repo stringlengths 7 54 | path stringlengths 4 223 | func_name stringlengths 1 134 | original_string stringlengths 75 104k | language stringclasses 1
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value | summary stringlengths 4 350 | obf_code stringlengths 7.85k 764k |
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polyaxon/polyaxon | polyaxon/api/utils/views/protected.py | ProtectedView.handle_exception | def handle_exception(self, exc):
"""Use custom exception handler for errors."""
if isinstance(
exc, (rest_exceptions.NotAuthenticated,
rest_exceptions.AuthenticationFailed)) and self.HANDLE_UNAUTHENTICATED:
return HttpResponseRedirect('{}?next={}'.format(
... | python | def handle_exception(self, exc):
"""Use custom exception handler for errors."""
if isinstance(
exc, (rest_exceptions.NotAuthenticated,
rest_exceptions.AuthenticationFailed)) and self.HANDLE_UNAUTHENTICATED:
return HttpResponseRedirect('{}?next={}'.format(
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polyaxon/polyaxon | polyaxon/scheduler/spawners/templates/resources.py | get_resources | def get_resources(resources): # pylint:disable=too-many-branches
"""Create resources requirements.
Args:
resources: `PodResourcesConfig`
Return:
`V1ResourceRequirements`
"""
limits = {}
requests = {}
if resources is None:
return None
if resources.cpu:
i... | python | def get_resources(resources): # pylint:disable=too-many-branches
"""Create resources requirements.
Args:
resources: `PodResourcesConfig`
Return:
`V1ResourceRequirements`
"""
limits = {}
requests = {}
if resources is None:
return None
if resources.cpu:
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polyaxon/polyaxon | polyaxon/scopes/permissions/projects.py | has_project_permissions | def has_project_permissions(user: 'User', project: 'Project', request_method: str) -> bool:
"""This logic is extracted here to be used also with Sanic api."""
# Superusers and the creator is allowed to do everything
if user.is_staff or user.is_superuser or project.user == user:
return True
# Ot... | python | def has_project_permissions(user: 'User', project: 'Project', request_method: str) -> bool:
"""This logic is extracted here to be used also with Sanic api."""
# Superusers and the creator is allowed to do everything
if user.is_staff or user.is_superuser or project.user == user:
return True
# Ot... | [
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polyaxon/polyaxon | polyaxon/signals/deletion.py | experiment_group_pre_delete | def experiment_group_pre_delete(sender, **kwargs):
"""Delete all group outputs."""
instance = kwargs['instance']
if instance.is_selection:
return
# Delete outputs and logs
celery_app.send_task(
SchedulerCeleryTasks.STORES_SCHEDULE_OUTPUTS_DELETION,
kwargs={
'per... | python | def experiment_group_pre_delete(sender, **kwargs):
"""Delete all group outputs."""
instance = kwargs['instance']
if instance.is_selection:
return
# Delete outputs and logs
celery_app.send_task(
SchedulerCeleryTasks.STORES_SCHEDULE_OUTPUTS_DELETION,
kwargs={
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polyaxon/polyaxon | polyaxon/signals/deletion.py | experiment_group_post_delete | def experiment_group_post_delete(sender, **kwargs):
"""Delete all group outputs."""
instance = kwargs['instance']
auditor.record(event_type=EXPERIMENT_GROUP_DELETED, instance=instance)
remove_bookmarks(object_id=instance.id, content_type='experimentgroup') | python | def experiment_group_post_delete(sender, **kwargs):
"""Delete all group outputs."""
instance = kwargs['instance']
auditor.record(event_type=EXPERIMENT_GROUP_DELETED, instance=instance)
remove_bookmarks(object_id=instance.id, content_type='experimentgroup') | [
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polyaxon/polyaxon | polyaxon/libs/statics.py | get_asset_url | def get_asset_url(module: str, path: str) -> str:
"""Return a static asset URL (located within Polyaxon's static files).
Example:
```python
>>> get_asset_url('polyaxon', 'dist/global.css')
... "/_static/74d127b78dc7daf2c51f/polyaxon/dist/global.css"
```
"""
return '{}/{}... | python | def get_asset_url(module: str, path: str) -> str:
"""Return a static asset URL (located within Polyaxon's static files).
Example:
```python
>>> get_asset_url('polyaxon', 'dist/global.css')
... "/_static/74d127b78dc7daf2c51f/polyaxon/dist/global.css"
```
"""
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polyaxon/polyaxon | polyaxon/scheduler/spawners/templates/jobs/manager.py | ResourceManager.get_init_container | def get_init_container(self,
init_command,
init_args,
env_vars,
context_mounts,
persistence_outputs,
persistence_data):
"""Pod init container for sett... | python | def get_init_container(self,
init_command,
init_args,
env_vars,
context_mounts,
persistence_outputs,
persistence_data):
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polyaxon/polyaxon | polyaxon/scheduler/spawners/templates/dockerizers/manager.py | ResourceManager.get_init_container | def get_init_container(self,
init_command,
init_args,
env_vars,
context_mounts,
persistence_outputs,
persistence_data):
"""Pod init container for sett... | python | def get_init_container(self,
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polyaxon/polyaxon | polyaxon/hpsearch/iteration_managers/base.py | BaseIterationManager.create_iteration | def create_iteration(self, num_suggestions):
"""Create an iteration for the experiment group (works for grid and random)."""
from db.models.experiment_groups import ExperimentGroupIteration
iteration_config = BaseIterationConfig(iteration=0,
num_su... | python | def create_iteration(self, num_suggestions):
"""Create an iteration for the experiment group (works for grid and random)."""
from db.models.experiment_groups import ExperimentGroupIteration
iteration_config = BaseIterationConfig(iteration=0,
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polyaxon/polyaxon | polyaxon/hpsearch/iteration_managers/base.py | BaseIterationManager.update_iteration | def update_iteration(self):
"""Update the last experiment group's iteration with experiment performance."""
iteration_config = self.get_iteration_config()
if not iteration_config:
return
experiments_metrics = self.experiment_group.get_experiments_metrics(
experime... | python | def update_iteration(self):
"""Update the last experiment group's iteration with experiment performance."""
iteration_config = self.get_iteration_config()
if not iteration_config:
return
experiments_metrics = self.experiment_group.get_experiments_metrics(
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polyaxon/polyaxon | polyaxon/hpsearch/iteration_managers/base.py | BaseIterationManager.update_iteration_num_suggestions | def update_iteration_num_suggestions(self, num_suggestions):
"""Update iteration's num_suggestions."""
iteration_config = self.experiment_group.iteration_config
iteration_config.num_suggestions = num_suggestions
self._update_config(iteration_config) | python | def update_iteration_num_suggestions(self, num_suggestions):
"""Update iteration's num_suggestions."""
iteration_config = self.experiment_group.iteration_config
iteration_config.num_suggestions = num_suggestions
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polyaxon/polyaxon | polyaxon/api/experiments/serializers.py | ExperimentCreateSerializer.validate_config | def validate_config(self, config):
"""We only validate the config if passed.
Also we use the ExperimentSpecification to check if this config was
intended as an experiment.
"""
# config is optional
if not config:
return config
spec = validate_experime... | python | def validate_config(self, config):
"""We only validate the config if passed.
Also we use the ExperimentSpecification to check if this config was
intended as an experiment.
"""
# config is optional
if not config:
return config
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polyaxon/polyaxon | polyaxon/event_manager/event.py | Event.get_event_action | def get_event_action(cls) -> Optional[str]:
"""Return the second part of the event_type
e.g.
>>> Event.event_type = 'experiment.deleted'
>>> Event.get_event_action() == 'deleted'
"""
if not cls.actor:
return None
return event_context.get_event_action... | python | def get_event_action(cls) -> Optional[str]:
"""Return the second part of the event_type
e.g.
>>> Event.event_type = 'experiment.deleted'
>>> Event.get_event_action() == 'deleted'
"""
if not cls.actor:
return None
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polyaxon/polyaxon | polyaxon/scheduler/dockerizer_scheduler.py | create_build_job | def create_build_job(user, project, config, code_reference, configmap_refs=None, secret_refs=None):
"""Get or Create a build job based on the params.
If a build job already exists, then we check if the build has already an image created.
If the image does not exists, and the job is already done we force cr... | python | def create_build_job(user, project, config, code_reference, configmap_refs=None, secret_refs=None):
"""Get or Create a build job based on the params.
If a build job already exists, then we check if the build has already an image created.
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yaml/pyyaml | lib/yaml/__init__.py | scan | def scan(stream, Loader=Loader):
"""
Scan a YAML stream and produce scanning tokens.
"""
loader = Loader(stream)
try:
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yield loader.get_token()
finally:
loader.dispose() | python | def scan(stream, Loader=Loader):
"""
Scan a YAML stream and produce scanning tokens.
"""
loader = Loader(stream)
try:
while loader.check_token():
yield loader.get_token()
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yaml/pyyaml | lib/yaml/__init__.py | parse | def parse(stream, Loader=Loader):
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loader.dispose() | python | def parse(stream, Loader=Loader):
"""
Parse a YAML stream and produce parsing events.
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loader = Loader(stream)
try:
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yield loader.get_event()
finally:
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yaml/pyyaml | lib/yaml/__init__.py | compose | def compose(stream, Loader=Loader):
"""
Parse the first YAML document in a stream
and produce the corresponding representation tree.
"""
loader = Loader(stream)
try:
return loader.get_single_node()
finally:
loader.dispose() | python | def compose(stream, Loader=Loader):
"""
Parse the first YAML document in a stream
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loader = Loader(stream)
try:
return loader.get_single_node()
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yaml/pyyaml | lib/yaml/__init__.py | compose_all | def compose_all(stream, Loader=Loader):
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"""
Parse all YAML documents in a stream
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loader = Loader(stream)
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yaml/pyyaml | lib/yaml/__init__.py | load | def load(stream, Loader=None):
"""
Parse the first YAML document in a stream
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"""
if Loader is None:
load_warning('load')
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loader = Loader(stream)
try:
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finally:
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"""
Parse the first YAML document in a stream
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if Loader is None:
load_warning('load')
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yaml/pyyaml | lib/yaml/__init__.py | load_all | def load_all(stream, Loader=None):
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Parse all YAML documents in a stream
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yield loader.... | python | def load_all(stream, Loader=None):
"""
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yaml/pyyaml | lib/yaml/__init__.py | emit | def emit(events, stream=None, Dumper=Dumper,
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allow_unicode=None, line_break=None):
"""
Emit YAML parsing events into a stream.
If stream is None, return the produced string instead.
"""
getvalue = None
if stream is None:
from Strin... | python | def emit(events, stream=None, Dumper=Dumper,
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Emit YAML parsing events into a stream.
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yaml/pyyaml | lib/yaml/__init__.py | serialize | def serialize(node, stream=None, Dumper=Dumper, **kwds):
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Serialize a representation tree into a YAML stream.
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"""
return serialize_all([node], stream, Dumper=Dumper, **kwds) | python | def serialize(node, stream=None, Dumper=Dumper, **kwds):
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yaml/pyyaml | lib/yaml/__init__.py | dump | def dump(data, stream=None, Dumper=Dumper, **kwds):
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yaml/pyyaml | lib/yaml/__init__.py | safe_dump_all | def safe_dump_all(documents, stream=None, **kwds):
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Serialize a sequence of Python objects into a YAML stream.
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return dump_all(documents, stream, Dumper=SafeDumper, **kwds) | python | def safe_dump_all(documents, stream=None, **kwds):
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yaml/pyyaml | lib/yaml/__init__.py | safe_dump | def safe_dump(data, stream=None, **kwds):
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Serialize a Python object into a YAML stream.
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return dump_all([data], stream, Dumper=SafeDumper, **kwds) | python | def safe_dump(data, stream=None, **kwds):
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yaml/pyyaml | lib/yaml/__init__.py | add_implicit_resolver | def add_implicit_resolver(tag, regexp, first=None,
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"""
Add an implicit scalar detector.
If an implicit scalar value matches the given regexp,
the corresponding tag is assigned to the scalar.
first is a sequence of possible initial characters or None.
"""
... | python | def add_implicit_resolver(tag, regexp, first=None,
Loader=Loader, Dumper=Dumper):
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Add an implicit scalar detector.
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yaml/pyyaml | lib/yaml/__init__.py | add_path_resolver | def add_path_resolver(tag, path, kind=None, Loader=Loader, Dumper=Dumper):
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Add a path based resolver for the given tag.
A path is a list of keys that forms a path
to a node in the representation tree.
Keys can be string values, integers, or None.
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Loader.add_path_resolver(tag, path, k... | python | def add_path_resolver(tag, path, kind=None, Loader=Loader, Dumper=Dumper):
"""
Add a path based resolver for the given tag.
A path is a list of keys that forms a path
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yaml/pyyaml | lib/yaml/__init__.py | YAMLObject.to_yaml | def to_yaml(cls, dumper, data):
"""
Convert a Python object to a representation node.
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return dumper.represent_yaml_object(cls.yaml_tag, data, cls,
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"""
Convert a Python object to a representation node.
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yaml/pyyaml | lib3/yaml/__init__.py | serialize_all | def serialize_all(nodes, stream=None, Dumper=Dumper,
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yaml/pyyaml | examples/pygments-lexer/yaml.py | something | def something(TokenClass):
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if not text:
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yield match.start(), TokenClass, text
context.pos = match.end()
return callback | python | def something(TokenClass):
"""Do not produce empty tokens."""
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yaml/pyyaml | examples/pygments-lexer/yaml.py | set_indent | def set_indent(TokenClass, implicit=False):
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context.indent_stack.append(context.indent)
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"""Set the previously saved indentation level."""
def callback(lexer, match, context):
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context.indent_stack.append(context.indent)
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yaml/pyyaml | examples/pygments-lexer/yaml.py | parse_block_scalar_empty_line | def parse_block_scalar_empty_line(IndentTokenClass, ContentTokenClass):
"""Process an empty line in a block scalar."""
def callback(lexer, match, context):
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len(text) <= context.block_scalar_indent):
if te... | python | def parse_block_scalar_empty_line(IndentTokenClass, ContentTokenClass):
"""Process an empty line in a block scalar."""
def callback(lexer, match, context):
text = match.group()
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yaml/pyyaml | examples/pygments-lexer/yaml.py | parse_plain_scalar_indent | def parse_plain_scalar_indent(TokenClass):
"""Process indentation spaces in a plain scalar."""
def callback(lexer, match, context):
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context.stack.pop()
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return
if text:
... | python | def parse_plain_scalar_indent(TokenClass):
"""Process indentation spaces in a plain scalar."""
def callback(lexer, match, context):
text = match.group()
if len(text) <= context.indent:
context.stack.pop()
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amueller/word_cloud | wordcloud/tokenization.py | score | def score(count_bigram, count1, count2, n_words):
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# only one words appears in the whole document
return 0
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p1 = c12 / c1
p2 = (c2 - c12)... | python | def score(count_bigram, count1, count2, n_words):
"""Collocation score"""
if n_words <= count1 or n_words <= count2:
# only one words appears in the whole document
return 0
N = n_words
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c1 = count1
c2 = count2
p = c2 / N
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amueller/word_cloud | wordcloud/tokenization.py | process_tokens | def process_tokens(words, normalize_plurals=True):
"""Normalize cases and remove plurals.
Each word is represented by the most common case.
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"""Normalize cases and remove plurals.
Each word is represented by the most common case.
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amueller/word_cloud | examples/colored_by_group.py | GroupedColorFunc.get_color_func | def get_color_func(self, word):
"""Returns a single_color_func associated with the word"""
try:
color_func = next(
color_func for (color_func, words) in self.color_func_to_words
if word in words)
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color_func = self.defa... | python | def get_color_func(self, word):
"""Returns a single_color_func associated with the word"""
try:
color_func = next(
color_func for (color_func, words) in self.color_func_to_words
if word in words)
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amueller/word_cloud | wordcloud/wordcloud.py | random_color_func | def random_color_func(word=None, font_size=None, position=None,
orientation=None, font_path=None, random_state=None):
"""Random hue color generation.
Default coloring method. This just picks a random hue with value 80% and
lumination 50%.
Parameters
----------
word, font_... | python | def random_color_func(word=None, font_size=None, position=None,
orientation=None, font_path=None, random_state=None):
"""Random hue color generation.
Default coloring method. This just picks a random hue with value 80% and
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amueller/word_cloud | wordcloud/wordcloud.py | get_single_color_func | def get_single_color_func(color):
"""Create a color function which returns a single hue and saturation with.
different values (HSV). Accepted values are color strings as usable by
PIL/Pillow.
>>> color_func1 = get_single_color_func('deepskyblue')
>>> color_func2 = get_single_color_func('#00b4d2')
... | python | def get_single_color_func(color):
"""Create a color function which returns a single hue and saturation with.
different values (HSV). Accepted values are color strings as usable by
PIL/Pillow.
>>> color_func1 = get_single_color_func('deepskyblue')
>>> color_func2 = get_single_color_func('#00b4d2')
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amueller/word_cloud | wordcloud/wordcloud.py | WordCloud.generate_from_frequencies | def generate_from_frequencies(self, frequencies, max_font_size=None): # noqa: C901
"""Create a word_cloud from words and frequencies.
Parameters
----------
frequencies : dict from string to float
A contains words and associated frequency.
max_font_size : int
... | python | def generate_from_frequencies(self, frequencies, max_font_size=None): # noqa: C901
"""Create a word_cloud from words and frequencies.
Parameters
----------
frequencies : dict from string to float
A contains words and associated frequency.
max_font_size : int
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amueller/word_cloud | wordcloud/wordcloud.py | WordCloud.process_text | def process_text(self, text):
"""Splits a long text into words, eliminates the stopwords.
Parameters
----------
text : string
The text to be processed.
Returns
-------
words : dict (string, int)
Word tokens with associated frequency.
... | python | def process_text(self, text):
"""Splits a long text into words, eliminates the stopwords.
Parameters
----------
text : string
The text to be processed.
Returns
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words : dict (string, int)
Word tokens with associated frequency.
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amueller/word_cloud | wordcloud/wordcloud.py | WordCloud.generate_from_text | def generate_from_text(self, text):
"""Generate wordcloud from text.
The input "text" is expected to be a natural text. If you pass a sorted
list of words, words will appear in your output twice. To remove this
duplication, set ``collocations=False``.
Calls process_text and gen... | python | def generate_from_text(self, text):
"""Generate wordcloud from text.
The input "text" is expected to be a natural text. If you pass a sorted
list of words, words will appear in your output twice. To remove this
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amueller/word_cloud | wordcloud/wordcloud.py | WordCloud.recolor | def recolor(self, random_state=None, color_func=None, colormap=None):
"""Recolor existing layout.
Applying a new coloring is much faster than generating the whole
wordcloud.
Parameters
----------
random_state : RandomState, int, or None, default=None
If not ... | python | def recolor(self, random_state=None, color_func=None, colormap=None):
"""Recolor existing layout.
Applying a new coloring is much faster than generating the whole
wordcloud.
Parameters
----------
random_state : RandomState, int, or None, default=None
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amueller/word_cloud | wordcloud/wordcloud.py | WordCloud.to_file | def to_file(self, filename):
"""Export to image file.
Parameters
----------
filename : string
Location to write to.
Returns
-------
self
"""
img = self.to_image()
img.save(filename, optimize=True)
return self | python | def to_file(self, filename):
"""Export to image file.
Parameters
----------
filename : string
Location to write to.
Returns
-------
self
"""
img = self.to_image()
img.save(filename, optimize=True)
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amueller/word_cloud | wordcloud/wordcloud.py | WordCloud._get_bolean_mask | def _get_bolean_mask(self, mask):
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boolean_mask = mask == 255
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"""Cast to two dimensional boolean mask."""
if mask.dtype.kind == 'f':
warnings.warn("mask image should be unsigned byte between 0"
" and 255. Got a float array")
if mask.ndim == 2:
boolean_mask = mask == 255
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amueller/word_cloud | wordcloud/wordcloud.py | WordCloud._draw_contour | def _draw_contour(self, img):
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mask = self._get_bolean_mask(self.mask) * 255
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"""Draw mask contour on a pillow image."""
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return img
mask = self._get_bolean_mask(self.mask) * 255
contour = Image.fromarray(mask.astype(np.uint8))
contour = contour.resize(img.size)
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DataDog/integrations-core | datadog_checks_base/datadog_checks/base/checks/kube_leader/mixins.py | KubeLeaderElectionMixin.check_election_status | def check_election_status(self, config):
"""
Retrieves the leader-election annotation from a given object, and
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or no record is found. Monitors on the service-check should have
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"""
Retrieves the leader-election annotation from a given object, and
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | _partition | def _partition(entity, sep):
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | _rpartition | def _rpartition(entity, sep):
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | parse_userinfo | def parse_userinfo(userinfo):
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Reserved characters like ':', '/', '+' and '@' must be escaped
following RFC 3986.
Returns a 2-tuple containing the unescaped username followed
by the unescaped password.
:Paramaters:
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"""Validates the format of user information in a MongoDB URI.
Reserved characters like ':', '/', '+' and '@' must be escaped
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Returns a 2-tuple containing the unescaped username followed
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | parse_ipv6_literal_host | def parse_ipv6_literal_host(entity, default_port):
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Returns a 2-tuple of IPv6 literal followed by port where
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... | python | def parse_ipv6_literal_host(entity, default_port):
"""Validates an IPv6 literal host:port string.
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | parse_host | def parse_host(entity, default_port=DEFAULT_PORT):
"""Validates a host string
Returns a 2-tuple of host followed by port where port is default_port
if it wasn't specified in the string.
:Parameters:
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hostname or IP... | python | def parse_host(entity, default_port=DEFAULT_PORT):
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | _parse_options | def _parse_options(opts, delim):
"""Helper method for split_options which creates the options dict.
Also handles the creation of a list for the URI tag_sets/
readpreferencetags portion."""
options = {}
for opt in opts.split(delim):
key, val = opt.split("=")
if key.lower() == 'readpre... | python | def _parse_options(opts, delim):
"""Helper method for split_options which creates the options dict.
Also handles the creation of a list for the URI tag_sets/
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options = {}
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | split_hosts | def split_hosts(hosts, default_port=DEFAULT_PORT):
"""Takes a string of the form host1[:port],host2[:port]... and
splits it into (host, port) tuples. If [:port] isn't present the
default_port is used.
Returns a set of 2-tuples containing the host name (or IP) followed by
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splits it into (host, port) tuples. If [:port] isn't present the
default_port is used.
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | parse_uri | def parse_uri(uri, default_port=DEFAULT_PORT, validate=True, warn=False):
"""Parse and validate a MongoDB URI.
Returns a dict of the form::
{
'nodelist': <list of (host, port) tuples>,
'username': <username> or None,
'password': <password> or None,
'data... | python | def parse_uri(uri, default_port=DEFAULT_PORT, validate=True, warn=False):
"""Parse and validate a MongoDB URI.
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{
'nodelist': <list of (host, port) tuples>,
'username': <username> or None,
'password': <password> or None,
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/max_staleness_selectors.py | _with_primary | def _with_primary(max_staleness, selection):
"""Apply max_staleness, in seconds, to a Selection with a known primary."""
primary = selection.primary
sds = []
for s in selection.server_descriptions:
if s.server_type == SERVER_TYPE.RSSecondary:
# See max-staleness.rst for explanation ... | python | def _with_primary(max_staleness, selection):
"""Apply max_staleness, in seconds, to a Selection with a known primary."""
primary = selection.primary
sds = []
for s in selection.server_descriptions:
if s.server_type == SERVER_TYPE.RSSecondary:
# See max-staleness.rst for explanation ... | [
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/max_staleness_selectors.py | _no_primary | def _no_primary(max_staleness, selection):
"""Apply max_staleness, in seconds, to a Selection with no known primary."""
# Secondary that's replicated the most recent writes.
smax = selection.secondary_with_max_last_write_date()
if not smax:
# No secondaries and no primary, short-circuit out of h... | python | def _no_primary(max_staleness, selection):
"""Apply max_staleness, in seconds, to a Selection with no known primary."""
# Secondary that's replicated the most recent writes.
smax = selection.secondary_with_max_last_write_date()
if not smax:
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/max_staleness_selectors.py | select | def select(max_staleness, selection):
"""Apply max_staleness, in seconds, to a Selection."""
if max_staleness == -1:
return selection
# Server Selection Spec: If the TopologyType is ReplicaSetWithPrimary or
# ReplicaSetNoPrimary, a client MUST raise an error if maxStaleness <
# heartbeatFre... | python | def select(max_staleness, selection):
"""Apply max_staleness, in seconds, to a Selection."""
if max_staleness == -1:
return selection
# Server Selection Spec: If the TopologyType is ReplicaSetWithPrimary or
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/tokumx.py | TokuMX.create_event | def create_event(self, state, server, agentConfig):
"""Create an event with a message describing the replication
state of a mongo node"""
def get_state_description(state):
if state == 0:
return 'Starting Up'
elif state == 1:
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"""Create an event with a message describing the replication
state of a mongo node"""
def get_state_description(state):
if state == 0:
return 'Starting Up'
elif state == 1:
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DataDog/integrations-core | datadog_checks_base/datadog_checks/base/utils/timeout.py | timeout | def timeout(timeout):
"""
A decorator to timeout a function. Decorated method calls are executed in a separate new thread
with a specified timeout.
Also check if a thread for the same function already exists before creating a new one.
Note: Compatible with Windows (thread based).
"""
def de... | python | def timeout(timeout):
"""
A decorator to timeout a function. Decorated method calls are executed in a separate new thread
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Also check if a thread for the same function already exists before creating a new one.
Note: Compatible with Windows (thread based).
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DataDog/integrations-core | process/datadog_checks/process/process.py | ProcessCheck.find_pids | def find_pids(self, name, search_string, exact_match, ignore_ad=True):
"""
Create a set of pids of selected processes.
Search for search_string
"""
if not self.should_refresh_pid_cache(name):
return self.pid_cache[name]
ad_error_logger = self.log.debug
... | python | def find_pids(self, name, search_string, exact_match, ignore_ad=True):
"""
Create a set of pids of selected processes.
Search for search_string
"""
if not self.should_refresh_pid_cache(name):
return self.pid_cache[name]
ad_error_logger = self.log.debug
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DataDog/integrations-core | process/datadog_checks/process/process.py | ProcessCheck.psutil_wrapper | def psutil_wrapper(self, process, method, accessors, try_sudo, *args, **kwargs):
"""
A psutil wrapper that is calling
* psutil.method(*args, **kwargs) and returns the result
OR
* psutil.method(*args, **kwargs).accessor[i] for each accessors
given in a list, the result bei... | python | def psutil_wrapper(self, process, method, accessors, try_sudo, *args, **kwargs):
"""
A psutil wrapper that is calling
* psutil.method(*args, **kwargs) and returns the result
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DataDog/integrations-core | process/datadog_checks/process/process.py | ProcessCheck._process_service_check | def _process_service_check(self, name, nb_procs, bounds, tags):
"""
Report a service check, for each process in search_string.
Report as OK if the process is in the warning thresholds
CRITICAL out of the critical thresholds
WARNING o... | python | def _process_service_check(self, name, nb_procs, bounds, tags):
"""
Report a service check, for each process in search_string.
Report as OK if the process is in the warning thresholds
CRITICAL out of the critical thresholds
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DataDog/integrations-core | process/datadog_checks/process/process.py | ProcessCheck._filter_by_user | def _filter_by_user(self, user, pids):
"""
Filter pids by it's username.
:param user: string with name of system user
:param pids: set of pids to filter
:return: set of filtered pids
"""
filtered_pids = set()
for pid in pids:
try:
... | python | def _filter_by_user(self, user, pids):
"""
Filter pids by it's username.
:param user: string with name of system user
:param pids: set of pids to filter
:return: set of filtered pids
"""
filtered_pids = set()
for pid in pids:
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DataDog/integrations-core | win32_event_log/datadog_checks/win32_event_log/win32_event_log.py | Win32EventLogWMI._dt_to_wmi | def _dt_to_wmi(self, dt):
''' A wrapper around wmi.from_time to get a WMI-formatted time from a
time struct.
'''
return from_time(
year=dt.year,
month=dt.month,
day=dt.day,
hours=dt.hour,
minutes=dt.minute,
secon... | python | def _dt_to_wmi(self, dt):
''' A wrapper around wmi.from_time to get a WMI-formatted time from a
time struct.
'''
return from_time(
year=dt.year,
month=dt.month,
day=dt.day,
hours=dt.hour,
minutes=dt.minute,
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DataDog/integrations-core | win32_event_log/datadog_checks/win32_event_log/win32_event_log.py | LogEvent._msg_text | def _msg_text(self):
"""
Generate the event's body to send to Datadog.
Consider `event_format` parameter:
* Only use the specified list of event properties.
* If unspecified, default to the EventLog's `Message` or `InsertionStrings`.
"""
msg_text = u""
i... | python | def _msg_text(self):
"""
Generate the event's body to send to Datadog.
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* Only use the specified list of event properties.
* If unspecified, default to the EventLog's `Message` or `InsertionStrings`.
"""
msg_text = u""
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DataDog/integrations-core | win32_event_log/datadog_checks/win32_event_log/win32_event_log.py | LogEvent.is_after | def is_after(self, ts):
''' Compare this event's timestamp to a give timestamp. '''
if self.timestamp >= int(calendar.timegm(ts.timetuple())):
return True
return False | python | def is_after(self, ts):
''' Compare this event's timestamp to a give timestamp. '''
if self.timestamp >= int(calendar.timegm(ts.timetuple())):
return True
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DataDog/integrations-core | win32_event_log/datadog_checks/win32_event_log/win32_event_log.py | LogEvent._wmi_to_ts | def _wmi_to_ts(self, wmi_ts):
''' Convert a wmi formatted timestamp into an epoch.
'''
year, month, day, hour, minute, second, microsecond, tz = to_time(wmi_ts)
tz_delta = timedelta(minutes=int(tz))
if '+' in wmi_ts:
tz_delta = -tz_delta
dt = (
da... | python | def _wmi_to_ts(self, wmi_ts):
''' Convert a wmi formatted timestamp into an epoch.
'''
year, month, day, hour, minute, second, microsecond, tz = to_time(wmi_ts)
tz_delta = timedelta(minutes=int(tz))
if '+' in wmi_ts:
tz_delta = -tz_delta
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DataDog/integrations-core | win32_event_log/datadog_checks/win32_event_log/win32_event_log.py | LogEvent._tags | def _tags(self, tags, event_code):
''' Inject additional tags into the list already supplied to LogEvent.
'''
tags_list = []
if tags is not None:
tags_list += list(tags)
tags_list.append("event_id:{event_id}".format(event_id=event_code))
return tags_list | python | def _tags(self, tags, event_code):
''' Inject additional tags into the list already supplied to LogEvent.
'''
tags_list = []
if tags is not None:
tags_list += list(tags)
tags_list.append("event_id:{event_id}".format(event_id=event_code))
return tags_list | [
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DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor_manager.py | CursorManager.close | def close(self, cursor_id, address):
"""Kill a cursor.
Raises TypeError if cursor_id is not an instance of (int, long).
:Parameters:
- `cursor_id`: cursor id to close
- `address`: the cursor's server's (host, port) pair
.. versionchanged:: 3.0
Now requir... | python | def close(self, cursor_id, address):
"""Kill a cursor.
Raises TypeError if cursor_id is not an instance of (int, long).
:Parameters:
- `cursor_id`: cursor id to close
- `address`: the cursor's server's (host, port) pair
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DataDog/integrations-core | etcd/datadog_checks/etcd/etcd.py | Etcd._get_health_status | def _get_health_status(self, url, ssl_params, timeout):
"""
Don't send the "can connect" service check if we have troubles getting
the health status
"""
try:
r = self._perform_request(url, "/health", ssl_params, timeout)
# we don't use get() here so we can... | python | def _get_health_status(self, url, ssl_params, timeout):
"""
Don't send the "can connect" service check if we have troubles getting
the health status
"""
try:
r = self._perform_request(url, "/health", ssl_params, timeout)
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DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/commands/env/stop.py | stop | def stop(check, env):
"""Stop environments."""
all_checks = check == 'all'
checks = get_configured_checks() if all_checks else [check]
if all_checks:
env_indent = DEFAULT_INDENT
status_indent = DEFAULT_INDENT * 2
else:
env_indent = None
status_indent = DEFAULT_INDENT... | python | def stop(check, env):
"""Stop environments."""
all_checks = check == 'all'
checks = get_configured_checks() if all_checks else [check]
if all_checks:
env_indent = DEFAULT_INDENT
status_indent = DEFAULT_INDENT * 2
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status_indent = DEFAULT_INDENT... | [
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DataDog/integrations-core | istio/datadog_checks/istio/istio.py | Istio.check | def check(self, instance):
"""
Process both the istio_mesh instance and process_mixer instance associated with this instance
"""
# Get the config for the istio_mesh instance
istio_mesh_endpoint = instance.get('istio_mesh_endpoint')
istio_mesh_config = self.config_map[ist... | python | def check(self, instance):
"""
Process both the istio_mesh instance and process_mixer instance associated with this instance
"""
# Get the config for the istio_mesh instance
istio_mesh_endpoint = instance.get('istio_mesh_endpoint')
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DataDog/integrations-core | istio/datadog_checks/istio/istio.py | Istio.create_generic_instances | def create_generic_instances(self, instances):
"""
Generalize each (single) Istio instance into two OpenMetricsBaseCheck instances
"""
generic_instances = []
for instance in instances:
istio_mesh_instance = self._create_istio_mesh_instance(instance)
proce... | python | def create_generic_instances(self, instances):
"""
Generalize each (single) Istio instance into two OpenMetricsBaseCheck instances
"""
generic_instances = []
for instance in instances:
istio_mesh_instance = self._create_istio_mesh_instance(instance)
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DataDog/integrations-core | istio/datadog_checks/istio/istio.py | Istio._create_istio_mesh_instance | def _create_istio_mesh_instance(self, instance):
"""
Grab the istio mesh scraper from the dict and return it if it exists,
otherwise create the scraper and add it to the dict
"""
endpoint = instance.get('istio_mesh_endpoint')
if endpoint is None:
raise CheckE... | python | def _create_istio_mesh_instance(self, instance):
"""
Grab the istio mesh scraper from the dict and return it if it exists,
otherwise create the scraper and add it to the dict
"""
endpoint = instance.get('istio_mesh_endpoint')
if endpoint is None:
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DataDog/integrations-core | istio/datadog_checks/istio/istio.py | Istio._create_process_mixer_instance | def _create_process_mixer_instance(self, instance):
"""
Grab the mixer scraper from the dict and return it if it exists,
otherwise create the scraper and add it to the dict
"""
endpoint = instance.get('mixer_endpoint')
if endpoint is None:
raise CheckException... | python | def _create_process_mixer_instance(self, instance):
"""
Grab the mixer scraper from the dict and return it if it exists,
otherwise create the scraper and add it to the dict
"""
endpoint = instance.get('mixer_endpoint')
if endpoint is None:
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DataDog/integrations-core | marathon/datadog_checks/marathon/marathon.py | Marathon.get_apps_json | def get_apps_json(self, url, timeout, auth, acs_url, ssl_verify, tags, group):
"""
The dictionary containing the apps is cached during collection and reset
at every `check()` call.
"""
if self.apps_response is not None:
return self.apps_response
# Marathon ap... | python | def get_apps_json(self, url, timeout, auth, acs_url, ssl_verify, tags, group):
"""
The dictionary containing the apps is cached during collection and reset
at every `check()` call.
"""
if self.apps_response is not None:
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DataDog/integrations-core | marathon/datadog_checks/marathon/marathon.py | Marathon.ensure_queue_count | def ensure_queue_count(
self, queued, url, timeout, auth, acs_url, ssl_verify, tags=None, label_tags=None, group=None
):
"""
Ensure `marathon.queue.count` is reported as zero for apps without queued instances.
"""
metric_name = '{}.count'.format(self.QUEUE_PREFIX)
ap... | python | def ensure_queue_count(
self, queued, url, timeout, auth, acs_url, ssl_verify, tags=None, label_tags=None, group=None
):
"""
Ensure `marathon.queue.count` is reported as zero for apps without queued instances.
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metric_name = '{}.count'.format(self.QUEUE_PREFIX)
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DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/commands/validate/py3.py | py3 | def py3(check):
"""Verify if a custom check or integration can run on python 3. CHECK
can be an integration name or a valid path to a Python module or package folder.
"""
if check in get_valid_checks():
path_to_module = os.path.dirname(get_version_file(check))
else:
path_to_module =... | python | def py3(check):
"""Verify if a custom check or integration can run on python 3. CHECK
can be an integration name or a valid path to a Python module or package folder.
"""
if check in get_valid_checks():
path_to_module = os.path.dirname(get_version_file(check))
else:
path_to_module =... | [
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DataDog/integrations-core | http_check/datadog_checks/http_check/config.py | from_instance | def from_instance(instance, default_ca_certs=None):
"""
Create a config object from an instance dictionary
"""
method = instance.get('method', 'get')
data = instance.get('data', {})
tags = instance.get('tags', [])
ntlm_domain = instance.get('ntlm_domain')
username = instance.get('usernam... | python | def from_instance(instance, default_ca_certs=None):
"""
Create a config object from an instance dictionary
"""
method = instance.get('method', 'get')
data = instance.get('data', {})
tags = instance.get('tags', [])
ntlm_domain = instance.get('ntlm_domain')
username = instance.get('usernam... | [
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DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/release.py | update_version_module | def update_version_module(check_name, old_ver, new_ver):
"""
Change the Python code in the __about__.py module so that `__version__`
contains the new value.
"""
version_file = get_version_file(check_name)
contents = read_file(version_file)
contents = contents.replace(old_ver, new_ver)
w... | python | def update_version_module(check_name, old_ver, new_ver):
"""
Change the Python code in the __about__.py module so that `__version__`
contains the new value.
"""
version_file = get_version_file(check_name)
contents = read_file(version_file)
contents = contents.replace(old_ver, new_ver)
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DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/release.py | get_agent_requirement_line | def get_agent_requirement_line(check, version):
"""
Compose a text line to be used in a requirements.txt file to install a check
pinned to a specific version.
"""
package_name = get_package_name(check)
# no manifest
if check in ('datadog_checks_base', 'datadog_checks_downloader'):
r... | python | def get_agent_requirement_line(check, version):
"""
Compose a text line to be used in a requirements.txt file to install a check
pinned to a specific version.
"""
package_name = get_package_name(check)
# no manifest
if check in ('datadog_checks_base', 'datadog_checks_downloader'):
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DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/release.py | update_agent_requirements | def update_agent_requirements(req_file, check, newline):
"""
Replace the requirements line for the given check
"""
package_name = get_package_name(check)
lines = read_file_lines(req_file)
for i, line in enumerate(lines):
current_package_name = line.split('==')[0]
if current_pac... | python | def update_agent_requirements(req_file, check, newline):
"""
Replace the requirements line for the given check
"""
package_name = get_package_name(check)
lines = read_file_lines(req_file)
for i, line in enumerate(lines):
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DataDog/integrations-core | directory/datadog_checks/directory/traverse.py | _walk | def _walk(top):
"""Modified version of https://docs.python.org/3/library/os.html#os.scandir
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directly to take advantage of possible cached os.stat calls.
"""
dirs = []
nondirs = []
try:
scandir_iter = scandi... | python | def _walk(top):
"""Modified version of https://docs.python.org/3/library/os.html#os.scandir
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dirs = []
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._yarn_cluster_metrics | def _yarn_cluster_metrics(self, rm_address, instance, addl_tags):
"""
Get metrics related to YARN cluster
"""
metrics_json = self._rest_request_to_json(rm_address, instance, YARN_CLUSTER_METRICS_PATH, addl_tags)
if metrics_json:
yarn_metrics = metrics_json[YARN_CLUS... | python | def _yarn_cluster_metrics(self, rm_address, instance, addl_tags):
"""
Get metrics related to YARN cluster
"""
metrics_json = self._rest_request_to_json(rm_address, instance, YARN_CLUSTER_METRICS_PATH, addl_tags)
if metrics_json:
yarn_metrics = metrics_json[YARN_CLUS... | [
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._yarn_app_metrics | def _yarn_app_metrics(self, rm_address, instance, app_tags, addl_tags):
"""
Get metrics for running applications
"""
metrics_json = self._rest_request_to_json(
rm_address, instance, YARN_APPS_PATH, addl_tags, states=YARN_APPLICATION_STATES
)
if metrics_json a... | python | def _yarn_app_metrics(self, rm_address, instance, app_tags, addl_tags):
"""
Get metrics for running applications
"""
metrics_json = self._rest_request_to_json(
rm_address, instance, YARN_APPS_PATH, addl_tags, states=YARN_APPLICATION_STATES
)
if metrics_json a... | [
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._yarn_node_metrics | def _yarn_node_metrics(self, rm_address, instance, addl_tags):
"""
Get metrics related to YARN nodes
"""
metrics_json = self._rest_request_to_json(rm_address, instance, YARN_NODES_PATH, addl_tags)
if metrics_json and metrics_json['nodes'] is not None and metrics_json['nodes']['n... | python | def _yarn_node_metrics(self, rm_address, instance, addl_tags):
"""
Get metrics related to YARN nodes
"""
metrics_json = self._rest_request_to_json(rm_address, instance, YARN_NODES_PATH, addl_tags)
if metrics_json and metrics_json['nodes'] is not None and metrics_json['nodes']['n... | [
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._yarn_scheduler_metrics | def _yarn_scheduler_metrics(self, rm_address, instance, addl_tags, queue_blacklist):
"""
Get metrics from YARN scheduler
"""
metrics_json = self._rest_request_to_json(rm_address, instance, YARN_SCHEDULER_PATH, addl_tags)
try:
metrics_json = metrics_json['scheduler'][... | python | def _yarn_scheduler_metrics(self, rm_address, instance, addl_tags, queue_blacklist):
"""
Get metrics from YARN scheduler
"""
metrics_json = self._rest_request_to_json(rm_address, instance, YARN_SCHEDULER_PATH, addl_tags)
try:
metrics_json = metrics_json['scheduler'][... | [
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._yarn_capacity_scheduler_metrics | def _yarn_capacity_scheduler_metrics(self, metrics_json, addl_tags, queue_blacklist):
"""
Get metrics from YARN scheduler if it's type is capacityScheduler
"""
tags = ['queue_name:{}'.format(metrics_json['queueName'])]
tags.extend(addl_tags)
self._set_yarn_metrics_from_j... | python | def _yarn_capacity_scheduler_metrics(self, metrics_json, addl_tags, queue_blacklist):
"""
Get metrics from YARN scheduler if it's type is capacityScheduler
"""
tags = ['queue_name:{}'.format(metrics_json['queueName'])]
tags.extend(addl_tags)
self._set_yarn_metrics_from_j... | [
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._set_yarn_metrics_from_json | def _set_yarn_metrics_from_json(self, tags, metrics_json, yarn_metrics):
"""
Parse the JSON response and set the metrics
"""
for dict_path, metric in iteritems(yarn_metrics):
metric_name, metric_type = metric
metric_value = self._get_value_from_json(dict_path, me... | python | def _set_yarn_metrics_from_json(self, tags, metrics_json, yarn_metrics):
"""
Parse the JSON response and set the metrics
"""
for dict_path, metric in iteritems(yarn_metrics):
metric_name, metric_type = metric
metric_value = self._get_value_from_json(dict_path, me... | [
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._get_value_from_json | def _get_value_from_json(self, dict_path, metrics_json):
"""
Get a value from a dictionary under N keys, represented as str("key1.key2...key{n}")
"""
for key in dict_path.split('.'):
if key in metrics_json:
metrics_json = metrics_json.get(key)
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"""
Get a value from a dictionary under N keys, represented as str("key1.key2...key{n}")
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for key in dict_path.split('.'):
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._set_metric | def _set_metric(self, metric_name, metric_type, value, tags=None, device_name=None):
"""
Set a metric
"""
if metric_type == GAUGE:
self.gauge(metric_name, value, tags=tags, device_name=device_name)
elif metric_type == INCREMENT:
self.increment(metric_name,... | python | def _set_metric(self, metric_name, metric_type, value, tags=None, device_name=None):
"""
Set a metric
"""
if metric_type == GAUGE:
self.gauge(metric_name, value, tags=tags, device_name=device_name)
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self.increment(metric_name,... | [
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._rest_request_to_json | def _rest_request_to_json(self, url, instance, object_path, tags, *args, **kwargs):
"""
Query the given URL and return the JSON response
"""
service_check_tags = ['url:{}'.format(self._get_url_base(url))] + tags
service_check_tags = list(set(service_check_tags))
if objec... | python | def _rest_request_to_json(self, url, instance, object_path, tags, *args, **kwargs):
"""
Query the given URL and return the JSON response
"""
service_check_tags = ['url:{}'.format(self._get_url_base(url))] + tags
service_check_tags = list(set(service_check_tags))
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._join_url_dir | def _join_url_dir(self, url, *args):
"""
Join a URL with multiple directories
"""
for path in args:
url = url.rstrip('/') + '/'
url = urljoin(url, path.lstrip('/'))
return url | python | def _join_url_dir(self, url, *args):
"""
Join a URL with multiple directories
"""
for path in args:
url = url.rstrip('/') + '/'
url = urljoin(url, path.lstrip('/'))
return url | [
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DataDog/integrations-core | yarn/datadog_checks/yarn/yarn.py | YarnCheck._get_url_base | def _get_url_base(self, url):
"""
Return the base of a URL
"""
s = urlsplit(url)
return urlunsplit([s.scheme, s.netloc, '', '', '']) | python | def _get_url_base(self, url):
"""
Return the base of a URL
"""
s = urlsplit(url)
return urlunsplit([s.scheme, s.netloc, '', '', '']) | [
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DataDog/integrations-core | ntp/datadog_checks/ntp/ntp.py | NtpCheck._get_service_port | def _get_service_port(self, instance):
"""
Get the ntp server port
"""
host = instance.get('host', DEFAULT_HOST)
port = instance.get('port', DEFAULT_PORT)
# default port is the name of the service but lookup would fail
# if the /etc/services file is missing. In th... | python | def _get_service_port(self, instance):
"""
Get the ntp server port
"""
host = instance.get('host', DEFAULT_HOST)
port = instance.get('port', DEFAULT_PORT)
# default port is the name of the service but lookup would fail
# if the /etc/services file is missing. In th... | [
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DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._create_cadvisor_prometheus_instance | def _create_cadvisor_prometheus_instance(self, instance):
"""
Create a copy of the instance and set default values.
This is so the base class can create a scraper_config with the proper values.
"""
cadvisor_instance = deepcopy(instance)
cadvisor_instance.update(
... | python | def _create_cadvisor_prometheus_instance(self, instance):
"""
Create a copy of the instance and set default values.
This is so the base class can create a scraper_config with the proper values.
"""
cadvisor_instance = deepcopy(instance)
cadvisor_instance.update(
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DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._is_container_metric | def _is_container_metric(labels):
"""
Return whether a metric is about a container or not.
It can be about pods, or even higher levels in the cgroup hierarchy
and we don't want to report on that.
:param metric:
:return: bool
"""
for lbl in CONTAINER_LABELS... | python | def _is_container_metric(labels):
"""
Return whether a metric is about a container or not.
It can be about pods, or even higher levels in the cgroup hierarchy
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:param metric:
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DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._is_pod_metric | def _is_pod_metric(labels):
"""
Return whether a metric is about a pod or not.
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:param metric
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"""
Return whether a metric is about a pod or not.
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:param metric
:return bool
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DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._get_container_id | def _get_container_id(self, labels):
"""
Should only be called on a container-scoped metric
It gets the container id from the podlist using the metrics labels
:param labels
:return str or None
"""
namespace = CadvisorPrometheusScraperMixin._get_container_label(la... | python | def _get_container_id(self, labels):
"""
Should only be called on a container-scoped metric
It gets the container id from the podlist using the metrics labels
:param labels
:return str or None
"""
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DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._get_entity_id_if_container_metric | def _get_entity_id_if_container_metric(self, labels):
"""
Checks the labels indicate a container metric,
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:param labels
:return str or None
"""
if CadvisorPrometheusScraperMixin._is_container_metric(labels):
pod... | python | def _get_entity_id_if_container_metric(self, labels):
"""
Checks the labels indicate a container metric,
then extract the container id from them.
:param labels
:return str or None
"""
if CadvisorPrometheusScraperMixin._is_container_metric(labels):
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