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def merge_subsets(a, b):
'Merges field subset definitions together. The b subset is merged into the a subset. Assumes that subsets have been stripped of non-ecs options.'
for key in b:
if (key not in a):
a[key] = b[key]
elif (('fields' in a[key]) and ('fields' in b[key])):
if (b[key]['fields'] == '*'):
a[key]['fields'] = '*'
elif (isinstance(a[key]['fields'], dict) and isinstance(b[key]['fields'], dict)):
merge_subsets(a[key]['fields'], b[key]['fields'])
elif (('fields' in a[key]) or ('fields' in b[key])):
raise ValueError("Subsets unmergeable: 'fields' found in key '{}' in only one subset".format(key))
if (a[key].get('enabled', True) or b[key].get('enabled', True)):
a[key].pop('enabled', None)
if (a[key].get('index', True) or b[key].get('index', True)):
a[key].pop('index', None) | -50,387,666,115,584,190 | Merges field subset definitions together. The b subset is merged into the a subset. Assumes that subsets have been stripped of non-ecs options. | scripts/schema/subset_filter.py | merge_subsets | 6un9-h0-Dan/ecs | python | def merge_subsets(a, b):
for key in b:
if (key not in a):
a[key] = b[key]
elif (('fields' in a[key]) and ('fields' in b[key])):
if (b[key]['fields'] == '*'):
a[key]['fields'] = '*'
elif (isinstance(a[key]['fields'], dict) and isinstance(b[key]['fields'], dict)):
merge_subsets(a[key]['fields'], b[key]['fields'])
elif (('fields' in a[key]) or ('fields' in b[key])):
raise ValueError("Subsets unmergeable: 'fields' found in key '{}' in only one subset".format(key))
if (a[key].get('enabled', True) or b[key].get('enabled', True)):
a[key].pop('enabled', None)
if (a[key].get('index', True) or b[key].get('index', True)):
a[key].pop('index', None) |
def extract_matching_fields(fields, subset_definitions):
'Removes fields that are not in the subset definition. Returns a copy without modifying the input fields dict.'
retained_fields = {x: fields[x].copy() for x in subset_definitions}
for (key, val) in subset_definitions.items():
retained_fields[key]['field_details'] = fields[key]['field_details'].copy()
for option in val:
if (option != 'fields'):
if ('intermediate' in retained_fields[key]['field_details']):
retained_fields[key]['field_details']['intermediate'] = False
retained_fields[key]['field_details'].setdefault('description', 'Intermediate field included by adding option with subset')
retained_fields[key]['field_details']['level'] = 'custom'
cleaner.field_cleanup(retained_fields[key])
retained_fields[key]['field_details'][option] = val[option]
if ('fields' in fields[key]):
if ('fields' not in val):
raise ValueError("'fields' key expected, not found in subset for {}".format(key))
elif isinstance(val['fields'], dict):
retained_fields[key]['fields'] = extract_matching_fields(fields[key]['fields'], val['fields'])
elif (val['fields'] != '*'):
raise ValueError("Unexpected value '{}' found in 'fields' key".format(val['fields']))
elif ('fields' in val):
raise ValueError("'fields' key not expected, found in subset for {}".format(key))
return retained_fields | -6,010,733,992,487,650,000 | Removes fields that are not in the subset definition. Returns a copy without modifying the input fields dict. | scripts/schema/subset_filter.py | extract_matching_fields | 6un9-h0-Dan/ecs | python | def extract_matching_fields(fields, subset_definitions):
retained_fields = {x: fields[x].copy() for x in subset_definitions}
for (key, val) in subset_definitions.items():
retained_fields[key]['field_details'] = fields[key]['field_details'].copy()
for option in val:
if (option != 'fields'):
if ('intermediate' in retained_fields[key]['field_details']):
retained_fields[key]['field_details']['intermediate'] = False
retained_fields[key]['field_details'].setdefault('description', 'Intermediate field included by adding option with subset')
retained_fields[key]['field_details']['level'] = 'custom'
cleaner.field_cleanup(retained_fields[key])
retained_fields[key]['field_details'][option] = val[option]
if ('fields' in fields[key]):
if ('fields' not in val):
raise ValueError("'fields' key expected, not found in subset for {}".format(key))
elif isinstance(val['fields'], dict):
retained_fields[key]['fields'] = extract_matching_fields(fields[key]['fields'], val['fields'])
elif (val['fields'] != '*'):
raise ValueError("Unexpected value '{}' found in 'fields' key".format(val['fields']))
elif ('fields' in val):
raise ValueError("'fields' key not expected, found in subset for {}".format(key))
return retained_fields |
@staticmethod
def from_file(filename: str) -> 'WallpaperConfig':
' Creates a WallpaperConfig from a YAML file '
with open(filename, 'r') as input_file:
return jsons.load(yaml.load(input_file, Loader=yaml.SafeLoader), WallpaperConfig) | -5,361,020,704,774,841,000 | Creates a WallpaperConfig from a YAML file | config_objects.py | from_file | JimTheCactus/RedditWallpaperWatcher | python | @staticmethod
def from_file(filename: str) -> 'WallpaperConfig':
' '
with open(filename, 'r') as input_file:
return jsons.load(yaml.load(input_file, Loader=yaml.SafeLoader), WallpaperConfig) |
@staticmethod
def from_file(filename: str) -> 'RedditAuthInfo':
' Creates a RedditAuthInfo from a YAML file '
with open(filename, 'r') as input_file:
auth = jsons.load(yaml.load(input_file, Loader=yaml.SafeLoader), RedditAuthInfo)
return auth | 7,710,573,328,413,913,000 | Creates a RedditAuthInfo from a YAML file | config_objects.py | from_file | JimTheCactus/RedditWallpaperWatcher | python | @staticmethod
def from_file(filename: str) -> 'RedditAuthInfo':
' '
with open(filename, 'r') as input_file:
auth = jsons.load(yaml.load(input_file, Loader=yaml.SafeLoader), RedditAuthInfo)
return auth |
def __init__(self, success=None, message=None, error_code=None, data=None):
'Constructor for the GetScheduledMessageResponse class'
self.success = success
self.message = message
self.error_code = error_code
self.data = data | -3,612,874,773,586,269,700 | Constructor for the GetScheduledMessageResponse class | unifonicnextgen/models/get_scheduled_message_response.py | __init__ | masaar/unifonic_python_sdk | python | def __init__(self, success=None, message=None, error_code=None, data=None):
self.success = success
self.message = message
self.error_code = error_code
self.data = data |
@classmethod
def from_dictionary(cls, dictionary):
"Creates an instance of this model from a dictionary\n\n Args:\n dictionary (dictionary): A dictionary representation of the object as\n obtained from the deserialization of the server's response. The keys\n MUST match property names in the API description.\n\n Returns:\n object: An instance of this structure class.\n\n "
if (dictionary is None):
return None
success = dictionary.get('success')
message = dictionary.get('message')
error_code = dictionary.get('errorCode')
data = dictionary.get('data')
return cls(success, message, error_code, data) | -1,881,683,673,075,648,500 | Creates an instance of this model from a dictionary
Args:
dictionary (dictionary): A dictionary representation of the object as
obtained from the deserialization of the server's response. The keys
MUST match property names in the API description.
Returns:
object: An instance of this structure class. | unifonicnextgen/models/get_scheduled_message_response.py | from_dictionary | masaar/unifonic_python_sdk | python | @classmethod
def from_dictionary(cls, dictionary):
"Creates an instance of this model from a dictionary\n\n Args:\n dictionary (dictionary): A dictionary representation of the object as\n obtained from the deserialization of the server's response. The keys\n MUST match property names in the API description.\n\n Returns:\n object: An instance of this structure class.\n\n "
if (dictionary is None):
return None
success = dictionary.get('success')
message = dictionary.get('message')
error_code = dictionary.get('errorCode')
data = dictionary.get('data')
return cls(success, message, error_code, data) |
def testing_job(progress_steps=None, retval=None, fail=False, skip=False, log_messages=None, step_duration=0):
'\n Job used for testing purposes.\n\n :param progress_steps:\n A list of tuples: ``(<group_name>, <steps>)``, where "group_name"\n is a tuple of name "levels", "steps" an integer representing how\n many steps should that level have.\n\n Progress reports will be sent in randomized order.\n\n :param retval:\n The return value for the job.\n\n :param fail:\n Whether this job should fail.\n\n :param skip:\n Whether this job should be skipped.\n\n :param log_messages:\n A list of tuples: ``(level, message)``\n\n :param step_duration:\n The time to sleep between steps, in milliseconds.\n '
from jobcontrol.globals import execution_context
logger = logging.getLogger('jobcontrol.utils.testing_job')
log_messages = list((log_messages or []))
if (progress_steps is None):
progress_steps = [(None, 10)]
totals = {}
counters = {}
progress_report_items = []
for (name, steps) in progress_steps:
if isinstance(name, list):
name = tuple(name)
if (not ((name is None) or isinstance(name, tuple))):
raise TypeError('Name must be a tuple or None')
for i in xrange(steps):
progress_report_items.append(name)
totals[name] = steps
counters[name] = 0
random.shuffle(progress_report_items)
sleep_time = ((step_duration * 1.0) / 1000)
def report_progress(name, cur, tot, status=None):
app = execution_context.current_app
app.report_progress(group_name=name, current=cur, total=tot, status_line=status)
def _should_fail():
return (random.randint(0, len(progress_report_items)) == 0)
for item in progress_report_items:
counters[item] += 1
report_progress(item, counters[item], totals[item], 'Doing action {0} [{1}/{2}]'.format(item, counters[item], totals[item]))
if len(log_messages):
(lev, msg) = log_messages.pop(0)
logger.log(lev, msg)
if (fail and _should_fail()):
raise RuntimeError('This is a simulated exception in the middle of the loop')
if (skip and _should_fail()):
raise SkipBuild('This is a simulated skip in the middle of the loop')
if sleep_time:
time.sleep(sleep_time)
if skip:
raise SkipBuild('This build should be skipped!')
if fail:
raise RuntimeError('This is a simulated exception')
return retval | 4,464,256,424,644,385,000 | Job used for testing purposes.
:param progress_steps:
A list of tuples: ``(<group_name>, <steps>)``, where "group_name"
is a tuple of name "levels", "steps" an integer representing how
many steps should that level have.
Progress reports will be sent in randomized order.
:param retval:
The return value for the job.
:param fail:
Whether this job should fail.
:param skip:
Whether this job should be skipped.
:param log_messages:
A list of tuples: ``(level, message)``
:param step_duration:
The time to sleep between steps, in milliseconds. | jobcontrol/utils/testing.py | testing_job | rshk/jobcontrol | python | def testing_job(progress_steps=None, retval=None, fail=False, skip=False, log_messages=None, step_duration=0):
'\n Job used for testing purposes.\n\n :param progress_steps:\n A list of tuples: ``(<group_name>, <steps>)``, where "group_name"\n is a tuple of name "levels", "steps" an integer representing how\n many steps should that level have.\n\n Progress reports will be sent in randomized order.\n\n :param retval:\n The return value for the job.\n\n :param fail:\n Whether this job should fail.\n\n :param skip:\n Whether this job should be skipped.\n\n :param log_messages:\n A list of tuples: ``(level, message)``\n\n :param step_duration:\n The time to sleep between steps, in milliseconds.\n '
from jobcontrol.globals import execution_context
logger = logging.getLogger('jobcontrol.utils.testing_job')
log_messages = list((log_messages or []))
if (progress_steps is None):
progress_steps = [(None, 10)]
totals = {}
counters = {}
progress_report_items = []
for (name, steps) in progress_steps:
if isinstance(name, list):
name = tuple(name)
if (not ((name is None) or isinstance(name, tuple))):
raise TypeError('Name must be a tuple or None')
for i in xrange(steps):
progress_report_items.append(name)
totals[name] = steps
counters[name] = 0
random.shuffle(progress_report_items)
sleep_time = ((step_duration * 1.0) / 1000)
def report_progress(name, cur, tot, status=None):
app = execution_context.current_app
app.report_progress(group_name=name, current=cur, total=tot, status_line=status)
def _should_fail():
return (random.randint(0, len(progress_report_items)) == 0)
for item in progress_report_items:
counters[item] += 1
report_progress(item, counters[item], totals[item], 'Doing action {0} [{1}/{2}]'.format(item, counters[item], totals[item]))
if len(log_messages):
(lev, msg) = log_messages.pop(0)
logger.log(lev, msg)
if (fail and _should_fail()):
raise RuntimeError('This is a simulated exception in the middle of the loop')
if (skip and _should_fail()):
raise SkipBuild('This is a simulated skip in the middle of the loop')
if sleep_time:
time.sleep(sleep_time)
if skip:
raise SkipBuild('This build should be skipped!')
if fail:
raise RuntimeError('This is a simulated exception')
return retval |
def job_failing_once():
'\n This job will fail exactly once; retry will be successful\n '
from jobcontrol.globals import current_job
exec_count = len(list(current_job.iter_runs()))
if (exec_count <= 1):
raise RuntimeError('Simulating failure')
return exec_count | 665,967,870,671,782,900 | This job will fail exactly once; retry will be successful | jobcontrol/utils/testing.py | job_failing_once | rshk/jobcontrol | python | def job_failing_once():
'\n \n '
from jobcontrol.globals import current_job
exec_count = len(list(current_job.iter_runs()))
if (exec_count <= 1):
raise RuntimeError('Simulating failure')
return exec_count |
def job_echo_config(*args, **kwargs):
'\n Simple job, "echoing" back the current configuration.\n '
from jobcontrol.globals import current_job, current_build
return {'args': args, 'kwargs': kwargs, 'build_id': current_build.id, 'job_id': current_job.id, 'dependencies': current_build.config['dependencies'], 'config': current_build.config} | 3,529,256,724,884,849,700 | Simple job, "echoing" back the current configuration. | jobcontrol/utils/testing.py | job_echo_config | rshk/jobcontrol | python | def job_echo_config(*args, **kwargs):
'\n \n '
from jobcontrol.globals import current_job, current_build
return {'args': args, 'kwargs': kwargs, 'build_id': current_build.id, 'job_id': current_job.id, 'dependencies': current_build.config['dependencies'], 'config': current_build.config} |
def CrossValidationFolds_Traversal(estimator, vdataset):
"\n Arguments: \n - estimator = classifer of model\n - vdataset = vehicld dataset \n \n This function computes acccuracy score with the\n Cross Validation Score for each KFold with K from 2 to 10 \n \n Output:\n returns matrix conatining value of K with it's corresponding performance score\n "
X = vdataset.drop(['Class', 'Class_code'], axis=1)
y = vdataset['Class_code']
scores = []
matrix = pd.DataFrame(columns=['KFold', 'Accuracy'])
for i in range(2, 11):
score = cross_val_score(estimator, X, y, cv=i, scoring='accuracy')
scores.append(score.mean())
matrix = matrix.append({'KFold': i, 'Accuracy': (score.mean() * 100)}, ignore_index=True)
return matrix | -815,941,616,666,243,500 | Arguments:
- estimator = classifer of model
- vdataset = vehicld dataset
This function computes acccuracy score with the
Cross Validation Score for each KFold with K from 2 to 10
Output:
returns matrix conatining value of K with it's corresponding performance score | dev/shiza16/Calibration plot/CrossValidationFold_Traversal.py | CrossValidationFolds_Traversal | Bolaji61/PRESC | python | def CrossValidationFolds_Traversal(estimator, vdataset):
"\n Arguments: \n - estimator = classifer of model\n - vdataset = vehicld dataset \n \n This function computes acccuracy score with the\n Cross Validation Score for each KFold with K from 2 to 10 \n \n Output:\n returns matrix conatining value of K with it's corresponding performance score\n "
X = vdataset.drop(['Class', 'Class_code'], axis=1)
y = vdataset['Class_code']
scores = []
matrix = pd.DataFrame(columns=['KFold', 'Accuracy'])
for i in range(2, 11):
score = cross_val_score(estimator, X, y, cv=i, scoring='accuracy')
scores.append(score.mean())
matrix = matrix.append({'KFold': i, 'Accuracy': (score.mean() * 100)}, ignore_index=True)
return matrix |
def Visulaize_CrossValidationFolds_Traversal(matrix):
"\n Argument:\n - matrix: Dataframe named matrix\n \n Line Plot is drawn for each KFold value with it's respective performance score.\n \n Output:\n - plot the line graph\n "
ax = plt.gca()
matrix.plot(kind='line', x='KFold', y='Accuracy', color='red', marker='o', markerfacecolor='blue', markersize=12, ax=ax)
plt.title("Line plot of No of Kfold with it's corresponding performance score\n")
plt.ylabel('Accuracy\n')
plt.xlabel('\nNo of KFolds')
plt.show() | 1,476,091,193,718,027,800 | Argument:
- matrix: Dataframe named matrix
Line Plot is drawn for each KFold value with it's respective performance score.
Output:
- plot the line graph | dev/shiza16/Calibration plot/CrossValidationFold_Traversal.py | Visulaize_CrossValidationFolds_Traversal | Bolaji61/PRESC | python | def Visulaize_CrossValidationFolds_Traversal(matrix):
"\n Argument:\n - matrix: Dataframe named matrix\n \n Line Plot is drawn for each KFold value with it's respective performance score.\n \n Output:\n - plot the line graph\n "
ax = plt.gca()
matrix.plot(kind='line', x='KFold', y='Accuracy', color='red', marker='o', markerfacecolor='blue', markersize=12, ax=ax)
plt.title("Line plot of No of Kfold with it's corresponding performance score\n")
plt.ylabel('Accuracy\n')
plt.xlabel('\nNo of KFolds')
plt.show() |
def addPath(rel_path, prepend=False):
" Adds a directory to the system python path, either by append (doesn't\n override default or globally installed package names) or by prepend\n (overrides default/global package names).\n "
path = (lambda *paths: (os.path.abspath(os.path.join(os.path.dirname(__file__), *paths)) + '/'))
if prepend:
return sys.path.insert(0, path(rel_path))
return sys.path.append(path(rel_path)) | -3,591,457,979,364,174,300 | Adds a directory to the system python path, either by append (doesn't
override default or globally installed package names) or by prepend
(overrides default/global package names). | example/manage.py | addPath | Locu/djoauth2 | python | def addPath(rel_path, prepend=False):
" Adds a directory to the system python path, either by append (doesn't\n override default or globally installed package names) or by prepend\n (overrides default/global package names).\n "
path = (lambda *paths: (os.path.abspath(os.path.join(os.path.dirname(__file__), *paths)) + '/'))
if prepend:
return sys.path.insert(0, path(rel_path))
return sys.path.append(path(rel_path)) |
def act(self, state):
'Returns actions for given state(s) as per current policy.'
state = np.reshape(state, [(- 1), self.state_size])
action = self.actor_local.model.predict(state)[0]
return list((action + self.noise.sample())) | -7,804,609,446,734,043,000 | Returns actions for given state(s) as per current policy. | home/agents/agent.py | act | GabrielTourinho/dlnd-teach-a-quadcopter-how-to-fly | python | def act(self, state):
state = np.reshape(state, [(- 1), self.state_size])
action = self.actor_local.model.predict(state)[0]
return list((action + self.noise.sample())) |
def learn(self, experiences):
'Update policy and value parameters using given batch of experience tuples.'
states = np.vstack([e.state for e in experiences if (e is not None)])
actions = np.array([e.action for e in experiences if (e is not None)]).astype(np.float32).reshape((- 1), self.action_size)
rewards = np.array([e.reward for e in experiences if (e is not None)]).astype(np.float32).reshape((- 1), 1)
dones = np.array([e.done for e in experiences if (e is not None)]).astype(np.uint8).reshape((- 1), 1)
next_states = np.vstack([e.next_state for e in experiences if (e is not None)])
actions_next = self.actor_target.model.predict_on_batch(next_states)
Q_targets_next = self.critic_target.model.predict_on_batch([next_states, actions_next])
Q_targets = (rewards + ((self.gamma * Q_targets_next) * (1 - dones)))
self.critic_local.model.train_on_batch(x=[states, actions], y=Q_targets)
action_gradients = np.reshape(self.critic_local.get_action_gradients([states, actions, 0]), ((- 1), self.action_size))
self.actor_local.train_fn([states, action_gradients, 1])
self.soft_update(self.critic_local.model, self.critic_target.model)
self.soft_update(self.actor_local.model, self.actor_target.model) | 9,061,022,206,806,542,000 | Update policy and value parameters using given batch of experience tuples. | home/agents/agent.py | learn | GabrielTourinho/dlnd-teach-a-quadcopter-how-to-fly | python | def learn(self, experiences):
states = np.vstack([e.state for e in experiences if (e is not None)])
actions = np.array([e.action for e in experiences if (e is not None)]).astype(np.float32).reshape((- 1), self.action_size)
rewards = np.array([e.reward for e in experiences if (e is not None)]).astype(np.float32).reshape((- 1), 1)
dones = np.array([e.done for e in experiences if (e is not None)]).astype(np.uint8).reshape((- 1), 1)
next_states = np.vstack([e.next_state for e in experiences if (e is not None)])
actions_next = self.actor_target.model.predict_on_batch(next_states)
Q_targets_next = self.critic_target.model.predict_on_batch([next_states, actions_next])
Q_targets = (rewards + ((self.gamma * Q_targets_next) * (1 - dones)))
self.critic_local.model.train_on_batch(x=[states, actions], y=Q_targets)
action_gradients = np.reshape(self.critic_local.get_action_gradients([states, actions, 0]), ((- 1), self.action_size))
self.actor_local.train_fn([states, action_gradients, 1])
self.soft_update(self.critic_local.model, self.critic_target.model)
self.soft_update(self.actor_local.model, self.actor_target.model) |
def soft_update(self, local_model, target_model):
'Soft update model parameters.'
local_weights = np.array(local_model.get_weights())
target_weights = np.array(target_model.get_weights())
assert (len(local_weights) == len(target_weights)), 'Local and target model parameters must have the same size'
new_weights = ((self.tau * local_weights) + ((1 - self.tau) * target_weights))
target_model.set_weights(new_weights) | -6,402,697,941,261,341,000 | Soft update model parameters. | home/agents/agent.py | soft_update | GabrielTourinho/dlnd-teach-a-quadcopter-how-to-fly | python | def soft_update(self, local_model, target_model):
local_weights = np.array(local_model.get_weights())
target_weights = np.array(target_model.get_weights())
assert (len(local_weights) == len(target_weights)), 'Local and target model parameters must have the same size'
new_weights = ((self.tau * local_weights) + ((1 - self.tau) * target_weights))
target_model.set_weights(new_weights) |
def plotfft(s, fmax, doplot=False):
' This functions computes the fft of a signal, returning the frequency\n and their magnitude values.\n\n Parameters\n ----------\n s: array-like\n the input signal.\n fmax: int\n the sampling frequency.\n doplot: boolean\n a variable to indicate whether the plot is done or not.\n\n Returns\n -------\n f: array-like\n the frequency values (xx axis)\n fs: array-like\n the amplitude of the frequency values (yy axis)\n '
fs = abs(np.fft.fft(s))
f = linspace(0, (fmax / 2), (len(s) / 2))
if doplot:
pl.plot(f[1:(len(s) / 2)], fs[1:(len(s) / 2)])
return (f[1:(len(s) / 2)].copy(), fs[1:(len(s) / 2)].copy()) | -2,794,040,221,416,781,000 | This functions computes the fft of a signal, returning the frequency
and their magnitude values.
Parameters
----------
s: array-like
the input signal.
fmax: int
the sampling frequency.
doplot: boolean
a variable to indicate whether the plot is done or not.
Returns
-------
f: array-like
the frequency values (xx axis)
fs: array-like
the amplitude of the frequency values (yy axis) | novainstrumentation/tools.py | plotfft | novabiosignals/novainstrumentation | python | def plotfft(s, fmax, doplot=False):
' This functions computes the fft of a signal, returning the frequency\n and their magnitude values.\n\n Parameters\n ----------\n s: array-like\n the input signal.\n fmax: int\n the sampling frequency.\n doplot: boolean\n a variable to indicate whether the plot is done or not.\n\n Returns\n -------\n f: array-like\n the frequency values (xx axis)\n fs: array-like\n the amplitude of the frequency values (yy axis)\n '
fs = abs(np.fft.fft(s))
f = linspace(0, (fmax / 2), (len(s) / 2))
if doplot:
pl.plot(f[1:(len(s) / 2)], fs[1:(len(s) / 2)])
return (f[1:(len(s) / 2)].copy(), fs[1:(len(s) / 2)].copy()) |
def load_with_cache(file_, recache=False, sampling=1, columns=None, temp_dir='.', data_type='int16'):
"@brief This function loads a file from the current directory and saves\n the cached file to later executions. It's also possible to make a recache\n or a subsampling of the signal and choose only a few columns of the signal,\n to accelerate the opening process.\n\n @param file String: the name of the file to open.\n @param recache Boolean: indication whether it's done recache or not\n (default = false).\n @param sampling Integer: the sampling step. if 1, the signal isn't\n sampled (default = 1).\n @param columns Array-Like: the columns to read from the file. if None,\n all columns are considered (default = None).\n\n @return data Array-Like: the data from the file.\n TODO: Should save cache in a different directory\n TODO: Create test function and check size of generated files\n TODO: receive a file handle\n "
cfile = ('%s.npy' % file_)
if ((not path.exists(cfile)) or recache):
if (columns == None):
data = np.loadtxt(file_)[::sampling, :]
else:
data = np.loadtxt(file_)[::sampling, columns]
np.save(cfile, data.astype(data_type))
else:
data = np.load(cfile)
return data | 4,169,040,887,613,408,000 | @brief This function loads a file from the current directory and saves
the cached file to later executions. It's also possible to make a recache
or a subsampling of the signal and choose only a few columns of the signal,
to accelerate the opening process.
@param file String: the name of the file to open.
@param recache Boolean: indication whether it's done recache or not
(default = false).
@param sampling Integer: the sampling step. if 1, the signal isn't
sampled (default = 1).
@param columns Array-Like: the columns to read from the file. if None,
all columns are considered (default = None).
@return data Array-Like: the data from the file.
TODO: Should save cache in a different directory
TODO: Create test function and check size of generated files
TODO: receive a file handle | novainstrumentation/tools.py | load_with_cache | novabiosignals/novainstrumentation | python | def load_with_cache(file_, recache=False, sampling=1, columns=None, temp_dir='.', data_type='int16'):
"@brief This function loads a file from the current directory and saves\n the cached file to later executions. It's also possible to make a recache\n or a subsampling of the signal and choose only a few columns of the signal,\n to accelerate the opening process.\n\n @param file String: the name of the file to open.\n @param recache Boolean: indication whether it's done recache or not\n (default = false).\n @param sampling Integer: the sampling step. if 1, the signal isn't\n sampled (default = 1).\n @param columns Array-Like: the columns to read from the file. if None,\n all columns are considered (default = None).\n\n @return data Array-Like: the data from the file.\n TODO: Should save cache in a different directory\n TODO: Create test function and check size of generated files\n TODO: receive a file handle\n "
cfile = ('%s.npy' % file_)
if ((not path.exists(cfile)) or recache):
if (columns == None):
data = np.loadtxt(file_)[::sampling, :]
else:
data = np.loadtxt(file_)[::sampling, columns]
np.save(cfile, data.astype(data_type))
else:
data = np.load(cfile)
return data |
def load_data(filename):
'\n :rtype : numpy matrix\n '
data = pandas.read_csv(filename, header=None, delimiter='\t', skiprows=9)
return data.as_matrix() | 4,191,160,812,623,671,000 | :rtype : numpy matrix | novainstrumentation/tools.py | load_data | novabiosignals/novainstrumentation | python | def load_data(filename):
'\n \n '
data = pandas.read_csv(filename, header=None, delimiter='\t', skiprows=9)
return data.as_matrix() |
def test_experiment_variables(jikken_experiment):
'test variables are initialized properly and are not settable'
(exp, expected_variables, *_) = jikken_experiment
assert (exp.variables == expected_variables)
with pytest.raises(AttributeError):
exp.variables = expected_variables | 4,985,580,147,700,100,000 | test variables are initialized properly and are not settable | tests/unit/test_experiment.py | test_experiment_variables | outcastofmusic/jikken | python | def test_experiment_variables(jikken_experiment):
(exp, expected_variables, *_) = jikken_experiment
assert (exp.variables == expected_variables)
with pytest.raises(AttributeError):
exp.variables = expected_variables |
def test_experiment_tags(jikken_experiment):
'test tags are initialized properly and are not settable'
(exp, _, expected_tags, _) = jikken_experiment
assert (exp.tags == expected_tags)
with pytest.raises(AttributeError):
exp.tags = expected_tags | -8,382,541,816,748,046,000 | test tags are initialized properly and are not settable | tests/unit/test_experiment.py | test_experiment_tags | outcastofmusic/jikken | python | def test_experiment_tags(jikken_experiment):
(exp, _, expected_tags, _) = jikken_experiment
assert (exp.tags == expected_tags)
with pytest.raises(AttributeError):
exp.tags = expected_tags |
def test_experiment_schema(jikken_experiment):
'test schema is constructed properly'
(exp, expected_variables, _, tmpdir) = jikken_experiment
expected_hash = '40a3f5106cf9426bd4b13b168717e7bf'
assert (exp.schema_hash == expected_hash)
exp_2 = Experiment(name='exp1', variables=expected_variables, code_dir=tmpdir.strpath)
assert (exp_2.schema_hash == exp.schema_hash) | -2,649,363,590,991,716,000 | test schema is constructed properly | tests/unit/test_experiment.py | test_experiment_schema | outcastofmusic/jikken | python | def test_experiment_schema(jikken_experiment):
(exp, expected_variables, _, tmpdir) = jikken_experiment
expected_hash = '40a3f5106cf9426bd4b13b168717e7bf'
assert (exp.schema_hash == expected_hash)
exp_2 = Experiment(name='exp1', variables=expected_variables, code_dir=tmpdir.strpath)
assert (exp_2.schema_hash == exp.schema_hash) |
def test_experiment_parameters_schema(jikken_experiment):
'test schema with parameters is constructed properly'
(exp, expected_variables, _, tmpdir) = jikken_experiment
expected_hash = '77c861c501833128e1cfb5b398588a7e'
assert (exp.parameters_hash == expected_hash) | 5,444,041,656,221,252,000 | test schema with parameters is constructed properly | tests/unit/test_experiment.py | test_experiment_parameters_schema | outcastofmusic/jikken | python | def test_experiment_parameters_schema(jikken_experiment):
(exp, expected_variables, _, tmpdir) = jikken_experiment
expected_hash = '77c861c501833128e1cfb5b398588a7e'
assert (exp.parameters_hash == expected_hash) |
def test_log_info(self):
'Test that INFO log entry does not go to the audit log.'
logging.setup(self.cfg_path)
log = logging.getLogger(__name__)
msg = uuid.uuid4().hex
log.info(msg)
info_log_entries = open(self.info_log_path).read()
self.assertIn(msg, info_log_entries)
audit_log_entries = open(self.audit_log_path).read()
self.assertNotIn(msg, audit_log_entries) | 2,806,284,644,488,858,000 | Test that INFO log entry does not go to the audit log. | st2common/tests/unit/test_logger.py | test_log_info | Anshika-Gautam/st2 | python | def test_log_info(self):
logging.setup(self.cfg_path)
log = logging.getLogger(__name__)
msg = uuid.uuid4().hex
log.info(msg)
info_log_entries = open(self.info_log_path).read()
self.assertIn(msg, info_log_entries)
audit_log_entries = open(self.audit_log_path).read()
self.assertNotIn(msg, audit_log_entries) |
def test_log_critical(self):
'Test that CRITICAL log entry does not go to the audit log.'
logging.setup(self.cfg_path)
log = logging.getLogger(__name__)
msg = uuid.uuid4().hex
log.critical(msg)
info_log_entries = open(self.info_log_path).read()
self.assertIn(msg, info_log_entries)
audit_log_entries = open(self.audit_log_path).read()
self.assertNotIn(msg, audit_log_entries) | 1,073,219,046,804,395,500 | Test that CRITICAL log entry does not go to the audit log. | st2common/tests/unit/test_logger.py | test_log_critical | Anshika-Gautam/st2 | python | def test_log_critical(self):
logging.setup(self.cfg_path)
log = logging.getLogger(__name__)
msg = uuid.uuid4().hex
log.critical(msg)
info_log_entries = open(self.info_log_path).read()
self.assertIn(msg, info_log_entries)
audit_log_entries = open(self.audit_log_path).read()
self.assertNotIn(msg, audit_log_entries) |
def test_log_audit(self):
'Test that AUDIT log entry goes to the audit log.'
logging.setup(self.cfg_path)
log = logging.getLogger(__name__)
msg = uuid.uuid4().hex
log.audit(msg)
info_log_entries = open(self.info_log_path).read()
self.assertIn(msg, info_log_entries)
audit_log_entries = open(self.audit_log_path).read()
self.assertIn(msg, audit_log_entries) | 1,515,286,437,568,597,800 | Test that AUDIT log entry goes to the audit log. | st2common/tests/unit/test_logger.py | test_log_audit | Anshika-Gautam/st2 | python | def test_log_audit(self):
logging.setup(self.cfg_path)
log = logging.getLogger(__name__)
msg = uuid.uuid4().hex
log.audit(msg)
info_log_entries = open(self.info_log_path).read()
self.assertIn(msg, info_log_entries)
audit_log_entries = open(self.audit_log_path).read()
self.assertIn(msg, audit_log_entries) |
def stats(fname, times=True):
'Return stats on the file which should have been preserved'
with open(fname) as fd:
st = os.fstat(fd.fileno())
stats = (st.st_mode, st.st_uid, st.st_gid, st.st_size)
if times:
return (stats + (st.st_atime, st.st_mtime))
else:
return stats | -4,470,607,643,816,927,000 | Return stats on the file which should have been preserved | datalad/customremotes/tests/test_archives.py | stats | soichih/datalad | python | def stats(fname, times=True):
with open(fname) as fd:
st = os.fstat(fd.fileno())
stats = (st.st_mode, st.st_uid, st.st_gid, st.st_size)
if times:
return (stats + (st.st_atime, st.st_mtime))
else:
return stats |
def turnAlarm(on):
'write command into file - pass enable/disable command'
print(('turn alarm on? %s' % on))
enable = on
disable = (not on)
alarm = AlarmService()
alarm.load()
alarm.save(enable, disable)
return True | 666,391,020,835,512,300 | write command into file - pass enable/disable command | web/home.py | turnAlarm | tommykoch/pyhome | python | def turnAlarm(on):
print(('turn alarm on? %s' % on))
enable = on
disable = (not on)
alarm = AlarmService()
alarm.load()
alarm.save(enable, disable)
return True |
async def async_setup_entry(hass, config_entry, async_add_entities):
'Set up config entry.'
discovery_info = config_entry.data
device_ids = set()
def supported(event):
return (isinstance(event.device, rfxtrxmod.LightingDevice) and event.device.known_to_be_dimmable)
entities = []
for (packet_id, entity_info) in discovery_info[CONF_DEVICES].items():
event = get_rfx_object(packet_id)
if (event is None):
_LOGGER.error('Invalid device: %s', packet_id)
continue
if (not supported(event)):
continue
device_id = get_device_id(event.device, data_bits=entity_info.get(CONF_DATA_BITS))
if (device_id in device_ids):
continue
device_ids.add(device_id)
entity = RfxtrxLight(event.device, device_id, entity_info[CONF_SIGNAL_REPETITIONS])
entities.append(entity)
async_add_entities(entities)
@callback
def light_update(event, device_id):
'Handle light updates from the RFXtrx gateway.'
if (not supported(event)):
return
if (device_id in device_ids):
return
device_ids.add(device_id)
_LOGGER.info('Added light (Device ID: %s Class: %s Sub: %s, Event: %s)', event.device.id_string.lower(), event.device.__class__.__name__, event.device.subtype, ''.join((f'{x:02x}' for x in event.data)))
entity = RfxtrxLight(event.device, device_id, DEFAULT_SIGNAL_REPETITIONS, event=event)
async_add_entities([entity])
if discovery_info[CONF_AUTOMATIC_ADD]:
hass.helpers.dispatcher.async_dispatcher_connect(SIGNAL_EVENT, light_update) | 2,629,040,797,358,438,400 | Set up config entry. | homeassistant/components/rfxtrx/light.py | async_setup_entry | 1e1/core-1 | python | async def async_setup_entry(hass, config_entry, async_add_entities):
discovery_info = config_entry.data
device_ids = set()
def supported(event):
return (isinstance(event.device, rfxtrxmod.LightingDevice) and event.device.known_to_be_dimmable)
entities = []
for (packet_id, entity_info) in discovery_info[CONF_DEVICES].items():
event = get_rfx_object(packet_id)
if (event is None):
_LOGGER.error('Invalid device: %s', packet_id)
continue
if (not supported(event)):
continue
device_id = get_device_id(event.device, data_bits=entity_info.get(CONF_DATA_BITS))
if (device_id in device_ids):
continue
device_ids.add(device_id)
entity = RfxtrxLight(event.device, device_id, entity_info[CONF_SIGNAL_REPETITIONS])
entities.append(entity)
async_add_entities(entities)
@callback
def light_update(event, device_id):
'Handle light updates from the RFXtrx gateway.'
if (not supported(event)):
return
if (device_id in device_ids):
return
device_ids.add(device_id)
_LOGGER.info('Added light (Device ID: %s Class: %s Sub: %s, Event: %s)', event.device.id_string.lower(), event.device.__class__.__name__, event.device.subtype, .join((f'{x:02x}' for x in event.data)))
entity = RfxtrxLight(event.device, device_id, DEFAULT_SIGNAL_REPETITIONS, event=event)
async_add_entities([entity])
if discovery_info[CONF_AUTOMATIC_ADD]:
hass.helpers.dispatcher.async_dispatcher_connect(SIGNAL_EVENT, light_update) |
@callback
def light_update(event, device_id):
'Handle light updates from the RFXtrx gateway.'
if (not supported(event)):
return
if (device_id in device_ids):
return
device_ids.add(device_id)
_LOGGER.info('Added light (Device ID: %s Class: %s Sub: %s, Event: %s)', event.device.id_string.lower(), event.device.__class__.__name__, event.device.subtype, ''.join((f'{x:02x}' for x in event.data)))
entity = RfxtrxLight(event.device, device_id, DEFAULT_SIGNAL_REPETITIONS, event=event)
async_add_entities([entity]) | -5,317,690,462,523,536,000 | Handle light updates from the RFXtrx gateway. | homeassistant/components/rfxtrx/light.py | light_update | 1e1/core-1 | python | @callback
def light_update(event, device_id):
if (not supported(event)):
return
if (device_id in device_ids):
return
device_ids.add(device_id)
_LOGGER.info('Added light (Device ID: %s Class: %s Sub: %s, Event: %s)', event.device.id_string.lower(), event.device.__class__.__name__, event.device.subtype, .join((f'{x:02x}' for x in event.data)))
entity = RfxtrxLight(event.device, device_id, DEFAULT_SIGNAL_REPETITIONS, event=event)
async_add_entities([entity]) |
async def async_added_to_hass(self):
'Restore RFXtrx device state (ON/OFF).'
(await super().async_added_to_hass())
if (self._event is None):
old_state = (await self.async_get_last_state())
if (old_state is not None):
self._state = (old_state.state == STATE_ON)
self._brightness = old_state.attributes.get(ATTR_BRIGHTNESS) | 229,973,618,490,358,560 | Restore RFXtrx device state (ON/OFF). | homeassistant/components/rfxtrx/light.py | async_added_to_hass | 1e1/core-1 | python | async def async_added_to_hass(self):
(await super().async_added_to_hass())
if (self._event is None):
old_state = (await self.async_get_last_state())
if (old_state is not None):
self._state = (old_state.state == STATE_ON)
self._brightness = old_state.attributes.get(ATTR_BRIGHTNESS) |
@property
def brightness(self):
'Return the brightness of this light between 0..255.'
return self._brightness | -3,846,976,056,796,552,000 | Return the brightness of this light between 0..255. | homeassistant/components/rfxtrx/light.py | brightness | 1e1/core-1 | python | @property
def brightness(self):
return self._brightness |
@property
def supported_features(self):
'Flag supported features.'
return SUPPORT_RFXTRX | -5,159,653,584,670,436,000 | Flag supported features. | homeassistant/components/rfxtrx/light.py | supported_features | 1e1/core-1 | python | @property
def supported_features(self):
return SUPPORT_RFXTRX |
@property
def is_on(self):
'Return true if device is on.'
return self._state | -3,559,686,018,939,803,600 | Return true if device is on. | homeassistant/components/rfxtrx/light.py | is_on | 1e1/core-1 | python | @property
def is_on(self):
return self._state |
async def async_turn_on(self, **kwargs):
'Turn the device on.'
brightness = kwargs.get(ATTR_BRIGHTNESS)
self._state = True
if (brightness is None):
(await self._async_send(self._device.send_on))
self._brightness = 255
else:
(await self._async_send(self._device.send_dim, ((brightness * 100) // 255)))
self._brightness = brightness
self.async_write_ha_state() | -27,936,814,387,729,360 | Turn the device on. | homeassistant/components/rfxtrx/light.py | async_turn_on | 1e1/core-1 | python | async def async_turn_on(self, **kwargs):
brightness = kwargs.get(ATTR_BRIGHTNESS)
self._state = True
if (brightness is None):
(await self._async_send(self._device.send_on))
self._brightness = 255
else:
(await self._async_send(self._device.send_dim, ((brightness * 100) // 255)))
self._brightness = brightness
self.async_write_ha_state() |
async def async_turn_off(self, **kwargs):
'Turn the device off.'
(await self._async_send(self._device.send_off))
self._state = False
self._brightness = 0
self.async_write_ha_state() | -1,614,410,703,092,717,800 | Turn the device off. | homeassistant/components/rfxtrx/light.py | async_turn_off | 1e1/core-1 | python | async def async_turn_off(self, **kwargs):
(await self._async_send(self._device.send_off))
self._state = False
self._brightness = 0
self.async_write_ha_state() |
def _apply_event(self, event):
'Apply command from rfxtrx.'
super()._apply_event(event)
if (event.values['Command'] in COMMAND_ON_LIST):
self._state = True
elif (event.values['Command'] in COMMAND_OFF_LIST):
self._state = False
elif (event.values['Command'] == 'Set level'):
self._brightness = ((event.values['Dim level'] * 255) // 100)
self._state = (self._brightness > 0) | -4,045,686,276,709,932,500 | Apply command from rfxtrx. | homeassistant/components/rfxtrx/light.py | _apply_event | 1e1/core-1 | python | def _apply_event(self, event):
super()._apply_event(event)
if (event.values['Command'] in COMMAND_ON_LIST):
self._state = True
elif (event.values['Command'] in COMMAND_OFF_LIST):
self._state = False
elif (event.values['Command'] == 'Set level'):
self._brightness = ((event.values['Dim level'] * 255) // 100)
self._state = (self._brightness > 0) |
@callback
def _handle_event(self, event, device_id):
'Check if event applies to me and update.'
if (device_id != self._device_id):
return
self._apply_event(event)
self.async_write_ha_state() | 8,437,661,162,664,978,000 | Check if event applies to me and update. | homeassistant/components/rfxtrx/light.py | _handle_event | 1e1/core-1 | python | @callback
def _handle_event(self, event, device_id):
if (device_id != self._device_id):
return
self._apply_event(event)
self.async_write_ha_state() |
def test_api_pages_list_success(self):
'\n\t\tEnsure get request returns 200.\n\t\t'
response = self.client.get(reverse('page_list', kwargs={'language': 'nl'}))
self.assertEqual(response.status_code, status.HTTP_200_OK)
self.assertEqual(response.data['count'], 1) | 1,200,097,847,982,713,000 | Ensure get request returns 200. | bluebottle/pages/tests/test_api.py | test_api_pages_list_success | maykinmedia/bluebottle | python | def test_api_pages_list_success(self):
'\n\t\t\n\t\t'
response = self.client.get(reverse('page_list', kwargs={'language': 'nl'}))
self.assertEqual(response.status_code, status.HTTP_200_OK)
self.assertEqual(response.data['count'], 1) |
def test_api_pages_list_content(self):
'\n\t\tEnsure get request returns record with correct data.\n\t\t'
response = self.client.get(reverse('page_list', kwargs={'language': 'nl'}))
page = response.data['results'][0]
self.assertEqual(page['title'], self.page1.title)
self.assertEqual(page['language'], self.page1.language)
self.assertEqual(page['body'], "<!-- no items in placeholder 'blog_contents' -->")
self.assertEqual(page['full_page'], self.page1.full_page) | -4,210,556,589,173,268,000 | Ensure get request returns record with correct data. | bluebottle/pages/tests/test_api.py | test_api_pages_list_content | maykinmedia/bluebottle | python | def test_api_pages_list_content(self):
'\n\t\t\n\t\t'
response = self.client.get(reverse('page_list', kwargs={'language': 'nl'}))
page = response.data['results'][0]
self.assertEqual(page['title'], self.page1.title)
self.assertEqual(page['language'], self.page1.language)
self.assertEqual(page['body'], "<!-- no items in placeholder 'blog_contents' -->")
self.assertEqual(page['full_page'], self.page1.full_page) |
def test_api_pages_detail_content(self):
'\n\t\tEnsure get request returns record with correct data.\n\t\t'
response = self.client.get(reverse('page_detail', kwargs={'language': 'en', 'slug': self.page2.slug}))
results = response.data
self.assertEqual(results['title'], self.page2.title)
self.assertEqual(results['language'], self.page2.language)
self.assertEqual(results['body'], "<!-- no items in placeholder 'blog_contents' -->")
self.assertEqual(results['full_page'], self.page2.full_page) | 1,916,083,978,927,994,400 | Ensure get request returns record with correct data. | bluebottle/pages/tests/test_api.py | test_api_pages_detail_content | maykinmedia/bluebottle | python | def test_api_pages_detail_content(self):
'\n\t\t\n\t\t'
response = self.client.get(reverse('page_detail', kwargs={'language': 'en', 'slug': self.page2.slug}))
results = response.data
self.assertEqual(results['title'], self.page2.title)
self.assertEqual(results['language'], self.page2.language)
self.assertEqual(results['body'], "<!-- no items in placeholder 'blog_contents' -->")
self.assertEqual(results['full_page'], self.page2.full_page) |
def _update_project(self, request, data):
'Update project info'
domain_id = identity.get_domain_id_for_operation(request)
try:
project_id = data['project_id']
EXTRA_INFO = settings.PROJECT_TABLE_EXTRA_INFO
kwargs = dict(((key, data.get(key)) for key in EXTRA_INFO))
return api.keystone.tenant_update(request, project_id, name=data['name'], description=data['description'], enabled=data['enabled'], domain=domain_id, **kwargs)
except exceptions.Conflict:
msg = (_('Project name "%s" is already used.') % data['name'])
self.failure_message = msg
return
except Exception as e:
LOG.debug('Project update failed: %s', e)
exceptions.handle(request, ignore=True)
return | 753,130,235,582,491,000 | Update project info | openstack_dashboard/dashboards/identity/projects/workflows.py | _update_project | LinkleYping/horizon-vul | python | def _update_project(self, request, data):
domain_id = identity.get_domain_id_for_operation(request)
try:
project_id = data['project_id']
EXTRA_INFO = settings.PROJECT_TABLE_EXTRA_INFO
kwargs = dict(((key, data.get(key)) for key in EXTRA_INFO))
return api.keystone.tenant_update(request, project_id, name=data['name'], description=data['description'], enabled=data['enabled'], domain=domain_id, **kwargs)
except exceptions.Conflict:
msg = (_('Project name "%s" is already used.') % data['name'])
self.failure_message = msg
return
except Exception as e:
LOG.debug('Project update failed: %s', e)
exceptions.handle(request, ignore=True)
return |
def alphanum_key(s):
' Turn a string into a list of string and number chunks.\n "z23a" -> ["z", 23, "a"]\n '
return [tryInt(c) for c in re.split('([0-9]+)', s)] | 2,718,573,483,697,511,000 | Turn a string into a list of string and number chunks.
"z23a" -> ["z", 23, "a"] | firstsession/measurement/measure_program.py | alphanum_key | Saqqe/Cream | python | def alphanum_key(s):
' Turn a string into a list of string and number chunks.\n "z23a" -> ["z", 23, "a"]\n '
return [tryInt(c) for c in re.split('([0-9]+)', s)] |
def sort_nicely(l):
' Sort the given list in the way that humans expect.\n '
l.sort(key=alphanum_key) | 7,898,580,595,700,768,000 | Sort the given list in the way that humans expect. | firstsession/measurement/measure_program.py | sort_nicely | Saqqe/Cream | python | def sort_nicely(l):
' \n '
l.sort(key=alphanum_key) |
@app.route('/', methods=['POST', 'GET'])
def index():
'\n Default app index.\n '
return 'Please contact your System Administrator.' | 1,470,829,655,005,580,500 | Default app index. | views.py | index | ayushrusiya47/quiz-extensions | python | @app.route('/', methods=['POST', 'GET'])
def index():
'\n \n '
return 'Please contact your System Administrator.' |
@app.route('/status', methods=['GET'])
def status():
'\n Runs smoke tests and reports status\n '
try:
job_queue_length = len(q.jobs)
except ConnectionError:
job_queue_length = (- 1)
status = {'tool': 'Quiz Extensions', 'checks': {'index': False, 'xml': False, 'api_key': False, 'redis': False, 'db': False, 'worker': False}, 'url': url_for('index', _external=True), 'api_url': config.API_URL, 'debug': app.debug, 'xml_url': url_for('xml', _external=True), 'job_queue': job_queue_length}
try:
response = requests.get(url_for('index', _external=True), verify=False)
status['checks']['index'] = (response.text == 'Please contact your System Administrator.')
except Exception:
logger.exception('Index check failed.')
try:
response = requests.get(url_for('xml', _external=True), verify=False)
status['checks']['xml'] = ('application/xml' in response.headers.get('Content-Type'))
except Exception:
logger.exception('XML check failed.')
try:
response = requests.get('{}users/self'.format(config.API_URL), headers={'Authorization': ('Bearer ' + config.API_KEY)})
status['checks']['api_key'] = (response.status_code == 200)
except Exception:
logger.exception('API Key check failed.')
try:
response = conn.echo('test')
status['checks']['redis'] = (response == b'test')
except ConnectionError:
logger.exception('Redis connection failed.')
try:
db.session.query(text('1')).all()
status['checks']['db'] = True
except Exception:
logger.exception('DB connection failed.')
status['checks']['worker'] = (call('ps aux | grep "rq worker" | grep "quizext" | grep -v grep', shell=True) == 0)
status['healthy'] = all(((v is True) for (k, v) in status['checks'].items()))
return Response(json.dumps(status), mimetype='application/json') | 8,651,372,796,350,657,000 | Runs smoke tests and reports status | views.py | status | ayushrusiya47/quiz-extensions | python | @app.route('/status', methods=['GET'])
def status():
'\n \n '
try:
job_queue_length = len(q.jobs)
except ConnectionError:
job_queue_length = (- 1)
status = {'tool': 'Quiz Extensions', 'checks': {'index': False, 'xml': False, 'api_key': False, 'redis': False, 'db': False, 'worker': False}, 'url': url_for('index', _external=True), 'api_url': config.API_URL, 'debug': app.debug, 'xml_url': url_for('xml', _external=True), 'job_queue': job_queue_length}
try:
response = requests.get(url_for('index', _external=True), verify=False)
status['checks']['index'] = (response.text == 'Please contact your System Administrator.')
except Exception:
logger.exception('Index check failed.')
try:
response = requests.get(url_for('xml', _external=True), verify=False)
status['checks']['xml'] = ('application/xml' in response.headers.get('Content-Type'))
except Exception:
logger.exception('XML check failed.')
try:
response = requests.get('{}users/self'.format(config.API_URL), headers={'Authorization': ('Bearer ' + config.API_KEY)})
status['checks']['api_key'] = (response.status_code == 200)
except Exception:
logger.exception('API Key check failed.')
try:
response = conn.echo('test')
status['checks']['redis'] = (response == b'test')
except ConnectionError:
logger.exception('Redis connection failed.')
try:
db.session.query(text('1')).all()
status['checks']['db'] = True
except Exception:
logger.exception('DB connection failed.')
status['checks']['worker'] = (call('ps aux | grep "rq worker" | grep "quizext" | grep -v grep', shell=True) == 0)
status['healthy'] = all(((v is True) for (k, v) in status['checks'].items()))
return Response(json.dumps(status), mimetype='application/json') |
@app.route('/lti.xml', methods=['GET'])
def xml():
'\n Returns the lti.xml file for the app.\n '
from urllib.parse import urlparse
domain = urlparse(request.url_root).netloc
return Response(render_template('lti.xml', tool_id=config.LTI_TOOL_ID, domain=domain), mimetype='application/xml') | 4,551,775,549,191,905,000 | Returns the lti.xml file for the app. | views.py | xml | ayushrusiya47/quiz-extensions | python | @app.route('/lti.xml', methods=['GET'])
def xml():
'\n \n '
from urllib.parse import urlparse
domain = urlparse(request.url_root).netloc
return Response(render_template('lti.xml', tool_id=config.LTI_TOOL_ID, domain=domain), mimetype='application/xml') |
@app.route('/quiz/<course_id>/', methods=['GET'])
@check_valid_user
@lti(error=error, request='session', role='staff', app=app)
def quiz(lti=lti, course_id=None):
'\n Main landing page for the app.\n\n Displays a page to the user that allows them to select students\n to moderate quizzes for.\n '
return render_template('userselect.html', course_id=course_id, current_page_number=1) | -1,338,936,958,936,886,800 | Main landing page for the app.
Displays a page to the user that allows them to select students
to moderate quizzes for. | views.py | quiz | ayushrusiya47/quiz-extensions | python | @app.route('/quiz/<course_id>/', methods=['GET'])
@check_valid_user
@lti(error=error, request='session', role='staff', app=app)
def quiz(lti=lti, course_id=None):
'\n Main landing page for the app.\n\n Displays a page to the user that allows them to select students\n to moderate quizzes for.\n '
return render_template('userselect.html', course_id=course_id, current_page_number=1) |
@app.route('/refresh/<course_id>/', methods=['POST'])
def refresh(course_id=None):
'\n Creates a new `refresh_background` job.\n\n :param course_id: The Canvas ID of the Course.\n :type course_id: int\n :rtype: flask.Response\n :returns: A JSON-formatted response containing a url for the started job.\n '
job = q.enqueue_call(func=refresh_background, args=(course_id,))
return Response(json.dumps({'refresh_job_url': url_for('job_status', job_key=job.get_id())}), mimetype='application/json', status=202) | -9,084,823,866,377,085,000 | Creates a new `refresh_background` job.
:param course_id: The Canvas ID of the Course.
:type course_id: int
:rtype: flask.Response
:returns: A JSON-formatted response containing a url for the started job. | views.py | refresh | ayushrusiya47/quiz-extensions | python | @app.route('/refresh/<course_id>/', methods=['POST'])
def refresh(course_id=None):
'\n Creates a new `refresh_background` job.\n\n :param course_id: The Canvas ID of the Course.\n :type course_id: int\n :rtype: flask.Response\n :returns: A JSON-formatted response containing a url for the started job.\n '
job = q.enqueue_call(func=refresh_background, args=(course_id,))
return Response(json.dumps({'refresh_job_url': url_for('job_status', job_key=job.get_id())}), mimetype='application/json', status=202) |
@app.route('/update/<course_id>/', methods=['POST'])
@check_valid_user
@lti(error=error, request='session', role='staff', app=app)
def update(lti=lti, course_id=None):
'\n Creates a new `update_background` job.\n\n :param course_id: The Canvas ID of the Course.\n :type coruse_id: int\n :rtype: flask.Response\n :returns: A JSON-formatted response containing urls for the started jobs.\n '
refresh_job = q.enqueue_call(func=refresh_background, args=(course_id,))
update_job = q.enqueue_call(func=update_background, args=(course_id, request.get_json()), depends_on=refresh_job)
return Response(json.dumps({'refresh_job_url': url_for('job_status', job_key=refresh_job.get_id()), 'update_job_url': url_for('job_status', job_key=update_job.get_id())}), mimetype='application/json', status=202) | -8,826,940,118,246,629,000 | Creates a new `update_background` job.
:param course_id: The Canvas ID of the Course.
:type coruse_id: int
:rtype: flask.Response
:returns: A JSON-formatted response containing urls for the started jobs. | views.py | update | ayushrusiya47/quiz-extensions | python | @app.route('/update/<course_id>/', methods=['POST'])
@check_valid_user
@lti(error=error, request='session', role='staff', app=app)
def update(lti=lti, course_id=None):
'\n Creates a new `update_background` job.\n\n :param course_id: The Canvas ID of the Course.\n :type coruse_id: int\n :rtype: flask.Response\n :returns: A JSON-formatted response containing urls for the started jobs.\n '
refresh_job = q.enqueue_call(func=refresh_background, args=(course_id,))
update_job = q.enqueue_call(func=update_background, args=(course_id, request.get_json()), depends_on=refresh_job)
return Response(json.dumps({'refresh_job_url': url_for('job_status', job_key=refresh_job.get_id()), 'update_job_url': url_for('job_status', job_key=update_job.get_id())}), mimetype='application/json', status=202) |
def update_background(course_id, extension_dict):
"\n Update time on selected students' quizzes to a specified percentage.\n\n :param course_id: The Canvas ID of the Course to update in\n :type course_id: int\n :param extension_dict: A dictionary that includes the percent of\n time and a list of canvas user ids.\n\n Example:\n {\n 'percent': '300',\n 'user_ids': [\n '0123456',\n '1234567',\n '9867543',\n '5555555'\n ]\n }\n :type extension_dict: dict\n "
job = get_current_job()
update_job(job, 0, 'Starting...', 'started')
with app.app_context():
if (not extension_dict):
update_job(job, 0, 'Invalid Request', 'failed', error=True)
logger.warning('Invalid Request: {}'.format(extension_dict))
return job.meta
try:
course_json = get_course(course_id)
except requests.exceptions.HTTPError:
update_job(job, 0, 'Course not found.', 'failed', error=True)
logger.exception('Unable to find course #{}'.format(course_id))
return job.meta
course_name = course_json.get('name', '<UNNAMED COURSE>')
user_ids = extension_dict.get('user_ids', [])
percent = extension_dict.get('percent', None)
if (not percent):
update_job(job, 0, '`percent` field required.', 'failed', error=True)
logger.warning('Percent field not provided. Request: {}'.format(extension_dict))
return job.meta
(course, created) = get_or_create(db.session, Course, canvas_id=course_id)
course.course_name = course_name
db.session.commit()
for user_id in user_ids:
try:
canvas_user = get_user(course_id, user_id)
sortable_name = canvas_user.get('sortable_name', '<MISSING NAME>')
sis_id = canvas_user.get('sis_user_id')
except requests.exceptions.HTTPError:
logger.warning('Unable to find user #{} in course #{}'.format(user_id, course_id))
continue
(user, created) = get_or_create(db.session, User, canvas_id=user_id)
user.sortable_name = sortable_name
user.sis_id = sis_id
db.session.commit()
(extension, created) = get_or_create(db.session, Extension, course_id=course.id, user_id=user.id)
extension.percent = percent
db.session.commit()
quizzes = get_quizzes(course_id)
num_quizzes = len(quizzes)
quiz_time_list = []
unchanged_quiz_time_list = []
if (num_quizzes < 1):
update_job(job, 0, 'Sorry, there are no quizzes for this course.', 'failed', error=True)
logger.warning('No quizzes found for course {}. Unable to update.'.format(course_id))
return job.meta
for (index, quiz) in enumerate(quizzes):
quiz_id = quiz.get('id', None)
quiz_title = quiz.get('title', '[UNTITLED QUIZ]')
comp_perc = int(((float(index) / float(num_quizzes)) * 100))
updating_str = 'Updating quiz #{} - {} [{} of {}]'
update_job(job, comp_perc, updating_str.format(quiz_id, quiz_title, (index + 1), num_quizzes), 'processing', error=False)
extension_response = extend_quiz(course_id, quiz, percent, user_ids)
if (extension_response.get('success', False) is True):
(quiz_obj, created) = get_or_create(db.session, Quiz, canvas_id=quiz_id, course_id=course.id)
quiz_obj.title = quiz_title
quiz_obj.time_limit = quiz.get('time_limit')
db.session.commit()
added_time = extension_response.get('added_time', None)
if (added_time is not None):
quiz_time_list.append({'title': quiz_title, 'added_time': added_time})
else:
unchanged_quiz_time_list.append({'title': quiz_title})
else:
update_job(job, comp_perc, extension_response.get('message', 'An unknown error occured.'), 'failed', error=True)
logger.error('Extension failed: {}'.format(extension_response))
return job.meta
msg_str = 'Success! {} {} been updated for {} student(s) to have {}% time. {} {} no time limit and were left unchanged.'
message = msg_str.format(len(quiz_time_list), ('quizzes have' if (len(quiz_time_list) != 1) else 'quiz has'), len(user_ids), percent, len(unchanged_quiz_time_list), ('quizzes have' if (len(unchanged_quiz_time_list) != 1) else 'quiz has'))
update_job(job, 100, message, 'complete', error=False)
job.meta['quiz_list'] = quiz_time_list
job.meta['unchanged_list'] = unchanged_quiz_time_list
job.save()
return job.meta | -4,985,010,300,237,697,000 | Update time on selected students' quizzes to a specified percentage.
:param course_id: The Canvas ID of the Course to update in
:type course_id: int
:param extension_dict: A dictionary that includes the percent of
time and a list of canvas user ids.
Example:
{
'percent': '300',
'user_ids': [
'0123456',
'1234567',
'9867543',
'5555555'
]
}
:type extension_dict: dict | views.py | update_background | ayushrusiya47/quiz-extensions | python | def update_background(course_id, extension_dict):
"\n Update time on selected students' quizzes to a specified percentage.\n\n :param course_id: The Canvas ID of the Course to update in\n :type course_id: int\n :param extension_dict: A dictionary that includes the percent of\n time and a list of canvas user ids.\n\n Example:\n {\n 'percent': '300',\n 'user_ids': [\n '0123456',\n '1234567',\n '9867543',\n '5555555'\n ]\n }\n :type extension_dict: dict\n "
job = get_current_job()
update_job(job, 0, 'Starting...', 'started')
with app.app_context():
if (not extension_dict):
update_job(job, 0, 'Invalid Request', 'failed', error=True)
logger.warning('Invalid Request: {}'.format(extension_dict))
return job.meta
try:
course_json = get_course(course_id)
except requests.exceptions.HTTPError:
update_job(job, 0, 'Course not found.', 'failed', error=True)
logger.exception('Unable to find course #{}'.format(course_id))
return job.meta
course_name = course_json.get('name', '<UNNAMED COURSE>')
user_ids = extension_dict.get('user_ids', [])
percent = extension_dict.get('percent', None)
if (not percent):
update_job(job, 0, '`percent` field required.', 'failed', error=True)
logger.warning('Percent field not provided. Request: {}'.format(extension_dict))
return job.meta
(course, created) = get_or_create(db.session, Course, canvas_id=course_id)
course.course_name = course_name
db.session.commit()
for user_id in user_ids:
try:
canvas_user = get_user(course_id, user_id)
sortable_name = canvas_user.get('sortable_name', '<MISSING NAME>')
sis_id = canvas_user.get('sis_user_id')
except requests.exceptions.HTTPError:
logger.warning('Unable to find user #{} in course #{}'.format(user_id, course_id))
continue
(user, created) = get_or_create(db.session, User, canvas_id=user_id)
user.sortable_name = sortable_name
user.sis_id = sis_id
db.session.commit()
(extension, created) = get_or_create(db.session, Extension, course_id=course.id, user_id=user.id)
extension.percent = percent
db.session.commit()
quizzes = get_quizzes(course_id)
num_quizzes = len(quizzes)
quiz_time_list = []
unchanged_quiz_time_list = []
if (num_quizzes < 1):
update_job(job, 0, 'Sorry, there are no quizzes for this course.', 'failed', error=True)
logger.warning('No quizzes found for course {}. Unable to update.'.format(course_id))
return job.meta
for (index, quiz) in enumerate(quizzes):
quiz_id = quiz.get('id', None)
quiz_title = quiz.get('title', '[UNTITLED QUIZ]')
comp_perc = int(((float(index) / float(num_quizzes)) * 100))
updating_str = 'Updating quiz #{} - {} [{} of {}]'
update_job(job, comp_perc, updating_str.format(quiz_id, quiz_title, (index + 1), num_quizzes), 'processing', error=False)
extension_response = extend_quiz(course_id, quiz, percent, user_ids)
if (extension_response.get('success', False) is True):
(quiz_obj, created) = get_or_create(db.session, Quiz, canvas_id=quiz_id, course_id=course.id)
quiz_obj.title = quiz_title
quiz_obj.time_limit = quiz.get('time_limit')
db.session.commit()
added_time = extension_response.get('added_time', None)
if (added_time is not None):
quiz_time_list.append({'title': quiz_title, 'added_time': added_time})
else:
unchanged_quiz_time_list.append({'title': quiz_title})
else:
update_job(job, comp_perc, extension_response.get('message', 'An unknown error occured.'), 'failed', error=True)
logger.error('Extension failed: {}'.format(extension_response))
return job.meta
msg_str = 'Success! {} {} been updated for {} student(s) to have {}% time. {} {} no time limit and were left unchanged.'
message = msg_str.format(len(quiz_time_list), ('quizzes have' if (len(quiz_time_list) != 1) else 'quiz has'), len(user_ids), percent, len(unchanged_quiz_time_list), ('quizzes have' if (len(unchanged_quiz_time_list) != 1) else 'quiz has'))
update_job(job, 100, message, 'complete', error=False)
job.meta['quiz_list'] = quiz_time_list
job.meta['unchanged_list'] = unchanged_quiz_time_list
job.save()
return job.meta |
def refresh_background(course_id):
'\n Look up existing extensions and apply them to new quizzes.\n\n :param course_id: The Canvas ID of the Course.\n :type course_id: int\n :rtype: dict\n :returns: A dictionary containing two parts:\n\n - success `bool` False if there was an error, True otherwise.\n - message `str` A long description of success or failure.\n '
job = get_current_job()
update_job(job, 0, 'Starting...', 'started')
with app.app_context():
(course, created) = get_or_create(db.session, Course, canvas_id=course_id)
try:
course_name = get_course(course_id).get('name', '<UNNAMED COURSE>')
course.course_name = course_name
db.session.commit()
except requests.exceptions.HTTPError:
update_job(job, 0, 'Course not found.', 'failed', error=True)
logger.exception('Unable to find course #{}'.format(course_id))
return job.meta
quizzes = missing_and_stale_quizzes(course_id)
num_quizzes = len(quizzes)
if (num_quizzes < 1):
update_job(job, 100, 'Complete. No quizzes required updates.', 'complete', error=False)
return job.meta
percent_user_map = defaultdict(list)
inactive_list = []
update_job(job, 0, 'Getting past extensions.', 'processing', False)
for extension in course.extensions:
if (not extension.active):
inactive_list.append(extension.user.sortable_name)
logger.debug('Extension #{} is inactive.'.format(extension.id))
continue
user_canvas_id = User.query.filter_by(id=extension.user_id).first().canvas_id
try:
canvas_user = get_user(course_id, user_canvas_id)
enrolls = canvas_user.get('enrollments', [])
type_list = [e['type'] for e in enrolls if (e['enrollment_state'] == 'active')]
if (not any(((t == 'StudentEnrollment') for t in type_list))):
logger.info('User #{} was found in course #{}, but is not an active student. Deactivating extension #{}. Roles found: {}'.format(user_canvas_id, course_id, extension.id, (', '.join(type_list) if (len(enrolls) > 0) else None)))
extension.active = False
db.session.commit()
inactive_list.append(extension.user.sortable_name)
continue
except requests.exceptions.HTTPError:
log_str = 'User #{} not in course #{}. Deactivating extension #{}.'
logger.info(log_str.format(user_canvas_id, course_id, extension.id))
extension.active = False
db.session.commit()
inactive_list.append(extension.user.sortable_name)
continue
percent_user_map[extension.percent].append(user_canvas_id)
if (len(percent_user_map) < 1):
msg_str = 'No active extensions were found.<br>'
if (len(inactive_list) > 0):
msg_str += ' Extensions for the following students are inactive:<br>{}'
msg_str = msg_str.format('<br>'.join(inactive_list))
update_job(job, 100, msg_str, 'complete', error=False)
return job.meta
for (index, quiz) in enumerate(quizzes):
quiz_id = quiz.get('id', None)
quiz_title = quiz.get('title', '[UNTITLED QUIZ]')
comp_perc = int(((float(index) / float(num_quizzes)) * 100))
refreshing_str = 'Refreshing quiz #{} - {} [{} of {}]'
update_job(job, comp_perc, refreshing_str.format(quiz_id, quiz_title, (index + 1), num_quizzes), 'processing', error=False)
for (percent, user_list) in percent_user_map.items():
extension_response = extend_quiz(course_id, quiz, percent, user_list)
if (extension_response.get('success', False) is True):
(quiz_obj, created) = get_or_create(db.session, Quiz, canvas_id=quiz_id, course_id=course.id)
quiz_obj.title = quiz_title
quiz_obj.time_limit = quiz.get('time_limit')
db.session.commit()
else:
error_message = "Some quizzes couldn't be updated. "
error_message += extension_response.get('message', '')
update_job(job, comp_perc, error_message, 'failed', error=True)
return job.meta
msg = '{} quizzes have been updated.'.format(len(quizzes))
update_job(job, 100, msg, 'complete', error=False)
return job.meta | -606,887,113,193,659,500 | Look up existing extensions and apply them to new quizzes.
:param course_id: The Canvas ID of the Course.
:type course_id: int
:rtype: dict
:returns: A dictionary containing two parts:
- success `bool` False if there was an error, True otherwise.
- message `str` A long description of success or failure. | views.py | refresh_background | ayushrusiya47/quiz-extensions | python | def refresh_background(course_id):
'\n Look up existing extensions and apply them to new quizzes.\n\n :param course_id: The Canvas ID of the Course.\n :type course_id: int\n :rtype: dict\n :returns: A dictionary containing two parts:\n\n - success `bool` False if there was an error, True otherwise.\n - message `str` A long description of success or failure.\n '
job = get_current_job()
update_job(job, 0, 'Starting...', 'started')
with app.app_context():
(course, created) = get_or_create(db.session, Course, canvas_id=course_id)
try:
course_name = get_course(course_id).get('name', '<UNNAMED COURSE>')
course.course_name = course_name
db.session.commit()
except requests.exceptions.HTTPError:
update_job(job, 0, 'Course not found.', 'failed', error=True)
logger.exception('Unable to find course #{}'.format(course_id))
return job.meta
quizzes = missing_and_stale_quizzes(course_id)
num_quizzes = len(quizzes)
if (num_quizzes < 1):
update_job(job, 100, 'Complete. No quizzes required updates.', 'complete', error=False)
return job.meta
percent_user_map = defaultdict(list)
inactive_list = []
update_job(job, 0, 'Getting past extensions.', 'processing', False)
for extension in course.extensions:
if (not extension.active):
inactive_list.append(extension.user.sortable_name)
logger.debug('Extension #{} is inactive.'.format(extension.id))
continue
user_canvas_id = User.query.filter_by(id=extension.user_id).first().canvas_id
try:
canvas_user = get_user(course_id, user_canvas_id)
enrolls = canvas_user.get('enrollments', [])
type_list = [e['type'] for e in enrolls if (e['enrollment_state'] == 'active')]
if (not any(((t == 'StudentEnrollment') for t in type_list))):
logger.info('User #{} was found in course #{}, but is not an active student. Deactivating extension #{}. Roles found: {}'.format(user_canvas_id, course_id, extension.id, (', '.join(type_list) if (len(enrolls) > 0) else None)))
extension.active = False
db.session.commit()
inactive_list.append(extension.user.sortable_name)
continue
except requests.exceptions.HTTPError:
log_str = 'User #{} not in course #{}. Deactivating extension #{}.'
logger.info(log_str.format(user_canvas_id, course_id, extension.id))
extension.active = False
db.session.commit()
inactive_list.append(extension.user.sortable_name)
continue
percent_user_map[extension.percent].append(user_canvas_id)
if (len(percent_user_map) < 1):
msg_str = 'No active extensions were found.<br>'
if (len(inactive_list) > 0):
msg_str += ' Extensions for the following students are inactive:<br>{}'
msg_str = msg_str.format('<br>'.join(inactive_list))
update_job(job, 100, msg_str, 'complete', error=False)
return job.meta
for (index, quiz) in enumerate(quizzes):
quiz_id = quiz.get('id', None)
quiz_title = quiz.get('title', '[UNTITLED QUIZ]')
comp_perc = int(((float(index) / float(num_quizzes)) * 100))
refreshing_str = 'Refreshing quiz #{} - {} [{} of {}]'
update_job(job, comp_perc, refreshing_str.format(quiz_id, quiz_title, (index + 1), num_quizzes), 'processing', error=False)
for (percent, user_list) in percent_user_map.items():
extension_response = extend_quiz(course_id, quiz, percent, user_list)
if (extension_response.get('success', False) is True):
(quiz_obj, created) = get_or_create(db.session, Quiz, canvas_id=quiz_id, course_id=course.id)
quiz_obj.title = quiz_title
quiz_obj.time_limit = quiz.get('time_limit')
db.session.commit()
else:
error_message = "Some quizzes couldn't be updated. "
error_message += extension_response.get('message', )
update_job(job, comp_perc, error_message, 'failed', error=True)
return job.meta
msg = '{} quizzes have been updated.'.format(len(quizzes))
update_job(job, 100, msg, 'complete', error=False)
return job.meta |
@app.route('/missing_and_stale_quizzes/<course_id>/', methods=['GET'])
def missing_and_stale_quizzes_check(course_id):
'\n Check if there are missing quizzes.\n\n :param course_id: The Canvas ID of the Course.\n :type course_id: int\n :rtype: str\n :returns: A JSON-formatted string representation of a boolean.\n "true" if there are missing quizzes, "false" if there are not.\n '
course = Course.query.filter_by(canvas_id=course_id).first()
if (course is None):
return 'false'
num_extensions = Extension.query.filter_by(course_id=course.id).count()
if (num_extensions == 0):
return 'false'
missing = (len(missing_and_stale_quizzes(course_id, True)) > 0)
return json.dumps(missing) | -8,747,239,967,523,165,000 | Check if there are missing quizzes.
:param course_id: The Canvas ID of the Course.
:type course_id: int
:rtype: str
:returns: A JSON-formatted string representation of a boolean.
"true" if there are missing quizzes, "false" if there are not. | views.py | missing_and_stale_quizzes_check | ayushrusiya47/quiz-extensions | python | @app.route('/missing_and_stale_quizzes/<course_id>/', methods=['GET'])
def missing_and_stale_quizzes_check(course_id):
'\n Check if there are missing quizzes.\n\n :param course_id: The Canvas ID of the Course.\n :type course_id: int\n :rtype: str\n :returns: A JSON-formatted string representation of a boolean.\n "true" if there are missing quizzes, "false" if there are not.\n '
course = Course.query.filter_by(canvas_id=course_id).first()
if (course is None):
return 'false'
num_extensions = Extension.query.filter_by(course_id=course.id).count()
if (num_extensions == 0):
return 'false'
missing = (len(missing_and_stale_quizzes(course_id, True)) > 0)
return json.dumps(missing) |
@app.route('/filter/<course_id>/', methods=['GET'])
@check_valid_user
@lti(error=error, request='session', role='staff', app=app)
def filter(lti=lti, course_id=None):
'\n Display a filtered and paginated list of students in the course.\n\n :param course_id:\n :type: int\n :rtype: str\n :returns: A list of students in the course using the template\n user_list.html.\n '
query = request.args.get('query', '').lower()
page = int(request.args.get('page', 1))
per_page = int(request.args.get('per_page', config.DEFAULT_PER_PAGE))
(user_list, max_pages) = search_students(course_id, per_page=per_page, page=page, search_term=query)
if ((not user_list) or (max_pages < 1)):
user_list = []
max_pages = 1
return render_template('user_list.html', users=user_list, current_page_number=page, max_pages=max_pages) | -5,975,147,192,149,251,000 | Display a filtered and paginated list of students in the course.
:param course_id:
:type: int
:rtype: str
:returns: A list of students in the course using the template
user_list.html. | views.py | filter | ayushrusiya47/quiz-extensions | python | @app.route('/filter/<course_id>/', methods=['GET'])
@check_valid_user
@lti(error=error, request='session', role='staff', app=app)
def filter(lti=lti, course_id=None):
'\n Display a filtered and paginated list of students in the course.\n\n :param course_id:\n :type: int\n :rtype: str\n :returns: A list of students in the course using the template\n user_list.html.\n '
query = request.args.get('query', ).lower()
page = int(request.args.get('page', 1))
per_page = int(request.args.get('per_page', config.DEFAULT_PER_PAGE))
(user_list, max_pages) = search_students(course_id, per_page=per_page, page=page, search_term=query)
if ((not user_list) or (max_pages < 1)):
user_list = []
max_pages = 1
return render_template('user_list.html', users=user_list, current_page_number=page, max_pages=max_pages) |
@app.route('/launch', methods=['POST'])
@lti(error=error, request='initial', role='staff', app=app)
def lti_tool(lti=lti):
'\n Bootstrapper for lti.\n '
course_id = request.values.get('custom_canvas_course_id')
canvas_user_id = request.values.get('custom_canvas_user_id')
canvas_domain = request.values.get('custom_canvas_api_domain')
if (canvas_domain not in config.ALLOWED_CANVAS_DOMAINS):
msg = '<p>This tool is only available from the following domain(s):<br/>{}</p><p>You attempted to access from this domain:<br/>{}</p>'
return render_template('error.html', message=msg.format(', '.join(config.ALLOWED_CANVAS_DOMAINS), canvas_domain))
roles = request.values.get('roles', [])
session['is_admin'] = ('Administrator' in roles)
session['canvas_user_id'] = canvas_user_id
session['lti_logged_in'] = True
return redirect(url_for('quiz', course_id=course_id)) | 1,882,419,556,337,132,300 | Bootstrapper for lti. | views.py | lti_tool | ayushrusiya47/quiz-extensions | python | @app.route('/launch', methods=['POST'])
@lti(error=error, request='initial', role='staff', app=app)
def lti_tool(lti=lti):
'\n \n '
course_id = request.values.get('custom_canvas_course_id')
canvas_user_id = request.values.get('custom_canvas_user_id')
canvas_domain = request.values.get('custom_canvas_api_domain')
if (canvas_domain not in config.ALLOWED_CANVAS_DOMAINS):
msg = '<p>This tool is only available from the following domain(s):<br/>{}</p><p>You attempted to access from this domain:<br/>{}</p>'
return render_template('error.html', message=msg.format(', '.join(config.ALLOWED_CANVAS_DOMAINS), canvas_domain))
roles = request.values.get('roles', [])
session['is_admin'] = ('Administrator' in roles)
session['canvas_user_id'] = canvas_user_id
session['lti_logged_in'] = True
return redirect(url_for('quiz', course_id=course_id)) |
@wraps(f)
def decorated_function(*args, **kwargs):
'\n Decorator to check if the user is allowed access to the app.\n If user is allowed, return the decorated function.\n Otherwise, return an error page with corresponding message.\n '
canvas_user_id = session.get('canvas_user_id')
lti_logged_in = session.get('lti_logged_in', False)
if ((not lti_logged_in) or (not canvas_user_id)):
return render_template('error.html', message='Not allowed!')
if ('course_id' not in kwargs.keys()):
return render_template('error.html', message='No course_id provided.')
course_id = int(kwargs.get('course_id'))
if (not session.get('is_admin', False)):
enrollments_url = '{}courses/{}/enrollments'.format(config.API_URL, course_id)
payload = {'user_id': canvas_user_id, 'type': ['TeacherEnrollment', 'TaEnrollment', 'DesignerEnrollment']}
user_enrollments_response = requests.get(enrollments_url, data=json.dumps(payload), headers=json_headers)
user_enrollments = user_enrollments_response.json()
if ((not user_enrollments) or ('errors' in user_enrollments)):
message = 'You are not enrolled in this course as a Teacher, TA, or Designer.'
return render_template('error.html', message=message)
return f(*args, **kwargs) | -1,688,540,081,320,270,000 | Decorator to check if the user is allowed access to the app.
If user is allowed, return the decorated function.
Otherwise, return an error page with corresponding message. | views.py | decorated_function | ayushrusiya47/quiz-extensions | python | @wraps(f)
def decorated_function(*args, **kwargs):
'\n Decorator to check if the user is allowed access to the app.\n If user is allowed, return the decorated function.\n Otherwise, return an error page with corresponding message.\n '
canvas_user_id = session.get('canvas_user_id')
lti_logged_in = session.get('lti_logged_in', False)
if ((not lti_logged_in) or (not canvas_user_id)):
return render_template('error.html', message='Not allowed!')
if ('course_id' not in kwargs.keys()):
return render_template('error.html', message='No course_id provided.')
course_id = int(kwargs.get('course_id'))
if (not session.get('is_admin', False)):
enrollments_url = '{}courses/{}/enrollments'.format(config.API_URL, course_id)
payload = {'user_id': canvas_user_id, 'type': ['TeacherEnrollment', 'TaEnrollment', 'DesignerEnrollment']}
user_enrollments_response = requests.get(enrollments_url, data=json.dumps(payload), headers=json_headers)
user_enrollments = user_enrollments_response.json()
if ((not user_enrollments) or ('errors' in user_enrollments)):
message = 'You are not enrolled in this course as a Teacher, TA, or Designer.'
return render_template('error.html', message=message)
return f(*args, **kwargs) |
def deferToThreadPool(reactor, threadpool, f, *args, **kwargs):
"\n Call the function C{f} using a thread from the given threadpool and return\n the result as a Deferred.\n\n This function is only used by client code which is maintaining its own\n threadpool. To run a function in the reactor's threadpool, use\n C{deferToThread}.\n\n @param reactor: The reactor in whose main thread the Deferred will be\n invoked.\n\n @param threadpool: An object which supports the C{callInThreadWithCallback}\n method of C{twisted.python.threadpool.ThreadPool}.\n\n @param f: The function to call.\n @param *args: positional arguments to pass to f.\n @param **kwargs: keyword arguments to pass to f.\n\n @return: A Deferred which fires a callback with the result of f, or an\n errback with a L{twisted.python.failure.Failure} if f throws an\n exception.\n "
d = defer.Deferred()
def onResult(success, result):
if success:
reactor.callFromThread(d.callback, result)
else:
reactor.callFromThread(d.errback, result)
threadpool.callInThreadWithCallback(onResult, f, *args, **kwargs)
return d | 4,905,041,117,132,150,000 | Call the function C{f} using a thread from the given threadpool and return
the result as a Deferred.
This function is only used by client code which is maintaining its own
threadpool. To run a function in the reactor's threadpool, use
C{deferToThread}.
@param reactor: The reactor in whose main thread the Deferred will be
invoked.
@param threadpool: An object which supports the C{callInThreadWithCallback}
method of C{twisted.python.threadpool.ThreadPool}.
@param f: The function to call.
@param *args: positional arguments to pass to f.
@param **kwargs: keyword arguments to pass to f.
@return: A Deferred which fires a callback with the result of f, or an
errback with a L{twisted.python.failure.Failure} if f throws an
exception. | src/twisted/internet/threads.py | deferToThreadPool | adamtheturtle/twisted | python | def deferToThreadPool(reactor, threadpool, f, *args, **kwargs):
"\n Call the function C{f} using a thread from the given threadpool and return\n the result as a Deferred.\n\n This function is only used by client code which is maintaining its own\n threadpool. To run a function in the reactor's threadpool, use\n C{deferToThread}.\n\n @param reactor: The reactor in whose main thread the Deferred will be\n invoked.\n\n @param threadpool: An object which supports the C{callInThreadWithCallback}\n method of C{twisted.python.threadpool.ThreadPool}.\n\n @param f: The function to call.\n @param *args: positional arguments to pass to f.\n @param **kwargs: keyword arguments to pass to f.\n\n @return: A Deferred which fires a callback with the result of f, or an\n errback with a L{twisted.python.failure.Failure} if f throws an\n exception.\n "
d = defer.Deferred()
def onResult(success, result):
if success:
reactor.callFromThread(d.callback, result)
else:
reactor.callFromThread(d.errback, result)
threadpool.callInThreadWithCallback(onResult, f, *args, **kwargs)
return d |
def deferToThread(f, *args, **kwargs):
'\n Run a function in a thread and return the result as a Deferred.\n\n @param f: The function to call.\n @param *args: positional arguments to pass to f.\n @param **kwargs: keyword arguments to pass to f.\n\n @return: A Deferred which fires a callback with the result of f,\n or an errback with a L{twisted.python.failure.Failure} if f throws\n an exception.\n '
from twisted.internet import reactor
return deferToThreadPool(reactor, reactor.getThreadPool(), f, *args, **kwargs) | 6,221,264,868,728,162,000 | Run a function in a thread and return the result as a Deferred.
@param f: The function to call.
@param *args: positional arguments to pass to f.
@param **kwargs: keyword arguments to pass to f.
@return: A Deferred which fires a callback with the result of f,
or an errback with a L{twisted.python.failure.Failure} if f throws
an exception. | src/twisted/internet/threads.py | deferToThread | adamtheturtle/twisted | python | def deferToThread(f, *args, **kwargs):
'\n Run a function in a thread and return the result as a Deferred.\n\n @param f: The function to call.\n @param *args: positional arguments to pass to f.\n @param **kwargs: keyword arguments to pass to f.\n\n @return: A Deferred which fires a callback with the result of f,\n or an errback with a L{twisted.python.failure.Failure} if f throws\n an exception.\n '
from twisted.internet import reactor
return deferToThreadPool(reactor, reactor.getThreadPool(), f, *args, **kwargs) |
def _runMultiple(tupleList):
'\n Run a list of functions.\n '
for (f, args, kwargs) in tupleList:
f(*args, **kwargs) | 5,765,581,595,930,412,000 | Run a list of functions. | src/twisted/internet/threads.py | _runMultiple | adamtheturtle/twisted | python | def _runMultiple(tupleList):
'\n \n '
for (f, args, kwargs) in tupleList:
f(*args, **kwargs) |
def callMultipleInThread(tupleList):
'\n Run a list of functions in the same thread.\n\n tupleList should be a list of (function, argsList, kwargsDict) tuples.\n '
from twisted.internet import reactor
reactor.callInThread(_runMultiple, tupleList) | -7,280,785,097,039,103,000 | Run a list of functions in the same thread.
tupleList should be a list of (function, argsList, kwargsDict) tuples. | src/twisted/internet/threads.py | callMultipleInThread | adamtheturtle/twisted | python | def callMultipleInThread(tupleList):
'\n Run a list of functions in the same thread.\n\n tupleList should be a list of (function, argsList, kwargsDict) tuples.\n '
from twisted.internet import reactor
reactor.callInThread(_runMultiple, tupleList) |
def blockingCallFromThread(reactor, f, *a, **kw):
"\n Run a function in the reactor from a thread, and wait for the result\n synchronously. If the function returns a L{Deferred}, wait for its\n result and return that.\n\n @param reactor: The L{IReactorThreads} provider which will be used to\n schedule the function call.\n @param f: the callable to run in the reactor thread\n @type f: any callable.\n @param a: the arguments to pass to C{f}.\n @param kw: the keyword arguments to pass to C{f}.\n\n @return: the result of the L{Deferred} returned by C{f}, or the result\n of C{f} if it returns anything other than a L{Deferred}.\n\n @raise: If C{f} raises a synchronous exception,\n C{blockingCallFromThread} will raise that exception. If C{f}\n returns a L{Deferred} which fires with a L{Failure},\n C{blockingCallFromThread} will raise that failure's exception (see\n L{Failure.raiseException}).\n "
queue = Queue.Queue()
def _callFromThread():
result = defer.maybeDeferred(f, *a, **kw)
result.addBoth(queue.put)
reactor.callFromThread(_callFromThread)
result = queue.get()
if isinstance(result, failure.Failure):
result.raiseException()
return result | -6,062,473,800,116,598,000 | Run a function in the reactor from a thread, and wait for the result
synchronously. If the function returns a L{Deferred}, wait for its
result and return that.
@param reactor: The L{IReactorThreads} provider which will be used to
schedule the function call.
@param f: the callable to run in the reactor thread
@type f: any callable.
@param a: the arguments to pass to C{f}.
@param kw: the keyword arguments to pass to C{f}.
@return: the result of the L{Deferred} returned by C{f}, or the result
of C{f} if it returns anything other than a L{Deferred}.
@raise: If C{f} raises a synchronous exception,
C{blockingCallFromThread} will raise that exception. If C{f}
returns a L{Deferred} which fires with a L{Failure},
C{blockingCallFromThread} will raise that failure's exception (see
L{Failure.raiseException}). | src/twisted/internet/threads.py | blockingCallFromThread | adamtheturtle/twisted | python | def blockingCallFromThread(reactor, f, *a, **kw):
"\n Run a function in the reactor from a thread, and wait for the result\n synchronously. If the function returns a L{Deferred}, wait for its\n result and return that.\n\n @param reactor: The L{IReactorThreads} provider which will be used to\n schedule the function call.\n @param f: the callable to run in the reactor thread\n @type f: any callable.\n @param a: the arguments to pass to C{f}.\n @param kw: the keyword arguments to pass to C{f}.\n\n @return: the result of the L{Deferred} returned by C{f}, or the result\n of C{f} if it returns anything other than a L{Deferred}.\n\n @raise: If C{f} raises a synchronous exception,\n C{blockingCallFromThread} will raise that exception. If C{f}\n returns a L{Deferred} which fires with a L{Failure},\n C{blockingCallFromThread} will raise that failure's exception (see\n L{Failure.raiseException}).\n "
queue = Queue.Queue()
def _callFromThread():
result = defer.maybeDeferred(f, *a, **kw)
result.addBoth(queue.put)
reactor.callFromThread(_callFromThread)
result = queue.get()
if isinstance(result, failure.Failure):
result.raiseException()
return result |
def read_tle_file(tlefile, **kwargs):
'\n \n Read in a TLE file and return the TLE that is closest to the date you want to\n propagate the orbit to.\n '
times = []
line1 = []
line2 = []
from os import path
from datetime import datetime
try:
f = open(tlefile, 'r')
except FileNotFoundError:
print(('Unable to open: ' + tlefile))
ln = 0
for line in f:
if (ln == 0):
year = int(line[18:20])
day = int(line[20:23])
times.extend([datetime.strptime('{}:{}'.format(year, day), '%y:%j')])
line1.extend([line.strip()])
ln = 1
else:
ln = 0
line2.extend([line.strip()])
f.close()
return (times, line1, line2) | 8,202,728,023,310,814,000 | Read in a TLE file and return the TLE that is closest to the date you want to
propagate the orbit to. | nustar_lunar_pointing/tracking.py | read_tle_file | bwgref/nustar_lunar_pointing | python | def read_tle_file(tlefile, **kwargs):
'\n \n Read in a TLE file and return the TLE that is closest to the date you want to\n propagate the orbit to.\n '
times = []
line1 = []
line2 = []
from os import path
from datetime import datetime
try:
f = open(tlefile, 'r')
except FileNotFoundError:
print(('Unable to open: ' + tlefile))
ln = 0
for line in f:
if (ln == 0):
year = int(line[18:20])
day = int(line[20:23])
times.extend([datetime.strptime('{}:{}'.format(year, day), '%y:%j')])
line1.extend([line.strip()])
ln = 1
else:
ln = 0
line2.extend([line.strip()])
f.close()
return (times, line1, line2) |
def get_epoch_tle(epoch, tlefile):
'\n \n Find the TLE that is closest to the epoch you want to search.\n \n epoch is a datetime object, tlefile is the file you want to search through.\n \n '
(times, line1, line2) = read_tle_file(tlefile)
from datetime import datetime
from astropy.time import Time
if (type(epoch) is Time):
epoch = epoch.datetime
mindt = 100.0
min_ind = 0
for (ind, t) in enumerate(times):
dt = abs((epoch - t).days)
if (dt < mindt):
min_ind = ind
mindt = dt
good_line1 = line1[min_ind]
good_line2 = line2[min_ind]
return (mindt, good_line1, good_line2) | -7,966,222,560,800,649,000 | Find the TLE that is closest to the epoch you want to search.
epoch is a datetime object, tlefile is the file you want to search through. | nustar_lunar_pointing/tracking.py | get_epoch_tle | bwgref/nustar_lunar_pointing | python | def get_epoch_tle(epoch, tlefile):
'\n \n Find the TLE that is closest to the epoch you want to search.\n \n epoch is a datetime object, tlefile is the file you want to search through.\n \n '
(times, line1, line2) = read_tle_file(tlefile)
from datetime import datetime
from astropy.time import Time
if (type(epoch) is Time):
epoch = epoch.datetime
mindt = 100.0
min_ind = 0
for (ind, t) in enumerate(times):
dt = abs((epoch - t).days)
if (dt < mindt):
min_ind = ind
mindt = dt
good_line1 = line1[min_ind]
good_line2 = line2[min_ind]
return (mindt, good_line1, good_line2) |
def convert_nustar_time(t, leap=5):
' \n \n Converts MET seconds to a datetime object.\n \n Default is to subtract off 5 leap seconds.\n\n '
import astropy.units as u
mjdref = (55197 * u.d)
met = (((t - leap) * u.s) + mjdref)
met_datetime = Time(met.to(u.d), format='mjd').datetime
return met_datetime | 1,218,465,157,810,114,300 | Converts MET seconds to a datetime object.
Default is to subtract off 5 leap seconds. | nustar_lunar_pointing/tracking.py | convert_nustar_time | bwgref/nustar_lunar_pointing | python | def convert_nustar_time(t, leap=5):
' \n \n Converts MET seconds to a datetime object.\n \n Default is to subtract off 5 leap seconds.\n\n '
import astropy.units as u
mjdref = (55197 * u.d)
met = (((t - leap) * u.s) + mjdref)
met_datetime = Time(met.to(u.d), format='mjd').datetime
return met_datetime |
def get_nustar_location(checktime, line1, line2):
' \n \n Code to determine the spacecraft location from the TLE.\n \n Inputs are a datetime object and the two lines of the TLE you want to use.\n \n Returns a tuple that has the X, Y, and Z geocentric coordinates (in km).\n \n '
from sgp4.earth_gravity import wgs72
from sgp4.io import twoline2rv
from astropy.coordinates import EarthLocation
satellite = twoline2rv(line1, line2, wgs72)
(position, velocity) = satellite.propagate(checktime.year, checktime.month, checktime.day, checktime.hour, checktime.minute, checktime.second)
return position | 167,206,073,857,276,930 | Code to determine the spacecraft location from the TLE.
Inputs are a datetime object and the two lines of the TLE you want to use.
Returns a tuple that has the X, Y, and Z geocentric coordinates (in km). | nustar_lunar_pointing/tracking.py | get_nustar_location | bwgref/nustar_lunar_pointing | python | def get_nustar_location(checktime, line1, line2):
' \n \n Code to determine the spacecraft location from the TLE.\n \n Inputs are a datetime object and the two lines of the TLE you want to use.\n \n Returns a tuple that has the X, Y, and Z geocentric coordinates (in km).\n \n '
from sgp4.earth_gravity import wgs72
from sgp4.io import twoline2rv
from astropy.coordinates import EarthLocation
satellite = twoline2rv(line1, line2, wgs72)
(position, velocity) = satellite.propagate(checktime.year, checktime.month, checktime.day, checktime.hour, checktime.minute, checktime.second)
return position |
def eci2el(x, y, z, dt):
'\n Convert Earth-Centered Inertial (ECI) cartesian coordinates to ITRS for astropy EarthLocation object.\n\n Inputs :\n x = ECI X-coordinate \n y = ECI Y-coordinate \n z = ECI Z-coordinate \n dt = UTC time (datetime object)\n '
from astropy.coordinates import GCRS, ITRS, EarthLocation, CartesianRepresentation
import astropy.units as u
tt = Time(dt, format='datetime')
gcrs = GCRS(CartesianRepresentation(x=x, y=y, z=z), obstime=tt)
itrs = gcrs.transform_to(ITRS(obstime=tt))
el = EarthLocation.from_geocentric(itrs.x, itrs.y, itrs.z)
return el | 339,705,923,134,611,260 | Convert Earth-Centered Inertial (ECI) cartesian coordinates to ITRS for astropy EarthLocation object.
Inputs :
x = ECI X-coordinate
y = ECI Y-coordinate
z = ECI Z-coordinate
dt = UTC time (datetime object) | nustar_lunar_pointing/tracking.py | eci2el | bwgref/nustar_lunar_pointing | python | def eci2el(x, y, z, dt):
'\n Convert Earth-Centered Inertial (ECI) cartesian coordinates to ITRS for astropy EarthLocation object.\n\n Inputs :\n x = ECI X-coordinate \n y = ECI Y-coordinate \n z = ECI Z-coordinate \n dt = UTC time (datetime object)\n '
from astropy.coordinates import GCRS, ITRS, EarthLocation, CartesianRepresentation
import astropy.units as u
tt = Time(dt, format='datetime')
gcrs = GCRS(CartesianRepresentation(x=x, y=y, z=z), obstime=tt)
itrs = gcrs.transform_to(ITRS(obstime=tt))
el = EarthLocation.from_geocentric(itrs.x, itrs.y, itrs.z)
return el |
def get_moon_j2000(epoch, line1, line2, position=None):
'\n \n Code to determine the apparent J2000 position for a given\n time and at a given position for the observatory.\n \n epoch needs to be a datetime or Time object.\n \n position is a list/tuple of X/Y/Z positions\n \n '
from astropy.time import Time
from astropy.coordinates import get_moon, EarthLocation
import astropy.units as u
import sys
from datetime import datetime
if (type(epoch) is Time):
epoch = epoch.datetime
if (position is None):
position = get_nustar_location(epoch, line1, line2)
t = Time(epoch)
loc = eci2el(*(position * u.km), t)
moon_coords = get_moon(t, loc)
(ra_moon, dec_moon) = ((moon_coords.ra.degree * u.deg), (moon_coords.dec.degree * u.deg))
return (ra_moon, dec_moon) | 6,202,994,355,039,850,000 | Code to determine the apparent J2000 position for a given
time and at a given position for the observatory.
epoch needs to be a datetime or Time object.
position is a list/tuple of X/Y/Z positions | nustar_lunar_pointing/tracking.py | get_moon_j2000 | bwgref/nustar_lunar_pointing | python | def get_moon_j2000(epoch, line1, line2, position=None):
'\n \n Code to determine the apparent J2000 position for a given\n time and at a given position for the observatory.\n \n epoch needs to be a datetime or Time object.\n \n position is a list/tuple of X/Y/Z positions\n \n '
from astropy.time import Time
from astropy.coordinates import get_moon, EarthLocation
import astropy.units as u
import sys
from datetime import datetime
if (type(epoch) is Time):
epoch = epoch.datetime
if (position is None):
position = get_nustar_location(epoch, line1, line2)
t = Time(epoch)
loc = eci2el(*(position * u.km), t)
moon_coords = get_moon(t, loc)
(ra_moon, dec_moon) = ((moon_coords.ra.degree * u.deg), (moon_coords.dec.degree * u.deg))
return (ra_moon, dec_moon) |
def __init__(self, form, context, *args, **kwargs):
'\n Dynamically add each of the form fields for the given form model\n instance and its related field model instances.\n '
self.form = form
self.form_fields = form.fields.visible()
initial = kwargs.pop('initial', {})
field_entries = {}
if kwargs.get('instance'):
for field_entry in kwargs['instance'].fields.all():
field_entries[field_entry.field_id] = field_entry.value
super(FormForForm, self).__init__(*args, **kwargs)
for field in self.form_fields:
field_key = ('field_%s' % field.id)
field_class = fields.CLASSES[field.field_type]
field_widget = fields.WIDGETS.get(field.field_type)
field_args = {'label': field.label, 'required': field.required, 'help_text': field.help_text}
if (field.required and (not field.help_text)):
field_args['help_text'] = _('required')
arg_names = field_class.__init__.__code__.co_varnames
if ('max_length' in arg_names):
field_args['max_length'] = settings.FORMS_FIELD_MAX_LENGTH
if ('choices' in arg_names):
choices = list(field.get_choices())
if ((field.field_type == fields.SELECT) and (field.default not in [c[0] for c in choices])):
choices.insert(0, ('', field.placeholder_text))
field_args['choices'] = choices
if (field_widget is not None):
field_args['widget'] = field_widget
initial_val = None
try:
initial_val = field_entries[field.id]
except KeyError:
try:
initial_val = initial[field_key]
except KeyError:
initial_val = Template(field.default).render(context)
if initial_val:
if field.is_a(*fields.MULTIPLE):
initial_val = split_choices(initial_val)
elif (field.field_type == fields.CHECKBOX):
initial_val = (initial_val != 'False')
self.initial[field_key] = initial_val
self.fields[field_key] = field_class(**field_args)
if (field.field_type == fields.DOB):
_now = datetime.now()
years = list(range(_now.year, (_now.year - 120), (- 1)))
self.fields[field_key].widget.years = years
setattr(self.fields[field_key], 'type', field_class.__name__.lower())
if (field.required and settings.FORMS_USE_HTML5 and (field.field_type != fields.CHECKBOX_MULTIPLE)):
self.fields[field_key].widget.attrs['required'] = ''
if (field.placeholder_text and (not field.default)):
text = field.placeholder_text
self.fields[field_key].widget.attrs['placeholder'] = text | 827,790,042,888,069,000 | Dynamically add each of the form fields for the given form model
instance and its related field model instances. | zhiliao/forms/forms.py | __init__ | gladgod/zhiliao | python | def __init__(self, form, context, *args, **kwargs):
'\n Dynamically add each of the form fields for the given form model\n instance and its related field model instances.\n '
self.form = form
self.form_fields = form.fields.visible()
initial = kwargs.pop('initial', {})
field_entries = {}
if kwargs.get('instance'):
for field_entry in kwargs['instance'].fields.all():
field_entries[field_entry.field_id] = field_entry.value
super(FormForForm, self).__init__(*args, **kwargs)
for field in self.form_fields:
field_key = ('field_%s' % field.id)
field_class = fields.CLASSES[field.field_type]
field_widget = fields.WIDGETS.get(field.field_type)
field_args = {'label': field.label, 'required': field.required, 'help_text': field.help_text}
if (field.required and (not field.help_text)):
field_args['help_text'] = _('required')
arg_names = field_class.__init__.__code__.co_varnames
if ('max_length' in arg_names):
field_args['max_length'] = settings.FORMS_FIELD_MAX_LENGTH
if ('choices' in arg_names):
choices = list(field.get_choices())
if ((field.field_type == fields.SELECT) and (field.default not in [c[0] for c in choices])):
choices.insert(0, (, field.placeholder_text))
field_args['choices'] = choices
if (field_widget is not None):
field_args['widget'] = field_widget
initial_val = None
try:
initial_val = field_entries[field.id]
except KeyError:
try:
initial_val = initial[field_key]
except KeyError:
initial_val = Template(field.default).render(context)
if initial_val:
if field.is_a(*fields.MULTIPLE):
initial_val = split_choices(initial_val)
elif (field.field_type == fields.CHECKBOX):
initial_val = (initial_val != 'False')
self.initial[field_key] = initial_val
self.fields[field_key] = field_class(**field_args)
if (field.field_type == fields.DOB):
_now = datetime.now()
years = list(range(_now.year, (_now.year - 120), (- 1)))
self.fields[field_key].widget.years = years
setattr(self.fields[field_key], 'type', field_class.__name__.lower())
if (field.required and settings.FORMS_USE_HTML5 and (field.field_type != fields.CHECKBOX_MULTIPLE)):
self.fields[field_key].widget.attrs['required'] =
if (field.placeholder_text and (not field.default)):
text = field.placeholder_text
self.fields[field_key].widget.attrs['placeholder'] = text |
def save(self, **kwargs):
'\n Create a ``FormEntry`` instance and related ``FieldEntry``\n instances for each form field.\n '
entry = super(FormForForm, self).save(commit=False)
entry.form = self.form
entry.entry_time = now()
entry.save()
entry_fields = entry.fields.values_list('field_id', flat=True)
new_entry_fields = []
for field in self.form_fields:
field_key = ('field_%s' % field.id)
value = self.cleaned_data[field_key]
if (value and self.fields[field_key].widget.needs_multipart_form):
value = fs.save(join('forms', str(uuid4()), value.name), value)
if isinstance(value, list):
value = ', '.join([v.strip() for v in value])
if (field.id in entry_fields):
field_entry = entry.fields.get(field_id=field.id)
field_entry.value = value
field_entry.save()
else:
new = {'entry': entry, 'field_id': field.id, 'value': value}
new_entry_fields.append(FieldEntry(**new))
if new_entry_fields:
FieldEntry.objects.bulk_create(new_entry_fields)
return entry | -4,948,100,640,383,101,000 | Create a ``FormEntry`` instance and related ``FieldEntry``
instances for each form field. | zhiliao/forms/forms.py | save | gladgod/zhiliao | python | def save(self, **kwargs):
'\n Create a ``FormEntry`` instance and related ``FieldEntry``\n instances for each form field.\n '
entry = super(FormForForm, self).save(commit=False)
entry.form = self.form
entry.entry_time = now()
entry.save()
entry_fields = entry.fields.values_list('field_id', flat=True)
new_entry_fields = []
for field in self.form_fields:
field_key = ('field_%s' % field.id)
value = self.cleaned_data[field_key]
if (value and self.fields[field_key].widget.needs_multipart_form):
value = fs.save(join('forms', str(uuid4()), value.name), value)
if isinstance(value, list):
value = ', '.join([v.strip() for v in value])
if (field.id in entry_fields):
field_entry = entry.fields.get(field_id=field.id)
field_entry.value = value
field_entry.save()
else:
new = {'entry': entry, 'field_id': field.id, 'value': value}
new_entry_fields.append(FieldEntry(**new))
if new_entry_fields:
FieldEntry.objects.bulk_create(new_entry_fields)
return entry |
def email_to(self):
'\n Return the value entered for the first field of type\n ``forms.fields.EMAIL``.\n '
for field in self.form_fields:
if field.is_a(fields.EMAIL):
return self.cleaned_data[('field_%s' % field.id)]
return None | -6,057,552,900,015,576,000 | Return the value entered for the first field of type
``forms.fields.EMAIL``. | zhiliao/forms/forms.py | email_to | gladgod/zhiliao | python | def email_to(self):
'\n Return the value entered for the first field of type\n ``forms.fields.EMAIL``.\n '
for field in self.form_fields:
if field.is_a(fields.EMAIL):
return self.cleaned_data[('field_%s' % field.id)]
return None |
def __init__(self, form, request, *args, **kwargs):
'\n Iterate through the fields of the ``forms.models.Form`` instance and\n create the form fields required to control including the field in\n the export (with a checkbox) or filtering the field which differs\n across field types. User a list of checkboxes when a fixed set of\n choices can be chosen from, a pair of date fields for date ranges,\n and for all other types provide a textbox for text search.\n '
self.form = form
self.request = request
self.form_fields = form.fields.all()
self.entry_time_name = str(FormEntry._meta.get_field('entry_time').verbose_name)
super(EntriesForm, self).__init__(*args, **kwargs)
for field in self.form_fields:
field_key = ('field_%s' % field.id)
self.fields[('%s_export' % field_key)] = forms.BooleanField(label=field.label, initial=True, required=False)
if field.is_a(*fields.CHOICES):
if field.is_a(fields.CHECKBOX):
choices = ((True, _('Checked')), (False, _('Not checked')))
else:
choices = field.get_choices()
contains_field = forms.MultipleChoiceField(label=' ', choices=choices, widget=forms.CheckboxSelectMultiple(), required=False)
self.fields[('%s_filter' % field_key)] = choice_filter_field
self.fields[('%s_contains' % field_key)] = contains_field
elif field.is_a(*fields.MULTIPLE):
contains_field = forms.MultipleChoiceField(label=' ', choices=field.get_choices(), widget=forms.CheckboxSelectMultiple(), required=False)
self.fields[('%s_filter' % field_key)] = multiple_filter_field
self.fields[('%s_contains' % field_key)] = contains_field
elif field.is_a(*fields.DATES):
self.fields[('%s_filter' % field_key)] = date_filter_field
self.fields[('%s_from' % field_key)] = forms.DateField(label=' ', widget=SelectDateWidget(), required=False)
self.fields[('%s_to' % field_key)] = forms.DateField(label=_('and'), widget=SelectDateWidget(), required=False)
else:
contains_field = forms.CharField(label=' ', required=False)
self.fields[('%s_filter' % field_key)] = text_filter_field
self.fields[('%s_contains' % field_key)] = contains_field
field_key = 'field_0'
self.fields[('%s_export' % field_key)] = forms.BooleanField(initial=True, label=FormEntry._meta.get_field('entry_time').verbose_name, required=False)
self.fields[('%s_filter' % field_key)] = date_filter_field
self.fields[('%s_from' % field_key)] = forms.DateField(label=' ', widget=SelectDateWidget(), required=False)
self.fields[('%s_to' % field_key)] = forms.DateField(label=_('and'), widget=SelectDateWidget(), required=False) | -7,674,941,775,648,542,000 | Iterate through the fields of the ``forms.models.Form`` instance and
create the form fields required to control including the field in
the export (with a checkbox) or filtering the field which differs
across field types. User a list of checkboxes when a fixed set of
choices can be chosen from, a pair of date fields for date ranges,
and for all other types provide a textbox for text search. | zhiliao/forms/forms.py | __init__ | gladgod/zhiliao | python | def __init__(self, form, request, *args, **kwargs):
'\n Iterate through the fields of the ``forms.models.Form`` instance and\n create the form fields required to control including the field in\n the export (with a checkbox) or filtering the field which differs\n across field types. User a list of checkboxes when a fixed set of\n choices can be chosen from, a pair of date fields for date ranges,\n and for all other types provide a textbox for text search.\n '
self.form = form
self.request = request
self.form_fields = form.fields.all()
self.entry_time_name = str(FormEntry._meta.get_field('entry_time').verbose_name)
super(EntriesForm, self).__init__(*args, **kwargs)
for field in self.form_fields:
field_key = ('field_%s' % field.id)
self.fields[('%s_export' % field_key)] = forms.BooleanField(label=field.label, initial=True, required=False)
if field.is_a(*fields.CHOICES):
if field.is_a(fields.CHECKBOX):
choices = ((True, _('Checked')), (False, _('Not checked')))
else:
choices = field.get_choices()
contains_field = forms.MultipleChoiceField(label=' ', choices=choices, widget=forms.CheckboxSelectMultiple(), required=False)
self.fields[('%s_filter' % field_key)] = choice_filter_field
self.fields[('%s_contains' % field_key)] = contains_field
elif field.is_a(*fields.MULTIPLE):
contains_field = forms.MultipleChoiceField(label=' ', choices=field.get_choices(), widget=forms.CheckboxSelectMultiple(), required=False)
self.fields[('%s_filter' % field_key)] = multiple_filter_field
self.fields[('%s_contains' % field_key)] = contains_field
elif field.is_a(*fields.DATES):
self.fields[('%s_filter' % field_key)] = date_filter_field
self.fields[('%s_from' % field_key)] = forms.DateField(label=' ', widget=SelectDateWidget(), required=False)
self.fields[('%s_to' % field_key)] = forms.DateField(label=_('and'), widget=SelectDateWidget(), required=False)
else:
contains_field = forms.CharField(label=' ', required=False)
self.fields[('%s_filter' % field_key)] = text_filter_field
self.fields[('%s_contains' % field_key)] = contains_field
field_key = 'field_0'
self.fields[('%s_export' % field_key)] = forms.BooleanField(initial=True, label=FormEntry._meta.get_field('entry_time').verbose_name, required=False)
self.fields[('%s_filter' % field_key)] = date_filter_field
self.fields[('%s_from' % field_key)] = forms.DateField(label=' ', widget=SelectDateWidget(), required=False)
self.fields[('%s_to' % field_key)] = forms.DateField(label=_('and'), widget=SelectDateWidget(), required=False) |
def __iter__(self):
'\n Yield pairs of include checkbox / filters for each field.\n '
for field_id in ([f.id for f in self.form_fields] + [0]):
prefix = ('field_%s_' % field_id)
fields = [f for f in super(EntriesForm, self).__iter__() if f.name.startswith(prefix)]
(yield (fields[0], fields[1], fields[2:])) | 1,984,044,150,900,896,500 | Yield pairs of include checkbox / filters for each field. | zhiliao/forms/forms.py | __iter__ | gladgod/zhiliao | python | def __iter__(self):
'\n \n '
for field_id in ([f.id for f in self.form_fields] + [0]):
prefix = ('field_%s_' % field_id)
fields = [f for f in super(EntriesForm, self).__iter__() if f.name.startswith(prefix)]
(yield (fields[0], fields[1], fields[2:])) |
def columns(self):
'\n Returns the list of selected column names.\n '
fields = [f.label for f in self.form_fields if self.cleaned_data[('field_%s_export' % f.id)]]
if self.cleaned_data['field_0_export']:
fields.append(self.entry_time_name)
return fields | 2,414,668,977,055,500,000 | Returns the list of selected column names. | zhiliao/forms/forms.py | columns | gladgod/zhiliao | python | def columns(self):
'\n \n '
fields = [f.label for f in self.form_fields if self.cleaned_data[('field_%s_export' % f.id)]]
if self.cleaned_data['field_0_export']:
fields.append(self.entry_time_name)
return fields |
def rows(self, csv=False):
'\n Returns each row based on the selected criteria.\n '
field_indexes = {}
file_field_ids = []
date_field_ids = []
for field in self.form_fields:
if self.cleaned_data[('field_%s_export' % field.id)]:
field_indexes[field.id] = len(field_indexes)
if field.is_a(fields.FILE):
file_field_ids.append(field.id)
elif field.is_a(*fields.DATES):
date_field_ids.append(field.id)
num_columns = len(field_indexes)
include_entry_time = self.cleaned_data['field_0_export']
if include_entry_time:
num_columns += 1
field_entries = FieldEntry.objects.filter(entry__form=self.form).order_by('-entry__id').select_related('entry')
if (self.cleaned_data['field_0_filter'] == FILTER_CHOICE_BETWEEN):
time_from = self.cleaned_data['field_0_from']
time_to = self.cleaned_data['field_0_to']
if (time_from and time_to):
field_entries = field_entries.filter(entry__entry_time__range=(time_from, time_to))
current_entry = None
current_row = None
valid_row = True
for field_entry in field_entries:
if (field_entry.entry_id != current_entry):
if (valid_row and (current_row is not None)):
if (not csv):
current_row.insert(0, current_entry)
(yield current_row)
current_entry = field_entry.entry_id
current_row = ([''] * num_columns)
valid_row = True
if include_entry_time:
current_row[(- 1)] = field_entry.entry.entry_time
field_value = (field_entry.value or '')
field_id = field_entry.field_id
filter_type = self.cleaned_data.get(('field_%s_filter' % field_id))
filter_args = None
if filter_type:
if (filter_type == FILTER_CHOICE_BETWEEN):
(f, t) = (('field_%s_from' % field_id), ('field_%s_to' % field_id))
filter_args = [self.cleaned_data[f], self.cleaned_data[t]]
else:
field_name = ('field_%s_contains' % field_id)
filter_args = self.cleaned_data[field_name]
if filter_args:
filter_args = [filter_args]
if filter_args:
if (field_id in date_field_ids):
(y, m, d) = field_value.split(' ')[0].split('-')
dte = date(int(y), int(m), int(d))
filter_args.append(dte)
else:
filter_args.append(field_value)
filter_func = FILTER_FUNCS[filter_type]
if (not filter_func(*filter_args)):
valid_row = False
if (field_entry.value and (field_id in file_field_ids)):
url = reverse('admin:form_file', args=(field_entry.id,))
field_value = self.request.build_absolute_uri(url)
if (not csv):
parts = (field_value, split(field_entry.value)[1])
field_value = mark_safe(('<a href="%s">%s</a>' % parts))
try:
current_row[field_indexes[field_id]] = field_value
except KeyError:
pass
if (valid_row and (current_row is not None)):
if (not csv):
current_row.insert(0, current_entry)
(yield current_row) | 6,989,815,682,023,497,000 | Returns each row based on the selected criteria. | zhiliao/forms/forms.py | rows | gladgod/zhiliao | python | def rows(self, csv=False):
'\n \n '
field_indexes = {}
file_field_ids = []
date_field_ids = []
for field in self.form_fields:
if self.cleaned_data[('field_%s_export' % field.id)]:
field_indexes[field.id] = len(field_indexes)
if field.is_a(fields.FILE):
file_field_ids.append(field.id)
elif field.is_a(*fields.DATES):
date_field_ids.append(field.id)
num_columns = len(field_indexes)
include_entry_time = self.cleaned_data['field_0_export']
if include_entry_time:
num_columns += 1
field_entries = FieldEntry.objects.filter(entry__form=self.form).order_by('-entry__id').select_related('entry')
if (self.cleaned_data['field_0_filter'] == FILTER_CHOICE_BETWEEN):
time_from = self.cleaned_data['field_0_from']
time_to = self.cleaned_data['field_0_to']
if (time_from and time_to):
field_entries = field_entries.filter(entry__entry_time__range=(time_from, time_to))
current_entry = None
current_row = None
valid_row = True
for field_entry in field_entries:
if (field_entry.entry_id != current_entry):
if (valid_row and (current_row is not None)):
if (not csv):
current_row.insert(0, current_entry)
(yield current_row)
current_entry = field_entry.entry_id
current_row = ([] * num_columns)
valid_row = True
if include_entry_time:
current_row[(- 1)] = field_entry.entry.entry_time
field_value = (field_entry.value or )
field_id = field_entry.field_id
filter_type = self.cleaned_data.get(('field_%s_filter' % field_id))
filter_args = None
if filter_type:
if (filter_type == FILTER_CHOICE_BETWEEN):
(f, t) = (('field_%s_from' % field_id), ('field_%s_to' % field_id))
filter_args = [self.cleaned_data[f], self.cleaned_data[t]]
else:
field_name = ('field_%s_contains' % field_id)
filter_args = self.cleaned_data[field_name]
if filter_args:
filter_args = [filter_args]
if filter_args:
if (field_id in date_field_ids):
(y, m, d) = field_value.split(' ')[0].split('-')
dte = date(int(y), int(m), int(d))
filter_args.append(dte)
else:
filter_args.append(field_value)
filter_func = FILTER_FUNCS[filter_type]
if (not filter_func(*filter_args)):
valid_row = False
if (field_entry.value and (field_id in file_field_ids)):
url = reverse('admin:form_file', args=(field_entry.id,))
field_value = self.request.build_absolute_uri(url)
if (not csv):
parts = (field_value, split(field_entry.value)[1])
field_value = mark_safe(('<a href="%s">%s</a>' % parts))
try:
current_row[field_indexes[field_id]] = field_value
except KeyError:
pass
if (valid_row and (current_row is not None)):
if (not csv):
current_row.insert(0, current_entry)
(yield current_row) |
def check_line_match(self, index, stripped, data_rows):
'Find lines matching stripped from lineMatchKeys and set value to immediately following row'
for (key, value) in self.lineMatches.items():
if (stripped == key):
next_row = data_rows[(index + 1)]
if next_row.find_all('b'):
print('Next row was bold element: {0}. Skipping...'.format(next_row))
return False
next_row_stripped = next_row.text.strip()
if (next_row_stripped in self.lineMatches):
print('Next row was {0} and is in lineMatchKeys, skipping...'.format(next_row_stripped))
return False
self.attribute_dictionary[value] = json.dumps(next_row_stripped)
print('Set {0} to {1}'.format(value, self.attribute_dictionary[value]))
del self.lineMatches[key]
return True
return False | 7,381,854,148,757,062,000 | Find lines matching stripped from lineMatchKeys and set value to immediately following row | DataObjects.py | check_line_match | ataboo/CalloutScrape | python | def check_line_match(self, index, stripped, data_rows):
for (key, value) in self.lineMatches.items():
if (stripped == key):
next_row = data_rows[(index + 1)]
if next_row.find_all('b'):
print('Next row was bold element: {0}. Skipping...'.format(next_row))
return False
next_row_stripped = next_row.text.strip()
if (next_row_stripped in self.lineMatches):
print('Next row was {0} and is in lineMatchKeys, skipping...'.format(next_row_stripped))
return False
self.attribute_dictionary[value] = json.dumps(next_row_stripped)
print('Set {0} to {1}'.format(value, self.attribute_dictionary[value]))
del self.lineMatches[key]
return True
return False |
def __init__(self, app_id=None, state=None, x_request_id=None):
'StopAppResponse - a model defined in huaweicloud sdk'
super(StopAppResponse, self).__init__()
self._app_id = None
self._state = None
self._x_request_id = None
self.discriminator = None
if (app_id is not None):
self.app_id = app_id
if (state is not None):
self.state = state
if (x_request_id is not None):
self.x_request_id = x_request_id | 7,441,684,750,325,065,000 | StopAppResponse - a model defined in huaweicloud sdk | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | __init__ | huaweicloud/huaweicloud-sdk-python-v3 | python | def __init__(self, app_id=None, state=None, x_request_id=None):
super(StopAppResponse, self).__init__()
self._app_id = None
self._state = None
self._x_request_id = None
self.discriminator = None
if (app_id is not None):
self.app_id = app_id
if (state is not None):
self.state = state
if (x_request_id is not None):
self.x_request_id = x_request_id |
@property
def app_id(self):
'Gets the app_id of this StopAppResponse.\n\n 应用id\n\n :return: The app_id of this StopAppResponse.\n :rtype: str\n '
return self._app_id | 8,293,203,077,026,026,000 | Gets the app_id of this StopAppResponse.
应用id
:return: The app_id of this StopAppResponse.
:rtype: str | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | app_id | huaweicloud/huaweicloud-sdk-python-v3 | python | @property
def app_id(self):
'Gets the app_id of this StopAppResponse.\n\n 应用id\n\n :return: The app_id of this StopAppResponse.\n :rtype: str\n '
return self._app_id |
@app_id.setter
def app_id(self, app_id):
'Sets the app_id of this StopAppResponse.\n\n 应用id\n\n :param app_id: The app_id of this StopAppResponse.\n :type: str\n '
self._app_id = app_id | -5,006,926,596,443,253,000 | Sets the app_id of this StopAppResponse.
应用id
:param app_id: The app_id of this StopAppResponse.
:type: str | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | app_id | huaweicloud/huaweicloud-sdk-python-v3 | python | @app_id.setter
def app_id(self, app_id):
'Sets the app_id of this StopAppResponse.\n\n 应用id\n\n :param app_id: The app_id of this StopAppResponse.\n :type: str\n '
self._app_id = app_id |
@property
def state(self):
'Gets the state of this StopAppResponse.\n\n\n :return: The state of this StopAppResponse.\n :rtype: AppState\n '
return self._state | 8,748,824,888,664,394,000 | Gets the state of this StopAppResponse.
:return: The state of this StopAppResponse.
:rtype: AppState | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | state | huaweicloud/huaweicloud-sdk-python-v3 | python | @property
def state(self):
'Gets the state of this StopAppResponse.\n\n\n :return: The state of this StopAppResponse.\n :rtype: AppState\n '
return self._state |
@state.setter
def state(self, state):
'Sets the state of this StopAppResponse.\n\n\n :param state: The state of this StopAppResponse.\n :type: AppState\n '
self._state = state | 4,817,263,328,804,627,000 | Sets the state of this StopAppResponse.
:param state: The state of this StopAppResponse.
:type: AppState | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | state | huaweicloud/huaweicloud-sdk-python-v3 | python | @state.setter
def state(self, state):
'Sets the state of this StopAppResponse.\n\n\n :param state: The state of this StopAppResponse.\n :type: AppState\n '
self._state = state |
@property
def x_request_id(self):
'Gets the x_request_id of this StopAppResponse.\n\n\n :return: The x_request_id of this StopAppResponse.\n :rtype: str\n '
return self._x_request_id | -72,288,185,045,706,720 | Gets the x_request_id of this StopAppResponse.
:return: The x_request_id of this StopAppResponse.
:rtype: str | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | x_request_id | huaweicloud/huaweicloud-sdk-python-v3 | python | @property
def x_request_id(self):
'Gets the x_request_id of this StopAppResponse.\n\n\n :return: The x_request_id of this StopAppResponse.\n :rtype: str\n '
return self._x_request_id |
@x_request_id.setter
def x_request_id(self, x_request_id):
'Sets the x_request_id of this StopAppResponse.\n\n\n :param x_request_id: The x_request_id of this StopAppResponse.\n :type: str\n '
self._x_request_id = x_request_id | -4,375,000,343,484,576,000 | Sets the x_request_id of this StopAppResponse.
:param x_request_id: The x_request_id of this StopAppResponse.
:type: str | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | x_request_id | huaweicloud/huaweicloud-sdk-python-v3 | python | @x_request_id.setter
def x_request_id(self, x_request_id):
'Sets the x_request_id of this StopAppResponse.\n\n\n :param x_request_id: The x_request_id of this StopAppResponse.\n :type: str\n '
self._x_request_id = x_request_id |
def to_dict(self):
'Returns the model properties as a dict'
result = {}
for (attr, _) in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
elif (attr in self.sensitive_list):
result[attr] = '****'
else:
result[attr] = value
return result | 2,594,216,033,120,720,000 | Returns the model properties as a dict | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | to_dict | huaweicloud/huaweicloud-sdk-python-v3 | python | def to_dict(self):
result = {}
for (attr, _) in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
elif (attr in self.sensitive_list):
result[attr] = '****'
else:
result[attr] = value
return result |
def to_str(self):
'Returns the string representation of the model'
import simplejson as json
if six.PY2:
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
return json.dumps(sanitize_for_serialization(self), ensure_ascii=False) | -6,095,553,759,700,562,000 | Returns the string representation of the model | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | to_str | huaweicloud/huaweicloud-sdk-python-v3 | python | def to_str(self):
import simplejson as json
if six.PY2:
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
return json.dumps(sanitize_for_serialization(self), ensure_ascii=False) |
def __repr__(self):
'For `print`'
return self.to_str() | -1,581,176,371,750,213,000 | For `print` | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | __repr__ | huaweicloud/huaweicloud-sdk-python-v3 | python | def __repr__(self):
return self.to_str() |
def __eq__(self, other):
'Returns true if both objects are equal'
if (not isinstance(other, StopAppResponse)):
return False
return (self.__dict__ == other.__dict__) | 2,557,606,281,473,039,000 | Returns true if both objects are equal | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | __eq__ | huaweicloud/huaweicloud-sdk-python-v3 | python | def __eq__(self, other):
if (not isinstance(other, StopAppResponse)):
return False
return (self.__dict__ == other.__dict__) |
def __ne__(self, other):
'Returns true if both objects are not equal'
return (not (self == other)) | 7,764,124,047,908,058,000 | Returns true if both objects are not equal | huaweicloud-sdk-cloudrtc/huaweicloudsdkcloudrtc/v2/model/stop_app_response.py | __ne__ | huaweicloud/huaweicloud-sdk-python-v3 | python | def __ne__(self, other):
return (not (self == other)) |
def _expand_name(name):
'Replaces common shorthands with respective full names.\n\n "tf.xxx" --> "tensorflow.xxx"\n "tx.xxx" --> "texar.tf.xxx"\n '
return name | 8,329,032,541,764,644,000 | Replaces common shorthands with respective full names.
"tf.xxx" --> "tensorflow.xxx"
"tx.xxx" --> "texar.tf.xxx" | texar/tf/utils/utils.py | _expand_name | awesomemachinelearning/texar | python | def _expand_name(name):
'Replaces common shorthands with respective full names.\n\n "tf.xxx" --> "tensorflow.xxx"\n "tx.xxx" --> "texar.tf.xxx"\n '
return name |
def _inspect_getargspec(fn):
'Returns `inspect.getargspec(fn)` for Py2 and `inspect.getfullargspec(fn)`\n for Py3\n '
try:
return inspect.getfullargspec(fn)
except AttributeError:
try:
return inspect.getargspec(fn)
except TypeError:
return inspect.getargspec(fn.__call__) | -8,735,037,290,325,360,000 | Returns `inspect.getargspec(fn)` for Py2 and `inspect.getfullargspec(fn)`
for Py3 | texar/tf/utils/utils.py | _inspect_getargspec | awesomemachinelearning/texar | python | def _inspect_getargspec(fn):
'Returns `inspect.getargspec(fn)` for Py2 and `inspect.getfullargspec(fn)`\n for Py3\n '
try:
return inspect.getfullargspec(fn)
except AttributeError:
try:
return inspect.getargspec(fn)
except TypeError:
return inspect.getargspec(fn.__call__) |
def get_args(fn):
'Gets the arguments of a function.\n\n Args:\n fn (callable): The function to inspect.\n\n Returns:\n list: A list of argument names (str) of the function.\n '
argspec = _inspect_getargspec(fn)
args = argspec.args
if (len(args) == 0):
args = funcsigs.signature(fn).parameters.keys()
args = list(args)
return args | -8,241,205,280,697,680,000 | Gets the arguments of a function.
Args:
fn (callable): The function to inspect.
Returns:
list: A list of argument names (str) of the function. | texar/tf/utils/utils.py | get_args | awesomemachinelearning/texar | python | def get_args(fn):
'Gets the arguments of a function.\n\n Args:\n fn (callable): The function to inspect.\n\n Returns:\n list: A list of argument names (str) of the function.\n '
argspec = _inspect_getargspec(fn)
args = argspec.args
if (len(args) == 0):
args = funcsigs.signature(fn).parameters.keys()
args = list(args)
return args |
def get_default_arg_values(fn):
'Gets the arguments and respective default values of a function.\n\n Only arguments with default values are included in the output dictionary.\n\n Args:\n fn (callable): The function to inspect.\n\n Returns:\n dict: A dictionary that maps argument names (str) to their default\n values. The dictionary is empty if no arguments have default values.\n '
argspec = _inspect_getargspec(fn)
if (argspec.defaults is None):
return {}
num_defaults = len(argspec.defaults)
return dict(zip(argspec.args[(- num_defaults):], argspec.defaults)) | 3,098,645,701,942,710,000 | Gets the arguments and respective default values of a function.
Only arguments with default values are included in the output dictionary.
Args:
fn (callable): The function to inspect.
Returns:
dict: A dictionary that maps argument names (str) to their default
values. The dictionary is empty if no arguments have default values. | texar/tf/utils/utils.py | get_default_arg_values | awesomemachinelearning/texar | python | def get_default_arg_values(fn):
'Gets the arguments and respective default values of a function.\n\n Only arguments with default values are included in the output dictionary.\n\n Args:\n fn (callable): The function to inspect.\n\n Returns:\n dict: A dictionary that maps argument names (str) to their default\n values. The dictionary is empty if no arguments have default values.\n '
argspec = _inspect_getargspec(fn)
if (argspec.defaults is None):
return {}
num_defaults = len(argspec.defaults)
return dict(zip(argspec.args[(- num_defaults):], argspec.defaults)) |
def check_or_get_class(class_or_name, module_path=None, superclass=None):
'Returns the class and checks if the class inherits :attr:`superclass`.\n\n Args:\n class_or_name: Name or full path to the class, or the class itself.\n module_paths (list, optional): Paths to candidate modules to search\n for the class. This is used if :attr:`class_or_name` is a string and\n the class cannot be located solely based on :attr:`class_or_name`.\n The first module in the list that contains the class\n is used.\n superclass (optional): A (list of) classes that the target class\n must inherit.\n\n Returns:\n The target class.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_or_name` and\n :attr:`module_paths`.\n TypeError: If class does not inherits :attr:`superclass`.\n '
class_ = class_or_name
if is_str(class_):
class_ = get_class(class_, module_path)
if (superclass is not None):
if (not issubclass(class_, superclass)):
raise TypeError('A subclass of {} is expected. Got: {}'.format(superclass, class_))
return class_ | 7,885,878,717,375,071,000 | Returns the class and checks if the class inherits :attr:`superclass`.
Args:
class_or_name: Name or full path to the class, or the class itself.
module_paths (list, optional): Paths to candidate modules to search
for the class. This is used if :attr:`class_or_name` is a string and
the class cannot be located solely based on :attr:`class_or_name`.
The first module in the list that contains the class
is used.
superclass (optional): A (list of) classes that the target class
must inherit.
Returns:
The target class.
Raises:
ValueError: If class is not found based on :attr:`class_or_name` and
:attr:`module_paths`.
TypeError: If class does not inherits :attr:`superclass`. | texar/tf/utils/utils.py | check_or_get_class | awesomemachinelearning/texar | python | def check_or_get_class(class_or_name, module_path=None, superclass=None):
'Returns the class and checks if the class inherits :attr:`superclass`.\n\n Args:\n class_or_name: Name or full path to the class, or the class itself.\n module_paths (list, optional): Paths to candidate modules to search\n for the class. This is used if :attr:`class_or_name` is a string and\n the class cannot be located solely based on :attr:`class_or_name`.\n The first module in the list that contains the class\n is used.\n superclass (optional): A (list of) classes that the target class\n must inherit.\n\n Returns:\n The target class.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_or_name` and\n :attr:`module_paths`.\n TypeError: If class does not inherits :attr:`superclass`.\n '
class_ = class_or_name
if is_str(class_):
class_ = get_class(class_, module_path)
if (superclass is not None):
if (not issubclass(class_, superclass)):
raise TypeError('A subclass of {} is expected. Got: {}'.format(superclass, class_))
return class_ |
def get_class(class_name, module_paths=None):
'Returns the class based on class name.\n\n Args:\n class_name (str): Name or full path to the class.\n module_paths (list): Paths to candidate modules to search for the\n class. This is used if the class cannot be located solely based on\n `class_name`. The first module in the list that contains the class\n is used.\n\n Returns:\n The target class.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_name` and\n :attr:`module_paths`.\n '
class_ = locate(class_name)
if ((class_ is None) and (module_paths is not None)):
for module_path in module_paths:
class_ = locate('.'.join([module_path, class_name]))
if (class_ is not None):
break
if (class_ is None):
raise ValueError('Class not found in {}: {}'.format(module_paths, class_name))
return class_ | 2,376,394,911,442,920,000 | Returns the class based on class name.
Args:
class_name (str): Name or full path to the class.
module_paths (list): Paths to candidate modules to search for the
class. This is used if the class cannot be located solely based on
`class_name`. The first module in the list that contains the class
is used.
Returns:
The target class.
Raises:
ValueError: If class is not found based on :attr:`class_name` and
:attr:`module_paths`. | texar/tf/utils/utils.py | get_class | awesomemachinelearning/texar | python | def get_class(class_name, module_paths=None):
'Returns the class based on class name.\n\n Args:\n class_name (str): Name or full path to the class.\n module_paths (list): Paths to candidate modules to search for the\n class. This is used if the class cannot be located solely based on\n `class_name`. The first module in the list that contains the class\n is used.\n\n Returns:\n The target class.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_name` and\n :attr:`module_paths`.\n '
class_ = locate(class_name)
if ((class_ is None) and (module_paths is not None)):
for module_path in module_paths:
class_ = locate('.'.join([module_path, class_name]))
if (class_ is not None):
break
if (class_ is None):
raise ValueError('Class not found in {}: {}'.format(module_paths, class_name))
return class_ |
def check_or_get_instance(ins_or_class_or_name, kwargs, module_paths=None, classtype=None):
'Returns a class instance and checks types.\n\n Args:\n ins_or_class_or_name: Can be of 3 types:\n\n - A class to instantiate.\n - A string of the name or full path to a class to instantiate.\n - The class instance to check types.\n\n kwargs (dict): Keyword arguments for the class constructor. Ignored\n if `ins_or_class_or_name` is a class instance.\n module_paths (list, optional): Paths to candidate modules to\n search for the class. This is used if the class cannot be\n located solely based on :attr:`class_name`. The first module\n in the list that contains the class is used.\n classtype (optional): A (list of) class of which the instance must\n be an instantiation.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_name` and\n :attr:`module_paths`.\n ValueError: If :attr:`kwargs` contains arguments that are invalid\n for the class construction.\n TypeError: If the instance is not an instantiation of\n :attr:`classtype`.\n '
ret = ins_or_class_or_name
if (is_str(ret) or isinstance(ret, type)):
ret = get_instance(ret, kwargs, module_paths)
if (classtype is not None):
if (not isinstance(ret, classtype)):
raise TypeError('An instance of {} is expected. Got: {}'.format(classtype, ret))
return ret | 3,205,836,329,023,062,500 | Returns a class instance and checks types.
Args:
ins_or_class_or_name: Can be of 3 types:
- A class to instantiate.
- A string of the name or full path to a class to instantiate.
- The class instance to check types.
kwargs (dict): Keyword arguments for the class constructor. Ignored
if `ins_or_class_or_name` is a class instance.
module_paths (list, optional): Paths to candidate modules to
search for the class. This is used if the class cannot be
located solely based on :attr:`class_name`. The first module
in the list that contains the class is used.
classtype (optional): A (list of) class of which the instance must
be an instantiation.
Raises:
ValueError: If class is not found based on :attr:`class_name` and
:attr:`module_paths`.
ValueError: If :attr:`kwargs` contains arguments that are invalid
for the class construction.
TypeError: If the instance is not an instantiation of
:attr:`classtype`. | texar/tf/utils/utils.py | check_or_get_instance | awesomemachinelearning/texar | python | def check_or_get_instance(ins_or_class_or_name, kwargs, module_paths=None, classtype=None):
'Returns a class instance and checks types.\n\n Args:\n ins_or_class_or_name: Can be of 3 types:\n\n - A class to instantiate.\n - A string of the name or full path to a class to instantiate.\n - The class instance to check types.\n\n kwargs (dict): Keyword arguments for the class constructor. Ignored\n if `ins_or_class_or_name` is a class instance.\n module_paths (list, optional): Paths to candidate modules to\n search for the class. This is used if the class cannot be\n located solely based on :attr:`class_name`. The first module\n in the list that contains the class is used.\n classtype (optional): A (list of) class of which the instance must\n be an instantiation.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_name` and\n :attr:`module_paths`.\n ValueError: If :attr:`kwargs` contains arguments that are invalid\n for the class construction.\n TypeError: If the instance is not an instantiation of\n :attr:`classtype`.\n '
ret = ins_or_class_or_name
if (is_str(ret) or isinstance(ret, type)):
ret = get_instance(ret, kwargs, module_paths)
if (classtype is not None):
if (not isinstance(ret, classtype)):
raise TypeError('An instance of {} is expected. Got: {}'.format(classtype, ret))
return ret |
def get_instance(class_or_name, kwargs, module_paths=None):
'Creates a class instance.\n\n Args:\n class_or_name: A class, or its name or full path to a class to\n instantiate.\n kwargs (dict): Keyword arguments for the class constructor.\n module_paths (list, optional): Paths to candidate modules to\n search for the class. This is used if the class cannot be\n located solely based on :attr:`class_name`. The first module\n in the list that contains the class is used.\n\n Returns:\n A class instance.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_or_name` and\n :attr:`module_paths`.\n ValueError: If :attr:`kwargs` contains arguments that are invalid\n for the class construction.\n '
class_ = class_or_name
if is_str(class_):
class_ = get_class(class_, module_paths)
class_args = set(get_args(class_.__init__))
if (kwargs is None):
kwargs = {}
for key in kwargs.keys():
if (key not in class_args):
raise ValueError(('Invalid argument for class %s.%s: %s, valid args: %s' % (class_.__module__, class_.__name__, key, list(class_args))))
return class_(**kwargs) | -7,312,332,245,295,531,000 | Creates a class instance.
Args:
class_or_name: A class, or its name or full path to a class to
instantiate.
kwargs (dict): Keyword arguments for the class constructor.
module_paths (list, optional): Paths to candidate modules to
search for the class. This is used if the class cannot be
located solely based on :attr:`class_name`. The first module
in the list that contains the class is used.
Returns:
A class instance.
Raises:
ValueError: If class is not found based on :attr:`class_or_name` and
:attr:`module_paths`.
ValueError: If :attr:`kwargs` contains arguments that are invalid
for the class construction. | texar/tf/utils/utils.py | get_instance | awesomemachinelearning/texar | python | def get_instance(class_or_name, kwargs, module_paths=None):
'Creates a class instance.\n\n Args:\n class_or_name: A class, or its name or full path to a class to\n instantiate.\n kwargs (dict): Keyword arguments for the class constructor.\n module_paths (list, optional): Paths to candidate modules to\n search for the class. This is used if the class cannot be\n located solely based on :attr:`class_name`. The first module\n in the list that contains the class is used.\n\n Returns:\n A class instance.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_or_name` and\n :attr:`module_paths`.\n ValueError: If :attr:`kwargs` contains arguments that are invalid\n for the class construction.\n '
class_ = class_or_name
if is_str(class_):
class_ = get_class(class_, module_paths)
class_args = set(get_args(class_.__init__))
if (kwargs is None):
kwargs = {}
for key in kwargs.keys():
if (key not in class_args):
raise ValueError(('Invalid argument for class %s.%s: %s, valid args: %s' % (class_.__module__, class_.__name__, key, list(class_args))))
return class_(**kwargs) |
def check_or_get_instance_with_redundant_kwargs(ins_or_class_or_name, kwargs, module_paths=None, classtype=None):
'Returns a class instance and checks types.\n\n Only those keyword arguments in :attr:`kwargs` that are included in the\n class construction method are used.\n\n Args:\n ins_or_class_or_name: Can be of 3 types:\n\n - A class to instantiate.\n - A string of the name or module path to a class to instantiate.\n - The class instance to check types.\n\n kwargs (dict): Keyword arguments for the class constructor.\n module_paths (list, optional): Paths to candidate modules to\n search for the class. This is used if the class cannot be\n located solely based on :attr:`class_name`. The first module\n in the list that contains the class is used.\n classtype (optional): A (list of) classes of which the instance must\n be an instantiation.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_name` and\n :attr:`module_paths`.\n ValueError: If :attr:`kwargs` contains arguments that are invalid\n for the class construction.\n TypeError: If the instance is not an instantiation of\n :attr:`classtype`.\n '
ret = ins_or_class_or_name
if (is_str(ret) or isinstance(ret, type)):
ret = get_instance_with_redundant_kwargs(ret, kwargs, module_paths)
if (classtype is not None):
if (not isinstance(ret, classtype)):
raise TypeError('An instance of {} is expected. Got: {}'.format(classtype, ret))
return ret | 7,174,078,021,465,491,000 | Returns a class instance and checks types.
Only those keyword arguments in :attr:`kwargs` that are included in the
class construction method are used.
Args:
ins_or_class_or_name: Can be of 3 types:
- A class to instantiate.
- A string of the name or module path to a class to instantiate.
- The class instance to check types.
kwargs (dict): Keyword arguments for the class constructor.
module_paths (list, optional): Paths to candidate modules to
search for the class. This is used if the class cannot be
located solely based on :attr:`class_name`. The first module
in the list that contains the class is used.
classtype (optional): A (list of) classes of which the instance must
be an instantiation.
Raises:
ValueError: If class is not found based on :attr:`class_name` and
:attr:`module_paths`.
ValueError: If :attr:`kwargs` contains arguments that are invalid
for the class construction.
TypeError: If the instance is not an instantiation of
:attr:`classtype`. | texar/tf/utils/utils.py | check_or_get_instance_with_redundant_kwargs | awesomemachinelearning/texar | python | def check_or_get_instance_with_redundant_kwargs(ins_or_class_or_name, kwargs, module_paths=None, classtype=None):
'Returns a class instance and checks types.\n\n Only those keyword arguments in :attr:`kwargs` that are included in the\n class construction method are used.\n\n Args:\n ins_or_class_or_name: Can be of 3 types:\n\n - A class to instantiate.\n - A string of the name or module path to a class to instantiate.\n - The class instance to check types.\n\n kwargs (dict): Keyword arguments for the class constructor.\n module_paths (list, optional): Paths to candidate modules to\n search for the class. This is used if the class cannot be\n located solely based on :attr:`class_name`. The first module\n in the list that contains the class is used.\n classtype (optional): A (list of) classes of which the instance must\n be an instantiation.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_name` and\n :attr:`module_paths`.\n ValueError: If :attr:`kwargs` contains arguments that are invalid\n for the class construction.\n TypeError: If the instance is not an instantiation of\n :attr:`classtype`.\n '
ret = ins_or_class_or_name
if (is_str(ret) or isinstance(ret, type)):
ret = get_instance_with_redundant_kwargs(ret, kwargs, module_paths)
if (classtype is not None):
if (not isinstance(ret, classtype)):
raise TypeError('An instance of {} is expected. Got: {}'.format(classtype, ret))
return ret |
def get_instance_with_redundant_kwargs(class_name, kwargs, module_paths=None):
'Creates a class instance.\n\n Only those keyword arguments in :attr:`kwargs` that are included in the\n class construction method are used.\n\n Args:\n class_name (str): A class or its name or module path.\n kwargs (dict): A dictionary of arguments for the class constructor. It\n may include invalid arguments which will be ignored.\n module_paths (list of str): A list of paths to candidate modules to\n search for the class. This is used if the class cannot be located\n solely based on :attr:`class_name`. The first module in the list\n that contains the class is used.\n\n Returns:\n A class instance.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_name` and\n :attr:`module_paths`.\n '
class_ = get_class(class_name, module_paths)
selected_kwargs = {}
class_args = set(get_args(class_.__init__))
if (kwargs is None):
kwargs = {}
for (key, value) in kwargs.items():
if (key in class_args):
selected_kwargs[key] = value
return class_(**selected_kwargs) | -2,217,281,050,100,717,800 | Creates a class instance.
Only those keyword arguments in :attr:`kwargs` that are included in the
class construction method are used.
Args:
class_name (str): A class or its name or module path.
kwargs (dict): A dictionary of arguments for the class constructor. It
may include invalid arguments which will be ignored.
module_paths (list of str): A list of paths to candidate modules to
search for the class. This is used if the class cannot be located
solely based on :attr:`class_name`. The first module in the list
that contains the class is used.
Returns:
A class instance.
Raises:
ValueError: If class is not found based on :attr:`class_name` and
:attr:`module_paths`. | texar/tf/utils/utils.py | get_instance_with_redundant_kwargs | awesomemachinelearning/texar | python | def get_instance_with_redundant_kwargs(class_name, kwargs, module_paths=None):
'Creates a class instance.\n\n Only those keyword arguments in :attr:`kwargs` that are included in the\n class construction method are used.\n\n Args:\n class_name (str): A class or its name or module path.\n kwargs (dict): A dictionary of arguments for the class constructor. It\n may include invalid arguments which will be ignored.\n module_paths (list of str): A list of paths to candidate modules to\n search for the class. This is used if the class cannot be located\n solely based on :attr:`class_name`. The first module in the list\n that contains the class is used.\n\n Returns:\n A class instance.\n\n Raises:\n ValueError: If class is not found based on :attr:`class_name` and\n :attr:`module_paths`.\n '
class_ = get_class(class_name, module_paths)
selected_kwargs = {}
class_args = set(get_args(class_.__init__))
if (kwargs is None):
kwargs = {}
for (key, value) in kwargs.items():
if (key in class_args):
selected_kwargs[key] = value
return class_(**selected_kwargs) |
def get_function(fn_or_name, module_paths=None):
'Returns the function of specified name and module.\n\n Args:\n fn_or_name (str or callable): Name or full path to a function, or the\n function itself.\n module_paths (list, optional): A list of paths to candidate modules to\n search for the function. This is used only when the function\n cannot be located solely based on :attr:`fn_or_name`. The first\n module in the list that contains the function is used.\n\n Returns:\n A function.\n '
if is_callable(fn_or_name):
return fn_or_name
fn = locate(fn_or_name)
if ((fn is None) and (module_paths is not None)):
for module_path in module_paths:
fn = locate('.'.join([module_path, fn_or_name]))
if (fn is not None):
break
if (fn is None):
raise ValueError('Method not found in {}: {}'.format(module_paths, fn_or_name))
return fn | 6,214,399,954,028,135,000 | Returns the function of specified name and module.
Args:
fn_or_name (str or callable): Name or full path to a function, or the
function itself.
module_paths (list, optional): A list of paths to candidate modules to
search for the function. This is used only when the function
cannot be located solely based on :attr:`fn_or_name`. The first
module in the list that contains the function is used.
Returns:
A function. | texar/tf/utils/utils.py | get_function | awesomemachinelearning/texar | python | def get_function(fn_or_name, module_paths=None):
'Returns the function of specified name and module.\n\n Args:\n fn_or_name (str or callable): Name or full path to a function, or the\n function itself.\n module_paths (list, optional): A list of paths to candidate modules to\n search for the function. This is used only when the function\n cannot be located solely based on :attr:`fn_or_name`. The first\n module in the list that contains the function is used.\n\n Returns:\n A function.\n '
if is_callable(fn_or_name):
return fn_or_name
fn = locate(fn_or_name)
if ((fn is None) and (module_paths is not None)):
for module_path in module_paths:
fn = locate('.'.join([module_path, fn_or_name]))
if (fn is not None):
break
if (fn is None):
raise ValueError('Method not found in {}: {}'.format(module_paths, fn_or_name))
return fn |
def call_function_with_redundant_kwargs(fn, kwargs):
"Calls a function and returns the results.\n\n Only those keyword arguments in :attr:`kwargs` that are included in the\n function's argument list are used to call the function.\n\n Args:\n fn (function): A callable. If :attr:`fn` is not a python function,\n :attr:`fn.__call__` is called.\n kwargs (dict): A `dict` of arguments for the callable. It\n may include invalid arguments which will be ignored.\n\n Returns:\n The returned results by calling :attr:`fn`.\n "
try:
fn_args = set(get_args(fn))
except TypeError:
fn_args = set(get_args(fn.__cal__))
if (kwargs is None):
kwargs = {}
selected_kwargs = {}
for (key, value) in kwargs.items():
if (key in fn_args):
selected_kwargs[key] = value
return fn(**selected_kwargs) | -4,426,932,169,605,291,500 | Calls a function and returns the results.
Only those keyword arguments in :attr:`kwargs` that are included in the
function's argument list are used to call the function.
Args:
fn (function): A callable. If :attr:`fn` is not a python function,
:attr:`fn.__call__` is called.
kwargs (dict): A `dict` of arguments for the callable. It
may include invalid arguments which will be ignored.
Returns:
The returned results by calling :attr:`fn`. | texar/tf/utils/utils.py | call_function_with_redundant_kwargs | awesomemachinelearning/texar | python | def call_function_with_redundant_kwargs(fn, kwargs):
"Calls a function and returns the results.\n\n Only those keyword arguments in :attr:`kwargs` that are included in the\n function's argument list are used to call the function.\n\n Args:\n fn (function): A callable. If :attr:`fn` is not a python function,\n :attr:`fn.__call__` is called.\n kwargs (dict): A `dict` of arguments for the callable. It\n may include invalid arguments which will be ignored.\n\n Returns:\n The returned results by calling :attr:`fn`.\n "
try:
fn_args = set(get_args(fn))
except TypeError:
fn_args = set(get_args(fn.__cal__))
if (kwargs is None):
kwargs = {}
selected_kwargs = {}
for (key, value) in kwargs.items():
if (key in fn_args):
selected_kwargs[key] = value
return fn(**selected_kwargs) |
def get_instance_kwargs(kwargs, hparams):
"Makes a dict of keyword arguments with the following structure:\n\n `kwargs_ = {'hparams': dict(hparams), **kwargs}`.\n\n This is typically used for constructing a module which takes a set of\n arguments as well as a argument named `hparams`.\n\n Args:\n kwargs (dict): A dict of keyword arguments. Can be `None`.\n hparams: A dict or an instance of :class:`~texar.tf.HParams` Can be `None`.\n\n Returns:\n A `dict` that contains the keyword arguments in :attr:`kwargs`, and\n an additional keyword argument named `hparams`.\n "
if ((hparams is None) or isinstance(hparams, dict)):
kwargs_ = {'hparams': hparams}
elif isinstance(hparams, HParams):
kwargs_ = {'hparams': hparams.todict()}
else:
raise ValueError('`hparams` must be a dict, an instance of HParams, or a `None`.')
kwargs_.update((kwargs or {}))
return kwargs_ | -3,281,419,015,722,989,000 | Makes a dict of keyword arguments with the following structure:
`kwargs_ = {'hparams': dict(hparams), **kwargs}`.
This is typically used for constructing a module which takes a set of
arguments as well as a argument named `hparams`.
Args:
kwargs (dict): A dict of keyword arguments. Can be `None`.
hparams: A dict or an instance of :class:`~texar.tf.HParams` Can be `None`.
Returns:
A `dict` that contains the keyword arguments in :attr:`kwargs`, and
an additional keyword argument named `hparams`. | texar/tf/utils/utils.py | get_instance_kwargs | awesomemachinelearning/texar | python | def get_instance_kwargs(kwargs, hparams):
"Makes a dict of keyword arguments with the following structure:\n\n `kwargs_ = {'hparams': dict(hparams), **kwargs}`.\n\n This is typically used for constructing a module which takes a set of\n arguments as well as a argument named `hparams`.\n\n Args:\n kwargs (dict): A dict of keyword arguments. Can be `None`.\n hparams: A dict or an instance of :class:`~texar.tf.HParams` Can be `None`.\n\n Returns:\n A `dict` that contains the keyword arguments in :attr:`kwargs`, and\n an additional keyword argument named `hparams`.\n "
if ((hparams is None) or isinstance(hparams, dict)):
kwargs_ = {'hparams': hparams}
elif isinstance(hparams, HParams):
kwargs_ = {'hparams': hparams.todict()}
else:
raise ValueError('`hparams` must be a dict, an instance of HParams, or a `None`.')
kwargs_.update((kwargs or {}))
return kwargs_ |
def dict_patch(tgt_dict, src_dict):
'Recursively patch :attr:`tgt_dict` by adding items from :attr:`src_dict`\n that do not exist in :attr:`tgt_dict`.\n\n If respective items in :attr:`src_dict` and :attr:`tgt_dict` are both\n `dict`, the :attr:`tgt_dict` item is patched recursively.\n\n Args:\n tgt_dict (dict): Target dictionary to patch.\n src_dict (dict): Source dictionary.\n\n Return:\n dict: The new :attr:`tgt_dict` that is patched.\n '
if (src_dict is None):
return tgt_dict
for (key, value) in src_dict.items():
if (key not in tgt_dict):
tgt_dict[key] = copy.deepcopy(value)
elif (isinstance(value, dict) and isinstance(tgt_dict[key], dict)):
tgt_dict[key] = dict_patch(tgt_dict[key], value)
return tgt_dict | -3,271,779,255,991,127,600 | Recursively patch :attr:`tgt_dict` by adding items from :attr:`src_dict`
that do not exist in :attr:`tgt_dict`.
If respective items in :attr:`src_dict` and :attr:`tgt_dict` are both
`dict`, the :attr:`tgt_dict` item is patched recursively.
Args:
tgt_dict (dict): Target dictionary to patch.
src_dict (dict): Source dictionary.
Return:
dict: The new :attr:`tgt_dict` that is patched. | texar/tf/utils/utils.py | dict_patch | awesomemachinelearning/texar | python | def dict_patch(tgt_dict, src_dict):
'Recursively patch :attr:`tgt_dict` by adding items from :attr:`src_dict`\n that do not exist in :attr:`tgt_dict`.\n\n If respective items in :attr:`src_dict` and :attr:`tgt_dict` are both\n `dict`, the :attr:`tgt_dict` item is patched recursively.\n\n Args:\n tgt_dict (dict): Target dictionary to patch.\n src_dict (dict): Source dictionary.\n\n Return:\n dict: The new :attr:`tgt_dict` that is patched.\n '
if (src_dict is None):
return tgt_dict
for (key, value) in src_dict.items():
if (key not in tgt_dict):
tgt_dict[key] = copy.deepcopy(value)
elif (isinstance(value, dict) and isinstance(tgt_dict[key], dict)):
tgt_dict[key] = dict_patch(tgt_dict[key], value)
return tgt_dict |
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