We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
[BUG] cElementTree has been deprecated and will be removed in favor of ElementTree
Reference : https://bugs.python.org/issue36543

```
bokeh/sampledata/us_states.py
33:import xml.etree.cElementTree as et

bokeh/sampledata/us_counties.py
40:import xml.etree.cElementTree as et
```


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `bokeh/sampledata/us_counties.py`
Content:
```
1 #-----------------------------------------------------------------------------
2 # Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors.
3 # All rights reserved.
4 #
5 # The full license is in the file LICENSE.txt, distributed with this software.
6 #-----------------------------------------------------------------------------
7 ''' This modules exposes geometry data for Unites States. It exposes a
8 dictionary ``data``, which is indexed by the two-tuples:
9 
10 .. code-block:: python
11 
12     (state_id, county_id)
13 
14 that have the following dictionaries as the associated value:
15 
16 .. code-block:: python
17 
18     data[(1,1)]['name']
19     data[(1,1)]['state']
20     data[(1,1)]['detailed name']
21     data[(1,1)]['lats']
22     data[(1,1)]['lons']
23 
24 Entries for ``'name'`` can have duplicates for certain states (e.g. Virginia).
25 The combination of ``'detailed name'`` and ``'state'`` will always be unique.
26 
27 '''
28 #-----------------------------------------------------------------------------
29 # Boilerplate
30 #-----------------------------------------------------------------------------
31 import logging # isort:skip
32 log = logging.getLogger(__name__)
33 
34 #-----------------------------------------------------------------------------
35 # Imports
36 #-----------------------------------------------------------------------------
37 
38 # Standard library imports
39 import csv
40 import xml.etree.cElementTree as et
41 
42 # Bokeh imports
43 from ..util.sampledata import external_path, open_csv
44 
45 #-----------------------------------------------------------------------------
46 # Globals and constants
47 #-----------------------------------------------------------------------------
48 
49 __all__ = (
50     'data',
51 )
52 
53 #-----------------------------------------------------------------------------
54 # General API
55 #-----------------------------------------------------------------------------
56 
57 #-----------------------------------------------------------------------------
58 # Dev API
59 #-----------------------------------------------------------------------------
60 
61 #-----------------------------------------------------------------------------
62 # Private API
63 #-----------------------------------------------------------------------------
64 
65 def _read_data():
66     '''
67 
68     '''
69     nan = float('NaN')
70 
71     data = {}
72 
73     with open_csv(external_path('US_Counties.csv')) as f:
74         next(f)
75         reader = csv.reader(f, delimiter=str(','), quotechar=str('"'))
76         for row in reader:
77             name, dummy, state, dummy, geometry, dummy, dummy, dummy, det_name, state_id, county_id, dummy, dummy = row
78             xml = et.fromstring(geometry)
79             lats = []
80             lons = []
81             for i, poly in enumerate(xml.findall('.//outerBoundaryIs/LinearRing/coordinates')):
82                 if i > 0:
83                     lats.append(nan)
84                     lons.append(nan)
85                 coords = (c.split(',')[:2] for c in poly.text.split())
86                 lat, lon = list(zip(*[(float(lat), float(lon)) for lon, lat in
87                     coords]))
88                 lats.extend(lat)
89                 lons.extend(lon)
90             data[(int(state_id), int(county_id))] = {
91                 'name' : name,
92                 'detailed name' : det_name,
93                 'state' : state,
94                 'lats' : lats,
95                 'lons' : lons,
96             }
97 
98     return data
99 
100 #-----------------------------------------------------------------------------
101 # Code
102 #-----------------------------------------------------------------------------
103 
104 data = _read_data()
105
```

Path: `bokeh/sampledata/us_states.py`
Content:
```
1 #-----------------------------------------------------------------------------
2 # Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors.
3 # All rights reserved.
4 #
5 # The full license is in the file LICENSE.txt, distributed with this software.
6 #-----------------------------------------------------------------------------
7 '''
8 This modules exposes geometry data for Unites States. It exposes a dictionary 'data' which is
9 indexed by the two letter state code (e.g., 'CA', 'TX') and has the following dictionary as the
10 associated value:
11 
12     data['CA']['name']
13     data['CA']['region']
14     data['CA']['lats']
15     data['CA']['lons']
16 
17 '''
18 
19 #-----------------------------------------------------------------------------
20 # Boilerplate
21 #-----------------------------------------------------------------------------
22 import logging # isort:skip
23 log = logging.getLogger(__name__)
24 
25 #-----------------------------------------------------------------------------
26 # Imports
27 #-----------------------------------------------------------------------------
28 
29 # Standard library imports
30 import codecs
31 import csv
32 import gzip
33 import xml.etree.cElementTree as et
34 
35 # Bokeh imports
36 from ..util.sampledata import package_path
37 
38 #-----------------------------------------------------------------------------
39 # Globals and constants
40 #-----------------------------------------------------------------------------
41 
42 __all__ = (
43     'data',
44 )
45 
46 #-----------------------------------------------------------------------------
47 # General API
48 #-----------------------------------------------------------------------------
49 
50 #-----------------------------------------------------------------------------
51 # Dev API
52 #-----------------------------------------------------------------------------
53 
54 #-----------------------------------------------------------------------------
55 # Private API
56 #-----------------------------------------------------------------------------
57 
58 def _read_data():
59     '''
60 
61     '''
62     nan = float('NaN')
63 
64     data = {}
65 
66     with gzip.open(package_path('US_Regions_State_Boundaries.csv.gz')) as f:
67         decoded = codecs.iterdecode(f, "utf-8")
68         next(decoded)
69         reader = csv.reader(decoded, delimiter=str(','), quotechar=str('"'))
70         for row in reader:
71             region, name, code, geometry, dummy = row
72             xml = et.fromstring(geometry)
73             lats = []
74             lons = []
75             for i, poly in enumerate(xml.findall('.//outerBoundaryIs/LinearRing/coordinates')):
76                 if i > 0:
77                     lats.append(nan)
78                     lons.append(nan)
79                 coords = (c.split(',')[:2] for c in poly.text.split())
80                 lat, lon = list(zip(*[(float(lat), float(lon)) for lon, lat in
81                     coords]))
82                 lats.extend(lat)
83                 lons.extend(lon)
84             data[code] = {
85                 'name'   : name,
86                 'region' : region,
87                 'lats'   : lats,
88                 'lons'   : lons,
89             }
90 
91     return data
92 
93 #-----------------------------------------------------------------------------
94 # Code
95 #-----------------------------------------------------------------------------
96 
97 data = _read_data()
98
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/bokeh/sampledata/us_counties.py b/bokeh/sampledata/us_counties.py
--- a/bokeh/sampledata/us_counties.py
+++ b/bokeh/sampledata/us_counties.py
@@ -37,7 +37,7 @@
 
 # Standard library imports
 import csv
-import xml.etree.cElementTree as et
+import xml.etree.ElementTree as et
 
 # Bokeh imports
 from ..util.sampledata import external_path, open_csv
diff --git a/bokeh/sampledata/us_states.py b/bokeh/sampledata/us_states.py
--- a/bokeh/sampledata/us_states.py
+++ b/bokeh/sampledata/us_states.py
@@ -30,7 +30,7 @@
 import codecs
 import csv
 import gzip
-import xml.etree.cElementTree as et
+import xml.etree.ElementTree as et
 
 # Bokeh imports
 from ..util.sampledata import package_path

{"golden_diff": "diff --git a/bokeh/sampledata/us_counties.py b/bokeh/sampledata/us_counties.py\n--- a/bokeh/sampledata/us_counties.py\n+++ b/bokeh/sampledata/us_counties.py\n@@ -37,7 +37,7 @@\n \n # Standard library imports\n import csv\n-import xml.etree.cElementTree as et\n+import xml.etree.ElementTree as et\n \n # Bokeh imports\n from ..util.sampledata import external_path, open_csv\ndiff --git a/bokeh/sampledata/us_states.py b/bokeh/sampledata/us_states.py\n--- a/bokeh/sampledata/us_states.py\n+++ b/bokeh/sampledata/us_states.py\n@@ -30,7 +30,7 @@\n import codecs\n import csv\n import gzip\n-import xml.etree.cElementTree as et\n+import xml.etree.ElementTree as et\n \n # Bokeh imports\n from ..util.sampledata import package_path\n", "issue": "[BUG] cElementTree has been deprecated and will be removed in favor of ElementTree\nReference : https://bugs.python.org/issue36543\r\n\r\n```\r\nbokeh/sampledata/us_states.py\r\n33:import xml.etree.cElementTree as et\r\n\r\nbokeh/sampledata/us_counties.py\r\n40:import xml.etree.cElementTree as et\r\n```\r\n\n", "before_files": [{"content": "#-----------------------------------------------------------------------------\n# Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors.\n# All rights reserved.\n#\n# The full license is in the file LICENSE.txt, distributed with this software.\n#-----------------------------------------------------------------------------\n''' This modules exposes geometry data for Unites States. It exposes a\ndictionary ``data``, which is indexed by the two-tuples:\n\n.. code-block:: python\n\n    (state_id, county_id)\n\nthat have the following dictionaries as the associated value:\n\n.. code-block:: python\n\n    data[(1,1)]['name']\n    data[(1,1)]['state']\n    data[(1,1)]['detailed name']\n    data[(1,1)]['lats']\n    data[(1,1)]['lons']\n\nEntries for ``'name'`` can have duplicates for certain states (e.g. Virginia).\nThe combination of ``'detailed name'`` and ``'state'`` will always be unique.\n\n'''\n#-----------------------------------------------------------------------------\n# Boilerplate\n#-----------------------------------------------------------------------------\nimport logging # isort:skip\nlog = logging.getLogger(__name__)\n\n#-----------------------------------------------------------------------------\n# Imports\n#-----------------------------------------------------------------------------\n\n# Standard library imports\nimport csv\nimport xml.etree.cElementTree as et\n\n# Bokeh imports\nfrom ..util.sampledata import external_path, open_csv\n\n#-----------------------------------------------------------------------------\n# Globals and constants\n#-----------------------------------------------------------------------------\n\n__all__ = (\n    'data',\n)\n\n#-----------------------------------------------------------------------------\n# General API\n#-----------------------------------------------------------------------------\n\n#-----------------------------------------------------------------------------\n# Dev API\n#-----------------------------------------------------------------------------\n\n#-----------------------------------------------------------------------------\n# Private API\n#-----------------------------------------------------------------------------\n\ndef _read_data():\n    '''\n\n    '''\n    nan = float('NaN')\n\n    data = {}\n\n    with open_csv(external_path('US_Counties.csv')) as f:\n        next(f)\n        reader = csv.reader(f, delimiter=str(','), quotechar=str('\"'))\n        for row in reader:\n            name, dummy, state, dummy, geometry, dummy, dummy, dummy, det_name, state_id, county_id, dummy, dummy = row\n            xml = et.fromstring(geometry)\n            lats = []\n            lons = []\n            for i, poly in enumerate(xml.findall('.//outerBoundaryIs/LinearRing/coordinates')):\n                if i > 0:\n                    lats.append(nan)\n                    lons.append(nan)\n                coords = (c.split(',')[:2] for c in poly.text.split())\n                lat, lon = list(zip(*[(float(lat), float(lon)) for lon, lat in\n                    coords]))\n                lats.extend(lat)\n                lons.extend(lon)\n            data[(int(state_id), int(county_id))] = {\n                'name' : name,\n                'detailed name' : det_name,\n                'state' : state,\n                'lats' : lats,\n                'lons' : lons,\n            }\n\n    return data\n\n#-----------------------------------------------------------------------------\n# Code\n#-----------------------------------------------------------------------------\n\ndata = _read_data()\n", "path": "bokeh/sampledata/us_counties.py"}, {"content": "#-----------------------------------------------------------------------------\n# Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors.\n# All rights reserved.\n#\n# The full license is in the file LICENSE.txt, distributed with this software.\n#-----------------------------------------------------------------------------\n'''\nThis modules exposes geometry data for Unites States. It exposes a dictionary 'data' which is\nindexed by the two letter state code (e.g., 'CA', 'TX') and has the following dictionary as the\nassociated value:\n\n    data['CA']['name']\n    data['CA']['region']\n    data['CA']['lats']\n    data['CA']['lons']\n\n'''\n\n#-----------------------------------------------------------------------------\n# Boilerplate\n#-----------------------------------------------------------------------------\nimport logging # isort:skip\nlog = logging.getLogger(__name__)\n\n#-----------------------------------------------------------------------------\n# Imports\n#-----------------------------------------------------------------------------\n\n# Standard library imports\nimport codecs\nimport csv\nimport gzip\nimport xml.etree.cElementTree as et\n\n# Bokeh imports\nfrom ..util.sampledata import package_path\n\n#-----------------------------------------------------------------------------\n# Globals and constants\n#-----------------------------------------------------------------------------\n\n__all__ = (\n    'data',\n)\n\n#-----------------------------------------------------------------------------\n# General API\n#-----------------------------------------------------------------------------\n\n#-----------------------------------------------------------------------------\n# Dev API\n#-----------------------------------------------------------------------------\n\n#-----------------------------------------------------------------------------\n# Private API\n#-----------------------------------------------------------------------------\n\ndef _read_data():\n    '''\n\n    '''\n    nan = float('NaN')\n\n    data = {}\n\n    with gzip.open(package_path('US_Regions_State_Boundaries.csv.gz')) as f:\n        decoded = codecs.iterdecode(f, \"utf-8\")\n        next(decoded)\n        reader = csv.reader(decoded, delimiter=str(','), quotechar=str('\"'))\n        for row in reader:\n            region, name, code, geometry, dummy = row\n            xml = et.fromstring(geometry)\n            lats = []\n            lons = []\n            for i, poly in enumerate(xml.findall('.//outerBoundaryIs/LinearRing/coordinates')):\n                if i > 0:\n                    lats.append(nan)\n                    lons.append(nan)\n                coords = (c.split(',')[:2] for c in poly.text.split())\n                lat, lon = list(zip(*[(float(lat), float(lon)) for lon, lat in\n                    coords]))\n                lats.extend(lat)\n                lons.extend(lon)\n            data[code] = {\n                'name'   : name,\n                'region' : region,\n                'lats'   : lats,\n                'lons'   : lons,\n            }\n\n    return data\n\n#-----------------------------------------------------------------------------\n# Code\n#-----------------------------------------------------------------------------\n\ndata = _read_data()\n", "path": "bokeh/sampledata/us_states.py"}], "after_files": [{"content": "#-----------------------------------------------------------------------------\n# Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors.\n# All rights reserved.\n#\n# The full license is in the file LICENSE.txt, distributed with this software.\n#-----------------------------------------------------------------------------\n''' This modules exposes geometry data for Unites States. It exposes a\ndictionary ``data``, which is indexed by the two-tuples:\n\n.. code-block:: python\n\n    (state_id, county_id)\n\nthat have the following dictionaries as the associated value:\n\n.. code-block:: python\n\n    data[(1,1)]['name']\n    data[(1,1)]['state']\n    data[(1,1)]['detailed name']\n    data[(1,1)]['lats']\n    data[(1,1)]['lons']\n\nEntries for ``'name'`` can have duplicates for certain states (e.g. Virginia).\nThe combination of ``'detailed name'`` and ``'state'`` will always be unique.\n\n'''\n#-----------------------------------------------------------------------------\n# Boilerplate\n#-----------------------------------------------------------------------------\nimport logging # isort:skip\nlog = logging.getLogger(__name__)\n\n#-----------------------------------------------------------------------------\n# Imports\n#-----------------------------------------------------------------------------\n\n# Standard library imports\nimport csv\nimport xml.etree.ElementTree as et\n\n# Bokeh imports\nfrom ..util.sampledata import external_path, open_csv\n\n#-----------------------------------------------------------------------------\n# Globals and constants\n#-----------------------------------------------------------------------------\n\n__all__ = (\n    'data',\n)\n\n#-----------------------------------------------------------------------------\n# General API\n#-----------------------------------------------------------------------------\n\n#-----------------------------------------------------------------------------\n# Dev API\n#-----------------------------------------------------------------------------\n\n#-----------------------------------------------------------------------------\n# Private API\n#-----------------------------------------------------------------------------\n\ndef _read_data():\n    '''\n\n    '''\n    nan = float('NaN')\n\n    data = {}\n\n    with open_csv(external_path('US_Counties.csv')) as f:\n        next(f)\n        reader = csv.reader(f, delimiter=str(','), quotechar=str('\"'))\n        for row in reader:\n            name, dummy, state, dummy, geometry, dummy, dummy, dummy, det_name, state_id, county_id, dummy, dummy = row\n            xml = et.fromstring(geometry)\n            lats = []\n            lons = []\n            for i, poly in enumerate(xml.findall('.//outerBoundaryIs/LinearRing/coordinates')):\n                if i > 0:\n                    lats.append(nan)\n                    lons.append(nan)\n                coords = (c.split(',')[:2] for c in poly.text.split())\n                lat, lon = list(zip(*[(float(lat), float(lon)) for lon, lat in\n                    coords]))\n                lats.extend(lat)\n                lons.extend(lon)\n            data[(int(state_id), int(county_id))] = {\n                'name' : name,\n                'detailed name' : det_name,\n                'state' : state,\n                'lats' : lats,\n                'lons' : lons,\n            }\n\n    return data\n\n#-----------------------------------------------------------------------------\n# Code\n#-----------------------------------------------------------------------------\n\ndata = _read_data()\n", "path": "bokeh/sampledata/us_counties.py"}, {"content": "#-----------------------------------------------------------------------------\n# Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors.\n# All rights reserved.\n#\n# The full license is in the file LICENSE.txt, distributed with this software.\n#-----------------------------------------------------------------------------\n'''\nThis modules exposes geometry data for Unites States. It exposes a dictionary 'data' which is\nindexed by the two letter state code (e.g., 'CA', 'TX') and has the following dictionary as the\nassociated value:\n\n    data['CA']['name']\n    data['CA']['region']\n    data['CA']['lats']\n    data['CA']['lons']\n\n'''\n\n#-----------------------------------------------------------------------------\n# Boilerplate\n#-----------------------------------------------------------------------------\nimport logging # isort:skip\nlog = logging.getLogger(__name__)\n\n#-----------------------------------------------------------------------------\n# Imports\n#-----------------------------------------------------------------------------\n\n# Standard library imports\nimport codecs\nimport csv\nimport gzip\nimport xml.etree.ElementTree as et\n\n# Bokeh imports\nfrom ..util.sampledata import package_path\n\n#-----------------------------------------------------------------------------\n# Globals and constants\n#-----------------------------------------------------------------------------\n\n__all__ = (\n    'data',\n)\n\n#-----------------------------------------------------------------------------\n# General API\n#-----------------------------------------------------------------------------\n\n#-----------------------------------------------------------------------------\n# Dev API\n#-----------------------------------------------------------------------------\n\n#-----------------------------------------------------------------------------\n# Private API\n#-----------------------------------------------------------------------------\n\ndef _read_data():\n    '''\n\n    '''\n    nan = float('NaN')\n\n    data = {}\n\n    with gzip.open(package_path('US_Regions_State_Boundaries.csv.gz')) as f:\n        decoded = codecs.iterdecode(f, \"utf-8\")\n        next(decoded)\n        reader = csv.reader(decoded, delimiter=str(','), quotechar=str('\"'))\n        for row in reader:\n            region, name, code, geometry, dummy = row\n            xml = et.fromstring(geometry)\n            lats = []\n            lons = []\n            for i, poly in enumerate(xml.findall('.//outerBoundaryIs/LinearRing/coordinates')):\n                if i > 0:\n                    lats.append(nan)\n                    lons.append(nan)\n                coords = (c.split(',')[:2] for c in poly.text.split())\n                lat, lon = list(zip(*[(float(lat), float(lon)) for lon, lat in\n                    coords]))\n                lats.extend(lat)\n                lons.extend(lon)\n            data[code] = {\n                'name'   : name,\n                'region' : region,\n                'lats'   : lats,\n                'lons'   : lons,\n            }\n\n    return data\n\n#-----------------------------------------------------------------------------\n# Code\n#-----------------------------------------------------------------------------\n\ndata = _read_data()\n", "path": "bokeh/sampledata/us_states.py"}]}