreshing
the component or the page.
- persistence_type (a value equal to: 'local', 'session', 'memory'; default 'local'):
Where persisted user changes will be stored: memory: only kept in
memory, reset on page refresh. local: window.localStorage, data is
kept after the browser quit. session: window.sessionStorage, data
is cleared once the browser quit."""
_children_props = []
_base_nodes = ["children"]
_namespace = "dash_table"
_type = "DataTable"
ColumnsFilterOptions = TypedDict(
"ColumnsFilterOptions",
{
"case": NotRequired[Literal["sensitive", "insensitive"]],
"placeholder_text": NotRequired[str],
},
)
ColumnsFormatLocale = TypedDict(
"ColumnsFormatLocale",
{
"symbol": NotRequired[typing.Sequence[str]],
"decimal": NotRequired[str],
"group": NotRequired[str],
"grouping": NotRequired[typing.Sequence[NumberType]],
"numerals": NotRequired[typing.Sequence[str]],
"percent": NotRequired[str],
"separate_4digits": NotRequired[bool],
},
)
ColumnsFormat = TypedDict(
"ColumnsFormat",
{
"locale": NotRequired["ColumnsFormatLocale"],
"nully": NotRequired[typing.Any],
"prefix": NotRequired[NumberType],
"specifier": NotRequired[str],
},
)
ColumnsOnChange = TypedDict(
"ColumnsOnChange",
{
"action": NotRequired[Literal["coerce", "none", "validate"]],
"failure": NotRequired[Literal["accept", "default", "reject"]],
},
)
ColumnsValidation = TypedDict(
"ColumnsValidation",
{
"allow_null": NotRequired[bool],
"default": NotRequired[typing.Any],
"allow_YY": NotRequired[bool],
},
)
Columns = TypedDict(
"Columns",
{
"id": str,
"name": typing.Union[str, typing.Sequence[str]],
"type": NotRequired[Literal["any", "numeric", "text", "datetime"]],
"presentation": NotRequired[Literal["input", "dropdown", "markdown"]],
"selectable": NotRequired[
typing.Union[Literal["first", "last"], bool, typing.Sequence[bool]]
],
"clearable": NotRequired[
typing.Union[Literal["first", "last"], bool, typing.Sequence[bool]]
],
"deletable": NotRequired[
typing.Union[Literal["first", "last"], bool, typing.Sequence[bool]]
],
"editable": NotRequired[bool],
"hideable": NotRequired[
typing.Union[Literal["first", "last"], bool, typing.Sequence[bool]]
],
"renamable": NotRequired[
typing.Union[Literal["first", "last"], bool, typing.Sequence[bool]]
],
"filter_options": NotRequired["ColumnsFilterOptions"],
"format": NotRequired["ColumnsFormat"],
"on_change": NotRequired["ColumnsOnChange"],
"sort_as_null": NotRequired[
typing.Sequence[typing.Union[str, NumberType, bool]]
],
"validation": NotRequired["ColumnsValidation"],
},
)
FixedColumns = TypedDict(
"FixedColumns", {"data": NotRequired[NumberType], "headers": NotRequired[bool]}
)
FixedRows = TypedDict(
"FixedRows", {"data": NotRequired[NumberType], "headers": NotRequired[bool]}
)
ActiveCell = TypedDict(
"ActiveCell",
{
"row": NotRequired[NumberType],
"column": NotRequired[NumberType],
"row_id": NotRequired[typing.Union[str, NumberType]],
"column_id": NotRequired[str],
},
)
SelectedCells = TypedDict(
"SelectedCells",
{
"row": NotRequired[NumberType],
"column": NotRequired[NumberType],
"row_id": NotRequired[typing.Union[str, NumberType]],
"column_id": NotRequired[str],
},
)
StartCell = TypedDict(
"StartCell",
{
"row": NotRequired[NumberType],
"column": NotRequired[NumberType],
"row_id": NotRequired[typing.Union[str, NumberType]],
"column_id": NotRequired[str],
},
)
EndCell = TypedDict(
"EndCell",
{
"row": NotRequired[NumberType],
"column": NotRequired[NumberType],
"row_id": NotRequired[typing.Union[str, NumberType]],
"column_id": NotRequired[str],
},
)
FilterAction = TypedDict(
"FilterAction",
{
"type": Literal["custom", "native"],
"operator": NotRequired[Literal["and", "or"]],
},
)
FilterOptions = TypedDict(
"FilterOptions",
{
"case": NotRequired[Literal["sensitive", "insensitive"]],
"placeholder_text": NotRequired[str],
},
)
SortBy = TypedDict(
"SortBy", {"column_id": str, "direction": Literal["asc", "desc"]}
)
DropdownOptions = TypedDict(
"DropdownOptions", {"label": str, "value": typing.Union[NumberType, str, bool]}
)
Dropdown = TypedDict(
"Dropdown",
{"clearable": NotRequired[bool], "options": typing.Sequence["DropdownOptions"]},
)
DropdownConditionalIf = TypedDict(
"DropdownConditionalIf",
{"column_id": NotRequired[str], "filter_query": NotRequired[str]},
)
DropdownConditionalOptions = TypedDict(
"DropdownConditionalOptions",
{"label": str, "value": typing.Union[NumberType, str, bool]},
)
DropdownConditional = TypedDict(
"DropdownConditional",
{
"clearable": NotRequired[bool],
"if": NotRequired["DropdownConditionalIf"],
"options": typing.Sequence["DropdownConditionalOptions"],
},
)
DropdownDataOptions = TypedDict(
"DropdownDataOptions",
{"label": str, "value": typing.Union[NumberType, str, bool]},
)
DropdownData = TypedDict(
"DropdownData",
{
"clearable": NotRequired[bool],
"options": typing.Sequence["DropdownDataOptions"],
},
)
Tooltip = TypedDict(
"Tooltip",
{
"delay": NotRequired[NumberType],
"duration": NotRequired[NumberType],
"type": NotRequired[Literal["text", "markdown"]],
"use_with": NotRequired[Literal["both", "data", "header"]],
"value": str,
},
)
TooltipConditionalIf = TypedDict(
"TooltipConditionalIf",
{
"column_id": NotRequired[str],
"filter_query": NotRequired[str],
"row_index": NotRequired[typing.Union[NumberType, Literal["odd", "even"]]],
},
)
TooltipConditional = TypedDict(
"TooltipConditional",
{
"delay": NotRequired[NumberType],
"duration": NotRequired[NumberType],
"if": "TooltipConditionalIf",
"type": NotRequired[Literal["text", "markdown"]],
"value": str,
},
)
TooltipData = TypedDict(
"TooltipData",
{
"delay": NotRequired[NumberType],
"duration": NotRequired[NumberType],
"type": NotRequired[Literal["text", "markdown"]],
"value": str,
},
)
TooltipHeader = TypedDict(
"TooltipHeader",
{
"delay": NotRequired[NumberType],
"duration": NotRequired[NumberType],
"type": NotRequired[Literal["text", "markdown"]],
"value": str,
},
)
LocaleFormat = TypedDict(
"LocaleFormat",
{
"symbol": NotRequired[typing.Sequence[str]],
"decimal": NotRequired[str],
"group": NotRequired[str],
"grouping": NotRequired[typing.Sequence[NumberType]],
"numerals": NotRequired[typing.Sequence[str]],
"percent": NotRequired[str],
"separate_4digits": NotRequired[bool],
},
)
MarkdownOptions = TypedDict(
"MarkdownOptions",
{
"link_target": NotRequired[
typing.Union[str, Literal["_blank", "_parent", "_self", "_top"]]
],
"html": NotRequired[bool],
},
)
Css = TypedDict("Css", {"selector": str, "rule": str})
StyleCellConditionalIf = TypedDict(
"StyleCellConditionalIf",
{
"column_id": NotRequired[typing.Union[str, typing.Sequence[str]]],
"column_type": NotRequired[Literal["any", "numeric", "text", "datetime"]],
},
)
StyleCellConditional = TypedDict(
"StyleCellConditional", {"if": NotRequired["StyleCellConditionalIf"]}
)
StyleDataConditionalIf = TypedDict(
"StyleDataConditionalIf",
{
"column_id": NotRequired[typing.Union[str, typing.Sequence[str]]],
"column_type": NotRequired[Literal["any", "numeric", "text", "datetime"]],
"filter_query": NotRequired[str],
"state": NotRequired[Literal["active", "selected"]],
"row_index": NotRequired[
typing.Union[
NumberType, Literal["odd", "even"], typing.Sequence[NumberType]
]
],
"column_editable": NotRequired[bool],
},
)
StyleDataConditional = TypedDict(
"StyleDataConditional", {"if": NotRequired["StyleDataConditionalIf"]}
)
StyleFilterConditionalIf = TypedDict(
"StyleFilterConditionalIf",
{
"column_id": NotRequired[typing.Union[str, typing.Sequence[str]]],
"column_type": NotRequired[Literal["any", "numeric", "text", "datetime"]],
"column_editable": NotRequired[bool],
},
)
StyleFilterConditional = TypedDict(
"StyleFilterConditional", {"if": NotRequired["StyleFilterConditionalIf"]}
)
StyleHeaderConditionalIf = TypedDict(
"StyleHeaderConditionalIf",
{
"column_id": NotRequired[typing.Union[str, typing.Sequence[str]]],
"column_type": NotRequired[Literal["any", "numeric", "text", "datetime"]],
"header_index": NotRequired[
typing.Union[
NumberType, typing.Sequence[NumberType], Literal["odd", "even"]
]
],
"column_editable": NotRequired[bool],
},
)
StyleHeaderConditional = TypedDict(
"StyleHeaderConditional", {"if": NotRequired["StyleHeaderConditionalIf"]}
)
LoadingState = TypedDict(
"LoadingState",
{
"is_loading": NotRequired[bool],
"prop_name": NotRequired[str],
"component_name": NotRequired[str],
},
)
def __init__(
self,
data: typing.Optional[
typing.Sequence[
typing.Dict[
typing.Union[str, float, int], typing.Union[str, NumberType, bool]
]
]
] = None,
columns: typing.Optional[typing.Sequence["Columns"]] = None,
editable: typing.Optional[bool] = None,
fixed_columns: typing.Optional["FixedColumns"] = None,
fixed_rows: typing.Optional["FixedRows"] = None,
column_selectable: typing.Optional[Literal["single", "multi", False]] = None,
cell_selectable: typing.Optional[bool] = None,
row_selectable: typing.Optional[Literal["single", "multi", False]] = None,
row_deletable: typing.Optional[bool] = None,
active_cell: typing.Optional["ActiveCell"] = None,
selected_cells: typing.Optional[typing.Sequence["SelectedCells"]] = None,
selected_rows: typing.Optional[typing.Sequence[NumberType]] = None,
selected_columns: typing.Optional[typing.Sequence[str]] = None,
selected_row_ids: typing.Optional[
typing.Sequence[typing.Union[str, NumberType]]
] = None,
start_cell: typing.Optional["StartCell"] = None,
end_cell: typing.Optional["EndCell"] = None,
data_previous: typing.Optional[typing.Sequence[dict]] = None,
hidden_columns: typing.Optional[typing.Sequence[str]] = None,
is_focused: typing.Optional[bool] = None,
merge_duplicate_headers: typing.Optional[bool] = None,
data_timestamp: typing.Optional[NumberType] = None,
include_headers_on_copy_paste: typing.Optional[bool] = None,
export_columns: typing.Optional[Literal["all", "visible"]] = None,
export_format: typing.Optional[Literal["csv", "xlsx", "none"]] = None,
export_headers: typing.Optional[
Literal["none", "ids", "names", "display"]
] = None,
page_action: typing.Optional[Literal["custom", "native", "none"]] = None,
page_current: typing.Optional[NumberType] = None,
page_count: typing.Optional[NumberType] = None,
page_size: typing.Optional[NumberType] = None,
filter_query: typing.Optional[str] = None,
filter_action: typing.Optional[
typing.Union[Literal["custom", "native", "none"], "FilterAction"]
] = None,
filter_options: typing.Optional["FilterOptions"] = None,
sort_action: typing.Optional[Literal["custom", "native", "none"]] = None,
sort_mode: typing.Optional[Literal["single", "multi"]] = None,
sort_by: typing.Optional[typing.Sequence["SortBy"]] = None,
sort_as_null: typing.Optional[
typing.Sequence[typing.Union[str, NumberType, bool]]
] = None,
dropdown: typing.Optional[
typing.Dict[typing.Union[str, float, int], "Dropdown"]
] = None,
dropdown_conditional: typing.Optional[
typing.Sequence["DropdownConditional"]
] = None,
dropdown_data: typing.Optional[
typing.Sequence[typing.Dict[typing.Union[str, float, int], "DropdownData"]]
] = None,
tooltip: typing.Optional[
typing.Dict[typing.Union[str, float, int], typing.Union[str, "Tooltip"]]
] = None,
tooltip_conditional: typing.Optional[
typing.Sequence["TooltipConditional"]
] = None,
tooltip_data: typing.Optional[
typing.Sequence[
typing.Dict[
typing.Union[str, float, int], typing.Union[str, "TooltipData"]
]
]
] = None,
tooltip_header: typing.Optional[
typing.Dict[
typing.Union[str, float, int],
typing.Union[
str,
"TooltipHeader",
typing.Sequence[typing.Union[Literal[None], str, "TooltipHeader"]],
],
]
] = None,
tooltip_delay: typing.Optional[NumberType] = None,
tooltip_duration: typing.Optional[NumberType] = None,
locale_format: typing.Optional["LocaleFormat"] = None,
style_as_list_view: typing.Optional[bool] = None,
fill_width: typing.Optional[bool] = None,
markdown_options: typing.Optional["MarkdownOptions"] = None,
css: typing.Optional[typing.Sequence["Css"]] = None,
style_table: typing.Optional[dict] = None,
style_cell: typing.Optional[dict] = None,
style_data: typing.Optional[dict] = None,
style_filter: typing.Optional[dict] = None,
style_header: typing.Optional[dict] = None,
style_cell_conditional: typing.Optional[
typing.Sequence["StyleCellConditional"]
] = None,
style_data_conditional: typing.Optional[
typing.Sequence["StyleDataConditional"]
] = None,
style_filter_conditional: typing.Optional[
typing.Sequence["StyleFilterConditional"]
] = None,
style_header_conditional: typing.Optional[
typing.Sequence["StyleHeaderConditional"]
] = None,
virtualization: typing.Optional[bool] = None,
derived_filter_query_structure: typing.Optional[dict] = None,
derived_viewport_data: typing.Optional[typing.Sequence[dict]] = None,
derived_viewport_indices: typing.Optional[typing.Sequence[NumberType]] = None,
derived_viewport_row_ids: typing.Optional[
typing.Sequence[typing.Union[str, NumberType]]
] = None,
derived_viewport_selected_columns: typing.Optional[typing.Sequence[str]] = None,
derived_viewport_selected_rows: typing.Optional[
typing.Sequence[NumberType]
] = None,
derived_viewport_selected_row_ids: typing.Optional[
typing.Sequence[typing.Union[str, NumberType]]
] = None,
derived_virtual_data: typing.Optional[typing.Sequence[dict]] = None,
derived_virtual_indices: typing.Optional[typing.Sequence[NumberType]] = None,
derived_virtual_row_ids: typing.Optional[
typing.Sequence[typing.Union[str, NumberType]]
] = None,
derived_virtual_selected_rows: typing.Optional[
typing.Sequence[NumberType]
] = None,
derived_virtual_selected_row_ids: typing.Optional[
typing.Sequence[typing.Union[str, NumberType]]
] = None,
id: typing.Optional[typing.Union[str, dict]] = None,
loading_state: typing.Optional["LoadingState"] = None,
persistence: typing.Optional[typing.Union[bool, str, NumberType]] = None,
persisted_props: typing.Optional[
typing.Sequence[
Literal[
"columns.name",
"data",
"filter_query",
"hidden_columns",
"page_current",
"selected_columns",
"selected_rows",
"sort_by",
]
]
] = None,
persistence_type: typing.Optional[Literal["local", "session", "memory"]] = None,
**kwargs
):
self._prop_names = [
"data",
"columns",
"editable",
"fixed_columns",
"fixed_rows",
"column_selectable",
"cell_selectable",
"row_selectable",
"row_deletable",
"active_cell",
"selected_cells",
"selected_rows",
"selected_columns",
"selected_row_ids",
"start_cell",
"end_cell",
"data_previous",
"hidden_columns",
"is_focused",
"merge_duplicate_headers",
"data_timestamp",
"include_headers_on_copy_paste",
"export_columns",
"export_format",
"export_headers",
"page_action",
"page_current",
"page_count",
"page_size",
"filter_query",
"filter_action",
"filter_options",
"sort_action",
"sort_mode",
"sort_by",
"sort_as_null",
"dropdown",
"dropdown_conditional",
"dropdown_data",
"tooltip",
"tooltip_conditional",
"tooltip_data",
"tooltip_header",
"tooltip_delay",
"tooltip_duration",
"locale_format",
"style_as_list_view",
"fill_width",
"markdown_options",
"css",
"style_table",
"style_cell",
"style_data",
"style_filter",
"style_header",
"style_cell_conditional",
"style_data_conditional",
"style_filter_conditional",
"style_header_conditional",
"virtualization",
"derived_filter_query_structure",
"derived_viewport_data",
"derived_viewport_indices",
"derived_viewport_row_ids",
"derived_viewport_selected_columns",
"derived_viewport_selected_rows",
"derived_viewport_selected_row_ids",
"derived_virtual_data",
"derived_virtual_indices",
"derived_virtual_row_ids",
"derived_virtual_selected_rows",
"derived_virtual_selected_row_ids",
"id",
"loading_state",
"persistence",
"persisted_props",
"persistence_type",
]
self._valid_wildcard_attributes = []
self.available_properties = [
"data",
"columns",
"editable",
"fixed_columns",
"fixed_rows",
"column_selectable",
"cell_selectable",
"row_selectable",
"row_deletable",
"active_cell",
"selected_cells",
"selected_rows",
"selected_columns",
"selected_row_ids",
"start_cell",
"end_cell",
"data_previous",
"hidden_columns",
"is_focused",
"merge_duplicate_headers",
"data_timestamp",
"include_headers_on_copy_paste",
"export_columns",
"export_format",
"export_headers",
"page_action",
"page_current",
"page_count",
"page_size",
"filter_query",
"filter_action",
"filter_options",
"sort_action",
"sort_mode",
"sort_by",
"sort_as_null",
"dropdown",
"dropdown_conditional",
"dropdown_data",
"tooltip",
"tooltip_conditional",
"tooltip_data",
"tooltip_header",
"tooltip_delay",
"tooltip_duration",
"locale_format",
"style_as_list_view",
"fill_width",
"markdown_options",
"css",
"style_table",
"style_cell",
"style_data",
"style_filter",
"style_header",
"style_cell_conditional",
"style_data_conditional",
"style_filter_conditional",
"style_header_conditional",
"virtualization",
"derived_filter_query_structure",
"derived_viewport_data",
"derived_viewport_indices",
"derived_viewport_row_ids",
"derived_viewport_selected_columns",
"derived_viewport_selected_rows",
"derived_viewport_selected_row_ids",
"derived_virtual_data",
"derived_virtual_indices",
"derived_virtual_row_ids",
"derived_virtual_selected_rows",
"derived_virtual_selected_row_ids",
"id",
"loading_state",
"persistence",
"persisted_props",
"persistence_type",
]
self.available_wildcard_properties = []
_explicit_args = kwargs.pop("_explicit_args")
_locals = locals()
_locals.update(kwargs) # For wildcard attrs and excess named props
args = {k: _locals[k] for k in _explicit_args}
super(DataTable, self).__init__(**args)
setattr(DataTable, "__init__", _explicitize_args(DataTable.__init__))
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