Bokeh error with show(plot) - TypeError: 'numpy.int64' object is not iterable

I am trying to adapt an example from the Bokeh gallery (http://bokeh.pydata.org/en/latest/docs/gallery/unemployment.html )
with my own data. I only changed the data sources, yet when I run this
code in my Jupyter notebook I get the following error with show§. Additionally, this then causes all of my other Bokeh plots in the same notebook to show the same error, even though they worked fine before running this below segment of code. The data types are all the same as the original example so I can’t figure out what is going on! Below is the error message (quite long) and my original code. Anyone have any ideas?

TypeError                                 Traceback (most recent call last)
<ipython-input-32-948a877f9774> in <module>()
     55 output_notebook()
     56
---> 57 show(p)      # show the plot

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in show(obj, browser, new)
    299
    300     '''
--> 301     return _show_with_state(obj, _state, browser, new)
    302
    303 def _show_with_state(obj, state, browser, new):

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in _show_with_state(obj, state, browser, new)
    307
    308     if state.notebook:
--> 309         comms_handle = _show_notebook_with_state(obj, state)
    310
    311     elif state.server_enabled:

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in _show_notebook_with_state(obj, state)
    328     else:
    329         comms_target = make_id()
--> 330         publish_display_data({'text/html': notebook_div(obj, comms_target)})
    331         handle = _CommsHandle(get_comms(comms_target), state.document, state.document.to_json())
    332         state.last_comms_handle = handle

/usr/local/lib/python3.4/dist-packages/bokeh/embed.py in notebook_div(model, notebook_comms_target)
    247
    248     with _ModelInDocument(model):
--> 249         (docs_json, render_items) = _standalone_docs_json_and_render_items([model])
    250
    251     item = render_items[0]

/usr/local/lib/python3.4/dist-packages/bokeh/embed.py in _standalone_docs_json_and_render_items(models)
    564     docs_json = {}
    565     for k, v in docs_by_id.items():
--> 566         docs_json[k] = v.to_json()
    567
    568     return (docs_json, render_items)

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in to_json(self)
    730         # this is a total hack to go via a string, needed because
    731         # our BokehJSONEncoder goes straight to a string.
--> 732         doc_json = self.to_json_string()
    733         return loads(doc_json)
    734

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in to_json_string(self, indent)
    718             'roots' : {
    719                 'root_ids' : root_ids,
--> 720                 'references' : self._references_json(root_references)
    721             },
    722             'version' : __version__

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in _references_json(cls, references)
    529         for r in references:
    530             ref = r.ref
--> 531             ref['attributes'] = r._to_json_like(include_defaults=False)
    532             references_json.append(ref)
    533

/usr/local/lib/python3.4/dist-packages/bokeh/models/sources.py in _to_json_like(self, include_defaults)
    173         attrs = super(ColumnDataSource, self)._to_json_like(include_defaults=include_defaults)
    174         if 'data' in attrs:
--> 175             attrs['data'] = transform_column_source_data(attrs['data'])
    176         return attrs
    177

/usr/local/lib/python3.4/dist-packages/bokeh/util/serialization.py in transform_column_source_data(data)
    127             data_copy[key] = transform_array(data[key])
    128         else:
--> 129             data_copy[key] = traverse_data(data[key])
    130     return data_copy

/usr/local/lib/python3.4/dist-packages/bokeh/util/serialization.py in traverse_data(datum, is_numpy, use_numpy)
     98     """
     99     is_numpy = is_numpy and use_numpy
--> 100     if is_numpy and not any(isinstance(el, (list, tuple)) for el in datum):
    101         return transform_array(np.asarray(datum))
    102     datum_copy = []

TypeError: 'numpy.int64' object is not iterable


from math import pi, floor
from bokeh.models import HoverTool
from bokeh.plotting import ColumnDataSource, figure, show
from bokeh.palettes import Reds9
from bokeh.io import output_notebook
groups = data.groupby(['DayOfWeek', 'hour']).size()
max_crimes = max(groups)
min_crimes = min(groups)
factor = (max_crimes - min_crimes) / 8.9999999
days = ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday']
days_abbr = [day[:4] for day in days]
hours = list(range(24))
# Set up the data for plotting. We will need to have values for every
# pair of day/hour names. Map the rate to a color.
day= []
hour = []
color = []
counts = []
for d in days:
for h in hours:
day.append(d)
hour.append(str(h))
count = groups[d][h:h+1].values[0]
counts.append(count)
color_index = floor((count - min_crimes) / factor)
color.append(Reds9[color_index]) source = ColumnDataSource(
data=dict(day=day, hour=hour, color=color, count=count)
)
TOOLS = "resize,hover,save,pan,box_zoom,wheel_zoom"
p = figure(title="Frequency of Crimes Throughout the Week", x_range=[str(h) for h in hours], y_range=days,
x_axis_location="above", plot_width=900, plot_height=400,
toolbar_location="left", tools=TOOLS)
p.grid.grid_line_color = None
p.axis.axis_line_color = None
p.axis.major_tick_line_color = None
p.axis.major_label_text_font_size = "5pt"
p.axis.major_label_standoff = 0
p.xaxis.major_label_orientation = pi/3
p.rect("day", "hour", 1, 1, source=source,
color="color", line_color=None)
p.select_one(HoverTool).tooltips = [
('Time of Week', '@day @hour'),
('Crime Count', '@count'),]
output_notebook()
show(p) # show the plot

You’re setting “count” in your data source (which is a number) instead of “counts” (which is the list of numbers).

Bryan

···

On Apr 17, 2016, at 07:42, [email protected] wrote:

I am trying to adapt an example from the Bokeh gallery (http://bokeh.pydata.org/en/latest/docs/gallery/unemployment.html )
with my own data. I only changed the data sources, yet when I run this
code in my Jupyter notebook I get the following error with show§. Additionally, this then causes all of my other Bokeh plots in the same notebook to show the same error, even though they worked fine before running this below segment of code. The data types are all the same as the original example so I can’t figure out what is going on! Below is the error message (quite long) and my original code. Anyone have any ideas?

TypeError                                 Traceback (most recent call last)
<ipython-input-32-948a877f9774> in <module>()
     55 output_notebook()
     56
---> 57 show(p)      # show the plot

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in show(obj, browser, new)
    299
    300     '''
--> 301     return _show_with_state(obj, _state, browser, new)
    302
    303 def _show_with_state(obj, state, browser, new):

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in _show_with_state(obj, state, browser, new)
    307
    308     if state.notebook:
--> 309         comms_handle = _show_notebook_with_state(obj, state)
    310
    311     elif state.server_enabled:

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in _show_notebook_with_state(obj, state)
    328     else:
    329         comms_target = make_id()
--> 330         publish_display_data({'text/html': notebook_div(obj, comms_target)})
    331         handle = _CommsHandle(get_comms(comms_target), state.document, state.document.to_json())
    332         state.last_comms_handle = handle

/usr/local/lib/python3.4/dist-packages/bokeh/embed.py in notebook_div(model, notebook_comms_target)
    247
    248     with _ModelInDocument(model):
--> 249         (docs_json, render_items) = _standalone_docs_json_and_render_items([model])
    250
    251     item = render_items[0]

/usr/local/lib/python3.4/dist-packages/bokeh/embed.py in _standalone_docs_json_and_render_items(models)
    564     docs_json = {}
    565     for k, v in docs_by_id.items():
--> 566         docs_json[k] = v.to_json()
    567
    568     return (docs_json, render_items)

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in to_json(self)
    730         # this is a total hack to go via a string, needed because
    731         # our BokehJSONEncoder goes straight to a string.
--> 732         doc_json = self.to_json_string()
    733         return loads(doc_json)
    734

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in to_json_string(self, indent)
    718             'roots' : {
    719                 'root_ids' : root_ids,
--> 720                 'references' : self._references_json(root_references)
    721             },
    722             'version' : __version__

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in _references_json(cls, references)
    529         for r in references:
    530             ref = r.ref
--> 531             ref['attributes'] = r._to_json_like(include_defaults=False)
    532             references_json.append(ref)
    533

/usr/local/lib/python3.4/dist-packages/bokeh/models/sources.py in _to_json_like(self, include_defaults)
    173         attrs = super(ColumnDataSource, self)._to_json_like(include_defaults=include_defaults)
    174         if 'data' in attrs:
--> 175             attrs['data'] = transform_column_source_data(attrs['data'])
    176         return attrs
    177

/usr/local/lib/python3.4/dist-packages/bokeh/util/serialization.py in transform_column_source_data(data)
    127             data_copy[key] = transform_array(data[key])
    128         else:
--> 129             data_copy[key] = traverse_data(data[key])
    130     return data_copy

/usr/local/lib/python3.4/dist-packages/bokeh/util/serialization.py in traverse_data(datum, is_numpy, use_numpy)
     98     """
     99     is_numpy = is_numpy and use_numpy
--> 100     if is_numpy and not any(isinstance(el, (list, tuple)) for el in datum):
    101         return transform_array(np.asarray(datum))
    102     datum_copy = []

TypeError: 'numpy.int64' object is not iterable




from math import pi, floor
from bokeh.models import HoverTool
from bokeh.plotting import ColumnDataSource, figure, show
from bokeh.palettes import Reds9
from [bokeh.io](http://bokeh.io) import output_notebook
groups = data.groupby(['DayOfWeek', 'hour']).size()
max_crimes = max(groups)
min_crimes = min(groups)
factor = (max_crimes - min_crimes) / 8.9999999
days = ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday']
days_abbr = [day[:4] for day in days]
hours = list(range(24))
# Set up the data for plotting. We will need to have values for every
# pair of day/hour names. Map the rate to a color.
day= []
hour = []
color = []
counts = []
for d in days:
for h in hours:
day.append(d)
hour.append(str(h))
count = groups[d][h:h+1].values[0]
counts.append(count)
color_index = floor((count - min_crimes) / factor)
color.append(Reds9[color_index]) source = ColumnDataSource(
data=dict(day=day, hour=hour, color=color, count=count)
)
TOOLS = "resize,hover,save,pan,box_zoom,wheel_zoom"
p = figure(title="Frequency of Crimes Throughout the Week", x_range=[str(h) for h in hours], y_range=days,
x_axis_location="above", plot_width=900, plot_height=400,
toolbar_location="left", tools=TOOLS)
p.grid.grid_line_color = None
p.axis.axis_line_color = None
p.axis.major_tick_line_color = None
p.axis.major_label_text_font_size = "5pt"
p.axis.major_label_standoff = 0
p.xaxis.major_label_orientation = pi/3
p.rect("day", "hour", 1, 1, source=source,
color="color", line_color=None)
p.select_one(HoverTool).tooltips = [
('Time of Week', '@day @hour'),
('Crime Count', '@count'),]
output_notebook()
show(p) # show the plot

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Hi Bryan,

Thanks for pointing it out. Sorry to bother with what turned out to be such a trivial error…

Out of curiosity, do you have a reason as to why that error causes my other bokeh plots within the same notebook to fail?

Bill

···

On Sunday, April 17, 2016 at 4:13:32 PM UTC+2, Bryan Van de ven wrote:

You’re setting “count” in your data source (which is a number) instead of “counts” (which is the list of numbers).

Bryan

On Apr 17, 2016, at 07:42, [email protected] wrote:

I am trying to adapt an example from the Bokeh gallery (http://bokeh.pydata.org/en/latest/docs/gallery/unemployment.html )
with my own data. I only changed the data sources, yet when I run this
code in my Jupyter notebook I get the following error with show§. Additionally, this then causes all of my other Bokeh plots in the same notebook to show the same error, even though they worked fine before running this below segment of code. The data types are all the same as the original example so I can’t figure out what is going on! Below is the error message (quite long) and my original code. Anyone have any ideas?

TypeError                                 Traceback (most recent call last)
<ipython-input-32-948a877f9774> in <module>()
     55 output_notebook()
     56
---> 57 show(p)      # show the plot

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in show(obj, browser, new)
    299
    300     '''
--> 301     return _show_with_state(obj, _state, browser, new)
    302
    303 def _show_with_state(obj, state, browser, new):

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in _show_with_state(obj, state, browser, new)
    307
    308     if state.notebook:
--> 309         comms_handle = _show_notebook_with_state(obj, state)
    310
    311     elif state.server_enabled:

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in _show_notebook_with_state(obj, state)
    328     else:
    329         comms_target = make_id()
--> 330         publish_display_data({'text/html': notebook_div(obj, comms_target)})
    331         handle = _CommsHandle(get_comms(comms_target), state.document, state.document.to_json())
    332         state.last_comms_handle = handle

/usr/local/lib/python3.4/dist-packages/bokeh/embed.py in notebook_div(model, notebook_comms_target)
    247
    248     with _ModelInDocument(model):
--> 249         (docs_json, render_items) = _standalone_docs_json_and_render_items([model])
    250
    251     item = render_items[0]

/usr/local/lib/python3.4/dist-packages/bokeh/embed.py in _standalone_docs_json_and_render_items(models)
    564     docs_json = {}
    565     for k, v in docs_by_id.items():
--> 566         docs_json[k] = v.to_json()
    567
    568     return (docs_json, render_items)

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in to_json(self)
    730         # this is a total hack to go via a string, needed because
    731         # our BokehJSONEncoder goes straight to a string.
--> 732         doc_json = self.to_json_string()
    733         return loads(doc_json)
    734

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in to_json_string(self, indent)
    718             'roots' : {
    719                 'root_ids' : root_ids,
--> 720                 'references' : self._references_json(root_references)
    721             },
    722             'version' : __version__

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in _references_json(cls, references)
    529         for r in references:
    530             ref = r.ref
--> 531             ref['attributes'] = r._to_json_like(include_defaults=False)
    532             references_json.append(ref)
    533

/usr/local/lib/python3.4/dist-packages/bokeh/models/sources.py in _to_json_like(self, include_defaults)
    173         attrs = super(ColumnDataSource, self)._to_json_like(include_defaults=include_defaults)
    174         if 'data' in attrs:
--> 175             attrs['data'] = transform_column_source_data(attrs['data'])
    176         return attrs
    177

/usr/local/lib/python3.4/dist-packages/bokeh/util/serialization.py in transform_column_source_data(data)
    127             data_copy[key] = transform_array(data[key])
    128         else:
--> 129             data_copy[key] = traverse_data(data[key])
    130     return data_copy

/usr/local/lib/python3.4/dist-packages/bokeh/util/serialization.py in traverse_data(datum, is_numpy, use_numpy)
     98     """
     99     is_numpy = is_numpy and use_numpy
--> 100     if is_numpy and not any(isinstance(el, (list, tuple)) for el in datum):
    101         return transform_array(np.asarray(datum))
    102     datum_copy = []

TypeError: 'numpy.int64' object is not iterable




from math import pi, floor
from bokeh.models import HoverTool
from bokeh.plotting import ColumnDataSource, figure, show
from bokeh.palettes import Reds9
from [bokeh.io](http://bokeh.io) import output_notebook
groups = data.groupby(['DayOfWeek', 'hour']).size()
max_crimes = max(groups)
min_crimes = min(groups)
factor = (max_crimes - min_crimes) / 8.9999999
days = ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday']
days_abbr = [day[:4] for day in days]
hours = list(range(24))
# Set up the data for plotting. We will need to have values for every
# pair of day/hour names. Map the rate to a color.
day= []
hour = []
color = []
counts = []
for d in days:
for h in hours:
day.append(d)
hour.append(str(h))
count = groups[d][h:h+1].values[0]
counts.append(count)
color_index = floor((count - min_crimes) / factor)
color.append(Reds9[color_
index]) source = ColumnDataSource(
data=dict(day=day, hour=hour, color=color, count=count)
)
TOOLS = "resize,hover,save,pan,box_
zoom,wheel_zoom"
p = figure(title="Frequency of Crimes Throughout the Week", x_range=[str(h) for h in hours], y_range=days,
x_axis_location="above", plot_width=900, plot_height=400,
toolbar_location="left", tools=TOOLS)
p.grid.grid_line_color = None
p.axis.axis_line_color = None
p.axis.major_tick_line_color = None
p.axis.major_label_text_font_size = "5pt"
p.axis.major_label_standoff = 0
p.xaxis.major_label_
orientation = pi/3
p.rect("day", "hour", 1, 1, source=source,
color="color", line_color=None)
p.select_one(HoverTool).    tooltips = [
('Time of Week', '@day @hour'),
('Crime Count', '@count'),]
output_notebook()
show(p) # show the plot

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Hi Bill,

BokehJS is a large and complicated JS library, and the Jupyter Notebook frontend is also a large and complicated JS library. Sometimes I think its a wonder that they can be made to work together at all. :slight_smile: Additionally, the notebook's concept of arbitrary execution order of cells often makes it difficult to reason about things effectively, too. But in any cse there's only one "copy" of BokehJS in a notebook page at a time, so I can imagine if it gets into a bad state that can affect multiple plots. I couldn't really speculate further without actually diving into things.

Thanks,

Bryan

···

On Apr 18, 2016, at 5:47 AM, [email protected] wrote:

Hi Bryan,

Thanks for pointing it out. Sorry to bother with what turned out to be such a trivial error...

Out of curiosity, do you have a reason as to why that error causes my other bokeh plots within the same notebook to fail?

Bill

On Sunday, April 17, 2016 at 4:13:32 PM UTC+2, Bryan Van de ven wrote:
You're setting "count" in your data source (which is a number) instead of "counts" (which is the list of numbers).

Bryan

On Apr 17, 2016, at 07:42, [email protected] wrote:

I am trying to adapt an example from the Bokeh gallery (http://bokeh.pydata.org/en/latest/docs/gallery/unemployment.html) with my own data. I only changed the data sources, yet when I run this code in my Jupyter notebook I get the following error with show(p). Additionally, this then causes all of my other Bokeh plots in the same notebook to show the same error, even though they worked fine before running this below segment of code. The data types are all the same as the original example so I can't figure out what is going on! Below is the error message (quite long) and my original code. Anyone have any ideas?

TypeError
                                 Traceback (most recent call last)

<ipython-input-32-948a877f9774> in <module>()
     55 output_notebook()
     56
---> 57 show(p) # show the plot

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in show(obj, browser, new)
    299
    300
     '''

--> 301 return _show_with_state(obj, _state, browser, new)
    302
    303 def _show_with_state(obj, state, browser, new):

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in _show_with_state(obj, state, browser, new)
    307
    308 if state.notebook:
--> 309 comms_handle = _show_notebook_with_state(obj, state)
    310
    311 elif state.server_enabled:

/usr/local/lib/python3.4/dist-packages/bokeh/io.py in _show_notebook_with_state(obj, state)
    328 else:
    329 comms_target = make_id()
--> 330 publish_display_data({'text/html': notebook_div(obj, comms_target)})
    331 handle = _CommsHandle(get_comms(comms_target), state.document, state.document.to_json())
    332 state.last_comms_handle = handle

/usr/local/lib/python3.4/dist-packages/bokeh/embed.py in notebook_div(model, notebook_comms_target)
    247
    248 with _ModelInDocument(model):
--> 249 (docs_json, render_items) = _standalone_docs_json_and_render_items([model])
    250
    251 item = render_items[0]

/usr/local/lib/python3.4/dist-packages/bokeh/embed.py in _standalone_docs_json_and_render_items(models)
    564 docs_json = {}
    565 for k, v in docs_by_id.items():
--> 566 docs_json[k] = v.to_json()
    567
    568 return (docs_json, render_items)

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in to_json(self)
    730 # this is a total hack to go via a string, needed because
    731 # our BokehJSONEncoder goes straight to a string.
--> 732 doc_json = self.to_json_string()
    733 return loads(doc_json)
    734

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in to_json_string(self, indent)
    718
             'roots' : {

    719 'root_ids' : root_ids,
--> 720 'references' : self._references_json(root_references)
    721
             },

    722 'version' : __version__

/usr/local/lib/python3.4/dist-packages/bokeh/document.py in _references_json(cls, references)
    529 for r in references:
    530 ref = r.ref
--> 531 ref['attributes'] = r._to_json_like(include_defaults=False)
    532 references_json.append(ref)
    533

/usr/local/lib/python3.4/dist-packages/bokeh/models/sources.py in _to_json_like(self, include_defaults)
    173 attrs = super(ColumnDataSource, self)._to_json_like(include_defaults=include_defaults)
    174 if 'data' in attrs:
--> 175 attrs['data'] = transform_column_source_data(attrs['data'])
    176 return attrs
    177

/usr/local/lib/python3.4/dist-packages/bokeh/util/serialization.py in transform_column_source_data(data)
    127 data_copy[key] = transform_array(data[key])
    128 else:
--> 129 data_copy[key] = traverse_data(data[key])
    130 return data_copy

/usr/local/lib/python3.4/dist-packages/bokeh/util/serialization.py in traverse_data(datum, is_numpy, use_numpy)
     98
     """

     99 is_numpy = is_numpy and use_numpy
--> 100 if is_numpy and not any(isinstance(el, (list, tuple)) for el in datum):
    101 return transform_array(np.asarray(datum))
    102 datum_copy =

TypeError
: 'numpy.int64' object is not iterable

from math import pi, floor
from bokeh.models import HoverTool
from bokeh.plotting import ColumnDataSource, figure, show
from bokeh.palettes import Reds9
from
bokeh.io
import output_notebook

groups = data.groupby(['DayOfWeek', 'hour']).size()
max_crimes = max(groups)
min_crimes = min(groups)
factor = (max_crimes - min_crimes) / 8.9999999

days = ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday']
days_abbr = [day[:4] for day in days]
hours = list(range(24))

# Set up the data for plotting. We will need to have values for every
# pair of day/hour names. Map the rate to a color.
day=
hour =
color =
counts =
for d in days:
    for h in hours:
        day.append(d)
        hour.append(str(h))
        count = groups[d][h:h+1].values[0]
        counts.append(count)
        color_index = floor((count - min_crimes) / factor)
        color.append(Reds9[color_
index])

source = ColumnDataSource(
    data=dict(day=day, hour=hour, color=color, count=count)
)

TOOLS = "resize,hover,save,pan,box_
zoom,wheel_zoom"

p = figure(title="Frequency of Crimes Throughout the Week", x_range=[str(h) for h in hours], y_range=days,
           x_axis_location="above", plot_width=900, plot_height=400,
           toolbar_location="left", tools=TOOLS)

p.grid.grid_line_color = None
p.axis.axis_line_color = None
p.axis.major_tick_line_color = None
p.axis.major_label_text_font_
size = "5pt"
p.axis.major_label_standoff = 0
p.xaxis.major_label_
orientation = pi/3

p.rect("day", "hour", 1, 1, source=source,
       color="color", line_color=None)

p.select_one(HoverTool).
tooltips = [
    ('Time of Week', '@day @hour'),
    ('Crime Count', '@count'),]

output_notebook()

show(p) # show the plot

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