My Note on Plotly Dash

Part 1: Introduction to Dash

Every Dash app requires a layout. The layout includes:

  • dash core components dcc.Graph
  • dash html components html.Div, html.H3
app.layout = html.Div(
children=[
html.Div(
className="data-class",
children=[
html.H3("head"),
dcc.Graph(id="my-id"),
],
),
]
)
  • html.Div is more like a wrapper, and it can contain other components like dcc.Graph etc.

Part 2: Notes

(1) if the ouput is html.Div, then its property is children

html.Div(id="my-div")@app.callback(Output("my-div", "children"))
def fun()
return html.Div([dcc.Graph(figure=fig)])

(2) if the output is dcc.Graph, then its property is figure

dcc.Graph(id="my-graph")@app.callback
def fun()
fig={
"data": [go.Bar()],
"layout":{ }
}or
@app.callback
def fun()
from plotly.subplots import make_subplots
fig = make_subplots(rows=2, cols=1, shared_xaxes=True, )

fig.add_trace(go.Scatter(x=x_ax, y=a),
row=1, col=1)
fig.add_trace(go.Scatter(x=x_ax, y=b),
row=2, col=1)
fig.update_layout(height=900, width=900,
title_text="process")
return fig

(3) Support file downloading

The best way I have found is to use flask, and here is an example downloadable_dash.py

This solution is based on Downloading dynamically generated files from a Dash/Flask app Stackoverflow question.

The second way of support file downloading is to put the generated files in /assets/ directory, then use the following code to access the file:

  • step 1: generate file in the denoted directory
file_to_be_dowload = ""
if os.path.exists(file_to_be_dowload):
pass
else:
# generate the file

This step is important because the generated files are located in assets directory, if every time we change files kept there, the Dash will refresh.

  • step 2: generate the file link as html content
text =  html.A(link_name, href=href_cont, target="_blank")
return html.Div([text])

Part 3: Figure

3. 1 Figure.Data

There are several ways of generating figures:

(1) make_subplots

from plotly.subplots import make_subplots
fig = make_subplots()

fig.add_trace()
fig.add_trace(go.Scatter())
fig.update_layout()

(2) fig dict

fig = {
'data': [ go.Bar(), ]
'layout':{
'title': title_name,
}
}

(3) go.Figure

fig = go.Figure()
fig.add_trace()

(4) figure_factory

import plotly.figure_factory as ff
fig = ff.create_table(df)

return html.Div([dcc.Graph(figure=fig)])

or an example Figure Factory Tables in Python

3.2 Figure.Layout

The properties in the figure that can be updated include:

  • height=
  • width=
  • title_text=
  • yaxis={‘visible’: False, ‘showticklabels’: False}
  • xaxis=
  • showlegend=False

Reference

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