Would it be possible to allow components like dcc.Dropdown and dcc.Checklist to accept options other than a list of dictionaries with a format like {'label': label, 'value': value} ? For example:
- A list of values would be preprocessed into to a list of
{'label': value, 'value': value} - A dictionary of
key -> val would be processed into a list of {'label': key, 'value': value}.
In a similar fashion, for dcc.Slider we could accept alternatives for the marks:
- A list of values would be preprocessed into a mapping
{i: str(i) for i in list} marks=True when there's a min, max, step value specified would display a mark on every stepmarks: int = n would display a mark at every n steps (so {i: str(i) for i in range(min, max, n*steps)})
Furthermore, the default for value could be improved: when set to None/null, it would be inferred:
- in the case of dropdown, the first element in
options - in the case of checklist, an empty list
- in the case of slider, the middle value
- in the case of range slider, it would be the entire range
- etc.
In the case of dcc.Slider, when the min and max are left as None/null, they could also be assigned to the small and largest values in marks, or 0 and 100 (and step to 1) if marks is not specified.
Overall this is just an idea but it would make the UX much nicer on the python side. Right now to define a slider we need:
my_slider=dcc.Slider(id='slider', min=0, max=10, step=2, value=5, marks={i: str(i) foriinrange(0, 11, 2)})With inferred default and polyvalent marks:
my_slider=dcc.Slider(id='slider', min=0, max=10, step=2, marks=True)
# assuming an order:my_slider=dcc.Slider(id='slider', 0, 10, 2, marks=True)
# equivalent to:my_slider=dcc.Slider(id='slider', marks=range(0, 11, 2))
Similarly for a dropdown:
my_lst= [...]
my_dropdown=dcc.Dropdown(options=[{'value': x, 'label': x} forxinmy_lst], value=my_lst[0])which could simply be
my_dropdown=dcc.Dropdown(my_lst)
And in the case where we want to access a dataframe column's unique values (super frequent use case for me):
# beforemy_dropdown=dcc.Dropdown(
[{'value': x, 'label': x} forxindf.my_col.unique().tolist()], value=df.my_col.unique().tolist()[0]
)
# aftermy_dropdown=dcc.Dropdown(df.my_col.unique().tolist())
# and if we add some helper to handle pandas behind the scene:my_dropdown=dcc.Dropdown(df.my_col.unique())Obviously sometimes a mapping would work better, but in that case a key-value pair would be more concise than writing "label" and "value" many times:
# beforedcc.Dropdown(
options=[
{'label': 'New York City', 'value': 'NYC'},
{'label': 'Montreal', 'value': 'MTL'},
{'label': 'San Francisco', 'value': 'SF'},
],
value='MTL',
clearable=False
) # afterdcc.Dropdown(
{"New York City": "NYC", "Montreal": "MTL", "San Francisco": "SF"},
clearable=False
)
Would it be possible to allow components like
dcc.Dropdownanddcc.Checklistto acceptoptionsother than a list of dictionaries with a format like{'label': label, 'value': value}? For example:{'label': value, 'value': value}key -> valwould be processed into a list of{'label': key, 'value': value}.In a similar fashion, for
dcc.Sliderwe could accept alternatives for themarks:{i: str(i) for i in list}marks=Truewhen there's a min, max, step value specified would display a mark on every stepmarks: int = nwould display a mark at everynsteps (so{i: str(i) for i in range(min, max, n*steps)})Furthermore, the default for
valuecould be improved: when set toNone/null, it would be inferred:optionsIn the case of
dcc.Slider, when the min and max are left asNone/null, they could also be assigned to the small and largest values inmarks, or 0 and 100 (and step to 1) ifmarksis not specified.Overall this is just an idea but it would make the UX much nicer on the python side. Right now to define a slider we need:
With inferred default and polyvalent marks:
Similarly for a dropdown:
which could simply be
And in the case where we want to access a dataframe column's unique values (super frequent use case for me):
Obviously sometimes a mapping would work better, but in that case a key-value pair would be more concise than writing "label" and "value" many times: