Search is not available for this dataset
identifier stringlengths 1 155 | parameters stringlengths 2 6.09k | docstring stringlengths 11 63.4k | docstring_summary stringlengths 0 63.4k | function stringlengths 29 99.8k | function_tokens list | start_point list | end_point list | language stringclasses 1
value | docstring_language stringlengths 2 7 | docstring_language_predictions stringlengths 18 23 | is_langid_reliable stringclasses 2
values |
|---|---|---|---|---|---|---|---|---|---|---|---|
request_wrapper | (view_fn) | Wraps requests by setting the current viewing context and fetching the
profile associated with that context.
| Wraps requests by setting the current viewing context and fetching the
profile associated with that context.
| def request_wrapper(view_fn):
"""Wraps requests by setting the current viewing context and fetching the
profile associated with that context.
"""
def real_view_fn(request, *args, **kwargs):
try:
profile = UserProfile.objects.get(username=request.user.username)
ans = view_... | [
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".",... | [
102,
0
] | [
131,
23
] | python | en | ['en', 'en', 'en'] | True |
index | (request, profile) | The main page shows patients and entities.
| The main page shows patients and entities.
| def index(request, profile):
"""The main page shows patients and entities.
"""
patients = Individual.objects.all()
entities = CoveredEntity.objects.all()
# TODO: Filter out ones you can't see?
data = {"patients": patients
, "entities": entities
, 'name': profile.name}
r... | [
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136,
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147,
31
] | python | en | ['en', 'en', 'en'] | True |
about_view | (request, user) | About the system.
| About the system.
| def about_view(request, user):
"""About the system.
"""
# TODO: This doesn't work.
return ("about.html"
, {'which_page' : "about"}) | [
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151,
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156,
39
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profile_view | (request, profile) | Displaying and updating profiles.
| Displaying and updating profiles.
| def profile_view(request, profile):
"""Displaying and updating profiles.
"""
if profile == None:
profile = UserProfile(user=request.user)
if request.method == 'POST':
profile.name = request.POST.get('name', '')
profile.email = request.POST.get('email', '')
profile.save()... | [
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161,
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174,
35
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users_view | (request, profile) | Viewing all users.
| Viewing all users.
| def users_view(request, profile):
"""Viewing all users.
"""
# TODO: Have a better mechanism than this for letting someone know they
# can't see something.
if profile.profiletype != 3:
return ("redirect", "/index")
user_profiles = UserProfile.objects.all()
if request.method == 'POST... | [
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treatments_view | (request, profile, patient) | Treatments.
| Treatments.
| def treatments_view(request, profile, patient):
"""Treatments.
"""
p = Individual.objects.get(jeeves_id=patient)
treatments = Treatment.objects.filter(Patient=p)
return ("treatments.html"
, {"first_name" : p.FirstName
, "last_name" : p.LastName
, "treatments" : treatments}) | [
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213,
38
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diagnoses_view | (request, profile, patient) | Diagnoses.
| Diagnoses.
| def diagnoses_view(request, profile, patient):
"""Diagnoses.
"""
p = Individual.objects.get(jeeves_id=patient)
newDiagnoses = Diagnosis.objects.filter(Patient=p)
diagnoses = [
{"Manifestation" : "A38.8"
, "DateRecognized" : date(2012, 10, 17)
, "RecognizingEntity" : {"Name" ... | [
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218,
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] | [
244,
43
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info_view | (request, profile, patient) | Viewing information about an individual.
| Viewing information about an individual.
| def info_view(request, profile, patient):
"""Viewing information about an individual.
"""
p = Individual.objects.get(jeeves_id=patient)
dataset = []
dataset.append(("Sex", p.Sex, False))
#print "HI"
#dataset.append(("Address",p.Address.String(), False))
#dataset.append(("Social Security ... | [
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"p"... | [
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260,
35
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directory_view | (request, profile, entity) | Viewing covered entities.
| Viewing covered entities.
| def directory_view(request, profile, entity):
"""Viewing covered entities.
"""
entity = CoveredEntity.objects.get(EIN=entity)
visits = entity.Patients.filter(DateReleased=None)
oldVisits = [
{"Patient" : {"Name" : "Joe McGray", "ID" : 5}
, "DateAdmitted" : date(2014, 5, 25)
... | [
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"=... | [
265,
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] | [
293,
49
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transactions_view | (request, profile, entity) |
Viewing transactions.
|
Viewing transactions.
| def transactions_view(request, profile, entity):
"""
Viewing transactions.
"""
entity = CoveredEntity.objects.get(EIN=entity)
transactions = Transaction.objects.filter(FirstParty=entity)
other_transactions = Transaction.objects.filter(SecondParty=entity)
return ("transactions.html"
... | [
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"FirstP... | [
298,
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] | [
308,
57
] | python | en | ['en', 'error', 'th'] | False |
BulkUsersTest.test_client_gravatar_option | (self) |
The main purpose of this test is to make sure we
return None for avatar_url when client_gravatar is
set to True. And we do a sanity check for when it's
False, but we leave it to other tests to validate
the specific URL.
|
The main purpose of this test is to make sure we
return None for avatar_url when client_gravatar is
set to True. And we do a sanity check for when it's
False, but we leave it to other tests to validate
the specific URL.
| def test_client_gravatar_option(self) -> None:
reset_emails_in_zulip_realm()
self.login("cordelia")
hamlet = self.example_user("hamlet")
def get_hamlet_avatar(client_gravatar: bool) -> Optional[str]:
data = dict(client_gravatar=orjson.dumps(client_gravatar).decode())
... | [
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GetProfileTest.test_cache_behavior | (self) | Tests whether fetching a user object the normal way, with
`get_user`, makes 1 cache query and 1 database query.
| Tests whether fetching a user object the normal way, with
`get_user`, makes 1 cache query and 1 database query.
| def test_cache_behavior(self) -> None:
"""Tests whether fetching a user object the normal way, with
`get_user`, makes 1 cache query and 1 database query.
"""
realm = get_realm("zulip")
email = self.example_user("hamlet").email
with queries_captured() as queries:
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":"... | [
1740,
4
] | [
1752,
51
] | python | en | ['en', 'en', 'en'] | True |
sequencer | () |
Use like this:
NEXT_ID = sequencer()
message_id = NEXT_ID('message')
|
Use like this: | def sequencer() -> Callable[[str], int]:
"""
Use like this:
NEXT_ID = sequencer()
message_id = NEXT_ID('message')
"""
seq_dict: Dict[str, Callable[[], int]] = {}
def next_one(name: str) -> int:
if name not in seq_dict:
seq_dict[name] = _seq()
seq = seq_dict[name... | [
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25,
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40,
19
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indent_log | (num=2) |
A context manager which will cause the log output to be indented for any
log messages emitted inside it.
|
A context manager which will cause the log output to be indented for any
log messages emitted inside it.
| def indent_log(num=2):
"""
A context manager which will cause the log output to be indented for any
log messages emitted inside it.
"""
# For thread-safety
_log_state.indentation = get_indentation()
_log_state.indentation += num
try:
yield
finally:
_log_state.indentat... | [
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"indentation"... | [
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111,
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setup_logging | (verbosity, no_color, user_log_file) | Configures and sets up all of the logging
Returns the requested logging level, as its integer value.
| Configures and sets up all of the logging | def setup_logging(verbosity, no_color, user_log_file):
"""Configures and sets up all of the logging
Returns the requested logging level, as its integer value.
"""
# Determine the level to be logging at.
if verbosity >= 1:
level = "DEBUG"
elif verbosity == -1:
level = "WARNING"
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] | python | en | ['en', 'en', 'en'] | True |
IndentingFormatter.__init__ | (self, *args, **kwargs) |
A logging.Formatter that obeys the indent_log() context manager.
:param add_timestamp: A bool indicating output lines should be prefixed
with their record's timestamp.
|
A logging.Formatter that obeys the indent_log() context manager. | def __init__(self, *args, **kwargs):
"""
A logging.Formatter that obeys the indent_log() context manager.
:param add_timestamp: A bool indicating output lines should be prefixed
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"""
self.add_timestamp = kwargs.pop("add_timestamp", False... | [
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IndentingFormatter.get_message_start | (self, formatted, levelno) |
Return the start of the formatted log message (not counting the
prefix to add to each line).
|
Return the start of the formatted log message (not counting the
prefix to add to each line).
| def get_message_start(self, formatted, levelno):
"""
Return the start of the formatted log message (not counting the
prefix to add to each line).
"""
if levelno < logging.WARNING:
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IndentingFormatter.format | (self, record) |
Calls the standard formatter, but will indent all of the log message
lines by our current indentation level.
|
Calls the standard formatter, but will indent all of the log message
lines by our current indentation level.
| def format(self, record):
"""
Calls the standard formatter, but will indent all of the log message
lines by our current indentation level.
"""
formatted = super(IndentingFormatter, self).format(record)
message_start = self.get_message_start(formatted, record.levelno)
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ColorizedStreamHandler._using_stdout | (self) |
Return whether the handler is using sys.stdout.
|
Return whether the handler is using sys.stdout.
| def _using_stdout(self):
"""
Return whether the handler is using sys.stdout.
"""
if WINDOWS and colorama:
# Then self.stream is an AnsiToWin32 object.
return self.stream.wrapped is sys.stdout
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AnsibletowerHookTests.test_ansibletower_project_update_successful_message | (self) |
Tests if ansibletower project update successful notification is handled correctly
|
Tests if ansibletower project update successful notification is handled correctly
| def test_ansibletower_project_update_successful_message(self) -> None:
"""
Tests if ansibletower project update successful notification is handled correctly
"""
expected_topic = "AWX - Project Update"
expected_message = (
"Project Update: [#2677 AWX - Project Update]"... | [
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AnsibletowerHookTests.test_ansibletower_project_update_failed_message | (self) |
Tests if ansibletower project update failed notification is handled correctly
|
Tests if ansibletower project update failed notification is handled correctly
| def test_ansibletower_project_update_failed_message(self) -> None:
"""
Tests if ansibletower project update failed notification is handled correctly
"""
expected_topic = "AWX - Project Update"
expected_message = (
"Project Update: [#2678 AWX - Project Update]"
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AnsibletowerHookTests.test_ansibletower_job_successful_multiple_hosts_message | (self) |
Tests if ansibletower job successful multiple hosts notification is handled correctly
|
Tests if ansibletower job successful multiple hosts notification is handled correctly
| def test_ansibletower_job_successful_multiple_hosts_message(self) -> None:
"""
Tests if ansibletower job successful multiple hosts notification is handled correctly
"""
expected_topic = "System - Deploy - Zabbix Agent"
expected_message = """
Job: [#2674 System - Deploy - Zabbix A... | [
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46,
93
] | python | en | ['en', 'error', 'th'] | False |
AnsibletowerHookTests.test_ansibletower_job_successful_message | (self) |
Tests if ansibletower job successful notification is handled correctly
|
Tests if ansibletower job successful notification is handled correctly
| def test_ansibletower_job_successful_message(self) -> None:
"""
Tests if ansibletower job successful notification is handled correctly
"""
expected_topic = "System - Deploy - Zabbix Agent"
expected_message = """
Job: [#2674 System - Deploy - Zabbix Agent](http://awx.example.co.uk... | [
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] | [
58,
78
] | python | en | ['en', 'error', 'th'] | False |
AnsibletowerHookTests.test_ansibletower_nine_job_successful_message | (self) |
Test to see if awx/ansibletower 9.x.x job successful notifications are
handled just as successfully as prior to 9.x.x.
|
Test to see if awx/ansibletower 9.x.x job successful notifications are
handled just as successfully as prior to 9.x.x.
| def test_ansibletower_nine_job_successful_message(self) -> None:
"""
Test to see if awx/ansibletower 9.x.x job successful notifications are
handled just as successfully as prior to 9.x.x.
"""
expected_topic = "Demo Job Template"
expected_message = """
Job: [#1 Demo Job Te... | [
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"\"\"\"\nJob: [#1 Demo Job Template](https://towerhost/#/jobs/playbook/1) was successful:\n* localhost: Success\n\"\"\"",
... | [
60,
4
] | [
71,
97
] | python | en | ['en', 'error', 'th'] | False |
AnsibletowerHookTests.test_ansibletower_job_failed_message | (self) |
Tests if ansibletower job failed notification is handled correctly
|
Tests if ansibletower job failed notification is handled correctly
| def test_ansibletower_job_failed_message(self) -> None:
"""
Tests if ansibletower job failed notification is handled correctly
"""
expected_topic = "System - Updates - Ubuntu"
expected_message = """
Job: [#2722 System - Updates - Ubuntu](http://awx.example.co.uk/#/jobs/playbook/2... | [
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73,
4
] | [
83,
74
] | python | en | ['en', 'error', 'th'] | False |
AnsibletowerHookTests.test_ansibletower_job_failed_multiple_hosts_message | (self) |
Tests if ansibletower job failed notification is handled correctly
|
Tests if ansibletower job failed notification is handled correctly
| def test_ansibletower_job_failed_multiple_hosts_message(self) -> None:
"""
Tests if ansibletower job failed notification is handled correctly
"""
expected_topic = "System - Updates - Ubuntu"
expected_message = """
Job: [#2722 System - Updates - Ubuntu](http://awx.example.co.uk/#/... | [
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85,
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] | [
99,
89
] | python | en | ['en', 'error', 'th'] | False |
AnsibletowerHookTests.test_ansibletower_inventory_update_successful_message | (self) |
Tests if ansibletower inventory update successful notification is handled correctly
|
Tests if ansibletower inventory update successful notification is handled correctly
| def test_ansibletower_inventory_update_successful_message(self) -> None:
"""
Tests if ansibletower inventory update successful notification is handled correctly
"""
expected_topic = "AWX - Inventory Update"
expected_message = (
"Inventory Update: [#2724 AWX - Inventor... | [
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"\"(http://awx.example.co.uk/#/jobs/inventory/... | [
101,
4
] | [
111,
91
] | python | en | ['en', 'error', 'th'] | False |
AnsibletowerHookTests.test_ansibletower_inventory_update_failed_message | (self) |
Tests if ansibletower inventory update failed notification is handled correctly
|
Tests if ansibletower inventory update failed notification is handled correctly
| def test_ansibletower_inventory_update_failed_message(self) -> None:
"""
Tests if ansibletower inventory update failed notification is handled correctly
"""
expected_topic = "AWX - Inventory Update"
expected_message = (
"Inventory Update: [#2724 AWX - Inventory Update... | [
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"\"(http://awx.example.co.uk/#/jobs/inventory/2724... | [
113,
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] | [
123,
87
] | python | en | ['en', 'error', 'th'] | False |
AnsibletowerHookTests.test_ansibletower_adhoc_command_successful_message | (self) |
Tests if ansibletower adhoc command successful notification is handled correctly
|
Tests if ansibletower adhoc command successful notification is handled correctly
| def test_ansibletower_adhoc_command_successful_message(self) -> None:
"""
Tests if ansibletower adhoc command successful notification is handled correctly
"""
expected_topic = "shell: uname -r"
expected_message = (
"AdHoc Command: [#2726 shell: uname -r]"
... | [
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"\"(http://awx.example.co.uk/#/jobs/command/2726) was successful.\... | [
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] | [
135,
88
] | python | en | ['en', 'error', 'th'] | False |
AnsibletowerHookTests.test_ansibletower_adhoc_command_failed_message | (self) |
Tests if ansibletower adhoc command failed notification is handled correctly
|
Tests if ansibletower adhoc command failed notification is handled correctly
| def test_ansibletower_adhoc_command_failed_message(self) -> None:
"""
Tests if ansibletower adhoc command failed notification is handled correctly
"""
expected_topic = "shell: uname -r"
expected_message = (
"AdHoc Command: [#2726 shell: uname -r]"
"(http:/... | [
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"\"(http://awx.example.co.uk/#/jobs/command/2726) failed.\"",
")",
... | [
137,
4
] | [
147,
84
] | python | en | ['en', 'error', 'th'] | False |
AnsibletowerHookTests.test_ansibletower_system_job_successful_message | (self) |
Tests if ansibletower system job successful notification is handled correctly
|
Tests if ansibletower system job successful notification is handled correctly
| def test_ansibletower_system_job_successful_message(self) -> None:
"""
Tests if ansibletower system job successful notification is handled correctly
"""
expected_topic = "Cleanup Job Details"
expected_message = (
"System Job: [#2721 Cleanup Job Details]"
"... | [
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"\"(http://awx.example.co.uk/#/jobs/system/2721) was successful.... | [
149,
4
] | [
159,
85
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AnsibletowerHookTests.test_ansibletower_system_job_failed_message | (self) |
Tests if ansibletower system job failed notification is handled correctly
|
Tests if ansibletower system job failed notification is handled correctly
| def test_ansibletower_system_job_failed_message(self) -> None:
"""
Tests if ansibletower system job failed notification is handled correctly
"""
expected_topic = "Cleanup Job Details"
expected_message = (
"System Job: [#2721 Cleanup Job Details]"
"(http://... | [
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"\"(http://awx.example.co.uk/#/jobs/system/2721) failed.\"",
")",
... | [
161,
4
] | [
171,
81
] | python | en | ['en', 'error', 'th'] | False |
ParseDateNode.render | (self, datestring) | Parses a date-like string into a timezone aware Python datetime. | Parses a date-like string into a timezone aware Python datetime. | def render(self, datestring):
"""Parses a date-like string into a timezone aware Python datetime."""
formats = ["%Y-%m-%dT%H:%M:%S.%f", "%Y-%m-%d %H:%M:%S.%f",
"%Y-%m-%dT%H:%M:%S", "%Y-%m-%d %H:%M:%S"]
if datestring:
for format in formats:
try:
... | [
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"formats",
... | [
32,
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] | [
45,
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] | python | en | ['en', 'en', 'en'] | True |
test_wrapper_func_transformer | (test_func) | Testing if WrapperFunctionTransformer still has functionality of an underlying FunctionTransformer. | Testing if WrapperFunctionTransformer still has functionality of an underlying FunctionTransformer. | def test_wrapper_func_transformer(test_func):
"""Testing if WrapperFunctionTransformer still has functionality of an underlying FunctionTransformer."""
test_arr = np.array([1, 1, 1, 2, 3, 4, 5]).reshape(-1, 1)
tr = FunctionTransformer(func=test_func)
wrap_tr = WrapperFunctionTransformer("test", clone(t... | [
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... | [
21,
0
] | [
32,
34
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test_wrapper_func_transformer_str | (test_text) | Testing if str() function of WrapperFunctionTransformer returns text provided as an argument. | Testing if str() function of WrapperFunctionTransformer returns text provided as an argument. | def test_wrapper_func_transformer_str(test_text):
"""Testing if str() function of WrapperFunctionTransformer returns text provided as an argument."""
wrap_tr = WrapperFunctionTransformer(test_text, FunctionTransformer())
assert str(wrap_tr) == test_text | [
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44,
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47,
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test_transformer_create_preprocessor_X | (categorical_features, numerical_features) | Testing if X preprocessor correctly assigns steps to columns depending on their type. | Testing if X preprocessor correctly assigns steps to columns depending on their type. | def test_transformer_create_preprocessor_X(categorical_features, numerical_features):
"""Testing if X preprocessor correctly assigns steps to columns depending on their type."""
categorical_features.remove("Target")
tr = Transformer(categorical_features, numerical_features, "Categorical")
preprocessor =... | [
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62,
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test_transformer_create_preprocessor_y | (categorical_features, numerical_features, target_type, expected_function) | Testing if y preprocessor is created correctly. | Testing if y preprocessor is created correctly. | def test_transformer_create_preprocessor_y(categorical_features, numerical_features, target_type, expected_function):
"""Testing if y preprocessor is created correctly."""
tr = Transformer(categorical_features, numerical_features, target_type)
preprocessor = tr._create_default_transformer_y()
assert ty... | [
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72,
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77,
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test_transformer_preprocessor_X_remainder | (
categorical_features, numerical_features, data_classification_balanced, expected_raw_mapping,
transformed_feature
) | Testing if feature not declared in either categorical or numerical features passes through unchanged. | Testing if feature not declared in either categorical or numerical features passes through unchanged. | def test_transformer_preprocessor_X_remainder(
categorical_features, numerical_features, data_classification_balanced, expected_raw_mapping,
transformed_feature
):
"""Testing if feature not declared in either categorical or numerical features passes through unchanged."""
categorical_features.rem... | [
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"... | [
88,
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] | [
114,
70
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test_transformer_preprocessor_X_remainder_order | (
categorical_features, numerical_features, data_classification_balanced, expected_raw_mapping,
transformed_features
) | Testing if remainder portion of ColumnTransformer returns the columns in the expected (alphabetical) order. | Testing if remainder portion of ColumnTransformer returns the columns in the expected (alphabetical) order. | def test_transformer_preprocessor_X_remainder_order(
categorical_features, numerical_features, data_classification_balanced, expected_raw_mapping,
transformed_features
):
"""Testing if remainder portion of ColumnTransformer returns the columns in the expected (alphabetical) order."""
categorical... | [
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124,
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] | [
147,
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test_transformer_create_preprocessor_y_invalid_target_type | (categorical_features, numerical_features, target_type) | Testing if ._create_preprocessor_y raises an Exception when invalid target_type is provided | Testing if ._create_preprocessor_y raises an Exception when invalid target_type is provided | def test_transformer_create_preprocessor_y_invalid_target_type(categorical_features, numerical_features, target_type):
"""Testing if ._create_preprocessor_y raises an Exception when invalid target_type is provided"""
tr = Transformer(categorical_features, numerical_features, "Categorical") # initiating with pr... | [
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test_transformer_transform_y_categorical | (
data_classification_balanced, categorical_features, numerical_features, expected_raw_mapping, feature_name
) | Testing if fit_y() and transform_y() are changing provided y correctly (when y is categorical) | Testing if fit_y() and transform_y() are changing provided y correctly (when y is categorical) | def test_transformer_transform_y_categorical(
data_classification_balanced, categorical_features, numerical_features, expected_raw_mapping, feature_name
):
"""Testing if fit_y() and transform_y() are changing provided y correctly (when y is categorical)"""
df = pd.concat([data_classification_balanced[0]... | [
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194,
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test_transformer_transform_y_numerical | (
data_classification_balanced, categorical_features, numerical_features, feature_name
) | Testing if fit_y() and transform_y() are changing provided y correctly (when y is numerical) | Testing if fit_y() and transform_y() are changing provided y correctly (when y is numerical) | def test_transformer_transform_y_numerical(
data_classification_balanced, categorical_features, numerical_features, feature_name
):
"""Testing if fit_y() and transform_y() are changing provided y correctly (when y is numerical)"""
df = pd.concat([data_classification_balanced[0], data_classification_bala... | [
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215,
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test_transformer_transform_y_classification_pos_label | (
data_classification_balanced, categorical_features, numerical_features, feature, classification_pos_label,
) | Testing if transformer correctly changes mappings of y when explicit classification_pos_label is provided. | Testing if transformer correctly changes mappings of y when explicit classification_pos_label is provided. | def test_transformer_transform_y_classification_pos_label(
data_classification_balanced, categorical_features, numerical_features, feature, classification_pos_label,
):
"""Testing if transformer correctly changes mappings of y when explicit classification_pos_label is provided."""
df = pd.concat([data_c... | [
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228,
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238,
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test_transformer_transform_y_classification_pos_label_multiclass | (
data_multiclass, categorical_features, numerical_features, classification_pos_label,
) | Testing if transformer correctly changes mappings of y when explicit classification_pos_label is provided
for multiclass problem (so the mapping changes it to classification problem). | Testing if transformer correctly changes mappings of y when explicit classification_pos_label is provided
for multiclass problem (so the mapping changes it to classification problem). | def test_transformer_transform_y_classification_pos_label_multiclass(
data_multiclass, categorical_features, numerical_features, classification_pos_label,
):
"""Testing if transformer correctly changes mappings of y when explicit classification_pos_label is provided
for multiclass problem (so the mappin... | [
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266,
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test_transformer_transform_X_categorical | (data_classification_balanced, feature_name, csr_matrix_flag) | Testing if every categorical column from a test data is transformed correctly. | Testing if every categorical column from a test data is transformed correctly. | def test_transformer_transform_X_categorical(data_classification_balanced, feature_name, csr_matrix_flag):
"""Testing if every categorical column from a test data is transformed correctly."""
df = pd.concat([data_classification_balanced[0], data_classification_balanced[1]], axis=1)
# replacing for SimpleImp... | [
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279,
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] | [
296,
76
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test_transformer_transform_X_numerical | (data_classification_balanced, feature_name) | Testing if every numerical column from a test data is transformed correctly. | Testing if every numerical column from a test data is transformed correctly. | def test_transformer_transform_X_numerical(data_classification_balanced, feature_name):
"""Testing if every numerical column from a test data is transformed correctly."""
random_state = 1
df = pd.concat([data_classification_balanced[0], data_classification_balanced[1]], axis=1)
feature = df[feature_name... | [
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test_transformer_y_classes_classification | (
data_classification_balanced, categorical_features, numerical_features, y_column, expected_result, seed
) | Testing if classification transformer returns correct classes from y. | Testing if classification transformer returns correct classes from y. | def test_transformer_y_classes_classification(
data_classification_balanced, categorical_features, numerical_features, y_column, expected_result, seed
):
"""Testing if classification transformer returns correct classes from y."""
df = pd.concat([data_classification_balanced[0], data_classification_balan... | [
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346,
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test_transformer_y_classes_regression_error | (categorical_features, numerical_features, seed) | Testing if y_classes raises an Error when target_type is provided as Numerical. | Testing if y_classes raises an Error when target_type is provided as Numerical. | def test_transformer_y_classes_regression_error(categorical_features, numerical_features, seed):
"""Testing if y_classes raises an Error when target_type is provided as Numerical."""
tr = Transformer(categorical_features, numerical_features, "Numerical", seed)
with pytest.raises(ValueError):
_ = tr.... | [
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26
] | python | en | ['en', 'en', 'en'] | True |
test_transformer_transformers | (transformer_classification_fitted, feature, category, seed) | Testing if correct transformers are returned when provided with a feature name. | Testing if correct transformers are returned when provided with a feature name. | def test_transformer_transformers(transformer_classification_fitted, feature, category, seed):
"""Testing if correct transformers are returned when provided with a feature name."""
if category == "Categorical":
expected_result = ["SimpleImputer(strategy='most_frequent')", "OneHotEncoder(handle_unknown='... | [
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test_transformer_custom_transformers | (categorical_features, numerical_features, seed) | Testing if setting custom transformers in Transformer object works correctly. | Testing if setting custom transformers in Transformer object works correctly. | def test_transformer_custom_transformers(categorical_features, numerical_features, seed):
"""Testing if setting custom transformers in Transformer object works correctly."""
categorical_tr = [SimpleImputer(strategy="most_frequent"), OrdinalEncoder()]
numerical_tr = [SimpleImputer(), PowerTransformer()]
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test_transformer_custom_transformer_none_transformers | (
categorical_features, numerical_features, seed, custom_transformers, tr_type
) | Testing if setting custom transformers with only one type of transformers provided works correctly. | Testing if setting custom transformers with only one type of transformers provided works correctly. | def test_transformer_custom_transformer_none_transformers(
categorical_features, numerical_features, seed, custom_transformers, tr_type
):
"""Testing if setting custom transformers with only one type of transformers provided works correctly."""
tr = Transformer(categorical_features, numerical_features, ... | [
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test_transformer_transformers_untransformed_feature | (transformer_classification_fitted, feature) | Testing if no transformers are returned from transformations() function when unused feature is provided. | Testing if no transformers are returned from transformations() function when unused feature is provided. | def test_transformer_transformers_untransformed_feature(transformer_classification_fitted, feature):
"""Testing if no transformers are returned from transformations() function when unused feature is provided."""
expected_result = None
actual_result = transformer_classification_fitted.transformers(feature)
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test_transformer_transformed_columns_names | (transformer_classification_fitted) | Testing if transformed_columns() returns correct combination of transformed column names. | Testing if transformed_columns() returns correct combination of transformed column names. | def test_transformer_transformed_columns_names(transformer_classification_fitted):
"""Testing if transformed_columns() returns correct combination of transformed column names."""
categorical_columns = [
"AgeGroup_18",
"AgeGroup_23",
"AgeGroup_28",
"AgeGroup_33",
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test_transformer_transformed_columns_categorical_encoding | (
transformer_classification_fitted, data_classification_balanced, feature
) | Testing if transformed_columns() returns transformed column names in correct order (OneHotEncoding). | Testing if transformed_columns() returns transformed column names in correct order (OneHotEncoding). | def test_transformer_transformed_columns_categorical_encoding(
transformer_classification_fitted, data_classification_balanced, feature
):
"""Testing if transformed_columns() returns transformed column names in correct order (OneHotEncoding)."""
categorical_columns = [
"AgeGroup_18",
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test_transformer_transformed_columns_no_one_hot_encoder | (
transformer_classification_fitted, data_classification_balanced
) | Testing if columns from transformed_columns() are correctly calculated when there is no OneHotEncoder present
in the preprocessor. | Testing if columns from transformed_columns() are correctly calculated when there is no OneHotEncoder present
in the preprocessor. | def test_transformer_transformed_columns_no_one_hot_encoder(
transformer_classification_fitted, data_classification_balanced
):
"""Testing if columns from transformed_columns() are correctly calculated when there is no OneHotEncoder present
in the preprocessor."""
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test_transformer_normal_transformations | (
transformer_classification_fitted, data_classification_balanced, feature, seed
) | Testing if normal_transformations() method returns correct 'normal' transformations for a given feature. | Testing if normal_transformations() method returns correct 'normal' transformations for a given feature. | def test_transformer_normal_transformations(
transformer_classification_fitted, data_classification_balanced, feature, seed
):
"""Testing if normal_transformations() method returns correct 'normal' transformations for a given feature."""
expected_transformers = [QuantileTransformer, PowerTransformer]
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test_transformer_normal_transformations_negative_input | (
transformer_classification_fitted, input_train_array, input_test_array, expected_transformers_len, seed
) | Testing if normal_transformations are returned correctly when input has negative values. | Testing if normal_transformations are returned correctly when input has negative values. | def test_transformer_normal_transformations_negative_input(
transformer_classification_fitted, input_train_array, input_test_array, expected_transformers_len, seed
):
"""Testing if normal_transformations are returned correctly when input has negative values."""
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test_transformer_normal_transformations_histogram | (
transformer_classification_fitted, data_classification_balanced, numerical_features, seed
) | Testing if histogram data is calculated for expected features and normal transformers. | Testing if histogram data is calculated for expected features and normal transformers. | def test_transformer_normal_transformations_histogram(
transformer_classification_fitted, data_classification_balanced, numerical_features, seed
):
"""Testing if histogram data is calculated for expected features and normal transformers."""
expected_keys = {"Price", "Height"}
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BaseHelper.cache | (self) |
Возвращает кеш помощника
|
Возвращает кеш помощника
| def cache(self):
"""
Возвращает кеш помощника
"""
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BaseHelper._prepare_cache_class | (self) |
Возвращает класс кеша помощника
|
Возвращает класс кеша помощника
| def _prepare_cache_class(self) -> Union[Optional[Type[BaseCache]], Optional[Type[CacheStorage]]]:
"""
Возвращает класс кеша помощника
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BaseHelper._prepare_cache | (self, *args, **kwargs) |
Метод создания кеша.
Кеш хранится в публичном свойстве cache. По умолчанию добавлена
заглушка.
|
Метод создания кеша. | def _prepare_cache(self, *args, **kwargs):
"""
Метод создания кеша.
Кеш хранится в публичном свойстве cache. По умолчанию добавлена
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CompletionCommand.run | (self, options, args) | Prints the completion code of the given shell | Prints the completion code of the given shell | def run(self, options, args):
# type: (Values, List[str]) -> int
"""Prints the completion code of the given shell"""
shells = COMPLETION_SCRIPTS.keys()
shell_options = ['--' + shell for shell in sorted(shells)]
if options.shell in shells:
script = textwrap.dedent(
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PushNotificationConsumer.notify | (self, event) |
Handler for calls like::
channel_layer.group_send(group_name, {
'type': 'notify', # This routes it to this handler.
'content': {
'type': str (will map to frontend Redux event),
'payload': {
'originatin... |
Handler for calls like:: | async def notify(self, event):
"""
Handler for calls like::
channel_layer.group_send(group_name, {
'type': 'notify', # This routes it to this handler.
'content': {
'type': str (will map to frontend Redux event),
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MappingFilterAction.filter | (self, table, mappings, filter_string) | Naive case-insensitive search. | Naive case-insensitive search. | def filter(self, table, mappings, filter_string):
"""Naive case-insensitive search."""
q = filter_string.lower()
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initial_password | (email: str) | Given an email address, returns the initial password for that account, as
created by populate_db. | Given an email address, returns the initial password for that account, as
created by populate_db. | def initial_password(email: str) -> Optional[str]:
"""Given an email address, returns the initial password for that account, as
created by populate_db."""
if settings.INITIAL_PASSWORD_SALT is not None:
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check_union | (allowed_type_funcs: Collection[Validator[ResultT]]) |
Use this validator if an argument is of a variable type (e.g. processing
properties that might be strings or booleans).
`allowed_type_funcs`: the check_* validator functions for the possible data
types for this variable.
|
Use this validator if an argument is of a variable type (e.g. processing
properties that might be strings or booleans). | def check_union(allowed_type_funcs: Collection[Validator[ResultT]]) -> Validator[ResultT]:
"""
Use this validator if an argument is of a variable type (e.g. processing
properties that might be strings or booleans).
`allowed_type_funcs`: the check_* validator functions for the possible data
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validate_select_field_data | (field_data: ProfileFieldData) |
This function is used to validate the data sent to the server while
creating/editing choices of the choice field in Organization settings.
|
This function is used to validate the data sent to the server while
creating/editing choices of the choice field in Organization settings.
| def validate_select_field_data(field_data: ProfileFieldData) -> Dict[str, Dict[str, str]]:
"""
This function is used to validate the data sent to the server while
creating/editing choices of the choice field in Organization settings.
"""
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validate_select_field | (var_name: str, field_data: str, value: object) |
This function is used to validate the value selected by the user against a
choice field. This is not used to validate admin data.
|
This function is used to validate the value selected by the user against a
choice field. This is not used to validate admin data.
| def validate_select_field(var_name: str, field_data: str, value: object) -> str:
"""
This function is used to validate the value selected by the user against a
choice field. This is not used to validate admin data.
"""
s = check_string(var_name, value)
field_data_dict = orjson.loads(field_data)
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Command.get_new_strings | (
self, old_strings: Mapping[str, str], translation_strings: List[str], locale: str
) |
Missing strings are removed, new strings are added and already
translated strings are not touched.
|
Missing strings are removed, new strings are added and already
translated strings are not touched.
| def get_new_strings(
self, old_strings: Mapping[str, str], translation_strings: List[str], locale: str
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Missing strings are removed, new strings are added and already
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Encoded.cast | (self, content) |
Cast the I{untyped} list items found in content I{value}.
Each items contained in the list is checked for XSD type information.
Items (values) that are I{untyped}, are replaced with suds objects and
type I{metadata} is added.
@param content: The content holding the collection.
... |
Cast the I{untyped} list items found in content I{value}.
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Items (values) that are I{untyped}, are replaced with suds objects and
type I{metadata} is added.
| def cast(self, content):
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Cast the I{untyped} list items found in content I{value}.
Each items contained in the list is checked for XSD type information.
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pkg_resources_distribution_for_wheel | (wheel_zip, name, location) | Get a pkg_resources distribution given a wheel.
:raises UnsupportedWheel: on any errors
| Get a pkg_resources distribution given a wheel. | def pkg_resources_distribution_for_wheel(wheel_zip, name, location):
# type: (ZipFile, str, str) -> Distribution
"""Get a pkg_resources distribution given a wheel.
:raises UnsupportedWheel: on any errors
"""
info_dir, _ = parse_wheel(wheel_zip, name)
metadata_files = [
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parse_wheel | (wheel_zip, name) | Extract information from the provided wheel, ensuring it meets basic
standards.
Returns the name of the .dist-info directory and the parsed WHEEL metadata.
| Extract information from the provided wheel, ensuring it meets basic
standards. | def parse_wheel(wheel_zip, name):
# type: (ZipFile, str) -> Tuple[str, Message]
"""Extract information from the provided wheel, ensuring it meets basic
standards.
Returns the name of the .dist-info directory and the parsed WHEEL metadata.
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wheel_dist_info_dir | (source, name) | Returns the name of the contained .dist-info directory.
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it doesn't match the provided name.
| Returns the name of the contained .dist-info directory. | def wheel_dist_info_dir(source, name):
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"""Returns the name of the contained .dist-info directory.
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wheel_metadata | (source, dist_info_dir) | Return the WHEEL metadata of an extracted wheel, if possible.
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wheel_version | (wheel_data) | Given WHEEL metadata, return the parsed Wheel-Version.
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check_compatibility | (version, name) | Raises errors or warns if called with an incompatible Wheel-Version.
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glob | (pathname, recursive=False) | Return a list of paths matching a pathname pattern.
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iglob | (pathname, recursive=False) | Return an iterator which yields the paths matching a pathname pattern.
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Element.buildPath | (self, parent, path) |
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Element.__init__ | (self, name, parent=None, ns=None) |
@param name: The element's (tag) name. May cotain a prefix.
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Element.rename | (self, name) |
Rename the element.
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@type name: basestring
|
Rename the element.
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Rename the element.
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Element.setPrefix | (self, p, u=None) |
Set the element namespace prefix.
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Element.qname | (self) |
Get the B{fully} qualified name of this element
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Get the B{fully} qualified name of this element
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Get the B{fully} qualified name of this element
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Element.getRoot | (self) |
Get the root (top) node of the tree.
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Get the root (top) node of the tree.
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Element.clone | (self, parent=None) |
Deep clone of this element and children.
@param parent: An optional parent for the copied fragment.
@type parent: I{Element}
@return: A deep copy parented by I{parent}
@rtype: I{Element}
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Deep clone of this element and children.
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Deep clone of this element and children.
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Element.detach | (self) |
Detach from parent.
@return: This element removed from its parent's
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Detach from parent.
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Detach from parent.
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Element.set | (self, name, value) |
Set an attribute's value.
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Element.unset | (self, name) |
Unset (remove) an attribute.
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Unset (remove) an attribute.
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Element.get | (self, name, ns=None, default=None) |
Get the value of an attribute by name.
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Get the value of an attribute by name.
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Element.setText | (self, value) |
Set the element's L{Text} content.
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@type value: basestring
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Set the element's L{Text} content.
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Element.getText | (self, default=None) |
Get the element's L{Text} content with optional default
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Get the element's L{Text} content with optional default
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Element.trim | (self) |
Trim leading and trailing whitespace.
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|
Trim leading and trailing whitespace.
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Trim leading and trailing whitespace.
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Element.hasText | (self) |
Get whether the element has I{text} and that it is not an empty
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Get whether the element has I{text} and that it is not an empty
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Get whether the element has I{text} and that it is not an empty
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Element.namespace | (self) |
Get the element's namespace.
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Get the element's namespace.
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] | [
285,
4
] | [
295,
50
] | python | en | ['en', 'error', 'th'] | False |
Element.defaultNamespace | (self) |
Get the default (unqualified namespace).
This is the expns of the first node (looking up the tree)
that has it set.
@return: The namespace of a node when not qualified.
@rtype: (I{prefix}, I{name})
|
Get the default (unqualified namespace).
This is the expns of the first node (looking up the tree)
that has it set.
| def defaultNamespace(self):
"""
Get the default (unqualified namespace).
This is the expns of the first node (looking up the tree)
that has it set.
@return: The namespace of a node when not qualified.
@rtype: (I{prefix}, I{name})
"""
p = self
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297,
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311,
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Element.append | (self, objects) |
Append the specified child based on whether it is an
element or an attrbuite.
@param objects: A (single|collection) of attribute(s) or element(s)
to be added as children.
@type objects: (L{Element}|L{Attribute})
@return: self
@rtype: L{Element}
|
Append the specified child based on whether it is an
element or an attrbuite.
| def append(self, objects):
"""
Append the specified child based on whether it is an
element or an attrbuite.
@param objects: A (single|collection) of attribute(s) or element(s)
to be added as children.
@type objects: (L{Element}|L{Attribute})
@return: self
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313,
4
] | [
335,
19
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Element.insert | (self, objects, index=0) |
Insert an L{Element} content at the specified index.
@param objects: A (single|collection) of attribute(s) or element(s)
to be added as children.
@type objects: (L{Element}|L{Attribute})
@param index: The position in the list of children to insert.
@type index: int
... |
Insert an L{Element} content at the specified index.
| def insert(self, objects, index=0):
"""
Insert an L{Element} content at the specified index.
@param objects: A (single|collection) of attribute(s) or element(s)
to be added as children.
@type objects: (L{Element}|L{Attribute})
@param index: The position in the list of... | [
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337,
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] | [
355,
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Element.remove | (self, child) |
Remove the specified child element or attribute.
@param child: A child to remove.
@type child: L{Element}|L{Attribute}
@return: The detached I{child} when I{child} is an element, else None.
@rtype: L{Element}|None
|
Remove the specified child element or attribute.
| def remove(self, child):
"""
Remove the specified child element or attribute.
@param child: A child to remove.
@type child: L{Element}|L{Attribute}
@return: The detached I{child} when I{child} is an element, else None.
@rtype: L{Element}|None
"""
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"."... | [
357,
4
] | [
369,
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] | python | en | ['en', 'error', 'th'] | False |
Element.replaceChild | (self, child, content) |
Replace I{child} with the specified I{content}.
@param child: A child element.
@type child: L{Element}
@param content: An element or collection of elements.
@type content: L{Element} or [L{Element},]
|
Replace I{child} with the specified I{content}.
| def replaceChild(self, child, content):
"""
Replace I{child} with the specified I{content}.
@param child: A child element.
@type child: L{Element}
@param content: An element or collection of elements.
@type content: L{Element} or [L{Element},]
"""
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... | [
371,
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] | [
388,
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] | python | en | ['en', 'error', 'th'] | False |
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