plotlyjs-flask-example/app.py at master · ivylee/plotlyjs-flask-example · GitHub

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fromflaskimportFlask, render_template

importjson
importplotly

importpandasaspd
importnumpyasnp

app=Flask(__name__)
app.debug=True


@app.route('/')
defindex():
rng=pd.date_range('1/1/2011', periods=7500, freq='H')
ts=pd.Series(np.random.randn(len(rng)), index=rng)

graphs= [
dict(
data=[
dict(
x=[1, 2, 3],
y=[10, 20, 30],
type='scatter'
 ),
 ],
layout=dict(
title='first graph'
 )
 ),

dict(
data=[
dict(
x=[1, 3, 5],
y=[10, 50, 30],
type='bar'
 ),
 ],
layout=dict(
title='second graph'
 )
 ),

dict(
data=[
dict(
x=ts.index, # Can use the pandas data structures directly
y=ts
 )
 ]
 )
 ]

# Add "ids" to each of the graphs to pass up to the client
# for templating
ids= ['graph-{}'.format(i) fori, _inenumerate(graphs)]

# Convert the figures to JSON
# PlotlyJSONEncoder appropriately converts pandas, datetime, etc
# objects to their JSON equivalents
graphJSON=json.dumps(graphs, cls=plotly.utils.PlotlyJSONEncoder)

returnrender_template('layouts/index.html',
ids=ids,
graphJSON=graphJSON)


if__name__=='__main__':
app.run(host='0.0.0.0', port=9999)
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fromflaskimportFlask, render_template

importjson
importplotly

importpandasaspd
importnumpyasnp

app=Flask(__name__)
app.debug=True


@app.route('/')
defindex():
rng=pd.date_range('1/1/2011', periods=7500, freq='H')
ts=pd.Series(np.random.randn(len(rng)), index=rng)

graphs= [
dict(
data=[
dict(
x=[1, 2, 3],
y=[10, 20, 30],
type='scatter'
 ),
 ],
layout=dict(
title='first graph'
 )
 ),

dict(
data=[
dict(
x=[1, 3, 5],
y=[10, 50, 30],
type='bar'
 ),
 ],
layout=dict(
title='second graph'
 )
 ),

dict(
data=[
dict(
x=ts.index, # Can use the pandas data structures directly
y=ts
 )
 ]
 )
 ]

# Add "ids" to each of the graphs to pass up to the client
# for templating
ids= ['graph-{}'.format(i) fori, _inenumerate(graphs)]

# Convert the figures to JSON
# PlotlyJSONEncoder appropriately converts pandas, datetime, etc
# objects to their JSON equivalents
graphJSON=json.dumps(graphs, cls=plotly.utils.PlotlyJSONEncoder)

returnrender_template('layouts/index.html',
ids=ids,
graphJSON=graphJSON)


if__name__=='__main__':
app.run(host='0.0.0.0', port=9999)
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fromflaskimportFlask, render_template

importjson
importplotly

importpandasaspd
importnumpyasnp

app=Flask(__name__)
app.debug=True


@app.route('/')
defindex():
rng=pd.date_range('1/1/2011', periods=7500, freq='H')
ts=pd.Series(np.random.randn(len(rng)), index=rng)

graphs= [
dict(
data=[
dict(
x=[1, 2, 3],
y=[10, 20, 30],
type='scatter'
 ),
 ],
layout=dict(
title='first graph'
 )
 ),

dict(
data=[
dict(
x=[1, 3, 5],
y=[10, 50, 30],
type='bar'
 ),
 ],
layout=dict(
title='second graph'
 )
 ),

dict(
data=[
dict(
x=ts.index, # Can use the pandas data structures directly
y=ts
 )
 ]
 )
 ]

# Add "ids" to each of the graphs to pass up to the client
# for templating
ids= ['graph-{}'.format(i) fori, _inenumerate(graphs)]

# Convert the figures to JSON
# PlotlyJSONEncoder appropriately converts pandas, datetime, etc
# objects to their JSON equivalents
graphJSON=json.dumps(graphs, cls=plotly.utils.PlotlyJSONEncoder)

returnrender_template('layouts/index.html',
ids=ids,
graphJSON=graphJSON)


if__name__=='__main__':
app.run(host='0.0.0.0', port=9999)
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fromflaskimportFlask, render_template

importjson
importplotly

importpandasaspd
importnumpyasnp

app=Flask(__name__)
app.debug=True


@app.route('/')
defindex():
rng=pd.date_range('1/1/2011', periods=7500, freq='H')
ts=pd.Series(np.random.randn(len(rng)), index=rng)

graphs= [
dict(
data=[
dict(
x=[1, 2, 3],
y=[10, 20, 30],
type='scatter'
 ),
 ],
layout=dict(
title='first graph'
 )
 ),

dict(
data=[
dict(
x=[1, 3, 5],
y=[10, 50, 30],
type='bar'
 ),
 ],
layout=dict(
title='second graph'
 )
 ),

dict(
data=[
dict(
x=ts.index, # Can use the pandas data structures directly
y=ts
 )
 ]
 )
 ]

# Add "ids" to each of the graphs to pass up to the client
# for templating
ids= ['graph-{}'.format(i) fori, _inenumerate(graphs)]

# Convert the figures to JSON
# PlotlyJSONEncoder appropriately converts pandas, datetime, etc
# objects to their JSON equivalents
graphJSON=json.dumps(graphs, cls=plotly.utils.PlotlyJSONEncoder)

returnrender_template('layouts/index.html',
ids=ids,
graphJSON=graphJSON)


if__name__=='__main__':
app.run(host='0.0.0.0', port=9999)
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fromflaskimportFlask, render_template

importjson
importplotly

importpandasaspd
importnumpyasnp

app=Flask(__name__)
app.debug=True


@app.route('/')
defindex():
rng=pd.date_range('1/1/2011', periods=7500, freq='H')
ts=pd.Series(np.random.randn(len(rng)), index=rng)

graphs= [
dict(
data=[
dict(
x=[1, 2, 3],
y=[10, 20, 30],
type='scatter'
 ),
 ],
layout=dict(
title='first graph'
 )
 ),

dict(
data=[
dict(
x=[1, 3, 5],
y=[10, 50, 30],
type='bar'
 ),
 ],
layout=dict(
title='second graph'
 )
 ),

dict(
data=[
dict(
x=ts.index, # Can use the pandas data structures directly
y=ts
 )
 ]
 )
 ]

# Add "ids" to each of the graphs to pass up to the client
# for templating
ids= ['graph-{}'.format(i) fori, _inenumerate(graphs)]

# Convert the figures to JSON
# PlotlyJSONEncoder appropriately converts pandas, datetime, etc
# objects to their JSON equivalents
graphJSON=json.dumps(graphs, cls=plotly.utils.PlotlyJSONEncoder)

returnrender_template('layouts/index.html',
ids=ids,
graphJSON=graphJSON)


if__name__=='__main__':
app.run(host='0.0.0.0', port=9999)
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fromflaskimportFlask, render_template

importjson
importplotly

importpandasaspd
importnumpyasnp

app=Flask(__name__)
app.debug=True


@app.route('/')
defindex():
rng=pd.date_range('1/1/2011', periods=7500, freq='H')
ts=pd.Series(np.random.randn(len(rng)), index=rng)

graphs= [
dict(
data=[
dict(
x=[1, 2, 3],
y=[10, 20, 30],
type='scatter'
 ),
 ],
layout=dict(
title='first graph'
 )
 ),

dict(
data=[
dict(
x=[1, 3, 5],
y=[10, 50, 30],
type='bar'
 ),
 ],
layout=dict(
title='second graph'
 )
 ),

dict(
data=[
dict(
x=ts.index, # Can use the pandas data structures directly
y=ts
 )
 ]
 )
 ]

# Add "ids" to each of the graphs to pass up to the client
# for templating
ids= ['graph-{}'.format(i) fori, _inenumerate(graphs)]

# Convert the figures to JSON
# PlotlyJSONEncoder appropriately converts pandas, datetime, etc
# objects to their JSON equivalents
graphJSON=json.dumps(graphs, cls=plotly.utils.PlotlyJSONEncoder)

returnrender_template('layouts/index.html',
ids=ids,
graphJSON=graphJSON)


if__name__=='__main__':
app.run(host='0.0.0.0', port=9999)
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fromflaskimportFlask, render_template

importjson
importplotly

importpandasaspd
importnumpyasnp

app=Flask(__name__)
app.debug=True


@app.route('/')
defindex():
rng=pd.date_range('1/1/2011', periods=7500, freq='H')
ts=pd.Series(np.random.randn(len(rng)), index=rng)

graphs= [
dict(
data=[
dict(
x=[1, 2, 3],
y=[10, 20, 30],
type='scatter'
 ),
 ],
layout=dict(
title='first graph'
 )
 ),

dict(
data=[
dict(
x=[1, 3, 5],
y=[10, 50, 30],
type='bar'
 ),
 ],
layout=dict(
title='second graph'
 )
 ),

dict(
data=[
dict(
x=ts.index, # Can use the pandas data structures directly
y=ts
 )
 ]
 )
 ]

# Add "ids" to each of the graphs to pass up to the client
# for templating
ids= ['graph-{}'.format(i) fori, _inenumerate(graphs)]

# Convert the figures to JSON
# PlotlyJSONEncoder appropriately converts pandas, datetime, etc
# objects to their JSON equivalents
graphJSON=json.dumps(graphs, cls=plotly.utils.PlotlyJSONEncoder)

returnrender_template('layouts/index.html',
ids=ids,
graphJSON=graphJSON)


if__name__=='__main__':
app.run(host='0.0.0.0', port=9999)
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fromflaskimportFlask, render_template

importjson
importplotly

importpandasaspd
importnumpyasnp

app=Flask(__name__)
app.debug=True


@app.route('/')
defindex():
rng=pd.date_range('1/1/2011', periods=7500, freq='H')
ts=pd.Series(np.random.randn(len(rng)), index=rng)

graphs= [
dict(
data=[
dict(
x=[1, 2, 3],
y=[10, 20, 30],
type='scatter'
 ),
 ],
layout=dict(
title='first graph'
 )
 ),

dict(
data=[
dict(
x=[1, 3, 5],
y=[10, 50, 30],
type='bar'
 ),
 ],
layout=dict(
title='second graph'
 )
 ),

dict(
data=[
dict(
x=ts.index, # Can use the pandas data structures directly
y=ts
 )
 ]
 )
 ]

# Add "ids" to each of the graphs to pass up to the client
# for templating
ids= ['graph-{}'.format(i) fori, _inenumerate(graphs)]

# Convert the figures to JSON
# PlotlyJSONEncoder appropriately converts pandas, datetime, etc
# objects to their JSON equivalents
graphJSON=json.dumps(graphs, cls=plotly.utils.PlotlyJSONEncoder)

returnrender_template('layouts/index.html',
ids=ids,
graphJSON=graphJSON)


if__name__=='__main__':
app.run(host='0.0.0.0', port=9999)