import time
import ScrollUtil
from appium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
desired_caps = {}
desired_caps['platformName'] = 'Android'
desired_caps['deviceName'] = 'Android'
desired_caps['appPackage'] = 'com.samsung.android.dialer'
desired_caps['appActivity'] = 'com.samsung.android.dialer.DialtactsActivity'
driver = webdriver.Remote('http://localhost:4723/wd/hub', desired_caps)
driver.implicitly_wait(10)
ScrollUtil.swipeUp(4,driver)
ScrollUtil.swipeDown(4,driver)
# driver.find_element_by_android_uiautomator(
# 'new UiScrollable(new UiSelector().scrollable(true).instance(0)).scrollIntoView(new UiSelector().textContains("Akash").instance(0))').click()
time.sleep(2)
driver.quit()
`
When I execute the above scripts I receive the below error messages and cannot be executed. I have already open the Appium Server
self.capabilities = response.get('value')
AttributeError: can't set attribute
Error message
Reinstall Appium-Python-Client using pip, instead of npm
And make sure selenium 3.XX version is installed
I'm trying to use Hyperopt parallel search with MongoDB, and encountered some issues with Mongotrials, which have been discussed here. I've tried all their methods, and I am still unable to find solutions to my specific problem. The specific model I'm trying to minimize is RadomForestRegressor from sklearn.
I've followed this tutorial. And I'm able to print out the calculated "fmin" with no issue.
Here are my steps so far:
1) Activate a virtual environment called "tensorflow" (I've installed all my libraries there)
2) Start MongoDB:
(tensorflow) bash-3.2$ mongod --dbpath . --port 1234 --directoryperdb --journal --nohttpinterface
3) Initiate workers:
(tensorflow) bash-3.2$ hyperopt-mongo-worker --mongo=localhost:1234/foo_db --poll-interval=0.1
4) Run my python code, and my python code is as follows:
import numpy as np
import pandas as pd
from sklearn.metrics import mean_absolute_error
from hyperopt import hp, fmin, tpe, STATUS_OK, Trials
from hyperopt.mongoexp import MongoTrials
# Preprocessing data
train_xg = pd.read_csv('train.csv')
n_train = len(train_xg)
print "Whole data set size: ", n_train
# Creating columns for features, and categorical features
features_col = [x for x in train_xg.columns if x not in ['id', 'loss', 'log_loss']]
cat_features_col = [x for x in train_xg.select_dtypes(include=['object']).columns if x not in ['id', 'loss', 'log_loss']]
for c in range(len(cat_features_col)):
train_xg[cat_features_col[c]] = train_xg[cat_features_col[c]].astype('category').cat.codes
# Use this to train random forest regressor
train_xg_x = np.array(train_xg[features_col])
train_xg_y = np.array(train_xg['loss'])
space_rf = { 'min_samples_leaf': hp.choice('min_samples_leaf', range(1,100)) }
trials = MongoTrials('mongo://localhost:1234/foo_db/jobs', exp_key='exp1')
def minMe(params):
# Hyperopt tuning for hyperparameters
from sklearn.model_selection import cross_val_score
from sklearn.ensemble import RandomForestRegressor
from hyperopt import STATUS_OK
try:
import dill as pickle
print('Went with dill')
except ImportError:
import pickle
def hyperopt_rf(params):
rf = RandomForestRegressor(**params)
return cross_val_score(rf, train_xg_x, train_xg_y).mean()
acc = hyperopt_rf(params)
print 'new acc:', acc, 'params: ', params
return {'loss': -acc, 'status': STATUS_OK}
best = fmin(fn=minMe, space=space_rf, trials=trials, algo=tpe.suggest, max_evals=100)
print "Best: ", best
5) After I run the above Python code, I get the following errors:
INFO:hyperopt.mongoexp:Error while unpickling. Try installing dill via "pip install dill" for enhanced pickling support.
INFO:hyperopt.mongoexp:job exception: 'module' object has no attribute 'minMe'
Traceback (most recent call last):
File "/Users/WernerChao/tensorflow/bin/hyperopt-mongo-worker", line 6, in <module>
sys.exit(hyperopt.mongoexp.main_worker())
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1302, in main_worker
return main_worker_helper(options, args)
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1249, in main_worker_helper
mworker.run_one(reserve_timeout=float(options.reserve_timeout))
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1064, in run_one
domain = pickle.loads(blob)
AttributeError: 'module' object has no attribute 'minMe'
INFO:hyperopt.mongoexp:PROTOCOL mongo
INFO:hyperopt.mongoexp:USERNAME None
INFO:hyperopt.mongoexp:HOSTNAME localhost
INFO:hyperopt.mongoexp:PORT 1234
INFO:hyperopt.mongoexp:PATH /foo_db/jobs
INFO:hyperopt.mongoexp:DB foo_db
INFO:hyperopt.mongoexp:COLLECTION jobs
INFO:hyperopt.mongoexp:PASS None
INFO:hyperopt.mongoexp:Error while unpickling. Try installing dill via "pip install dill" for enhanced pickling support.
INFO:hyperopt.mongoexp:job exception: 'module' object has no attribute 'minMe'
Traceback (most recent call last):
File "/Users/WernerChao/tensorflow/bin/hyperopt-mongo-worker", line 6, in <module>
sys.exit(hyperopt.mongoexp.main_worker())
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1302, in main_worker
return main_worker_helper(options, args)
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1249, in main_worker_helper
mworker.run_one(reserve_timeout=float(options.reserve_timeout))
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1064, in run_one
domain = pickle.loads(blob)
AttributeError: 'module' object has no attribute 'minMe'
INFO:hyperopt.mongoexp:PROTOCOL mongo
INFO:hyperopt.mongoexp:USERNAME None
INFO:hyperopt.mongoexp:HOSTNAME localhost
INFO:hyperopt.mongoexp:PORT 1234
INFO:hyperopt.mongoexp:PATH /foo_db/jobs
INFO:hyperopt.mongoexp:DB foo_db
INFO:hyperopt.mongoexp:COLLECTION jobs
INFO:hyperopt.mongoexp:PASS None
INFO:hyperopt.mongoexp:Error while unpickling. Try installing dill via "pip install dill" for enhanced pickling support.
INFO:hyperopt.mongoexp:job exception: 'module' object has no attribute 'minMe'
Traceback (most recent call last):
File "/Users/WernerChao/tensorflow/bin/hyperopt-mongo-worker", line 6, in <module>
sys.exit(hyperopt.mongoexp.main_worker())
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1302, in main_worker
return main_worker_helper(options, args)
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1249, in main_worker_helper
mworker.run_one(reserve_timeout=float(options.reserve_timeout))
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1064, in run_one
domain = pickle.loads(blob)
AttributeError: 'module' object has no attribute 'minMe'
INFO:hyperopt.mongoexp:PROTOCOL mongo
INFO:hyperopt.mongoexp:USERNAME None
INFO:hyperopt.mongoexp:HOSTNAME localhost
INFO:hyperopt.mongoexp:PORT 1234
INFO:hyperopt.mongoexp:PATH /foo_db/jobs
INFO:hyperopt.mongoexp:DB foo_db
INFO:hyperopt.mongoexp:COLLECTION jobs
INFO:hyperopt.mongoexp:PASS None
INFO:hyperopt.mongoexp:no job found, sleeping for 0.7s
INFO:hyperopt.mongoexp:Error while unpickling. Try installing dill via "pip install dill" for enhanced pickling support.
INFO:hyperopt.mongoexp:job exception: 'module' object has no attribute 'minMe'
Traceback (most recent call last):
File "/Users/WernerChao/tensorflow/bin/hyperopt-mongo-worker", line 6, in <module>
sys.exit(hyperopt.mongoexp.main_worker())
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1302, in main_worker
return main_worker_helper(options, args)
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1249, in main_worker_helper
mworker.run_one(reserve_timeout=float(options.reserve_timeout))
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1064, in run_one
domain = pickle.loads(blob)
AttributeError: 'module' object has no attribute 'minMe'
INFO:hyperopt.mongoexp:exiting with N=9223372036854775803 after 4 consecutive exceptions
6) Then Mongo workers would shut off.
Things I've tried:
install "dill" as the error suggested -> didn't work
Put global imports into the objective function so it can pickle -> didn't work
Put try except with "dill" or "pickle" as import -> didn't work
Does anyone have similar issues? I'm running out of ideas to try, and have been working on this for 2 days in vain. I think I am missing something really simple here, just can't seem to find it.
What am I missing?
Any suggestion is welcomed please!
Had the same problem in python 3.5. Installing Dill didn't help, nor dir setting workdir in MongoTrials or hyperopt-mongo-worker cli. hyperopt-mongo-worker doesn't seem to have access to __main__ where the function was defined:
AttributeError: Can't get attribute 'minMe' on <module '__main__' from ...hyperopt-mongo-worker
As #jaikumarm suggested, I circumvented the problem by writing a module file with all the required functions. However, instead of soft-linking it into the bin directory, I extended the PYTHONPATH before running hyperopt-mongo-worker:
export PYTHONPATH="${PYTHONPATH}:<dir_with_the_module.py>"
hyperopt-mongo-worker ...
That way, the hyperopt-monogo-worker is able to import the module containing minMe.
I fought with this for several days before coming up with a workable solution. there are two problems:
1. the mongo worker spawns off a separate process to run the optimizer so any context from your original python file is lost and unavailable for this new process.
2. the imports on this new process happen in the context of the hyperopt-mongo-worker scipy, which is in your case will be /Users/WernerChao/tensorflow/bin/.
So my solution is to make this new optimizer function completely self sufficient
optimizer.py
import numpy as np
import pandas as pd
from sklearn.metrics import mean_absolute_error
# Preprocessing data
train_xg = pd.read_csv('train.csv')
n_train = len(train_xg)
print "Whole data set size: ", n_train
# Creating columns for features, and categorical features
features_col = [x for x in train_xg.columns if x not in ['id', 'loss', 'log_loss']]
cat_features_col = [x for x in train_xg.select_dtypes(include=['object']).columns if x not in ['id', 'loss', 'log_loss']]
for c in range(len(cat_features_col)):
train_xg[cat_features_col[c]] = train_xg[cat_features_col[c]].astype('category').cat.codes
# Use this to train random forest regressor
train_xg_x = np.array(train_xg[features_col])
train_xg_y = np.array(train_xg['loss'])
def minMe(params):
# Hyperopt tuning for hyperparameters
from sklearn.model_selection import cross_val_score
from sklearn.ensemble import RandomForestRegressor
from hyperopt import STATUS_OK
try:
import dill as pickle
print('Went with dill')
except ImportError:
import pickle
def hyperopt_rf(params):
rf = RandomForestRegressor(**params)
return cross_val_score(rf, train_xg_x, train_xg_y).mean()
acc = hyperopt_rf(params)
print 'new acc:', acc, 'params: ', params
return {'loss': -acc, 'status': STATUS_OK}
wrapper.py
from hyperopt import hp, fmin, tpe, STATUS_OK, Trials
from hyperopt.mongoexp import MongoTrials
import optimizer
space_rf = { 'min_samples_leaf': hp.choice('min_samples_leaf', range(1,100)) }
best = fmin(fn=optimizer.minMe, space=space_rf, trials=trials, algo=tpe.suggest, max_evals=100)
print "Best: ", best
trials = MongoTrials('mongo://localhost:1234/foo_db/jobs', exp_key='exp1')
Once you have this code link the optimizer.py to the bin folder
ln -s /Users/WernerChao/Git/test/optimizer.py /Users/WernerChao/tensorflow/bin/
now run the wrapper.py and then the mongo worker it should be able to import the optimizer from its local context and run the minMe function.
Try to install Dill in the Python environment of your tensorflow (or possibly the worker):
/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt
Your aim is to get rid of the hyperopt error message:
hyperopt.mongoexp:Error while unpickling. Try installing dill via "pip install dill" for enhanced pickling support.
This is because the Python by default cannot marshal a function. It requires dill library to extend Python's pickling module for serialising/de-serialising Python objects. In your case, it failed to serialise your function minMe().
I made a separate file which calculates the loss and copied it to /anaconda2/bin/
and
/anaconda2/lib/python2.7/site-packages/hyperopt
it is working fine.
This was my Traceback
Traceback (most recent call last):
File "/home/greatskull/anaconda2/bin/hyperopt-mongo-worker", line 6, in <module>
sys.exit(hyperopt.mongoexp.main_worker())
File "/home/greatskull/anaconda2/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1302, in main_worker
return main_worker_helper(options, args)
File "/home/greatskull/anaconda2/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1249, in main_worker_helper
mworker.run_one(reserve_timeout=float(options.reserve_timeout))
File "/home/greatskull/anaconda2/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1073, in run_one
with temp_dir(workdir, erase_created_workdir), working_dir(workdir):
File "/home/greatskull/anaconda2/lib/python2.7/contextlib.py", line 17, in __enter__
return self.gen.next()
File "/home/greatskull/anaconda2/lib/python2.7/site-packages/hyperopt/utils.py", line 229, in temp_dir
os.makedirs(dir)
File "/home/greatskull/anaconda2/lib/python2.7/os.py", line 150, in makedirs
makedirs(head, mode)
File "/home/greatskull/anaconda2/lib/python2.7/os.py", line 157, in makedirs
mkdir(name, mode)
I'm trying to do some basic module setups on my server using Python. Its a bit difficult as I have no access to the internet.
This is my code
import sys
import os
from subprocess import CalledProcessError, STDOUT, check_output
def run_in_path(command, dir_path, env_var=''):
env_var = os.environ["PATH"] = os.environ["PATH"] + env_var
print(env_var)
try:
p = check_output(command, cwd=dir_path, stderr=STDOUT)
except CalledProcessError as e:
sys.stderr.write(e.output.decode("utf-8"))
sys.stderr.flush()
return e.returncode
else:
return 0
def main():
requests_install = run_in_path('python setup.py build',
'D:\installed_software\python modules\kennethreitz-requests-e95e173')
SQL_install = run_in_path('python setup.py install', # install SQL module pypyodbc
'D:\installed_software\python modules\pypyodbc-1.3.3\pypyodbc-1.3.3')
setup_tools = run_in_path('python setup.py install', # install setup tools
'D:\installed_software\python modules\setuptools-17.1.1')
psycopg2 = run_in_path('easy_install psycopg2-2.6.1.win-amd64-py3.3-pg9.4.4-release', # install setup tools
'D:\installed_software\python modules', ';C:\srv_apps\Python33\Scripts\easy_install.exe')
print('setup complete')
if __name__ == "__main__":
sys.exit(main())
now it gets tricky when i start trying to use easy install. It appears my env variables are not being used by my subprocess.check_output call
File "C:\srv_apps\Python33\lib\subprocess.py", line 1110, in _execute_child
raise WindowsError(*e.args)
FileNotFoundError: [WinError 2] The system cannot find the file specified
I don't want to have to upgrade to 3.4 where easy install is installed by default because my other modules are not supported on 3.4. My main challenge is the subprocess.check_call method does not take environment variables as an input and im wary of trying to use Popen() as I have never really got it to work successfully in the past. Any help would be greatly appreciated.
PATH should contain directories e.g., r'C:\Python33\Scripts', not files such as: r'C:\Python33\Scripts\easy_install.exe'
Don't hardcode utf-8 for an arbitrary command, you could enable text mode using universal_newlines parameter (not tested):
#!/usr/bin/env python3
import locale
import sys
from subprocess import CalledProcessError, STDOUT, check_output
def run(command, *, cwd=None, env=None):
try:
ignored = check_output(command, cwd=cwd, env=env,
stderr=STDOUT,
universal_newlines=True)
except CalledProcessError as e:
sys.stderr.write(e.output)
sys.stderr.flush()
return e.returncode
else:
return 0
Example:
import os
path_var = os.pathsep.join(os.environ.get('PATH', os.defpath), some_dir)
env = dict(os.environ, PATH=path_var)
run("some_command", cwd=some_path, env=env)
run("another_command", cwd=another_path, env=env)
import the necessary packages
from matplotlib import pyplot as plt
import numpy as np
import argparse
import cv2
# construct the argument parser and parse the arguments
**ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required = True, help = "Path to the image")
args = vars(ap.parse_args())**
# load the image and show it
image = cv2.imread(args["image"])
cv2.imshow("image", image)**
My error is:
usage: -c [-h] -i IMAGE
-c: error: argument **-i/--image is required**
If this is my current wd: C:\Users\Jeremy\Documents\IPython Notebooks
what is wrong? what should I be inputing for -i/--image?
I am using selenium and i have properly installed the selenium module on redhat linux 6.
Below is my script:
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import Select
from selenium.common.exceptions import NoSuchElementException
import unittest, time, re
import zlib
class Sele1(unittest.TestCase):
def setUp(self):
self.driver = webdriver.Firefox()
self.driver.implicitly_wait(30)
self.base_url = "https://bugzilla.example.com/"
self.verificationErrors = []
def test_sele1(self):
driver = self.driver
driver.get(self.base_url + "/")
driver.find_element_by_id("Bugzilla_login").clear()
driver.find_element_by_id("Bugzilla_login").send_keys("username")
driver.find_element_by_id("Bugzilla_password").clear()
driver.find_element_by_id("Bugzilla_password").send_keys("password")
driver.find_element_by_id("log_in").click()
driver.find_element_by_id("quicksearch").clear()
driver.find_element_by_id("quicksearch").send_keys("new bugs is bugzilla tool")
driver.find_element_by_xpath("//input[#value='Find Bugs']").click()
def is_element_present(self, how, what):
try: self.driver.find_element(by=how, value=what)
except NoSuchElementException, e: return False
return True
def tearDown(self):
self.driver.quit()
self.assertEqual([], self.verificationErrors)
if __name__ == "__main__":
unittest.main()
When i am running this script it is showing errors:
ERROR: test_sele1 (main.Sele1)
Traceback (most recent call last):
File "sele1.py", line 19, in test_sele1
driver.find_element_by_id("Bugzilla_login").clear()
AttributeError: 'NoneType' object has no attribute 'clear'
Ran 1 test in 2.018s
FAILED (errors=1)
Plateform: Redhat
Python Version: 2.6
Note: while running the same script in windows7, it is running fine but not running in linux with python2.6
Please help me for this...
Thanks in advance!
Simple: Selenium can't find an element called "Bugzilla_login".
There could be hundreds of reasons this may be happening. I'd start with checking whether you're loading the correct page.