partition stringclasses 3
values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
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train | get_single_color_func | 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') | wordcloud/wordcloud.py | 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')
... | 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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train | WordCloud.generate_from_frequencies | Create a word_cloud from words and frequencies.
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frequencies : dict from string to float
A contains words and associated frequency.
max_font_size : int
Use this font-size instead of self.max_font_size
Returns
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... | wordcloud/wordcloud.py | 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
... | 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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train | WordCloud.process_text | Splits a long text into words, eliminates the stopwords.
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text : string
The text to be processed.
Returns
-------
words : dict (string, int)
Word tokens with associated frequency.
..versionchanged:: 1.2.2
... | wordcloud/wordcloud.py | 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.
... | 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.
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train | WordCloud.generate_from_text | Generate wordcloud from text.
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list of words, words will appear in your output twice. To remove this
duplication, set ``collocations=False``.
Calls process_text and generate_from_frequencies.
..versionchang... | wordcloud/wordcloud.py | 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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Calls process_text and gen... | 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
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train | WordCloud.recolor | 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 None, a fixed random state is used. If an int is given, this
is used ... | wordcloud/wordcloud.py | 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 ... | 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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train | WordCloud.to_file | Export to image file.
Parameters
----------
filename : string
Location to write to.
Returns
-------
self | wordcloud/wordcloud.py | 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 | def to_file(self, filename):
"""Export to image file.
Parameters
----------
filename : string
Location to write to.
Returns
-------
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"""
img = self.to_image()
img.save(filename, optimize=True)
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train | WordCloud._get_bolean_mask | Cast to two dimensional boolean mask. | wordcloud/wordcloud.py | def _get_bolean_mask(self, mask):
"""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
... | def _get_bolean_mask(self, mask):
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train | WordCloud._draw_contour | Draw mask contour on a pillow image. | wordcloud/wordcloud.py | def _draw_contour(self, img):
"""Draw mask contour on a pillow image."""
if self.mask is None or self.contour_width == 0:
return img
mask = self._get_bolean_mask(self.mask) * 255
contour = Image.fromarray(mask.astype(np.uint8))
contour = contour.resize(img.size)
... | def _draw_contour(self, img):
"""Draw mask contour on a pillow image."""
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mask = self._get_bolean_mask(self.mask) * 255
contour = Image.fromarray(mask.astype(np.uint8))
contour = contour.resize(img.size)
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train | KubeLeaderElectionMixin.check_election_status | Retrieves the leader-election annotation from a given object, and
submits metrics and a service check.
An integration warning is sent if the object is not retrievable,
or no record is found. Monitors on the service-check should have
no-data alerts enabled to account for this.
T... | datadog_checks_base/datadog_checks/base/checks/kube_leader/mixins.py | def check_election_status(self, config):
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Retrieves the leader-election annotation from a given object, and
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An integration warning is sent if the object is not retrievable,
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... | def check_election_status(self, config):
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Split the string at the first occurrence of sep, and return a
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... | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | def _partition(entity, sep):
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our own that mimics str.partition from later releases.
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3-tuple containing the part before the separator, the separator
itself, and the part after the... | def _partition(entity, sep):
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Split the string at the last occurrence of sep, and return a
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train | parse_userinfo | Validates the format of user information in a MongoDB URI.
Reserved characters like ':', '/', '+' and '@' must be escaped
following RFC 3986.
Returns a 2-tuple containing the unescaped username followed
by the unescaped password.
:Paramaters:
- `userinfo`: A string of the form <username>:<... | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | def parse_userinfo(userinfo):
"""Validates the format of user information in a MongoDB URI.
Reserved characters like ':', '/', '+' and '@' must be escaped
following RFC 3986.
Returns a 2-tuple containing the unescaped username followed
by the unescaped password.
:Paramaters:
- `userinf... | def parse_userinfo(userinfo):
"""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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train | parse_ipv6_literal_host | Validates an IPv6 literal host:port string.
Returns a 2-tuple of IPv6 literal followed by port where
port is default_port if it wasn't specified in entity.
:Parameters:
- `entity`: A string that represents an IPv6 literal enclosed
in braces (e.g. '[::1]' or '[::1]:27017').
... | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | def parse_ipv6_literal_host(entity, default_port):
"""Validates an IPv6 literal host:port string.
Returns a 2-tuple of IPv6 literal followed by port where
port is default_port if it wasn't specified in entity.
:Parameters:
- `entity`: A string that represents an IPv6 literal enclosed
... | def parse_ipv6_literal_host(entity, default_port):
"""Validates an IPv6 literal host:port string.
Returns a 2-tuple of IPv6 literal followed by port where
port is default_port if it wasn't specified in entity.
:Parameters:
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train | parse_host | 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:
- `entity`: A host or host:port string where host could be a
hostname or IP address.
- `default_port`: The port number to use... | tokumx/datadog_checks/tokumx/vendor/pymongo/uri_parser.py | 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:
- `entity`: A host or host:port string where host could be a
hostname or IP... | 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
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:Parameters:
- `entity`: A host or host:port string where host could be a
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train | parse_uri | Parse and validate a MongoDB URI.
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train | _with_primary | Apply max_staleness, in seconds, to a Selection with a known primary. | tokumx/datadog_checks/tokumx/vendor/pymongo/max_staleness_selectors.py | def _with_primary(max_staleness, selection):
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train | _no_primary | Apply max_staleness, in seconds, to a Selection with no known primary. | tokumx/datadog_checks/tokumx/vendor/pymongo/max_staleness_selectors.py | def _no_primary(max_staleness, selection):
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train | select | Apply max_staleness, in seconds, to a Selection. | tokumx/datadog_checks/tokumx/vendor/pymongo/max_staleness_selectors.py | def select(max_staleness, selection):
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train | TokuMX.create_event | Create an event with a message describing the replication
state of a mongo node | tokumx/datadog_checks/tokumx/tokumx.py | def create_event(self, state, server, agentConfig):
"""Create an event with a message describing the replication
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def get_state_description(state):
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train | 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). | datadog_checks_base/datadog_checks/base/utils/timeout.py | def timeout(timeout):
"""
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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).
"""
def de... | def timeout(timeout):
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train | ProcessCheck.find_pids | Create a set of pids of selected processes.
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"""
Create a set of pids of selected processes.
Search for search_string
"""
if not self.should_refresh_pid_cache(name):
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... | def find_pids(self, name, search_string, exact_match, ignore_ad=True):
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train | ProcessCheck.psutil_wrapper | A psutil wrapper that is calling
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train | ProcessCheck._process_service_check | Report a service check, for each process in search_string.
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Report a service check, for each process in search_string.
Report as OK if the process is in the warning thresholds
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train | ProcessCheck._filter_by_user | Filter pids by it's username.
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:return: set of filtered pids | process/datadog_checks/process/process.py | def _filter_by_user(self, user, pids):
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train | Win32EventLogWMI._dt_to_wmi | A wrapper around wmi.from_time to get a WMI-formatted time from a
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'''
return from_time(
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month=dt.month,
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hours=dt.hour,
minutes=dt.minute,
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train | LogEvent._msg_text | Generate the event's body to send to Datadog.
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* If unspecified, default to the EventLog's `Message` or `InsertionStrings`. | win32_event_log/datadog_checks/win32_event_log/win32_event_log.py | def _msg_text(self):
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train | LogEvent.is_after | Compare this event's timestamp to a give timestamp. | win32_event_log/datadog_checks/win32_event_log/win32_event_log.py | def is_after(self, ts):
''' Compare this event's timestamp to a give timestamp. '''
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''' Compare this event's timestamp to a give timestamp. '''
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train | LogEvent._wmi_to_ts | Convert a wmi formatted timestamp into an epoch. | win32_event_log/datadog_checks/win32_event_log/win32_event_log.py | def _wmi_to_ts(self, wmi_ts):
''' Convert a wmi formatted timestamp into an epoch.
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year, month, day, hour, minute, second, microsecond, tz = to_time(wmi_ts)
tz_delta = timedelta(minutes=int(tz))
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da... | def _wmi_to_ts(self, wmi_ts):
''' Convert a wmi formatted timestamp into an epoch.
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tz_delta = timedelta(minutes=int(tz))
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train | LogEvent._tags | Inject additional tags into the list already supplied to LogEvent. | win32_event_log/datadog_checks/win32_event_log/win32_event_log.py | 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 | def _tags(self, tags, event_code):
''' Inject additional tags into the list already supplied to LogEvent.
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tags_list = []
if tags is not None:
tags_list += list(tags)
tags_list.append("event_id:{event_id}".format(event_id=event_code))
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train | CursorManager.close | 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 requires an `address` argument. | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor_manager.py | 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... | def close(self, cursor_id, address):
"""Kill a cursor.
Raises TypeError if cursor_id is not an instance of (int, long).
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- `cursor_id`: cursor id to close
- `address`: the cursor's server's (host, port) pair
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train | Etcd._get_health_status | Don't send the "can connect" service check if we have troubles getting
the health status | etcd/datadog_checks/etcd/etcd.py | def _get_health_status(self, url, ssl_params, timeout):
"""
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"""
try:
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# we don't use get() here so we can... | def _get_health_status(self, url, ssl_params, timeout):
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Don't send the "can connect" service check if we have troubles getting
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train | stop | Stop environments. | datadog_checks_dev/datadog_checks/dev/tooling/commands/env/stop.py | 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... | def stop(check, env):
"""Stop environments."""
all_checks = check == 'all'
checks = get_configured_checks() if all_checks else [check]
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env_indent = DEFAULT_INDENT
status_indent = DEFAULT_INDENT * 2
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train | Istio.check | Process both the istio_mesh instance and process_mixer instance associated with this instance | istio/datadog_checks/istio/istio.py | def check(self, instance):
"""
Process both the istio_mesh instance and process_mixer instance associated with this instance
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# Get the config for the istio_mesh instance
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train | Istio.create_generic_instances | Generalize each (single) Istio instance into two OpenMetricsBaseCheck instances | istio/datadog_checks/istio/istio.py | 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... | def create_generic_instances(self, instances):
"""
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generic_instances = []
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istio_mesh_instance = self._create_istio_mesh_instance(instance)
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train | Istio._create_istio_mesh_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 | istio/datadog_checks/istio/istio.py | 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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"""
Grab the istio mesh scraper from the dict and return it if it exists,
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train | Istio._create_process_mixer_instance | Grab the mixer scraper from the dict and return it if it exists,
otherwise create the scraper and add it to the dict | istio/datadog_checks/istio/istio.py | def _create_process_mixer_instance(self, instance):
"""
Grab the mixer scraper from the dict and return it if it exists,
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"""
endpoint = instance.get('mixer_endpoint')
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raise CheckException... | def _create_process_mixer_instance(self, instance):
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Grab the mixer scraper from the dict and return it if it exists,
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"""
endpoint = instance.get('mixer_endpoint')
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train | Marathon.get_apps_json | The dictionary containing the apps is cached during collection and reset
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The dictionary containing the apps is cached during collection and reset
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"""
if self.apps_response is not None:
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# Marathon ap... | def get_apps_json(self, url, timeout, auth, acs_url, ssl_verify, tags, group):
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if self.apps_response is not None:
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train | Marathon.ensure_queue_count | Ensure `marathon.queue.count` is reported as zero for apps without queued instances. | marathon/datadog_checks/marathon/marathon.py | def ensure_queue_count(
self, queued, url, timeout, auth, acs_url, ssl_verify, tags=None, label_tags=None, group=None
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Ensure `marathon.queue.count` is reported as zero for apps without queued instances.
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metric_name = '{}.count'.format(self.QUEUE_PREFIX)
ap... | def ensure_queue_count(
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Ensure `marathon.queue.count` is reported as zero for apps without queued instances.
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train | py3 | 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. | datadog_checks_dev/datadog_checks/dev/tooling/commands/validate/py3.py | 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 =... | def py3(check):
"""Verify if a custom check or integration can run on python 3. CHECK
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if check in get_valid_checks():
path_to_module = os.path.dirname(get_version_file(check))
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train | from_instance | Create a config object from an instance dictionary | http_check/datadog_checks/http_check/config.py | 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... | 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 | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/http_check/datadog_checks/http_check/config.py#L24-L94 | [
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train | update_version_module | Change the Python code in the __about__.py module so that `__version__`
contains the new value. | datadog_checks_dev/datadog_checks/dev/tooling/release.py | 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... | def update_version_module(check_name, old_ver, new_ver):
"""
Change the Python code in the __about__.py module so that `__version__`
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"""
version_file = get_version_file(check_name)
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train | get_agent_requirement_line | Compose a text line to be used in a requirements.txt file to install a check
pinned to a specific version. | datadog_checks_dev/datadog_checks/dev/tooling/release.py | 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... | def get_agent_requirement_line(check, version):
"""
Compose a text line to be used in a requirements.txt file to install a check
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"""
package_name = get_package_name(check)
# no manifest
if check in ('datadog_checks_base', 'datadog_checks_downloader'):
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train | update_agent_requirements | Replace the requirements line for the given check | datadog_checks_dev/datadog_checks/dev/tooling/release.py | 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... | 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)
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train | _walk | Modified version of https://docs.python.org/3/library/os.html#os.scandir
that returns https://docs.python.org/3/library/os.html#os.DirEntry for files
directly to take advantage of possible cached os.stat calls. | directory/datadog_checks/directory/traverse.py | 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:
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"""Modified version of https://docs.python.org/3/library/os.html#os.scandir
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"""
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train | YarnCheck._yarn_cluster_metrics | Get metrics related to YARN cluster | yarn/datadog_checks/yarn/yarn.py | 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... | 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)
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yarn_metrics = metrics_json[YARN_CLUS... | [
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train | YarnCheck._yarn_app_metrics | Get metrics for running applications | yarn/datadog_checks/yarn/yarn.py | 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... | 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 | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/yarn/datadog_checks/yarn/yarn.py#L199-L222 | [
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train | YarnCheck._yarn_node_metrics | Get metrics related to YARN nodes | yarn/datadog_checks/yarn/yarn.py | 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... | 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)
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train | YarnCheck._yarn_scheduler_metrics | Get metrics from YARN scheduler | yarn/datadog_checks/yarn/yarn.py | 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'][... | 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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train | YarnCheck._yarn_capacity_scheduler_metrics | Get metrics from YARN scheduler if it's type is capacityScheduler | yarn/datadog_checks/yarn/yarn.py | 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... | 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'])]
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train | YarnCheck._set_yarn_metrics_from_json | Parse the JSON response and set the metrics | yarn/datadog_checks/yarn/yarn.py | 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... | 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
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train | YarnCheck._get_value_from_json | Get a value from a dictionary under N keys, represented as str("key1.key2...key{n}") | yarn/datadog_checks/yarn/yarn.py | 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)
else... | 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('.'):
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train | YarnCheck._set_metric | Set a metric | yarn/datadog_checks/yarn/yarn.py | 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,... | def _set_metric(self, metric_name, metric_type, value, tags=None, device_name=None):
"""
Set a metric
"""
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self.gauge(metric_name, value, tags=tags, device_name=device_name)
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train | YarnCheck._rest_request_to_json | Query the given URL and return the JSON response | yarn/datadog_checks/yarn/yarn.py | 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... | 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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train | YarnCheck._join_url_dir | Join a URL with multiple directories | yarn/datadog_checks/yarn/yarn.py | def _join_url_dir(self, url, *args):
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Join a URL with multiple directories
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Join a URL with multiple directories
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Get the ntp server port
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train | CadvisorPrometheusScraperMixin._is_pod_metric | Return whether a metric is about a pod or not.
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train | CadvisorPrometheusScraperMixin._get_container_id | Should only be called on a container-scoped metric
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train | CadvisorPrometheusScraperMixin._get_entity_id_if_container_metric | Checks the labels indicate a container metric,
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train | CadvisorPrometheusScraperMixin._get_pod_uid | Return the id of a pod
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train | CadvisorPrometheusScraperMixin._is_pod_host_networked | Return if the pod is on host Network
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train | CadvisorPrometheusScraperMixin._get_pod_by_metric_label | :param labels: metric labels: iterable
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train | CadvisorPrometheusScraperMixin._process_container_metric | Takes a simple metric about a container, reports it as a rate or gauge.
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train | CadvisorPrometheusScraperMixin._process_pod_rate | Takes a simple metric about a pod, reports it as a rate.
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train | CadvisorPrometheusScraperMixin._process_usage_metric | Takes a metric object, a metric name, and a cache dict where it will store
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train | CadvisorPrometheusScraperMixin._process_limit_metric | Reports limit metrics if m_name is not an empty string,
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train | CadvisorPrometheusScraperMixin.container_fs_usage_bytes | Number of bytes that are consumed by the container on this filesystem. | kubelet/datadog_checks/kubelet/prometheus.py | def container_fs_usage_bytes(self, metric, scraper_config):
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train | CadvisorPrometheusScraperMixin.container_fs_limit_bytes | Number of bytes that can be consumed by the container on this filesystem.
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train | MongoDb._report_replica_set_state | Report the member's replica set state
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train | MongoDb.hostname_for_event | Return a reasonable hostname for a replset membership event to mention. | mongo/datadog_checks/mongo/mongo.py | def hostname_for_event(self, clean_server_name):
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train | MongoDb.create_event | Create an event with a message describing the replication
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train | MongoDb._build_metric_list_to_collect | Build the metric list to collect based on the instance preferences. | mongo/datadog_checks/mongo/mongo.py | def _build_metric_list_to_collect(self, additional_metrics):
"""
Build the metric list to collect based on the instance preferences.
"""
metrics_to_collect = {}
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train | MongoDb._get_metrics_to_collect | Return and cache the list of metrics to collect. | mongo/datadog_checks/mongo/mongo.py | def _get_metrics_to_collect(self, instance_key, additional_metrics):
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Return and cache the list of metrics to collect.
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train | MongoDb._resolve_metric | Return the submit method and the metric name to use.
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* If available, the normalized metric name alias
* (Or) the normalized original metric name | mongo/datadog_checks/mongo/mongo.py | def _resolve_metric(self, original_metric_name, metrics_to_collect, prefix=""):
"""
Return the submit method and the metric name to use.
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train | MongoDb._normalize | Replace case-sensitive metric name characters, normalize the metric name,
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"""
Replace case-sensitive metric name characters, normalize the metric name,
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train | MongoDb._authenticate | Authenticate to the database.
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* X.509
More information:
https://api.mongodb.com/python/current/examples/authentication.html | mongo/datadog_checks/mongo/mongo.py | def _authenticate(self, database, username, password, use_x509, server_name, service_check_tags):
"""
Authenticate to the database.
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https://api.mongodb.com/python/current/examples/authenticati... | def _authenticate(self, database, username, password, use_x509, server_name, service_check_tags):
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Authenticate to the database.
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train | MongoDb._parse_uri | Parses a MongoDB-formatted URI (e.g. mongodb://user:pass@server/db) and returns parsed elements
and a sanitized URI. | mongo/datadog_checks/mongo/mongo.py | def _parse_uri(cls, server, sanitize_username=False):
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train | MongoDb._collect_indexes_stats | Collect indexes statistics for all collections in the configuration.
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"""
Collect indexes statistics for all collections in the configuration.
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"""
for coll_name in instance.get('collections', []):
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"""
Collect indexes statistics for all collections in the configuration.
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"""
for coll_name in instance.get('collections', []):
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train | MongoDb.check | Returns a dictionary that looks a lot like what's sent back by
db.serverStatus() | mongo/datadog_checks/mongo/mongo.py | def check(self, instance):
"""
Returns a dictionary that looks a lot like what's sent back by
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"""
def total_seconds(td):
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Returns total seconds of a timedelta in a way that's safe for
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Returns a dictionary that looks a lot like what's sent back by
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Returns total seconds of a timedelta in a way that's safe for
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train | get_normal_connection | Get the connection either with a username and password or without | ibm_mq/datadog_checks/ibm_mq/connection.py | def get_normal_connection(config):
"""
Get the connection either with a username and password or without
"""
if config.username and config.password:
log.debug("connecting with username and password")
queue_manager = pymqi.connect(
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train | get_ssl_connection | Get the connection with SSL | ibm_mq/datadog_checks/ibm_mq/connection.py | def get_ssl_connection(config):
"""
Get the connection with SSL
"""
cd = pymqi.CD()
cd.ChannelName = config.channel
cd.ConnectionName = config.host_and_port
cd.ChannelType = pymqi.CMQC.MQCHT_CLNTCONN
cd.TransportType = pymqi.CMQC.MQXPT_TCP
cd.SSLCipherSpec = config.ssl_cipher_spec
... | def get_ssl_connection(config):
"""
Get the connection with SSL
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cd = pymqi.CD()
cd.ChannelName = config.channel
cd.ConnectionName = config.host_and_port
cd.ChannelType = pymqi.CMQC.MQCHT_CLNTCONN
cd.TransportType = pymqi.CMQC.MQXPT_TCP
cd.SSLCipherSpec = config.ssl_cipher_spec
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train | check_run | Run an Agent check. | datadog_checks_dev/datadog_checks/dev/tooling/commands/env/check.py | def check_run(check, env, rate, times, pause, delay, log_level, as_json, break_point):
"""Run an Agent check."""
envs = get_configured_envs(check)
if not envs:
echo_failure('No active environments found for `{}`.'.format(check))
echo_info('See what is available to start via `ddev env ls {}`.... | def check_run(check, env, rate, times, pause, delay, log_level, as_json, break_point):
"""Run an Agent check."""
envs = get_configured_envs(check)
if not envs:
echo_failure('No active environments found for `{}`.'.format(check))
echo_info('See what is available to start via `ddev env ls {}`.... | [
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train | OpenStackScope.get_user_identity | Parse user identity out of init_config
To guarantee a uniquely identifiable user, expects
{"user": {"name": "my_username", "password": "my_password",
"domain": {"id": "my_domain_id"}
}
} | openstack/datadog_checks/openstack/openstack.py | def get_user_identity(cls, instance_config):
"""
Parse user identity out of init_config
To guarantee a uniquely identifiable user, expects
{"user": {"name": "my_username", "password": "my_password",
"domain": {"id": "my_domain_id"}
}
}
... | def get_user_identity(cls, instance_config):
"""
Parse user identity out of init_config
To guarantee a uniquely identifiable user, expects
{"user": {"name": "my_username", "password": "my_password",
"domain": {"id": "my_domain_id"}
}
}
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train | OpenStackScope.get_auth_scope | Parse authorization scope out of init_config
To guarantee a uniquely identifiable scope, expects either:
{'project': {'name': 'my_project', 'domain': {'id': 'my_domain_id'}}}
OR
{'project': {'id': 'my_project_id'}} | openstack/datadog_checks/openstack/openstack.py | def get_auth_scope(cls, instance_config):
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Parse authorization scope out of init_config
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Parse authorization scope out of init_config
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train | KeystoneCatalog.get_neutron_endpoint | Parse the service catalog returned by the Identity API for an endpoint matching the Neutron service
Sends a CRITICAL service check when none are found registered in the Catalog | openstack/datadog_checks/openstack/openstack.py | def get_neutron_endpoint(cls, json_resp):
"""
Parse the service catalog returned by the Identity API for an endpoint matching the Neutron service
Sends a CRITICAL service check when none are found registered in the Catalog
"""
catalog = json_resp.get('token', {}).get('catalog', [... | def get_neutron_endpoint(cls, json_resp):
"""
Parse the service catalog returned by the Identity API for an endpoint matching the Neutron service
Sends a CRITICAL service check when none are found registered in the Catalog
"""
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train | KeystoneCatalog.get_nova_endpoint | Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog | openstack/datadog_checks/openstack/openstack.py | def get_nova_endpoint(cls, json_resp, nova_api_version=None):
"""
Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog
"""
... | def get_nova_endpoint(cls, json_resp, nova_api_version=None):
"""
Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog
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train | OpenStackCheck._make_request_with_auth_fallback | Generic request handler for OpenStack API requests
Raises specialized Exceptions for commonly encountered error codes | openstack/datadog_checks/openstack/openstack.py | def _make_request_with_auth_fallback(self, url, headers=None, params=None):
"""
Generic request handler for OpenStack API requests
Raises specialized Exceptions for commonly encountered error codes
"""
self.log.debug("Request URL and Params: %s, %s", url, params)
try:
... | def _make_request_with_auth_fallback(self, url, headers=None, params=None):
"""
Generic request handler for OpenStack API requests
Raises specialized Exceptions for commonly encountered error codes
"""
self.log.debug("Request URL and Params: %s, %s", url, params)
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train | OpenStackCheck.get_network_stats | Collect stats for all reachable networks | openstack/datadog_checks/openstack/openstack.py | def get_network_stats(self, tags):
"""
Collect stats for all reachable networks
"""
# FIXME: (aaditya) Check all networks defaults to true
# until we can reliably assign agents to networks to monitor
if is_affirmative(self.init_config.get('check_all_networks', True)):
... | def get_network_stats(self, tags):
"""
Collect stats for all reachable networks
"""
# FIXME: (aaditya) Check all networks defaults to true
# until we can reliably assign agents to networks to monitor
if is_affirmative(self.init_config.get('check_all_networks', True)):
... | [
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train | OpenStackCheck._parse_uptime_string | Parse u' 16:53:48 up 1 day, 21:34, 3 users, load average: 0.04, 0.14, 0.19\n' | openstack/datadog_checks/openstack/openstack.py | def _parse_uptime_string(self, uptime):
""" Parse u' 16:53:48 up 1 day, 21:34, 3 users, load average: 0.04, 0.14, 0.19\n' """
uptime = uptime.strip()
load_averages = uptime[uptime.find('load average:') :].split(':')[1].split(',')
uptime_sec = uptime.split(',')[0]
return {'load... | def _parse_uptime_string(self, uptime):
""" Parse u' 16:53:48 up 1 day, 21:34, 3 users, load average: 0.04, 0.14, 0.19\n' """
uptime = uptime.strip()
load_averages = uptime[uptime.find('load average:') :].split(':')[1].split(',')
uptime_sec = uptime.split(',')[0]
return {'load... | [
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train | OpenStackCheck.ensure_auth_scope | Guarantees a valid auth scope for this instance, and returns it
Communicates with the identity server and initializes a new scope when one is absent, or has been forcibly
removed due to token expiry | openstack/datadog_checks/openstack/openstack.py | def ensure_auth_scope(self, instance):
"""
Guarantees a valid auth scope for this instance, and returns it
Communicates with the identity server and initializes a new scope when one is absent, or has been forcibly
removed due to token expiry
"""
instance_scope = None
... | def ensure_auth_scope(self, instance):
"""
Guarantees a valid auth scope for this instance, and returns it
Communicates with the identity server and initializes a new scope when one is absent, or has been forcibly
removed due to token expiry
"""
instance_scope = None
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train | OpenStackCheck.get_local_hypervisor | Returns the hypervisor running on this host, and assumes a 1-1 between host and hypervisor | openstack/datadog_checks/openstack/openstack.py | def get_local_hypervisor(self):
"""
Returns the hypervisor running on this host, and assumes a 1-1 between host and hypervisor
"""
# Look up hypervisors available filtered by my hostname
host = self.get_my_hostname()
hyp = self.get_all_hypervisor_ids(filter_by_host=host)
... | def get_local_hypervisor(self):
"""
Returns the hypervisor running on this host, and assumes a 1-1 between host and hypervisor
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# Look up hypervisors available filtered by my hostname
host = self.get_my_hostname()
hyp = self.get_all_hypervisor_ids(filter_by_host=host)
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train | OpenStackCheck.get_all_projects | Returns all projects in the domain | openstack/datadog_checks/openstack/openstack.py | def get_all_projects(self, scope):
"""
Returns all projects in the domain
"""
url = "{0}/{1}/{2}".format(self.keystone_server_url, DEFAULT_KEYSTONE_API_VERSION, "projects")
headers = {'X-Auth-Token': scope.auth_token}
try:
r = self._make_request_with_auth_fall... | def get_all_projects(self, scope):
"""
Returns all projects in the domain
"""
url = "{0}/{1}/{2}".format(self.keystone_server_url, DEFAULT_KEYSTONE_API_VERSION, "projects")
headers = {'X-Auth-Token': scope.auth_token}
try:
r = self._make_request_with_auth_fall... | [
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] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L1323-L1337 | [
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train | OpenStackCheck.get_scoped_project | Returns the project that this instance of the check is scoped to | openstack/datadog_checks/openstack/openstack.py | def get_scoped_project(self, project_auth_scope):
"""
Returns the project that this instance of the check is scoped to
"""
filter_params = {}
url = "{0}/{1}/{2}".format(self.keystone_server_url, DEFAULT_KEYSTONE_API_VERSION, "projects")
if project_auth_scope.tenant_id:
... | def get_scoped_project(self, project_auth_scope):
"""
Returns the project that this instance of the check is scoped to
"""
filter_params = {}
url = "{0}/{1}/{2}".format(self.keystone_server_url, DEFAULT_KEYSTONE_API_VERSION, "projects")
if project_auth_scope.tenant_id:
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train | OpenStackCheck.get_my_hostname | Returns a best guess for the hostname registered with OpenStack for this host | openstack/datadog_checks/openstack/openstack.py | def get_my_hostname(self, split_hostname_on_first_period=False):
"""
Returns a best guess for the hostname registered with OpenStack for this host
"""
hostname = self.init_config.get("os_host") or self.hostname
if split_hostname_on_first_period:
hostname = hostname.s... | def get_my_hostname(self, split_hostname_on_first_period=False):
"""
Returns a best guess for the hostname registered with OpenStack for this host
"""
hostname = self.init_config.get("os_host") or self.hostname
if split_hostname_on_first_period:
hostname = hostname.s... | [
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] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L1374-L1383 | [
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train | OpenStackCheck.get_external_host_tags | Returns a list of tags for every guest server that is detected by the OpenStack
integration.
List of pairs (hostname, list_of_tags) | openstack/datadog_checks/openstack/openstack.py | def get_external_host_tags(self):
""" Returns a list of tags for every guest server that is detected by the OpenStack
integration.
List of pairs (hostname, list_of_tags)
"""
self.log.debug("Collecting external_host_tags now")
external_host_tags = []
for k, v in it... | def get_external_host_tags(self):
""" Returns a list of tags for every guest server that is detected by the OpenStack
integration.
List of pairs (hostname, list_of_tags)
"""
self.log.debug("Collecting external_host_tags now")
external_host_tags = []
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] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L1416-L1427 | [
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"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
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