Loosing data in bokeh client / server application

Hi all,

I am having a problem with my online plot that is being updated with new data each 5 seconds.

The plots draws a stock price and its volume.

Unfortunately from time to time the data gets lost so I am loosing all the lines drawn before that error happens.

When I log data I see these few lines:

DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [280 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [348 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [12246 bytes]

DEBUG:bokeh.client.connection:Running state CONNECTED_AFTER_ACK

Normally only a few of these lines are there:

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

So this line seems to be messing up everything:

DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session

Does anybody knows why bokeh server is issuing the PATCH-DOC message?

This messes up everything and plot gets lost all the data and the plotting starts again from the scratch.

Thank you for your response.

Tony

Hi Tony,

PATCH-DOC is the message sent from the server to the client, that tells the client to actually update things like data, so those messages are entirely expected.

It's going to be extremely difficult or impossible to offer specific help or guidance without knowing details of what exactly you have tried. Is it possible you can share some code that reproduces what you are seeing?

Thanks,

Bryan

···

On Apr 21, 2016, at 11:46 AM, [email protected] wrote:

Hi all,

I am having a problem with my online plot that is being updated with new data each 5 seconds.
The plots draws a stock price and its volume.

Unfortunately from time to time the data gets lost so I am loosing all the lines drawn before that error happens.
When I log data I see these few lines:

DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session

DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [305 bytes]

DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [280 bytes]

DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [348 bytes]

DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [305 bytes]

DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [12246 bytes]

DEBUG:bokeh.client.connection:Running state CONNECTED_AFTER_ACK

Normally only a few of these lines are there:

DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [305 bytes]

So this line seems to be messing up everything:

DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session

Does anybody knows why bokeh server is issuing the PATCH-DOC message?

This messes up everything and plot gets lost all the data and the plotting starts again from the scratch.

Thank you for your response.

Tony

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For more options, visit https://groups.google.com/a/continuum.io/d/optout.

Hi Bryan,

Thanks for your quick reply.
It may be that I am doing something wrong.

I just only found out that after I see that server message (PATCH-DOC) it goes wrong…

Here is my code:

======== CODE START ===================

d_np = [np.datetime64(datetime.now()).astype(long) / 1000]

data_now = monitor.get_data()

if data_now and ‘price’ in data_now:

price_now = float(data_now['price'])

volume_now = float(data_now['volume'])

price_last_close = price_now - float(data_now['priceChange'])

plot = figure(plot_width = 1200, plot_height = 400, x_axis_type = “datetime”, tools = ‘pan,box_select,crosshair,resize,reset,wheel_zoom,hover’)

main_line = plot.line(np.array(d_np), [price_now], name = ‘main_line’, color = “#00BFFF”, legend = ‘price’)

bullet_line = plot.circle(np.array(d_np), [price_now], name = ‘main_bullets’, color = “#00BFFF”)

plot.title = data_now[‘name’]

plot.legend.location = “top_left”

plot.xaxis.axis_label = ‘Time’

plot.yaxis.axis_label = ‘Price’

plot.grid.bounds = (15000, 18000)

plot.y_range = Range1d(start = price_now - ((1 * price_last_close) / 100), end = price_last_close + ((1 * price_last_close) / 100))

plot.x_range = Range1d(start = np.datetime64(datetime.now() - timedelta(hours = 1)).astype(long) / 1000, end = np.datetime64(datetime.now() + timedelta(hours = 2)).astype(long) / 1000)

plot_volume = figure(plot_width = 1200, plot_height = 400, x_range = plot.x_range, x_axis_type = “datetime”, tools = ‘pan,box_select,crosshair,resize,reset,wheel_zoom,hover’)

volume_line = plot_volume.segment(x0 = np.array(d_np), y0 = [0], x1 = np.array(d_np), y1 = [volume_now], name = ‘volume_line’, color = “#FF1493”)

plot_volume.title = data_now[‘name’]

plot_volume.legend.location = “top_left”

plot_volume.xaxis.axis_label = ‘Time’

plot_volume.yaxis.axis_label = ‘Volume’

plot_volume.y_range = Range1d(start = 0, end = 0.1)

volume_line_glyph = volume_line.glyph

main_line_glyph = main_line.glyph

name = data_now[‘price’] + " (" + data_now[‘priceChangePercent’] + “%)”

plot.text(x = np.array(d_np), y = [price_now], text = [name], text_color = ([‘red’] if ‘-’ in data_now[‘priceChangePercent’] else [‘green’]), name = “text_description”)

time_data = [datetime.today() - timedelta(days = 5), datetime.today() + timedelta(days = 5)] # draw close_rate line over +/- 5 days (10 days)

d_np = [np.datetime64(dd).astype(long) / 1000 for dd in time_data]

plot.line (np.array(d_np), [price_last_close, price_last_close], name = ‘close_line’, color = “#8B008B”, legend = ‘price’)

plots = gridplot([[plot, None], [plot_volume, None]], toolbar_location = “above”)

show(plots)

···

#################################################################################

#################################################################################

renderer_main_line = plot.select(dict(name = “main_line”))

ds_main_line = renderer_main_line[0].data_source

renderer_main_bullets = plot.select(dict(name = “main_bullets”))

ds_main_bullets = renderer_main_bullets[0].data_source

renderer_text_description = plot.select(dict(name = “text_description”))

ds_text_description = renderer_text_description[0].data_source

renderer_volume_line = plot_volume.select(dict(name = “volume_line”))

ds_volume_line = renderer_volume_line[0].data_source

last_y_value = None

last_volume = None

#################################################################################

#################################################################################

def update():

global plot_volume

global last_y_value

global last_volume

global ds_main_line

global ds_main_bullets

global ds_text_description

global ds_volume_line

new_data = monitor.get_data()

if new_data:

    new_volume = float(new_data['volume'])

    new_y_value = float(new_data['price'])

   y_value_difference = 0

    if last_y_value:

        y_value_difference = new_y_value - last_y_value

    volume_difference = 0

    if last_volume and new_volume != last_volume:

        volume_difference = new_volume - last_volume

    last_volume = new_volume

    last_y_value = new_y_value

    d_np = [np.datetime64(datetime.now()).astype(long) / 1000]

    python_array = np.array(ds_main_line.data["x"]).tolist()

    new_x_value = np.datetime64(datetime.now()).astype(long) / 1000

     python_array.append(new_x_value)

    ds_main_line.data["x"] = np.array(python_array)

     ds_main_line.data["y"].append(new_y_value)

    name = new_data['price'] + " (" + new_data['priceChangePercent'] + "%)"

     ds_main_bullets.data["x"] = np.array(d_np)

     ds_main_bullets.data["y"] = [new_y_value]

    if '-' in str(new_data['priceChangePercent']):

        main_line_color = "#EE2233"

    else:

        main_line_color = "#1E9C3D"

    main_line_glyph.line_color = main_line_color

    if volume_difference:

        if y_value_difference > 0:

            volume_color = "#1E9C3D"

        elif y_value_difference < 0:

            volume_color = "#EE2233"

        else:

             volume_color = "#000000"

        volume_line_glyph.line_color = volume_color

       ds_volume_line.data["x0"] = ds_main_line.data["x"]

        ds_volume_line.data["y0"].append(0)

        ds_volume_line.data["x1"] = ds_main_line.data["x"]

        ds_volume_line.data["y1"].append(volume_difference)

    ds_text_description.data['x'] = np.array(d_np)

     ds_text_description.data['y'] = [new_y_value + (0.1 * new_y_value / 100)]

   if '-' in str(new_data['priceChangePercent']):

        quote_info_color = "#EE2233"

    else:

        quote_info_color = "#1E9C3D"

    ds_text_description.data['text'] = [name]

    ds_text_description.data['text_color'] = [quote_info_color]

   ds_main_line.data.update(x = np.array(python_array))

   ds_volume_line.data.update(x0 = np.array(python_array))

    ds_volume_line.data.update(x1 = np.array(python_array))

time.sleep(3.5)

####################################################################################

####################################################################################

session = push_session(curdoc())

curdoc().add_periodic_callback(update, 30)

session.show() # open the document in a browser

session.loop_until_closed()

``

======== CODE END ====================

On Thursday, April 21, 2016 at 6:51:18 PM UTC+2, Bryan Van de ven wrote:

Hi Tony,

PATCH-DOC is the message sent from the server to the client, that tells the client to actually update things like data, so those messages are entirely expected.

It’s going to be extremely difficult or impossible to offer specific help or guidance without knowing details of what exactly you have tried. Is it possible you can share some code that reproduces what you are seeing?

Thanks,

Bryan

On Apr 21, 2016, at 11:46 AM, [email protected] wrote:

Hi all,

I am having a problem with my online plot that is being updated with new data each 5 seconds.

The plots draws a stock price and its volume.

Unfortunately from time to time the data gets lost so I am loosing all the lines drawn before that error happens.

When I log data I see these few lines:

DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [280 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [348 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [12246 bytes]

DEBUG:bokeh.client.connection:Running state CONNECTED_AFTER_ACK

Normally only a few of these lines are there:

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

So this line seems to be messing up everything:

DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session

Does anybody knows why bokeh server is issuing the PATCH-DOC message?

This messes up everything and plot gets lost all the data and the plotting starts again from the scratch.

Thank you for your response.

Tony


You received this message because you are subscribed to the Google Groups “Bokeh Discussion - Public” group.

To unsubscribe from this group and stop receiving emails from it, send an email to [email protected].

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For more options, visit https://groups.google.com/a/continuum.io/d/optout.

I'm no sure offhand, one thing to note is that you should really always update the entire .data property on a column data source *at once*, and not do it one column at at time. So do this:

  new_data = { .... }
        source.data = new_data

and DON'T do this:

  source.data['x'] = ...
  source.data['y'] = ...

The reason is because updates trigger immediately, so the second version triggers two updates. Apart from being wasteful, this can also cause problems if the new data is of a different length, because you will have a funky intermediate state where not all the columns have the same length, which breaks the assumptions of a column data source (all columns of a given source should *always* be the same length)

Also, if this is a streaming use-case, where you are appending new data to an existing set of columns, there is a streaming interface that is much more efficient than re-sending all the old data every update. You can see an example here:

  https://github.com/bokeh/bokeh/tree/master/examples/app/ohlc

Of course, if all the data is completely new, you have to send all the data. The streaming interface is useful when you just need to add new values.

Try those first, and let me know if there is an improvement.

Thanks,

Bryan

···

On Apr 21, 2016, at 1:58 PM, [email protected] wrote:

Hi Bryan,

Thanks for your quick reply.
It may be that I am doing something wrong.
I just only found out that after I see that server message (PATCH-DOC) it goes wrong...
Here is my code:

======== CODE START ===================

d_np = [np.datetime64(datetime.now()).astype(long) / 1000]

data_now = monitor.get_data()

if data_now and 'price' in data_now:

   price_now = float(data_now['price'])

   volume_now = float(data_now['volume'])

   price_last_close = price_now - float(data_now['priceChange'])

plot = figure(plot_width = 1200, plot_height = 400, x_axis_type = "datetime", tools = 'pan,box_select,crosshair,resize,reset,wheel_zoom,hover')

main_line = plot.line(np.array(d_np), [price_now], name = 'main_line', color = "#00BFFF", legend = 'price')

bullet_line = plot.circle(np.array(d_np), [price_now], name = 'main_bullets', color = "#00BFFF")

plot.title = data_now['name']

plot.legend.location = "top_left"

plot.xaxis.axis_label = 'Time'

plot.yaxis.axis_label = 'Price'

plot.grid.bounds = (15000, 18000)

plot.y_range = Range1d(start = price_now - ((1 * price_last_close) / 100), end = price_last_close + ((1 * price_last_close) / 100))

plot.x_range = Range1d(start = np.datetime64(datetime.now() - timedelta(hours = 1)).astype(long) / 1000, end = np.datetime64(datetime.now() + timedelta(hours = 2)).astype(long) / 1000)

plot_volume = figure(plot_width = 1200, plot_height = 400, x_range = plot.x_range, x_axis_type = "datetime", tools = 'pan,box_select,crosshair,resize,reset,wheel_zoom,hover')

volume_line = plot_volume.segment(x0 = np.array(d_np), y0 = [0], x1 = np.array(d_np), y1 = [volume_now], name = 'volume_line', color = "#FF1493")

plot_volume.title = data_now['name']

plot_volume.legend.location = "top_left"

plot_volume.xaxis.axis_label = 'Time'

plot_volume.yaxis.axis_label = 'Volume'

plot_volume.y_range = Range1d(start = 0, end = 0.1)

volume_line_glyph = volume_line.glyph

main_line_glyph = main_line.glyph

name = data_now['price'] + " (" + data_now['priceChangePercent'] + "%)"

plot.text(x = np.array(d_np), y = [price_now], text = [name], text_color = (['red'] if '-' in data_now['priceChangePercent'] else ['green']), name = "text_description")

time_data = [datetime.today() - timedelta(days = 5), datetime.today() + timedelta(days = 5)] # draw close_rate line over +/- 5 days (10 days)

d_np = [np.datetime64(dd).astype(long) / 1000 for dd in time_data]

plot.line (np.array(d_np), [price_last_close, price_last_close], name = 'close_line', color = "#8B008B", legend = 'price')

plots = gridplot([[plot, None], [plot_volume, None]], toolbar_location = "above")

show(plots)

#################################################################################

#################################################################################

renderer_main_line = plot.select(dict(name = "main_line"))

ds_main_line = renderer_main_line[0].data_source

renderer_main_bullets = plot.select(dict(name = "main_bullets"))

ds_main_bullets = renderer_main_bullets[0].data_source

renderer_text_description = plot.select(dict(name = "text_description"))

ds_text_description = renderer_text_description[0].data_source

renderer_volume_line = plot_volume.select(dict(name = "volume_line"))

ds_volume_line = renderer_volume_line[0].data_source

last_y_value = None

last_volume = None

#################################################################################

#################################################################################

def update():

   global plot_volume

   global last_y_value

   global last_volume

   global ds_main_line

   global ds_main_bullets

   global ds_text_description

   global ds_volume_line

   new_data = monitor.get_data()

    if new_data:

       new_volume = float(new_data['volume'])

       new_y_value = float(new_data['price'])

       y_value_difference = 0

       if last_y_value:

           y_value_difference = new_y_value - last_y_value

       volume_difference = 0

        if last_volume and new_volume != last_volume:

           volume_difference = new_volume - last_volume

       last_volume = new_volume

       last_y_value = new_y_value

        d_np = [np.datetime64(datetime.now()).astype(long) / 1000]

        python_array = np.array(ds_main_line.data["x"]).tolist()

        new_x_value = np.datetime64(datetime.now()).astype(long) / 1000

        python_array.append(new_x_value)

        ds_main_line.data["x"] = np.array(python_array)

        ds_main_line.data["y"].append(new_y_value)

        name = new_data['price'] + " (" + new_data['priceChangePercent'] + "%)"

        ds_main_bullets.data["x"] = np.array(d_np)

        ds_main_bullets.data["y"] = [new_y_value]

        if '-' in str(new_data['priceChangePercent']):

           main_line_color = "#EE2233"

       else:

           main_line_color = "#1E9C3D"

       main_line_glyph.line_color = main_line_color

        if volume_difference:

           if y_value_difference > 0:

               volume_color = "#1E9C3D"

           elif y_value_difference < 0:

               volume_color = "#EE2233"

           else:

                volume_color = "#000000"

           volume_line_glyph.line_color = volume_color

           ds_volume_line.data["x0"] = ds_main_line.data["x"]

           ds_volume_line.data["y0"].append(0)

           ds_volume_line.data["x1"] = ds_main_line.data["x"]

           ds_volume_line.data["y1"].append(volume_difference)

        ds_text_description.data['x'] = np.array(d_np)

        ds_text_description.data['y'] = [new_y_value + (0.1 * new_y_value / 100)]

       if '-' in str(new_data['priceChangePercent']):

           quote_info_color = "#EE2233"

       else:

           quote_info_color = "#1E9C3D"

       ds_text_description.data['text'] = [name]

       ds_text_description.data['text_color'] = [quote_info_color]

       ds_main_line.data.update(x = np.array(python_array))

       ds_volume_line.data.update(x0 = np.array(python_array))

       ds_volume_line.data.update(x1 = np.array(python_array))

    time.sleep(3.5)

####################################################################################

####################################################################################

session = push_session(curdoc())

curdoc().add_periodic_callback(update, 30)

session.show() # open the document in a browser

session.loop_until_closed()

======== CODE END ====================

On Thursday, April 21, 2016 at 6:51:18 PM UTC+2, Bryan Van de ven wrote:
Hi Tony,

PATCH-DOC is the message sent from the server to the client, that tells the client to actually update things like data, so those messages are entirely expected.

It's going to be extremely difficult or impossible to offer specific help or guidance without knowing details of what exactly you have tried. Is it possible you can share some code that reproduces what you are seeing?

Thanks,

Bryan

> On Apr 21, 2016, at 11:46 AM, [email protected] wrote:
>
> Hi all,
>
> I am having a problem with my online plot that is being updated with new data each 5 seconds.
> The plots draws a stock price and its volume.
>
> Unfortunately from time to time the data gets lost so I am loosing all the lines drawn before that error happens.
> When I log data I see these few lines:
>
> DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session
>
> DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [305 bytes]
>
> DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [280 bytes]
>
> DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [348 bytes]
>
> DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [305 bytes]
>
> DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [12246 bytes]
>
> DEBUG:bokeh.client.connection:Running state CONNECTED_AFTER_ACK
>
>
>
> Normally only a few of these lines are there:
>
> DEBUG:bokeh.client.connection:Sent Message 'PATCH-DOC' (revision 1) [305 bytes]
>
>
>
> So this line seems to be messing up everything:
>
> DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session
>
>
>
> Does anybody knows why bokeh server is issuing the PATCH-DOC message?
>
> This messes up everything and plot gets lost all the data and the plotting starts again from the scratch.
>
>
>
> Thank you for your response.
>
>
>
> Tony
>
>
>
>
> --
> You received this message because you are subscribed to the Google Groups "Bokeh Discussion - Public" group.
> To unsubscribe from this group and stop receiving emails from it, send an email to [email protected].
> To post to this group, send email to [email protected].
> To view this discussion on the web visit https://groups.google.com/a/continuum.io/d/msgid/bokeh/65d95ae7-b8a1-4efd-93d3-1840f5c53f45%40continuum.io.
> For more options, visit https://groups.google.com/a/continuum.io/d/optout.

--
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For more options, visit https://groups.google.com/a/continuum.io/d/optout.

I see.
I will have a look at the examples and try to follow your suggestions then I will let you know.

Thanks a lot!

Tony

···

On Thursday, April 21, 2016 at 9:31:38 PM UTC+2, Bryan Van de ven wrote:

I’m no sure offhand, one thing to note is that you should really always update the entire .data property on a column data source at once, and not do it one column at at time. So do this:

    new_data = { .... }

    source.data = new_data

and DON’T do this:

    source.data['x'] = ...

    source.data['y'] = ...

The reason is because updates trigger immediately, so the second version triggers two updates. Apart from being wasteful, this can also cause problems if the new data is of a different length, because you will have a funky intermediate state where not all the columns have the same length, which breaks the assumptions of a column data source (all columns of a given source should always be the same length)

Also, if this is a streaming use-case, where you are appending new data to an existing set of columns, there is a streaming interface that is much more efficient than re-sending all the old data every update. You can see an example here:

    [https://github.com/bokeh/bokeh/tree/master/examples/app/ohlc](https://github.com/bokeh/bokeh/tree/master/examples/app/ohlc)

Of course, if all the data is completely new, you have to send all the data. The streaming interface is useful when you just need to add new values.

Try those first, and let me know if there is an improvement.

Thanks,

Bryan

On Apr 21, 2016, at 1:58 PM, [email protected] wrote:

Hi Bryan,

Thanks for your quick reply.

It may be that I am doing something wrong.

I just only found out that after I see that server message (PATCH-DOC) it goes wrong…

Here is my code:

======== CODE START ===================

d_np = [np.datetime64(datetime.now()).astype(long) / 1000]

data_now = monitor.get_data()

if data_now and ‘price’ in data_now:

price_now = float(data_now[‘price’])

volume_now = float(data_now[‘volume’])

price_last_close = price_now - float(data_now[‘priceChange’])

plot = figure(plot_width = 1200, plot_height = 400, x_axis_type = “datetime”, tools = ‘pan,box_select,crosshair,resize,reset,wheel_zoom,hover’)

main_line = plot.line(np.array(d_np), [price_now], name = ‘main_line’, color = “#00BFFF”, legend = ‘price’)

bullet_line = plot.circle(np.array(d_np), [price_now], name = ‘main_bullets’, color = “#00BFFF”)

plot.title = data_now[‘name’]

plot.legend.location = “top_left”

plot.xaxis.axis_label = ‘Time’

plot.yaxis.axis_label = ‘Price’

plot.grid.bounds = (15000, 18000)

plot.y_range = Range1d(start = price_now - ((1 * price_last_close) / 100), end = price_last_close + ((1 * price_last_close) / 100))

plot.x_range = Range1d(start = np.datetime64(datetime.now() - timedelta(hours = 1)).astype(long) / 1000, end = np.datetime64(datetime.now() + timedelta(hours = 2)).astype(long) / 1000)

plot_volume = figure(plot_width = 1200, plot_height = 400, x_range = plot.x_range, x_axis_type = “datetime”, tools = ‘pan,box_select,crosshair,resize,reset,wheel_zoom,hover’)

volume_line = plot_volume.segment(x0 = np.array(d_np), y0 = [0], x1 = np.array(d_np), y1 = [volume_now], name = ‘volume_line’, color = “#FF1493”)

plot_volume.title = data_now[‘name’]

plot_volume.legend.location = “top_left”

plot_volume.xaxis.axis_label = ‘Time’

plot_volume.yaxis.axis_label = ‘Volume’

plot_volume.y_range = Range1d(start = 0, end = 0.1)

volume_line_glyph = volume_line.glyph

main_line_glyph = main_line.glyph

name = data_now[‘price’] + " (" + data_now[‘priceChangePercent’] + “%)”

plot.text(x = np.array(d_np), y = [price_now], text = [name], text_color = ([‘red’] if ‘-’ in data_now[‘priceChangePercent’] else [‘green’]), name = “text_description”)

time_data = [datetime.today() - timedelta(days = 5), datetime.today() + timedelta(days = 5)] # draw close_rate line over +/- 5 days (10 days)

d_np = [np.datetime64(dd).astype(long) / 1000 for dd in time_data]

plot.line (np.array(d_np), [price_last_close, price_last_close], name = ‘close_line’, color = “#8B008B”, legend = ‘price’)

plots = gridplot([[plot, None], [plot_volume, None]], toolbar_location = “above”)

show(plots)

#################################################################################

#################################################################################

renderer_main_line = plot.select(dict(name = “main_line”))

ds_main_line = renderer_main_line[0].data_source

renderer_main_bullets = plot.select(dict(name = “main_bullets”))

ds_main_bullets = renderer_main_bullets[0].data_source

renderer_text_description = plot.select(dict(name = “text_description”))

ds_text_description = renderer_text_description[0].data_source

renderer_volume_line = plot_volume.select(dict(name = “volume_line”))

ds_volume_line = renderer_volume_line[0].data_source

last_y_value = None

last_volume = None

#################################################################################

#################################################################################

def update():

global plot_volume

global last_y_value

global last_volume

global ds_main_line

global ds_main_bullets

global ds_text_description

global ds_volume_line

new_data = monitor.get_data()

if new_data:
   new_volume = float(new_data['volume'])
   new_y_value = float(new_data['price'])
   y_value_difference = 0
   if last_y_value:
       y_value_difference = new_y_value - last_y_value
   volume_difference = 0
    if last_volume and new_volume != last_volume:
       volume_difference = new_volume - last_volume
   last_volume = new_volume
   last_y_value = new_y_value
    d_np = [np.datetime64(datetime.now()).astype(long) / 1000]
    python_array = np.array(ds_main_line.data["x"]).tolist()
    new_x_value = np.datetime64(datetime.now()).astype(long) / 1000
    python_array.append(new_x_value)
    ds_main_line.data["x"] = np.array(python_array)
    ds_main_line.data["y"].append(new_y_value)
    name = new_data['price'] + " (" + new_data['priceChangePercent'] + "%)"
    ds_main_bullets.data["x"] = np.array(d_np)
    ds_main_bullets.data["y"] = [new_y_value]
    if '-' in str(new_data['priceChangePercent']):
       main_line_color = "#EE2233"
   else:
       main_line_color = "#1E9C3D"
   main_line_glyph.line_color = main_line_color
    if volume_difference:
       if y_value_difference > 0:
           volume_color = "#1E9C3D"
       elif y_value_difference < 0:
           volume_color = "#EE2233"
       else:
            volume_color = "#000000"
       volume_line_glyph.line_color = volume_color
       ds_volume_line.data["x0"] = ds_main_line.data["x"]
       ds_volume_line.data["y0"].append(0)
       ds_volume_line.data["x1"] = ds_main_line.data["x"]
       ds_volume_line.data["y1"].append(volume_difference)
    ds_text_description.data['x'] = np.array(d_np)
    ds_text_description.data['y'] = [new_y_value + (0.1 * new_y_value / 100)]
   if '-' in str(new_data['priceChangePercent']):
       quote_info_color = "#EE2233"
   else:
       quote_info_color = "#1E9C3D"
   ds_text_description.data['text'] = [name]
   ds_text_description.data['text_color'] = [quote_info_color]
   ds_main_line.data.update(x = np.array(python_array))
   ds_volume_line.data.update(x0 = np.array(python_array))
   ds_volume_line.data.update(x1 = np.array(python_array))
time.sleep(3.5)

####################################################################################

####################################################################################

session = push_session(curdoc())

curdoc().add_periodic_callback(update, 30)

session.show() # open the document in a browser

session.loop_until_closed()

======== CODE END ====================

On Thursday, April 21, 2016 at 6:51:18 PM UTC+2, Bryan Van de ven wrote:

Hi Tony,

PATCH-DOC is the message sent from the server to the client, that tells the client to actually update things like data, so those messages are entirely expected.

It’s going to be extremely difficult or impossible to offer specific help or guidance without knowing details of what exactly you have tried. Is it possible you can share some code that reproduces what you are seeing?

Thanks,

Bryan

On Apr 21, 2016, at 11:46 AM, [email protected] wrote:

Hi all,

I am having a problem with my online plot that is being updated with new data each 5 seconds.
The plots draws a stock price and its volume.

Unfortunately from time to time the data gets lost so I am loosing all the lines drawn before that error happens.
When I log data I see these few lines:

DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [280 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [348 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [12246 bytes]

DEBUG:bokeh.client.connection:Running state CONNECTED_AFTER_ACK

Normally only a few of these lines are there:

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

So this line seems to be messing up everything:

DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session

Does anybody knows why bokeh server is issuing the PATCH-DOC message?

This messes up everything and plot gets lost all the data and the plotting starts again from the scratch.

Thank you for your response.

Tony


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You received this message because you are subscribed to the Google Groups “Bokeh Discussion - Public” group.

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To post to this group, send email to [email protected].

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Hi Bryan,

Following your advice I did modifications to my script applying streaming interface from your example.

Now the plot is continuous and the problem seems solved.

Thank you!

···

On Thursday, April 21, 2016 at 10:03:41 PM UTC+2, [email protected] wrote:

I see.
I will have a look at the examples and try to follow your suggestions then I will let you know.

Thanks a lot!

Tony

On Thursday, April 21, 2016 at 9:31:38 PM UTC+2, Bryan Van de ven wrote:

I’m no sure offhand, one thing to note is that you should really always update the entire .data property on a column data source at once, and not do it one column at at time. So do this:

    new_data = { .... }

    source.data = new_data

and DON’T do this:

    source.data['x'] = ...

    source.data['y'] = ...

The reason is because updates trigger immediately, so the second version triggers two updates. Apart from being wasteful, this can also cause problems if the new data is of a different length, because you will have a funky intermediate state where not all the columns have the same length, which breaks the assumptions of a column data source (all columns of a given source should always be the same length)

Also, if this is a streaming use-case, where you are appending new data to an existing set of columns, there is a streaming interface that is much more efficient than re-sending all the old data every update. You can see an example here:

    [https://github.com/bokeh/bokeh/tree/master/examples/app/ohlc](https://github.com/bokeh/bokeh/tree/master/examples/app/ohlc)

Of course, if all the data is completely new, you have to send all the data. The streaming interface is useful when you just need to add new values.

Try those first, and let me know if there is an improvement.

Thanks,

Bryan

On Apr 21, 2016, at 1:58 PM, [email protected] wrote:

Hi Bryan,

Thanks for your quick reply.

It may be that I am doing something wrong.

I just only found out that after I see that server message (PATCH-DOC) it goes wrong…

Here is my code:

======== CODE START ===================

d_np = [np.datetime64(datetime.now()).astype(long) / 1000]

data_now = monitor.get_data()

if data_now and ‘price’ in data_now:

price_now = float(data_now[‘price’])

volume_now = float(data_now[‘volume’])

price_last_close = price_now - float(data_now[‘priceChange’])

plot = figure(plot_width = 1200, plot_height = 400, x_axis_type = “datetime”, tools = ‘pan,box_select,crosshair,resize,reset,wheel_zoom,hover’)

main_line = plot.line(np.array(d_np), [price_now], name = ‘main_line’, color = “#00BFFF”, legend = ‘price’)

bullet_line = plot.circle(np.array(d_np), [price_now], name = ‘main_bullets’, color = “#00BFFF”)

plot.title = data_now[‘name’]

plot.legend.location = “top_left”

plot.xaxis.axis_label = ‘Time’

plot.yaxis.axis_label = ‘Price’

plot.grid.bounds = (15000, 18000)

plot.y_range = Range1d(start = price_now - ((1 * price_last_close) / 100), end = price_last_close + ((1 * price_last_close) / 100))

plot.x_range = Range1d(start = np.datetime64(datetime.now() - timedelta(hours = 1)).astype(long) / 1000, end = np.datetime64(datetime.now() + timedelta(hours = 2)).astype(long) / 1000)

plot_volume = figure(plot_width = 1200, plot_height = 400, x_range = plot.x_range, x_axis_type = “datetime”, tools = ‘pan,box_select,crosshair,resize,reset,wheel_zoom,hover’)

volume_line = plot_volume.segment(x0 = np.array(d_np), y0 = [0], x1 = np.array(d_np), y1 = [volume_now], name = ‘volume_line’, color = “#FF1493”)

plot_volume.title = data_now[‘name’]

plot_volume.legend.location = “top_left”

plot_volume.xaxis.axis_label = ‘Time’

plot_volume.yaxis.axis_label = ‘Volume’

plot_volume.y_range = Range1d(start = 0, end = 0.1)

volume_line_glyph = volume_line.glyph

main_line_glyph = main_line.glyph

name = data_now[‘price’] + " (" + data_now[‘priceChangePercent’] + “%)”

plot.text(x = np.array(d_np), y = [price_now], text = [name], text_color = ([‘red’] if ‘-’ in data_now[‘priceChangePercent’] else [‘green’]), name = “text_description”)

time_data = [datetime.today() - timedelta(days = 5), datetime.today() + timedelta(days = 5)] # draw close_rate line over +/- 5 days (10 days)

d_np = [np.datetime64(dd).astype(long) / 1000 for dd in time_data]

plot.line (np.array(d_np), [price_last_close, price_last_close], name = ‘close_line’, color = “#8B008B”, legend = ‘price’)

plots = gridplot([[plot, None], [plot_volume, None]], toolbar_location = “above”)

show(plots)

#################################################################################

#################################################################################

renderer_main_line = plot.select(dict(name = “main_line”))

ds_main_line = renderer_main_line[0].data_source

renderer_main_bullets = plot.select(dict(name = “main_bullets”))

ds_main_bullets = renderer_main_bullets[0].data_source

renderer_text_description = plot.select(dict(name = “text_description”))

ds_text_description = renderer_text_description[0].data_source

renderer_volume_line = plot_volume.select(dict(name = “volume_line”))

ds_volume_line = renderer_volume_line[0].data_source

last_y_value = None

last_volume = None

#################################################################################

#################################################################################

def update():

global plot_volume

global last_y_value

global last_volume

global ds_main_line

global ds_main_bullets

global ds_text_description

global ds_volume_line

new_data = monitor.get_data()

if new_data:
   new_volume = float(new_data['volume'])
   new_y_value = float(new_data['price'])
   y_value_difference = 0
   if last_y_value:
       y_value_difference = new_y_value - last_y_value
   volume_difference = 0
    if last_volume and new_volume != last_volume:
       volume_difference = new_volume - last_volume
   last_volume = new_volume
   last_y_value = new_y_value
    d_np = [np.datetime64(datetime.now()).astype(long) / 1000]
    python_array = np.array(ds_main_line.data["x"]).tolist()
    new_x_value = np.datetime64(datetime.now()).astype(long) / 1000
    python_array.append(new_x_value)
    ds_main_line.data["x"] = np.array(python_array)
    ds_main_line.data["y"].append(new_y_value)
    name = new_data['price'] + " (" + new_data['priceChangePercent'] + "%)"
    ds_main_bullets.data["x"] = np.array(d_np)
    ds_main_bullets.data["y"] = [new_y_value]
    if '-' in str(new_data['priceChangePercent']):
       main_line_color = "#EE2233"
   else:
       main_line_color = "#1E9C3D"
   main_line_glyph.line_color = main_line_color
    if volume_difference:
       if y_value_difference > 0:
           volume_color = "#1E9C3D"
       elif y_value_difference < 0:
           volume_color = "#EE2233"
       else:
            volume_color = "#000000"
       volume_line_glyph.line_color = volume_color
       ds_volume_line.data["x0"] = ds_main_line.data["x"]
       ds_volume_line.data["y0"].append(0)
       ds_volume_line.data["x1"] = ds_main_line.data["x"]
       ds_volume_line.data["y1"].append(volume_difference)
    ds_text_description.data['x'] = np.array(d_np)
    ds_text_description.data['y'] = [new_y_value + (0.1 * new_y_value / 100)]
   if '-' in str(new_data['priceChangePercent']):
       quote_info_color = "#EE2233"
   else:
       quote_info_color = "#1E9C3D"
   ds_text_description.data['text'] = [name]
   ds_text_description.data['text_color'] = [quote_info_color]
   ds_main_line.data.update(x = np.array(python_array))
   ds_volume_line.data.update(x0 = np.array(python_array))
   ds_volume_line.data.update(x1 = np.array(python_array))
time.sleep(3.5)

####################################################################################

####################################################################################

session = push_session(curdoc())

curdoc().add_periodic_callback(update, 30)

session.show() # open the document in a browser

session.loop_until_closed()

======== CODE END ====================

On Thursday, April 21, 2016 at 6:51:18 PM UTC+2, Bryan Van de ven wrote:

Hi Tony,

PATCH-DOC is the message sent from the server to the client, that tells the client to actually update things like data, so those messages are entirely expected.

It’s going to be extremely difficult or impossible to offer specific help or guidance without knowing details of what exactly you have tried. Is it possible you can share some code that reproduces what you are seeing?

Thanks,

Bryan

On Apr 21, 2016, at 11:46 AM, [email protected] wrote:

Hi all,

I am having a problem with my online plot that is being updated with new data each 5 seconds.
The plots draws a stock price and its volume.

Unfortunately from time to time the data gets lost so I am loosing all the lines drawn before that error happens.
When I log data I see these few lines:

DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [280 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [348 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [12246 bytes]

DEBUG:bokeh.client.connection:Running state CONNECTED_AFTER_ACK

Normally only a few of these lines are there:

DEBUG:bokeh.client.connection:Sent Message ‘PATCH-DOC’ (revision 1) [305 bytes]

So this line seems to be messing up everything:

DEBUG:bokeh.client.connection:Got PATCH-DOC, applying to session

Does anybody knows why bokeh server is issuing the PATCH-DOC message?

This messes up everything and plot gets lost all the data and the plotting starts again from the scratch.

Thank you for your response.

Tony


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