I have nav drawer with "Settings" as TextView without an ID.
I can get the home_nav_view but when trying to iterate over the children I get the exception "com.android.chimpchat.core.ChimpException: Node with given ID does not exist"
Am I doing something wrong?
>>> c = easy_device.getViewById("com.catonetworks.vpnclient:id/home_nav_view")
>>> print c.getLocation().right
840
>>> print c.getLocation().bottom
1794
>>> print dir(c)
['__class__', '__delattr__', '__doc__', '__getattribute__', '__hash__', '__init__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__str__', 'getAccessibilityIds', 'getChecked', 'getChildren', 'getEnabled', 'getFocused', 'getLocation', 'getParent', 'getSelected', 'getText', 'getViewClass', 'setFocused', 'setSelected']
>>> print c.getChildren()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
at com.android.chimpchat.ChimpManager.queryView(ChimpManager.java:415)
at com.android.chimpchat.core.ChimpView.queryView(ChimpView.java:54)
at com.android.chimpchat.core.ChimpView.getChildren(ChimpView.java:175)
at com.android.monkeyrunner.MonkeyView.getChildren(MonkeyView.java:148)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
com.android.chimpchat.core.ChimpException: com.android.chimpchat.core.ChimpException: Node with given ID does not exist
The problem is that under the view there are Preferences and Android converts them to TextView that is why they don't have ID
Related
I have a stateful DoFn that basically batches the elements that are coming and when the buffer reaches a certain size, the buffer is cleared and the elements are inserted into BigQuery. What I've noticed is that from time to time, the pipeline is raising an exception, the exception is not stopping the job to run. Below is the stacktrace:
Error message from worker: generic::unknown: Traceback (most recent call last):
File "apache_beam/runners/common.py", line 1213, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam/runners/common.py", line 742, in apache_beam.runners.common.PerWindowInvoker.invoke_process
File "apache_beam/runners/common.py", line 867, in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
File "/usr/local/lib/python3.7/site-packages/gp/pipelines/common/writer_transforms.py", line 140, in process
self._flush_buffer(buffer_state, count_state, buffer_size_state)
File "/usr/local/lib/python3.7/site-packages/gp/pipelines/common/writer_transforms.py", line 162, in _flush_buffer
rows = self._extract_rows(buffer_state)
File "/usr/local/lib/python3.7/site-packages/gp/pipelines/common/writer_transforms.py", line 197, in _extract_rows
for row in buffer.read():
File "/usr/local/lib/python3.7/site-packages/apache_beam/runners/worker/bundle_processor.py", line 510, in __iter__
for elem in self.first:
File "/usr/local/lib/python3.7/site-packages/apache_beam/runners/worker/sdk_worker.py", line 1039, in _lazy_iterator
self._underlying.get_raw(state_key, continuation_token))
File "/usr/local/lib/python3.7/site-packages/apache_beam/runners/worker/sdk_worker.py", line 846, in get_raw
continuation_token=continuation_token)))
File "/usr/local/lib/python3.7/site-packages/apache_beam/runners/worker/sdk_worker.py", line 886, in _blocking_request
raise RuntimeError(response.error)
RuntimeError: INTERNAL: Work token invalid
This is raised when the process method is called and it tries to extract the elements from the buffer, see rows = self._extract_rows(buffer_state)
The DoFn is implemented exactly like in the example https://beam.apache.org/blog/timely-processing/#example-batched-rpc
I've confirmed this error is expected during work reassignments, e.g. when autoscaling. The work item will be retried on the new machine and the pipeline will continue processing correctly. (I agree the error message could be improved.)
I used this code:
from statsmodels.tsa.arima_model import ARIMA
model = ARIMA(ts_log, order=(2, 1, 0))
This error came out:
Traceback (most recent call last):
File "", line 1, in
model = ARIMA(ts_log, order=(2, 1, 0))
File "C:\Users\April\Anaconda3\lib\site-packages\statsmodels\tsa\arima_model.py", line 996, in new
mod.init(endog, order, exog, dates, freq, missing)
File "C:\Users\April\Anaconda3\lib\site-packages\statsmodels\tsa\arima_model.py", line 1015, in init
super(ARIMA, self).init(endog, (p, q), exog, dates, freq, missing)
File "C:\Users\April\Anaconda3\lib\site-packages\statsmodels\tsa\arima_model.py", line 435, in init
super(ARMA, self).init(endog, exog, dates, freq, missing=missing)
File "C:\Users\April\Anaconda3\lib\site-packages\statsmodels\tsa\base\tsa_model.py", line 58, in init
self._init_dates(dates, freq)
File "C:\Users\April\Anaconda3\lib\site-packages\statsmodels\tsa\base\tsa_model.py", line 191, in _init_dates
start=index[0], end=index[-1], freq=freq)
TypeError: new() got an unexpected keyword argument 'start'
I really appreciate your help! :)
It worked when upgraded to new version statsmodels (1.12.0). Initial version is (0.9.0)
pip install --user statsmodels -U
I am trying to use Dask to perform a groupby operation on a Dataframe.
The code below does not work but it seems that if I initialize the Client from another console the code works, even though I can't see anything on the dashboard ( http://localhost:8787/status ): I mean, there is a dashboard, but all the figures look empty. I am on macOS.
Code:
from datetime import datetime
import numpy as np
import os
from dask import dataframe as dd
from dask.distributed import Client
import pandas as pd
client = Client()
# open http://localhost:8787/status
csv_path = 'chicago-complete.monthly.2018-07-01-to-2018-07-31/data.csv'
dir_destination = 'data'
df = dd.read_csv(csv_path,
dtype = {
'timestamp': str,
'node_id': str,
'subsystem': str,
'sensor': str,
'parameter': str,
'value_raw': str,
'value_hrf': str,
},
parse_dates=['timestamp'],
date_parser=lambda x: pd.datetime.strptime(x, '%Y/%m/%d %H:%M:%S')
)
#%%
if not os.path.exists(dir_destination):
os.makedirs(dir_destination)
def create_node_csv(df_node):
# test function
return len(df_node)
res = df.groupby('node_id').apply(create_node_csv, meta=int)
The csv file is simply composed by columns of string. My goal is to group of all the rows that contains a certain value in a column and than save them as separates file using create_node_csv(df_node) (even though right now is a dummy function). Any other way to do it is appreciated, but I would like to understand what's going on here.
When I run it, the console prints multiple times the following errors:
tornado.application - ERROR - Multiple exceptions in yield list
Traceback (most recent call last):
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 883, in callback
result_list.append(f.result())
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 1141, in run
yielded = self.gen.throw(*exc_info)
File "/anaconda3/lib/python3.7/site-packages/distributed/deploy/local.py", line 208, in _start_worker
yield w._start()
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 1133, in run
value = future.result()
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 1141, in run
yielded = self.gen.throw(*exc_info)
File "/anaconda3/lib/python3.7/site-packages/distributed/nanny.py", line 157, in _start
response = yield self.instantiate()
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 1133, in run
value = future.result()
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 1141, in run
yielded = self.gen.throw(*exc_info)
File "/anaconda3/lib/python3.7/site-packages/distributed/nanny.py", line 226, in instantiate
self.process.start()
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 1133, in run
value = future.result()
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 1141, in run
yielded = self.gen.throw(*exc_info)
File "/anaconda3/lib/python3.7/site-packages/distributed/nanny.py", line 370, in start
yield self.process.start()
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 1133, in run
value = future.result()
File "/anaconda3/lib/python3.7/site-packages/distributed/process.py", line 35, in _call_and_set_future
res = func(*args, **kwargs)
File "/anaconda3/lib/python3.7/site-packages/distributed/process.py", line 184, in _start
process.start()
File "/anaconda3/lib/python3.7/multiprocessing/process.py", line 112, in start
self._popen = self._Popen(self)
File "/anaconda3/lib/python3.7/multiprocessing/context.py", line 291, in _Popen
return Popen(process_obj)
File "/anaconda3/lib/python3.7/multiprocessing/popen_forkserver.py", line 35, in __init__
super().__init__(process_obj)
File "/anaconda3/lib/python3.7/multiprocessing/popen_fork.py", line 20, in __init__
self._launch(process_obj)
File "/anaconda3/lib/python3.7/multiprocessing/popen_forkserver.py", line 42, in _launch
prep_data = spawn.get_preparation_data(process_obj._name)
File "/anaconda3/lib/python3.7/multiprocessing/spawn.py", line 143, in get_preparation_data
_check_not_importing_main()
File "/anaconda3/lib/python3.7/multiprocessing/spawn.py", line 136, in _check_not_importing_main
is not going to be frozen to produce an executable.''')
RuntimeError:
An attempt has been made to start a new process before the
current process has finished its bootstrapping phase.
This probably means that you are not using fork to start your
child processes and you have forgotten to use the proper idiom
in the main module:
if __name__ == '__main__':
freeze_support()
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce an executable.
And:
distributed.nanny - WARNING - Worker process 1844 exited with status 1
distributed.nanny - WARNING - Restarting worker
And:
Traceback (most recent call last):
File "/anaconda3/lib/python3.7/multiprocessing/queues.py", line 242, in _feed
send_bytes(obj)
File "/anaconda3/lib/python3.7/multiprocessing/connection.py", line 200, in send_bytes
self._send_bytes(m[offset:offset + size])
File "/anaconda3/lib/python3.7/multiprocessing/connection.py", line 404, in _send_bytes
self._send(header + buf)
File "/anaconda3/lib/python3.7/multiprocessing/connection.py", line 368, in _send
n = write(self._handle, buf)
BrokenPipeError: [Errno 32] Broken pipe
tornado.application - ERROR - Multiple exceptions in yield list
Traceback (most recent call last):
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 883, in callback
result_list.append(f.result())
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 1147, in run
yielded = self.gen.send(value)
File "/anaconda3/lib/python3.7/site-packages/distributed/deploy/local.py", line 217, in _start_worker
raise gen.TimeoutError("Worker failed to start")
tornado.util.TimeoutError: Worker failed to start
tornado.application - ERROR - Multiple exceptions in yield list
Traceback (most recent call last):
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 883, in callback
result_list.append(f.result())
File "/anaconda3/lib/python3.7/site-packages/tornado/gen.py", line 1147, in run
yielded = self.gen.send(value)
File "/anaconda3/lib/python3.7/site-packages/distributed/deploy/local.py", line 217, in _start_worker
EDIT:
Based on the answer:
- How do I prevent the creation of a new Client if I run the program again?
- How can I do the following?
def create_node_csv(df_node):
return len(df_node)
It returns me the following error, is it related to the meta parameter?
ValueError: cannot reindex from a duplicate axis
When you run the script, Client() is causing new Dask workers to be spawned, which also get copies of variables from the original main process. In some some cases, this involves re-importing the script in each worker, each of which, of course, then tries to create a Client and new set of processes.
The best answer, as in general with anything running in processes, is to use functions, and protect the main execution. The following would be a way to do this, without changing your one-script structure:
from datetime import datetime
import numpy as np
import os
from dask import dataframe as dd
from dask.distributed import Client
import pandas as pd
csv_path = 'chicago-complete.monthly.2018-07-01-to-2018-07-31/data.csv'
dir_destination = 'data'
def run():
client = Client()
df = dd.read_csv(csv_path, ...)
if not os.path.exists(dir_destination):
os.makedirs(dir_destination)
def create_node_csv(df_node):
# test function
return len(df_node)
res = df.groupby('node_id').apply(create_node_csv, meta=int)
print(res.compute())
if __name__ == "__main__":
run()
How do I prevent the creation of a new Client if I run the program again?
In the call to Client() you can include the address of an existing cluster, if you know what that would be. Also, some specific types of deployments (are there are a few) may have a concept of the "current cluster".
I'm trying to replace a Series dask partition with my own partition.
I've used the code snippet given by #MRocklin in this post.
list_of_delayed = dask_df.to_delayed()
new_partition = dask.delayed(pd.read_csv)(filename)
list_of_delayed[i] = new_partition
new_dask_df = dd.from_delayed(list_of_delayed, meta=dask_df._meta)
I've done exactly the same except dask_df is a series in my case. I'm getting the following error:
Traceback (most recent call last):
File "sdfr_dhruvkmr.py", line 465, in <module>
pts = task[(task.task_date <= dtm.Time.iloc[i]) & (task.T_Date == dtm.Date.iloc[i])]
File "/usr/lib/python2.7/site-packages/edask/dataframe.py", line 130, in __getitem__
new_dask_df = dd.from_delayed(list_of_delayed)
File "/usr/lib/python2.7/site-packages/edask/edask/dask/dataframe/io/io.py", line 493, in from_delayed
type(df).__name__)
TypeError: Expected Delayed object, got Delayed
I think this might be an obvious to the seasoned py2neo users, but I could not get over it since I'm new. I'm trying to follow py2neo online doc: http://book.py2neo.org/en/latest/graphs_nodes_relationships/, but I was able to use the 'Node' methods for the instance returned from
GraphDatabaseService.create, but when I use GraphDatabaseService.node to retrieve the node, all the expected Node methods stop working, I've narrowed it down to an example below using the Node.len method.
Thanks in advance for any helpful insights.
Bruce
My env:
windows 7 professional
pycharm 3.4
py2neo 1.6.4
python2.7.5
Here are the codes:
from py2neo import node, neo4j
db = neo4j.GraphDatabaseService()
db.clear()
a, = db.create(node({'name': ['a']}))
a.add_labels('Label')
b = db.node(a._id)
print db.neo4j_version
print b, type(b)
print "There is %s node in db" % db.order
print len(b)
Here are the outputs:
C:\Python27\python.exe C:/Users/you_zhang/PycharmProjects/py2neo/ex11.py
(2, 0, 3, u'')
(10) <class 'py2neo.neo4j.Node'>
There is 1 node in db
Traceback (most recent call last):
File "C:/Users/you_zhang/PycharmProjects/py2neo/ex11.py", line 11, in <module>
print len(b)
File "C:\Users\you_zhang\AppData\Roaming\Python\Python27\site-packages\py2neo\neo4j.py", line 1339, in __len__
return len(self.get_properties())
File "C:\Users\you_zhang\AppData\Roaming\Python\Python27\site-packages\py2neo\neo4j.py", line 1398, in get_properties
self._properties = assembled(self._properties_resource._get()) or {}
File "C:\Users\you_zhang\AppData\Roaming\Python\Python27\site-packages\py2neo\neo4j.py", line 1349, in _properties_resource
return self._subresource("properties")
File "C:\Users\you_zhang\AppData\Roaming\Python\Python27\site-packages\py2neo\neo4j.py", line 403, in _subresource
uri = URI(self.__metadata__[key])
File "C:\Users\you_zhang\AppData\Roaming\Python\Python27\site-packages\py2neo\neo4j.py", line 338, in __metadata__
self.refresh()
File "C:\Users\you_zhang\AppData\Roaming\Python\Python27\site-packages\py2neo\neo4j.py", line 360, in refresh
self._metadata = ResourceMetadata(self._get().content)
File "C:\Users\you_zhang\AppData\Roaming\Python\Python27\site-packages\py2neo\neo4j.py", line 367, in _get
raise ClientError(e)
py2neo.exceptions.ClientError: Not Found
Your exact code snippet works for me (OS X, neo4j 2.1.2). There shouldn't be any problem. Have you tried to install the latest version of neo4j and run your code on a fresh and untouched database? I have encountered inconsistencies in corrupted databases.
Have you tried to load the node with .find()?
result = db.find('Label')
for n in result:
print(n)