dash_charts.datatable⚓︎
DataTable Base Classes.
View Source
"""DataTable Base Classes."""
from dash import dash_table
# TODO: See pattern mathing callbacks for adding buttons (to show modal) to datatables
# https://dash.plotly.com/pattern-matching-callbacks
# PLANNED: see conditional formatting: https://dash.plotly.com/datatable/conditional-formatting
# PLANNED: These methods may be replaced in a future version of Dash
# Currently, edge case when column is string, but filter could be a number
# See: https://dash.plot.ly/datatable/callbacks & https://github.com/plotly/dash-table/issues/441
OPERATORS = [
['ge ', '>='],
['le ', '<='],
['lt ', '<'],
['gt ', '>'],
['ne ', '!='],
['eq ', '='],
['contains '],
['datestartswith '],
]
"""List of lists containing each possible filter string."""
def split_filter_part(filter_part): # noqa: CCR001
"""Split the filter into `(name, operator, value)` components.
Based on `Backend Paging with Filtering`: https://dash.plot.ly/datatable/callbacks
Args:
filter_part: string filter query
Returns:
tuple: `(name, operator, value)` which could be all None if no match was found
"""
for operator_type in OPERATORS:
for operator in operator_type:
if operator in filter_part:
name_part, value_part = filter_part.split(operator, 1)
name = name_part[name_part.find('{') + 1: name_part.rfind('}')]
value_part = value_part.strip()
v0 = value_part[0]
if (v0 == value_part[-1] and v0 in ("'", '"', '`')):
value = value_part[1: -1].replace(f'\\{v0}', v0)
else:
try:
value = float(value_part)
except ValueError:
value = value_part
# Word operators need spaces after them in the filter string, but we don't want these later
return (name, operator_type[0].strip(), value)
return [None, None, None]
def apply_datatable_filters(df_table, filter_query):
"""Filter a dataframe based on Dash datatable filterquery.
Based on `Backend Paging with Filtering`: https://dash.plot.ly/datatable/callbacks
Args:
df_table: pandas dataframe to filter
filter_query: Dash datatable string filter query
Returns:
dataframe: filtered dataframe
"""
filtering_expressions = filter_query.split(' && ')
for filter_part in filtering_expressions:
col_name, operator, filter_value = split_filter_part(filter_part)
if operator in ('eq', 'ne', 'lt', 'le', 'gt', 'ge'):
# these operators match pandas series operator method names
df_table = df_table.loc[getattr(df_table[col_name], operator)(filter_value)]
elif operator == 'contains':
df_table = df_table.loc[df_table[col_name].str.contains(filter_value)]
elif operator == 'datestartswith':
# this is a simplification of the front-end filtering logic,
# only works with complete fields in standard format
df_table = df_table.loc[df_table[col_name].str.startswith(filter_value)]
return df_table
# PLANNED: Maybe move parameters to attr.ib classes?
class BaseDataTable: # noqa: H601
"""Base Class for Data Tables."""
filter_summary = """Table Filter Syntax:
Full documentation at: [https://dash.plot.ly/datatable/filtering](https://dash.plot.ly/datatable/filtering)
- `eq`: exact match (applies to number columns and will try to convert string to number)
- `contains`: search for exact (case-sensitive) substring in each cell
- `datestartswith`: matches partial datetime. For example, datestartswith `2018-03-01` will match `2018-03-01 12:59`
but not `2018-03`
- `ne`, `gt`, `ge`, `lt`, `le`: comparison operators for not equal, greater than, greater or equal, less than, etc.
Applies to numbers and string columns (uses numbers, symbols, uppercase letter, lowercase letters)
Press enter of tab to apply the filter"""
"""Markdown text explaining dash_table.DataTable filtering rules with link to full documentation."""
# dash_table.DataTable Parameters. Documentation: https://dash.plot.ly/datatable/reference
style_table = None
"""DataTable.style_table dictionary. Default enables overflowX scroll. Set in `initialize_mutables`."""
css = None
"""DataTable.css list. Use the style_* properties first. Set in `initialize_mutables`.
Default sets row margin to zero to fix a negative margin issue when using dash_table and Bootstrap
See: https://github.com/facultyai/dash-bootstrap-components/issues/334
Also sets other various style tweaks to highlight the filter icons on hover, etc.
"""
style_cell = None
"""DataTable.style_cell dictionary. Default is empty dictionary. Set in `initialize_mutables`."""
style_cell_conditional = None
"""DataTable.style_cell_conditional list. Default is empty list. Set in `initialize_mutables`."""
style_data = None
"""DataTable.style_data dictionary. Default is empty dictionary. Set in `initialize_mutables`."""
style_data_conditional = None
"""DataTable.style_data_conditional list. Default is for odd rows to have an off-white background (zebra stripe).
Set in `initialize_mutables`
"""
style_header = None
"""DataTable.style_header dictionary. Default is bold and off-white background. Set in `initialize_mutables`."""
style_header_conditional = None
"""DataTable.style_header_conditional list. Default is empty list. Set in `initialize_mutables`."""
style_filter = None
"""DataTable.style_filter dictionary. Default is empty dictionary. Set in `initialize_mutables`."""
style_filter_conditional = None
"""DataTable.style_filter_conditional list. Default is empty list. Set in `initialize_mutables`."""
column_selectable = None
"""DataTable.column_selectable. Default is `None`."""
column_kwarg_lookup = None
"""Lookup for keyword arguments for each column allowing deletable, selectable, etc. to be set per column."""
export_format = 'none'
"""DataTable.export_format. Default is `'none'`. Could be one of `(csv, xlsx)`."""
export_headers = 'names'
"""DataTable.export_headers. Default is `'names'`. See documentation."""
filter_action = 'native'
"""DataTable.filter_action. Default is `'native'`."""
page_size = 25
"""DataTable.page_size. Default is `'25'`."""
row_selectable = None
"""DataTable.row_selectable. Default is `None`."""
style_as_list_view = False
"""DataTable.style_as_list_view. Default is False."""
sort_action = 'native'
"""DataTable.sort_action. Default is `'native'`."""
sort_mode = 'single'
"""DataTable.sort_mode. Default is `'single'`."""
# CSS Variables
text_color = '#333333'
"""Default text color."""
background_color = '#ffffff'
"""Default background color."""
zebra_color = '#f9f9f9'
"""Default background color for odd rows (zebra-stripe)."""
selected_cell_color = '#eaeaea'
"""Default color for selected cells."""
def __init__(self):
"""Initialize class."""
self.initialize_mutables()
def initialize_mutables(self):
"""Initialize the mutable data members to prevent modifying one attribute and impacting all instances."""
self.style_table = {'overflowX': 'scroll'}
self.css = [
# Fix width when overflow is True and using dash_bootstrap_components
{'selector': '.row', 'rule': 'margin: 0'},
# Based on: https://community.plot.ly/t/dash-table-datatable-styling-examples/15594/
# Align the select icon to the left and the sort icon to the right
{
'selector': 'th.dash-header div',
'rule': 'display: flex; align-items: center;',
},
{
'selector': 'th.dash-header div span.column-header--select',
'rule': 'order: 1; flex-shrink: 5; text-align: left;',
},
{
'selector': 'th.dash-header div span.column-header-name',
'rule': 'order: 2; flex-grow: 5; text-align: center;',
},
{
'selector': 'th.dash-header div span.column-header--sort',
'rule': 'order: 3; flex-shrink: 5; text-align: right;',
},
# Remove excess borders to better match JQuery DataTables styling
# (Some border styles don't appear to work from `self.style_header`)
{'selector': 'th.dash-filter', 'rule': 'border-bottom-color: rgb(17, 17, 17) !important;'},
]
self.style_cell = {
'backgroundColor': self.background_color,
'borderStyle': f'1px solid {self.zebra_color}',
'color': self.text_color,
}
self.style_cell_conditional = []
self.style_data = {}
self.style_data_conditional = [
{'if': {'row_index': 'even'}, 'backgroundColor': self.zebra_color},
]
self.style_header = {
'borderLeft': 'none',
'borderRight': 'none',
'borderTop': 'none',
'fontWeight': 'bold',
}
self.style_header_conditional = []
self.style_filter = {
'borderBottomColor': 'rgb(17, 17, 17)',
}
self.style_filter_conditional = []
self.initialize_column_kwarg_lookup() # Must be called last
def initialize_column_kwarg_lookup(self):
"""Initialize the column lookup based on the other mutables.
Documentation: https://dash.plot.ly/datatable/reference
Additional kwargs not set in default lookup:
- clearable, deletable, editable, hideable, renamable, format, presentation, on_change, sort_as_null,
validation, type
"""
self.column_kwarg_lookup = {
'default_kwargs': {
'selectable': True,
},
}
def create_table(self, df_raw, columns=None, **kwargs_datatable):
"""Create the dash_table.DataTable.
Args:
df_raw: data to pass to datatable
columns: list of column names to display. Default is None to use all columns from df_raw
kwargs_datatable: keyword arguments to pass to the datatable
Returns:
DataTable: returns dash_table.DataTable object
"""
if columns is None:
columns = df_raw.columns
return dash_table.DataTable(**self._create_datatable(df_raw, columns), **kwargs_datatable)
def format_datatable_columns(self, df_raw, columns):
"""Return a list of column names formatted for a dash_table. Uses `self.self.column_name_kwarg_lookup`.
Args:
df_raw: data to pass to datatable
columns: list of strings or None
Returns:
list: of dict with keys `(name, id, deleteable, selectable)` in order of df_raw columns
"""
return [
{'name': col, 'id': col, **self.column_kwarg_lookup.get(col, self.column_kwarg_lookup['default_kwargs'])}
for col in df_raw.columns if (columns is None or col in columns)
]
def _create_datatable(self, df_raw, columns, **table_kwargs):
"""Return dictionary of keyword arguments for datatable.
Args:
df_raw: data to pass to datatable
columns: will auto format list of string column names to display or use list of dicts
table_kwargs: additional keyword arguments to pass to datatable, such as id
Returns:
dict: keys include `(columns, data)` and all data members
"""
return {
'columns': self.format_datatable_columns(df_raw, columns) if isinstance(columns[0], str) else columns,
'data': (df_raw.loc[:, columns] if columns is not None else df_raw).to_dict('records'),
# Add all datamembers
'css': self.css,
'style_table': self.style_table,
'style_cell': self.style_cell,
'style_cell_conditional': self.style_cell_conditional,
'style_data': self.style_data,
'style_data_conditional': self.style_data_conditional,
'style_header': self.style_header,
'style_header_conditional': self.style_header_conditional,
'style_filter': self.style_filter,
'style_filter_conditional': self.style_filter_conditional,
'column_selectable': self.column_selectable,
'export_format': self.export_format,
'export_headers': self.export_headers,
'filter_action': self.filter_action,
'page_size': self.page_size,
'row_selectable': self.row_selectable,
'style_as_list_view': self.style_as_list_view,
'sort_action': self.sort_action,
'sort_mode': self.sort_mode,
}
Variables⚓︎
OPERATORS
List of lists containing each possible filter string.
Functions⚓︎
apply_datatable_filters⚓︎
def apply_datatable_filters(
df_table,
filter_query
)
Filter a dataframe based on Dash datatable filterquery.
Based on Backend Paging with Filtering: https://dash.plot.ly/datatable/callbacks
Parameters:
| Name | Description |
|---|---|
| df_table | pandas dataframe to filter |
| filter_query | Dash datatable string filter query |
Returns:
| Type | Description |
|---|---|
| dataframe | filtered dataframe |
View Source
def apply_datatable_filters(df_table, filter_query):
"""Filter a dataframe based on Dash datatable filterquery.
Based on `Backend Paging with Filtering`: https://dash.plot.ly/datatable/callbacks
Args:
df_table: pandas dataframe to filter
filter_query: Dash datatable string filter query
Returns:
dataframe: filtered dataframe
"""
filtering_expressions = filter_query.split(' && ')
for filter_part in filtering_expressions:
col_name, operator, filter_value = split_filter_part(filter_part)
if operator in ('eq', 'ne', 'lt', 'le', 'gt', 'ge'):
# these operators match pandas series operator method names
df_table = df_table.loc[getattr(df_table[col_name], operator)(filter_value)]
elif operator == 'contains':
df_table = df_table.loc[df_table[col_name].str.contains(filter_value)]
elif operator == 'datestartswith':
# this is a simplification of the front-end filtering logic,
# only works with complete fields in standard format
df_table = df_table.loc[df_table[col_name].str.startswith(filter_value)]
return df_table
split_filter_part⚓︎
def split_filter_part(
filter_part
)
Split the filter into (name, operator, value) components.
Based on Backend Paging with Filtering: https://dash.plot.ly/datatable/callbacks
Parameters:
| Name | Description |
|---|---|
| filter_part | string filter query |
Returns:
| Type | Description |
|---|---|
| tuple | (name, operator, value) which could be all None if no match was found |
View Source
def split_filter_part(filter_part): # noqa: CCR001
"""Split the filter into `(name, operator, value)` components.
Based on `Backend Paging with Filtering`: https://dash.plot.ly/datatable/callbacks
Args:
filter_part: string filter query
Returns:
tuple: `(name, operator, value)` which could be all None if no match was found
"""
for operator_type in OPERATORS:
for operator in operator_type:
if operator in filter_part:
name_part, value_part = filter_part.split(operator, 1)
name = name_part[name_part.find('{') + 1: name_part.rfind('}')]
value_part = value_part.strip()
v0 = value_part[0]
if (v0 == value_part[-1] and v0 in ("'", '"', '`')):
value = value_part[1: -1].replace(f'\\{v0}', v0)
else:
try:
value = float(value_part)
except ValueError:
value = value_part
# Word operators need spaces after them in the filter string, but we don't want these later
return (name, operator_type[0].strip(), value)
return [None, None, None]
Classes⚓︎
BaseDataTable⚓︎
class BaseDataTable(
)
View Source
class BaseDataTable: # noqa: H601
"""Base Class for Data Tables."""
filter_summary = """Table Filter Syntax:
Full documentation at: [https://dash.plot.ly/datatable/filtering](https://dash.plot.ly/datatable/filtering)
- `eq`: exact match (applies to number columns and will try to convert string to number)
- `contains`: search for exact (case-sensitive) substring in each cell
- `datestartswith`: matches partial datetime. For example, datestartswith `2018-03-01` will match `2018-03-01 12:59`
but not `2018-03`
- `ne`, `gt`, `ge`, `lt`, `le`: comparison operators for not equal, greater than, greater or equal, less than, etc.
Applies to numbers and string columns (uses numbers, symbols, uppercase letter, lowercase letters)
Press enter of tab to apply the filter"""
"""Markdown text explaining dash_table.DataTable filtering rules with link to full documentation."""
# dash_table.DataTable Parameters. Documentation: https://dash.plot.ly/datatable/reference
style_table = None
"""DataTable.style_table dictionary. Default enables overflowX scroll. Set in `initialize_mutables`."""
css = None
"""DataTable.css list. Use the style_* properties first. Set in `initialize_mutables`.
Default sets row margin to zero to fix a negative margin issue when using dash_table and Bootstrap
See: https://github.com/facultyai/dash-bootstrap-components/issues/334
Also sets other various style tweaks to highlight the filter icons on hover, etc.
"""
style_cell = None
"""DataTable.style_cell dictionary. Default is empty dictionary. Set in `initialize_mutables`."""
style_cell_conditional = None
"""DataTable.style_cell_conditional list. Default is empty list. Set in `initialize_mutables`."""
style_data = None
"""DataTable.style_data dictionary. Default is empty dictionary. Set in `initialize_mutables`."""
style_data_conditional = None
"""DataTable.style_data_conditional list. Default is for odd rows to have an off-white background (zebra stripe).
Set in `initialize_mutables`
"""
style_header = None
"""DataTable.style_header dictionary. Default is bold and off-white background. Set in `initialize_mutables`."""
style_header_conditional = None
"""DataTable.style_header_conditional list. Default is empty list. Set in `initialize_mutables`."""
style_filter = None
"""DataTable.style_filter dictionary. Default is empty dictionary. Set in `initialize_mutables`."""
style_filter_conditional = None
"""DataTable.style_filter_conditional list. Default is empty list. Set in `initialize_mutables`."""
column_selectable = None
"""DataTable.column_selectable. Default is `None`."""
column_kwarg_lookup = None
"""Lookup for keyword arguments for each column allowing deletable, selectable, etc. to be set per column."""
export_format = 'none'
"""DataTable.export_format. Default is `'none'`. Could be one of `(csv, xlsx)`."""
export_headers = 'names'
"""DataTable.export_headers. Default is `'names'`. See documentation."""
filter_action = 'native'
"""DataTable.filter_action. Default is `'native'`."""
page_size = 25
"""DataTable.page_size. Default is `'25'`."""
row_selectable = None
"""DataTable.row_selectable. Default is `None`."""
style_as_list_view = False
"""DataTable.style_as_list_view. Default is False."""
sort_action = 'native'
"""DataTable.sort_action. Default is `'native'`."""
sort_mode = 'single'
"""DataTable.sort_mode. Default is `'single'`."""
# CSS Variables
text_color = '#333333'
"""Default text color."""
background_color = '#ffffff'
"""Default background color."""
zebra_color = '#f9f9f9'
"""Default background color for odd rows (zebra-stripe)."""
selected_cell_color = '#eaeaea'
"""Default color for selected cells."""
def __init__(self):
"""Initialize class."""
self.initialize_mutables()
def initialize_mutables(self):
"""Initialize the mutable data members to prevent modifying one attribute and impacting all instances."""
self.style_table = {'overflowX': 'scroll'}
self.css = [
# Fix width when overflow is True and using dash_bootstrap_components
{'selector': '.row', 'rule': 'margin: 0'},
# Based on: https://community.plot.ly/t/dash-table-datatable-styling-examples/15594/
# Align the select icon to the left and the sort icon to the right
{
'selector': 'th.dash-header div',
'rule': 'display: flex; align-items: center;',
},
{
'selector': 'th.dash-header div span.column-header--select',
'rule': 'order: 1; flex-shrink: 5; text-align: left;',
},
{
'selector': 'th.dash-header div span.column-header-name',
'rule': 'order: 2; flex-grow: 5; text-align: center;',
},
{
'selector': 'th.dash-header div span.column-header--sort',
'rule': 'order: 3; flex-shrink: 5; text-align: right;',
},
# Remove excess borders to better match JQuery DataTables styling
# (Some border styles don't appear to work from `self.style_header`)
{'selector': 'th.dash-filter', 'rule': 'border-bottom-color: rgb(17, 17, 17) !important;'},
]
self.style_cell = {
'backgroundColor': self.background_color,
'borderStyle': f'1px solid {self.zebra_color}',
'color': self.text_color,
}
self.style_cell_conditional = []
self.style_data = {}
self.style_data_conditional = [
{'if': {'row_index': 'even'}, 'backgroundColor': self.zebra_color},
]
self.style_header = {
'borderLeft': 'none',
'borderRight': 'none',
'borderTop': 'none',
'fontWeight': 'bold',
}
self.style_header_conditional = []
self.style_filter = {
'borderBottomColor': 'rgb(17, 17, 17)',
}
self.style_filter_conditional = []
self.initialize_column_kwarg_lookup() # Must be called last
def initialize_column_kwarg_lookup(self):
"""Initialize the column lookup based on the other mutables.
Documentation: https://dash.plot.ly/datatable/reference
Additional kwargs not set in default lookup:
- clearable, deletable, editable, hideable, renamable, format, presentation, on_change, sort_as_null,
validation, type
"""
self.column_kwarg_lookup = {
'default_kwargs': {
'selectable': True,
},
}
def create_table(self, df_raw, columns=None, **kwargs_datatable):
"""Create the dash_table.DataTable.
Args:
df_raw: data to pass to datatable
columns: list of column names to display. Default is None to use all columns from df_raw
kwargs_datatable: keyword arguments to pass to the datatable
Returns:
DataTable: returns dash_table.DataTable object
"""
if columns is None:
columns = df_raw.columns
return dash_table.DataTable(**self._create_datatable(df_raw, columns), **kwargs_datatable)
def format_datatable_columns(self, df_raw, columns):
"""Return a list of column names formatted for a dash_table. Uses `self.self.column_name_kwarg_lookup`.
Args:
df_raw: data to pass to datatable
columns: list of strings or None
Returns:
list: of dict with keys `(name, id, deleteable, selectable)` in order of df_raw columns
"""
return [
{'name': col, 'id': col, **self.column_kwarg_lookup.get(col, self.column_kwarg_lookup['default_kwargs'])}
for col in df_raw.columns if (columns is None or col in columns)
]
def _create_datatable(self, df_raw, columns, **table_kwargs):
"""Return dictionary of keyword arguments for datatable.
Args:
df_raw: data to pass to datatable
columns: will auto format list of string column names to display or use list of dicts
table_kwargs: additional keyword arguments to pass to datatable, such as id
Returns:
dict: keys include `(columns, data)` and all data members
"""
return {
'columns': self.format_datatable_columns(df_raw, columns) if isinstance(columns[0], str) else columns,
'data': (df_raw.loc[:, columns] if columns is not None else df_raw).to_dict('records'),
# Add all datamembers
'css': self.css,
'style_table': self.style_table,
'style_cell': self.style_cell,
'style_cell_conditional': self.style_cell_conditional,
'style_data': self.style_data,
'style_data_conditional': self.style_data_conditional,
'style_header': self.style_header,
'style_header_conditional': self.style_header_conditional,
'style_filter': self.style_filter,
'style_filter_conditional': self.style_filter_conditional,
'column_selectable': self.column_selectable,
'export_format': self.export_format,
'export_headers': self.export_headers,
'filter_action': self.filter_action,
'page_size': self.page_size,
'row_selectable': self.row_selectable,
'style_as_list_view': self.style_as_list_view,
'sort_action': self.sort_action,
'sort_mode': self.sort_mode,
}
Class variables⚓︎
background_color
Default background color.
column_kwarg_lookup
Lookup for keyword arguments for each column allowing deletable, selectable, etc. to be set per column.
column_selectable
DataTable.column_selectable. Default is None.
css
DataTable.css list. Use the style_* properties first. Set in initialize_mutables.
Default sets row margin to zero to fix a negative margin issue when using dash_table and Bootstrap See: https://github.com/facultyai/dash-bootstrap-components/issues/334
Also sets other various style tweaks to highlight the filter icons on hover, etc.
export_format
DataTable.export_format. Default is 'none'. Could be one of (csv, xlsx).
export_headers
DataTable.export_headers. Default is 'names'. See documentation.
filter_action
DataTable.filter_action. Default is 'native'.
filter_summary
Markdown text explaining dash_table.DataTable filtering rules with link to full documentation.
page_size
DataTable.page_size. Default is '25'.
row_selectable
DataTable.row_selectable. Default is None.
selected_cell_color
Default color for selected cells.
sort_action
DataTable.sort_action. Default is 'native'.
sort_mode
DataTable.sort_mode. Default is 'single'.
style_as_list_view
DataTable.style_as_list_view. Default is False.
style_cell
DataTable.style_cell dictionary. Default is empty dictionary. Set in initialize_mutables.
style_cell_conditional
DataTable.style_cell_conditional list. Default is empty list. Set in initialize_mutables.
style_data
DataTable.style_data dictionary. Default is empty dictionary. Set in initialize_mutables.
style_data_conditional
DataTable.style_data_conditional list. Default is for odd rows to have an off-white background (zebra stripe).
Set in initialize_mutables
style_filter
DataTable.style_filter dictionary. Default is empty dictionary. Set in initialize_mutables.
style_filter_conditional
DataTable.style_filter_conditional list. Default is empty list. Set in initialize_mutables.
style_header
DataTable.style_header dictionary. Default is bold and off-white background. Set in initialize_mutables.
style_header_conditional
DataTable.style_header_conditional list. Default is empty list. Set in initialize_mutables.
style_table
DataTable.style_table dictionary. Default enables overflowX scroll. Set in initialize_mutables.
text_color
Default text color.
zebra_color
Default background color for odd rows (zebra-stripe).
Methods⚓︎
create_table⚓︎
def create_table(
self,
df_raw,
columns=None,
**kwargs_datatable
)
Create the dash_table.DataTable.
Parameters:
| Name | Description |
|---|---|
| df_raw | data to pass to datatable |
| columns | list of column names to display. Default is None to use all columns from df_raw |
| kwargs_datatable | keyword arguments to pass to the datatable |
Returns:
| Type | Description |
|---|---|
| DataTable | returns dash_table.DataTable object |
View Source
def create_table(self, df_raw, columns=None, **kwargs_datatable):
"""Create the dash_table.DataTable.
Args:
df_raw: data to pass to datatable
columns: list of column names to display. Default is None to use all columns from df_raw
kwargs_datatable: keyword arguments to pass to the datatable
Returns:
DataTable: returns dash_table.DataTable object
"""
if columns is None:
columns = df_raw.columns
return dash_table.DataTable(**self._create_datatable(df_raw, columns), **kwargs_datatable)
format_datatable_columns⚓︎
def format_datatable_columns(
self,
df_raw,
columns
)
Return a list of column names formatted for a dash_table. Uses self.self.column_name_kwarg_lookup.
Parameters:
| Name | Description |
|---|---|
| df_raw | data to pass to datatable |
| columns | list of strings or None |
Returns:
| Type | Description |
|---|---|
| list | of dict with keys (name, id, deleteable, selectable) in order of df_raw columns |
View Source
def format_datatable_columns(self, df_raw, columns):
"""Return a list of column names formatted for a dash_table. Uses `self.self.column_name_kwarg_lookup`.
Args:
df_raw: data to pass to datatable
columns: list of strings or None
Returns:
list: of dict with keys `(name, id, deleteable, selectable)` in order of df_raw columns
"""
return [
{'name': col, 'id': col, **self.column_kwarg_lookup.get(col, self.column_kwarg_lookup['default_kwargs'])}
for col in df_raw.columns if (columns is None or col in columns)
]
initialize_column_kwarg_lookup⚓︎
def initialize_column_kwarg_lookup(
self
)
Initialize the column lookup based on the other mutables.
Documentation: https://dash.plot.ly/datatable/reference
Additional kwargs not set in default lookup: - clearable, deletable, editable, hideable, renamable, format, presentation, on_change, sort_as_null, validation, type
View Source
def initialize_column_kwarg_lookup(self):
"""Initialize the column lookup based on the other mutables.
Documentation: https://dash.plot.ly/datatable/reference
Additional kwargs not set in default lookup:
- clearable, deletable, editable, hideable, renamable, format, presentation, on_change, sort_as_null,
validation, type
"""
self.column_kwarg_lookup = {
'default_kwargs': {
'selectable': True,
},
}
initialize_mutables⚓︎
def initialize_mutables(
self
)
Initialize the mutable data members to prevent modifying one attribute and impacting all instances.
View Source
def initialize_mutables(self):
"""Initialize the mutable data members to prevent modifying one attribute and impacting all instances."""
self.style_table = {'overflowX': 'scroll'}
self.css = [
# Fix width when overflow is True and using dash_bootstrap_components
{'selector': '.row', 'rule': 'margin: 0'},
# Based on: https://community.plot.ly/t/dash-table-datatable-styling-examples/15594/
# Align the select icon to the left and the sort icon to the right
{
'selector': 'th.dash-header div',
'rule': 'display: flex; align-items: center;',
},
{
'selector': 'th.dash-header div span.column-header--select',
'rule': 'order: 1; flex-shrink: 5; text-align: left;',
},
{
'selector': 'th.dash-header div span.column-header-name',
'rule': 'order: 2; flex-grow: 5; text-align: center;',
},
{
'selector': 'th.dash-header div span.column-header--sort',
'rule': 'order: 3; flex-shrink: 5; text-align: right;',
},
# Remove excess borders to better match JQuery DataTables styling
# (Some border styles don't appear to work from `self.style_header`)
{'selector': 'th.dash-filter', 'rule': 'border-bottom-color: rgb(17, 17, 17) !important;'},
]
self.style_cell = {
'backgroundColor': self.background_color,
'borderStyle': f'1px solid {self.zebra_color}',
'color': self.text_color,
}
self.style_cell_conditional = []
self.style_data = {}
self.style_data_conditional = [
{'if': {'row_index': 'even'}, 'backgroundColor': self.zebra_color},
]
self.style_header = {
'borderLeft': 'none',
'borderRight': 'none',
'borderTop': 'none',
'fontWeight': 'bold',
}
self.style_header_conditional = []
self.style_filter = {
'borderBottomColor': 'rgb(17, 17, 17)',
}
self.style_filter_conditional = []
self.initialize_column_kwarg_lookup() # Must be called last
Last update:
August 5, 2022
Created: August 5, 2022
Created: August 5, 2022