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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
train | pattern_filter | This filters `items` by a regular expression `whitelist` and/or
`blacklist`, with the `blacklist` taking precedence. An optional `key`
function can be provided that will be passed each item. | datadog_checks_base/datadog_checks/base/utils/common.py | def pattern_filter(items, whitelist=None, blacklist=None, key=None):
"""This filters `items` by a regular expression `whitelist` and/or
`blacklist`, with the `blacklist` taking precedence. An optional `key`
function can be provided that will be passed each item.
"""
key = key or __return_self
if... | def pattern_filter(items, whitelist=None, blacklist=None, key=None):
"""This filters `items` by a regular expression `whitelist` and/or
`blacklist`, with the `blacklist` taking precedence. An optional `key`
function can be provided that will be passed each item.
"""
key = key or __return_self
if... | [
"This",
"filters",
"items",
"by",
"a",
"regular",
"expression",
"whitelist",
"and",
"/",
"or",
"blacklist",
"with",
"the",
"blacklist",
"taking",
"precedence",
".",
"An",
"optional",
"key",
"function",
"can",
"be",
"provided",
"that",
"will",
"be",
"passed",
... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/utils/common.py#L36-L57 | [
"def",
"pattern_filter",
"(",
"items",
",",
"whitelist",
"=",
"None",
",",
"blacklist",
"=",
"None",
",",
"key",
"=",
"None",
")",
":",
"key",
"=",
"key",
"or",
"__return_self",
"if",
"whitelist",
":",
"whitelisted",
"=",
"_filter",
"(",
"items",
",",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | updated_topology_description | Return an updated copy of a TopologyDescription.
:Parameters:
- `topology_description`: the current TopologyDescription
- `server_description`: a new ServerDescription that resulted from
an ismaster call
Called after attempting (successfully or not) to call ismaster on the
server at se... | tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py | def updated_topology_description(topology_description, server_description):
"""Return an updated copy of a TopologyDescription.
:Parameters:
- `topology_description`: the current TopologyDescription
- `server_description`: a new ServerDescription that resulted from
an ismaster call
Cal... | def updated_topology_description(topology_description, server_description):
"""Return an updated copy of a TopologyDescription.
:Parameters:
- `topology_description`: the current TopologyDescription
- `server_description`: a new ServerDescription that resulted from
an ismaster call
Cal... | [
"Return",
"an",
"updated",
"copy",
"of",
"a",
"TopologyDescription",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py#L252-L353 | [
"def",
"updated_topology_description",
"(",
"topology_description",
",",
"server_description",
")",
":",
"address",
"=",
"server_description",
".",
"address",
"# These values will be updated, if necessary, to form the new",
"# TopologyDescription.",
"topology_type",
"=",
"topology_... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | _update_rs_from_primary | Update topology description from a primary's ismaster response.
Pass in a dict of ServerDescriptions, current replica set name, the
ServerDescription we are processing, and the TopologyDescription's
max_set_version and max_election_id if any.
Returns (new topology type, new replica_set_name, new max_s... | tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py | def _update_rs_from_primary(
sds,
replica_set_name,
server_description,
max_set_version,
max_election_id):
"""Update topology description from a primary's ismaster response.
Pass in a dict of ServerDescriptions, current replica set name, the
ServerDescription we are ... | def _update_rs_from_primary(
sds,
replica_set_name,
server_description,
max_set_version,
max_election_id):
"""Update topology description from a primary's ismaster response.
Pass in a dict of ServerDescriptions, current replica set name, the
ServerDescription we are ... | [
"Update",
"topology",
"description",
"from",
"a",
"primary",
"s",
"ismaster",
"response",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py#L356-L429 | [
"def",
"_update_rs_from_primary",
"(",
"sds",
",",
"replica_set_name",
",",
"server_description",
",",
"max_set_version",
",",
"max_election_id",
")",
":",
"if",
"replica_set_name",
"is",
"None",
":",
"replica_set_name",
"=",
"server_description",
".",
"replica_set_name... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | _update_rs_with_primary_from_member | RS with known primary. Process a response from a non-primary.
Pass in a dict of ServerDescriptions, current replica set name, and the
ServerDescription we are processing.
Returns new topology type. | tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py | def _update_rs_with_primary_from_member(
sds,
replica_set_name,
server_description):
"""RS with known primary. Process a response from a non-primary.
Pass in a dict of ServerDescriptions, current replica set name, and the
ServerDescription we are processing.
Returns new topolog... | def _update_rs_with_primary_from_member(
sds,
replica_set_name,
server_description):
"""RS with known primary. Process a response from a non-primary.
Pass in a dict of ServerDescriptions, current replica set name, and the
ServerDescription we are processing.
Returns new topolog... | [
"RS",
"with",
"known",
"primary",
".",
"Process",
"a",
"response",
"from",
"a",
"non",
"-",
"primary",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py#L432-L452 | [
"def",
"_update_rs_with_primary_from_member",
"(",
"sds",
",",
"replica_set_name",
",",
"server_description",
")",
":",
"assert",
"replica_set_name",
"is",
"not",
"None",
"if",
"replica_set_name",
"!=",
"server_description",
".",
"replica_set_name",
":",
"sds",
".",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | _update_rs_no_primary_from_member | RS without known primary. Update from a non-primary's response.
Pass in a dict of ServerDescriptions, current replica set name, and the
ServerDescription we are processing.
Returns (new topology type, new replica_set_name). | tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py | def _update_rs_no_primary_from_member(
sds,
replica_set_name,
server_description):
"""RS without known primary. Update from a non-primary's response.
Pass in a dict of ServerDescriptions, current replica set name, and the
ServerDescription we are processing.
Returns (new topolo... | def _update_rs_no_primary_from_member(
sds,
replica_set_name,
server_description):
"""RS without known primary. Update from a non-primary's response.
Pass in a dict of ServerDescriptions, current replica set name, and the
ServerDescription we are processing.
Returns (new topolo... | [
"RS",
"without",
"known",
"primary",
".",
"Update",
"from",
"a",
"non",
"-",
"primary",
"s",
"response",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py#L455-L484 | [
"def",
"_update_rs_no_primary_from_member",
"(",
"sds",
",",
"replica_set_name",
",",
"server_description",
")",
":",
"topology_type",
"=",
"TOPOLOGY_TYPE",
".",
"ReplicaSetNoPrimary",
"if",
"replica_set_name",
"is",
"None",
":",
"replica_set_name",
"=",
"server_descripti... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | _check_has_primary | Current topology type is ReplicaSetWithPrimary. Is primary still known?
Pass in a dict of ServerDescriptions.
Returns new topology type. | tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py | def _check_has_primary(sds):
"""Current topology type is ReplicaSetWithPrimary. Is primary still known?
Pass in a dict of ServerDescriptions.
Returns new topology type.
"""
for s in sds.values():
if s.server_type == SERVER_TYPE.RSPrimary:
return TOPOLOGY_TYPE.ReplicaSetWithPrim... | def _check_has_primary(sds):
"""Current topology type is ReplicaSetWithPrimary. Is primary still known?
Pass in a dict of ServerDescriptions.
Returns new topology type.
"""
for s in sds.values():
if s.server_type == SERVER_TYPE.RSPrimary:
return TOPOLOGY_TYPE.ReplicaSetWithPrim... | [
"Current",
"topology",
"type",
"is",
"ReplicaSetWithPrimary",
".",
"Is",
"primary",
"still",
"known?"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py#L487-L498 | [
"def",
"_check_has_primary",
"(",
"sds",
")",
":",
"for",
"s",
"in",
"sds",
".",
"values",
"(",
")",
":",
"if",
"s",
".",
"server_type",
"==",
"SERVER_TYPE",
".",
"RSPrimary",
":",
"return",
"TOPOLOGY_TYPE",
".",
"ReplicaSetWithPrimary",
"else",
":",
"retu... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | TopologyDescription.reset | A copy of this description, with all servers marked Unknown. | tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py | def reset(self):
"""A copy of this description, with all servers marked Unknown."""
if self._topology_type == TOPOLOGY_TYPE.ReplicaSetWithPrimary:
topology_type = TOPOLOGY_TYPE.ReplicaSetNoPrimary
else:
topology_type = self._topology_type
# The default ServerDesc... | def reset(self):
"""A copy of this description, with all servers marked Unknown."""
if self._topology_type == TOPOLOGY_TYPE.ReplicaSetWithPrimary:
topology_type = TOPOLOGY_TYPE.ReplicaSetNoPrimary
else:
topology_type = self._topology_type
# The default ServerDesc... | [
"A",
"copy",
"of",
"this",
"description",
"with",
"all",
"servers",
"marked",
"Unknown",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py#L104-L121 | [
"def",
"reset",
"(",
"self",
")",
":",
"if",
"self",
".",
"_topology_type",
"==",
"TOPOLOGY_TYPE",
".",
"ReplicaSetWithPrimary",
":",
"topology_type",
"=",
"TOPOLOGY_TYPE",
".",
"ReplicaSetNoPrimary",
"else",
":",
"topology_type",
"=",
"self",
".",
"_topology_type... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | TopologyDescription.common_wire_version | Minimum of all servers' max wire versions, or None. | tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py | def common_wire_version(self):
"""Minimum of all servers' max wire versions, or None."""
servers = self.known_servers
if servers:
return min(s.max_wire_version for s in self.known_servers)
return None | def common_wire_version(self):
"""Minimum of all servers' max wire versions, or None."""
servers = self.known_servers
if servers:
return min(s.max_wire_version for s in self.known_servers)
return None | [
"Minimum",
"of",
"all",
"servers",
"max",
"wire",
"versions",
"or",
"None",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py#L163-L169 | [
"def",
"common_wire_version",
"(",
"self",
")",
":",
"servers",
"=",
"self",
".",
"known_servers",
"if",
"servers",
":",
"return",
"min",
"(",
"s",
".",
"max_wire_version",
"for",
"s",
"in",
"self",
".",
"known_servers",
")",
"return",
"None"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | TopologyDescription.has_readable_server | Does this topology have any readable servers available matching the
given read preference?
:Parameters:
- `read_preference`: an instance of a read preference from
:mod:`~pymongo.read_preferences`. Defaults to
:attr:`~pymongo.read_preferences.ReadPreference.PRIMARY`.
... | tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py | def has_readable_server(self, read_preference=ReadPreference.PRIMARY):
"""Does this topology have any readable servers available matching the
given read preference?
:Parameters:
- `read_preference`: an instance of a read preference from
:mod:`~pymongo.read_preferences`. De... | def has_readable_server(self, read_preference=ReadPreference.PRIMARY):
"""Does this topology have any readable servers available matching the
given read preference?
:Parameters:
- `read_preference`: an instance of a read preference from
:mod:`~pymongo.read_preferences`. De... | [
"Does",
"this",
"topology",
"have",
"any",
"readable",
"servers",
"available",
"matching",
"the",
"given",
"read",
"preference?"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/topology_description.py#L213-L228 | [
"def",
"has_readable_server",
"(",
"self",
",",
"read_preference",
"=",
"ReadPreference",
".",
"PRIMARY",
")",
":",
"common",
".",
"validate_read_preference",
"(",
"\"read_preference\"",
",",
"read_preference",
")",
"return",
"any",
"(",
"self",
".",
"apply_selector... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | get_os | Human-friendly OS name | datadog_checks_base/datadog_checks/base/utils/platform.py | def get_os():
"""
Human-friendly OS name
"""
if sys.platform == 'darwin':
return 'mac'
elif sys.platform.find('freebsd') != -1:
return 'freebsd'
elif sys.platform.find('linux') != -1:
return 'linux'
elif sys.platform.find('win32') != -1:
return 'windows'
e... | def get_os():
"""
Human-friendly OS name
"""
if sys.platform == 'darwin':
return 'mac'
elif sys.platform.find('freebsd') != -1:
return 'freebsd'
elif sys.platform.find('linux') != -1:
return 'linux'
elif sys.platform.find('win32') != -1:
return 'windows'
e... | [
"Human",
"-",
"friendly",
"OS",
"name"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/utils/platform.py#L11-L26 | [
"def",
"get_os",
"(",
")",
":",
"if",
"sys",
".",
"platform",
"==",
"'darwin'",
":",
"return",
"'mac'",
"elif",
"sys",
".",
"platform",
".",
"find",
"(",
"'freebsd'",
")",
"!=",
"-",
"1",
":",
"return",
"'freebsd'",
"elif",
"sys",
".",
"platform",
".... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Platform.is_bsd | Return true if this is a BSD like operating system. | datadog_checks_base/datadog_checks/base/utils/platform.py | def is_bsd(name=None):
""" Return true if this is a BSD like operating system. """
name = name or sys.platform
return Platform.is_darwin(name) or Platform.is_freebsd(name) | def is_bsd(name=None):
""" Return true if this is a BSD like operating system. """
name = name or sys.platform
return Platform.is_darwin(name) or Platform.is_freebsd(name) | [
"Return",
"true",
"if",
"this",
"is",
"a",
"BSD",
"like",
"operating",
"system",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/utils/platform.py#L54-L57 | [
"def",
"is_bsd",
"(",
"name",
"=",
"None",
")",
":",
"name",
"=",
"name",
"or",
"sys",
".",
"platform",
"return",
"Platform",
".",
"is_darwin",
"(",
"name",
")",
"or",
"Platform",
".",
"is_freebsd",
"(",
"name",
")"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Platform.is_unix | Return true if the platform is a unix, False otherwise. | datadog_checks_base/datadog_checks/base/utils/platform.py | def is_unix(name=None):
""" Return true if the platform is a unix, False otherwise. """
name = name or sys.platform
return Platform.is_darwin(name) or Platform.is_linux(name) or Platform.is_freebsd(name) | def is_unix(name=None):
""" Return true if the platform is a unix, False otherwise. """
name = name or sys.platform
return Platform.is_darwin(name) or Platform.is_linux(name) or Platform.is_freebsd(name) | [
"Return",
"true",
"if",
"the",
"platform",
"is",
"a",
"unix",
"False",
"otherwise",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/utils/platform.py#L65-L68 | [
"def",
"is_unix",
"(",
"name",
"=",
"None",
")",
":",
"name",
"=",
"name",
"or",
"sys",
".",
"platform",
"return",
"Platform",
".",
"is_darwin",
"(",
"name",
")",
"or",
"Platform",
".",
"is_linux",
"(",
"name",
")",
"or",
"Platform",
".",
"is_freebsd",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | get_subprocess_output | Run the given subprocess command and return its output. Raise an Exception
if an error occurs.
:param command: The command to run. Using a list of strings is recommended. The command
will be run in a subprocess without using a shell, as such shell features like
shell pip... | datadog_checks_base/datadog_checks/base/utils/subprocess_output.py | def get_subprocess_output(command, log, raise_on_empty_output=True, log_debug=True):
"""
Run the given subprocess command and return its output. Raise an Exception
if an error occurs.
:param command: The command to run. Using a list of strings is recommended. The command
will be run... | def get_subprocess_output(command, log, raise_on_empty_output=True, log_debug=True):
"""
Run the given subprocess command and return its output. Raise an Exception
if an error occurs.
:param command: The command to run. Using a list of strings is recommended. The command
will be run... | [
"Run",
"the",
"given",
"subprocess",
"command",
"and",
"return",
"its",
"output",
".",
"Raise",
"an",
"Exception",
"if",
"an",
"error",
"occurs",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/utils/subprocess_output.py#L28-L69 | [
"def",
"get_subprocess_output",
"(",
"command",
",",
"log",
",",
"raise_on_empty_output",
"=",
"True",
",",
"log_debug",
"=",
"True",
")",
":",
"cmd_args",
"=",
"[",
"]",
"if",
"isinstance",
"(",
"command",
",",
"string_types",
")",
":",
"for",
"arg",
"in"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | changes | Show changes since a specific date. | datadog_checks_dev/datadog_checks/dev/tooling/commands/meta/changes.py | def changes(since, out_file, eager):
"""Show changes since a specific date."""
root = get_root()
history_data = defaultdict(lambda: {'lines': deque(), 'releasers': set()})
with chdir(root):
result = run_command(
(
'git log "--pretty=format:%H %s" --date-order --date=... | def changes(since, out_file, eager):
"""Show changes since a specific date."""
root = get_root()
history_data = defaultdict(lambda: {'lines': deque(), 'releasers': set()})
with chdir(root):
result = run_command(
(
'git log "--pretty=format:%H %s" --date-order --date=... | [
"Show",
"changes",
"since",
"a",
"specific",
"date",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/commands/meta/changes.py#L31-L132 | [
"def",
"changes",
"(",
"since",
",",
"out_file",
",",
"eager",
")",
":",
"root",
"=",
"get_root",
"(",
")",
"history_data",
"=",
"defaultdict",
"(",
"lambda",
":",
"{",
"'lines'",
":",
"deque",
"(",
")",
",",
"'releasers'",
":",
"set",
"(",
")",
"}",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | changelog | Generates a markdown file containing the list of checks that changed for a
given Agent release. Agent version numbers are derived inspecting tags on
`integrations-core` so running this tool might provide unexpected results
if the repo is not up to date with the Agent release process.
If neither `--sinc... | datadog_checks_dev/datadog_checks/dev/tooling/commands/agent/changelog.py | def changelog(since, to, write, force):
"""
Generates a markdown file containing the list of checks that changed for a
given Agent release. Agent version numbers are derived inspecting tags on
`integrations-core` so running this tool might provide unexpected results
if the repo is not up to date wit... | def changelog(since, to, write, force):
"""
Generates a markdown file containing the list of checks that changed for a
given Agent release. Agent version numbers are derived inspecting tags on
`integrations-core` so running this tool might provide unexpected results
if the repo is not up to date wit... | [
"Generates",
"a",
"markdown",
"file",
"containing",
"the",
"list",
"of",
"checks",
"that",
"changed",
"for",
"a",
"given",
"Agent",
"release",
".",
"Agent",
"version",
"numbers",
"are",
"derived",
"inspecting",
"tags",
"on",
"integrations",
"-",
"core",
"so",
... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/commands/agent/changelog.py#L30-L123 | [
"def",
"changelog",
"(",
"since",
",",
"to",
",",
"write",
",",
"force",
")",
":",
"agent_tags",
"=",
"get_agent_tags",
"(",
"since",
",",
"to",
")",
"# store the changes in a mapping {agent_version --> {check_name --> current_version}}",
"changes_per_agent",
"=",
"Orde... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | MetadataCache.init_instance | Create an empty instance if it doesn't exist.
If the instance already exists, this is a noop. | vsphere/datadog_checks/vsphere/metadata_cache.py | def init_instance(self, key):
"""
Create an empty instance if it doesn't exist.
If the instance already exists, this is a noop.
"""
with self._lock:
if key not in self._metadata:
self._metadata[key] = {}
self._metric_ids[key] = [] | def init_instance(self, key):
"""
Create an empty instance if it doesn't exist.
If the instance already exists, this is a noop.
"""
with self._lock:
if key not in self._metadata:
self._metadata[key] = {}
self._metric_ids[key] = [] | [
"Create",
"an",
"empty",
"instance",
"if",
"it",
"doesn",
"t",
"exist",
".",
"If",
"the",
"instance",
"already",
"exists",
"this",
"is",
"a",
"noop",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/metadata_cache.py#L22-L30 | [
"def",
"init_instance",
"(",
"self",
",",
"key",
")",
":",
"with",
"self",
".",
"_lock",
":",
"if",
"key",
"not",
"in",
"self",
".",
"_metadata",
":",
"self",
".",
"_metadata",
"[",
"key",
"]",
"=",
"{",
"}",
"self",
".",
"_metric_ids",
"[",
"key",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | MetadataCache.contains | Return whether a counter_id is present for a given instance key.
If the key is not in the cache, raises a KeyError. | vsphere/datadog_checks/vsphere/metadata_cache.py | def contains(self, key, counter_id):
"""
Return whether a counter_id is present for a given instance key.
If the key is not in the cache, raises a KeyError.
"""
with self._lock:
return counter_id in self._metadata[key] | def contains(self, key, counter_id):
"""
Return whether a counter_id is present for a given instance key.
If the key is not in the cache, raises a KeyError.
"""
with self._lock:
return counter_id in self._metadata[key] | [
"Return",
"whether",
"a",
"counter_id",
"is",
"present",
"for",
"a",
"given",
"instance",
"key",
".",
"If",
"the",
"key",
"is",
"not",
"in",
"the",
"cache",
"raises",
"a",
"KeyError",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/metadata_cache.py#L32-L38 | [
"def",
"contains",
"(",
"self",
",",
"key",
",",
"counter_id",
")",
":",
"with",
"self",
".",
"_lock",
":",
"return",
"counter_id",
"in",
"self",
".",
"_metadata",
"[",
"key",
"]"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | MetadataCache.set_metadata | Store the metadata for the given instance key. | vsphere/datadog_checks/vsphere/metadata_cache.py | def set_metadata(self, key, metadata):
"""
Store the metadata for the given instance key.
"""
with self._lock:
self._metadata[key] = metadata | def set_metadata(self, key, metadata):
"""
Store the metadata for the given instance key.
"""
with self._lock:
self._metadata[key] = metadata | [
"Store",
"the",
"metadata",
"for",
"the",
"given",
"instance",
"key",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/metadata_cache.py#L40-L45 | [
"def",
"set_metadata",
"(",
"self",
",",
"key",
",",
"metadata",
")",
":",
"with",
"self",
".",
"_lock",
":",
"self",
".",
"_metadata",
"[",
"key",
"]",
"=",
"metadata"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | MetadataCache.set_metric_ids | Store the list of metric IDs we will want to collect for the given instance key | vsphere/datadog_checks/vsphere/metadata_cache.py | def set_metric_ids(self, key, metric_ids):
"""
Store the list of metric IDs we will want to collect for the given instance key
"""
with self._lock:
self._metric_ids[key] = metric_ids | def set_metric_ids(self, key, metric_ids):
"""
Store the list of metric IDs we will want to collect for the given instance key
"""
with self._lock:
self._metric_ids[key] = metric_ids | [
"Store",
"the",
"list",
"of",
"metric",
"IDs",
"we",
"will",
"want",
"to",
"collect",
"for",
"the",
"given",
"instance",
"key"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/metadata_cache.py#L47-L52 | [
"def",
"set_metric_ids",
"(",
"self",
",",
"key",
",",
"metric_ids",
")",
":",
"with",
"self",
".",
"_lock",
":",
"self",
".",
"_metric_ids",
"[",
"key",
"]",
"=",
"metric_ids"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | MetadataCache.get_metadata | Return the metadata for the metric identified by `counter_id` for the given instance key.
If the key is not in the cache, raises a KeyError.
If there's no metric with the given counter_id, raises a MetadataNotFoundError. | vsphere/datadog_checks/vsphere/metadata_cache.py | def get_metadata(self, key, counter_id):
"""
Return the metadata for the metric identified by `counter_id` for the given instance key.
If the key is not in the cache, raises a KeyError.
If there's no metric with the given counter_id, raises a MetadataNotFoundError.
"""
wi... | def get_metadata(self, key, counter_id):
"""
Return the metadata for the metric identified by `counter_id` for the given instance key.
If the key is not in the cache, raises a KeyError.
If there's no metric with the given counter_id, raises a MetadataNotFoundError.
"""
wi... | [
"Return",
"the",
"metadata",
"for",
"the",
"metric",
"identified",
"by",
"counter_id",
"for",
"the",
"given",
"instance",
"key",
".",
"If",
"the",
"key",
"is",
"not",
"in",
"the",
"cache",
"raises",
"a",
"KeyError",
".",
"If",
"there",
"s",
"no",
"metric... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/metadata_cache.py#L62-L73 | [
"def",
"get_metadata",
"(",
"self",
",",
"key",
",",
"counter_id",
")",
":",
"with",
"self",
".",
"_lock",
":",
"metadata",
"=",
"self",
".",
"_metadata",
"[",
"key",
"]",
"try",
":",
"return",
"metadata",
"[",
"counter_id",
"]",
"except",
"KeyError",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | manifest | Validate `manifest.json` files. | datadog_checks_dev/datadog_checks/dev/tooling/commands/validate/manifest.py | def manifest(fix, include_extras):
"""Validate `manifest.json` files."""
all_guids = {}
root = get_root()
root_name = basepath(get_root())
ok_checks = 0
failed_checks = 0
fixed_checks = 0
echo_info("Validating all manifest.json files...")
for check_name in sorted(os.listdir(root)):... | def manifest(fix, include_extras):
"""Validate `manifest.json` files."""
all_guids = {}
root = get_root()
root_name = basepath(get_root())
ok_checks = 0
failed_checks = 0
fixed_checks = 0
echo_info("Validating all manifest.json files...")
for check_name in sorted(os.listdir(root)):... | [
"Validate",
"manifest",
".",
"json",
"files",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/commands/validate/manifest.py#L55-L373 | [
"def",
"manifest",
"(",
"fix",
",",
"include_extras",
")",
":",
"all_guids",
"=",
"{",
"}",
"root",
"=",
"get_root",
"(",
")",
"root_name",
"=",
"basepath",
"(",
"get_root",
"(",
")",
")",
"ok_checks",
"=",
"0",
"failed_checks",
"=",
"0",
"fixed_checks",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | _get_py_loglevel | Map log levels to strings | datadog_checks_base/datadog_checks/base/log.py | def _get_py_loglevel(lvl):
"""
Map log levels to strings
"""
if not lvl:
lvl = 'INFO'
return LOG_LEVEL_MAP.get(lvl.upper(), logging.DEBUG) | def _get_py_loglevel(lvl):
"""
Map log levels to strings
"""
if not lvl:
lvl = 'INFO'
return LOG_LEVEL_MAP.get(lvl.upper(), logging.DEBUG) | [
"Map",
"log",
"levels",
"to",
"strings"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/log.py#L52-L59 | [
"def",
"_get_py_loglevel",
"(",
"lvl",
")",
":",
"if",
"not",
"lvl",
":",
"lvl",
"=",
"'INFO'",
"return",
"LOG_LEVEL_MAP",
".",
"get",
"(",
"lvl",
".",
"upper",
"(",
")",
",",
"logging",
".",
"DEBUG",
")"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | init_logging | Initialize logging (set up forwarding to Go backend and sane defaults) | datadog_checks_base/datadog_checks/base/log.py | def init_logging():
"""
Initialize logging (set up forwarding to Go backend and sane defaults)
"""
# Forward to Go backend
logging.addLevelName(TRACE_LEVEL, 'TRACE')
logging.setLoggerClass(AgentLogger)
rootLogger = logging.getLogger()
rootLogger.addHandler(AgentLogHandler())
rootLogg... | def init_logging():
"""
Initialize logging (set up forwarding to Go backend and sane defaults)
"""
# Forward to Go backend
logging.addLevelName(TRACE_LEVEL, 'TRACE')
logging.setLoggerClass(AgentLogger)
rootLogger = logging.getLogger()
rootLogger.addHandler(AgentLogHandler())
rootLogg... | [
"Initialize",
"logging",
"(",
"set",
"up",
"forwarding",
"to",
"Go",
"backend",
"and",
"sane",
"defaults",
")"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/log.py#L62-L77 | [
"def",
"init_logging",
"(",
")",
":",
"# Forward to Go backend",
"logging",
".",
"addLevelName",
"(",
"TRACE_LEVEL",
",",
"'TRACE'",
")",
"logging",
".",
"setLoggerClass",
"(",
"AgentLogger",
")",
"rootLogger",
"=",
"logging",
".",
"getLogger",
"(",
")",
"rootLo... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | TailFile.tail | Read line-by-line and run callback on each line.
line_by_line: yield each time a callback has returned True
move_end: start from the last line of the log | datadog_checks_base/datadog_checks/base/utils/tailfile.py | def tail(self, line_by_line=True, move_end=True):
"""Read line-by-line and run callback on each line.
line_by_line: yield each time a callback has returned True
move_end: start from the last line of the log"""
try:
self._open_file(move_end=move_end)
while True:
... | def tail(self, line_by_line=True, move_end=True):
"""Read line-by-line and run callback on each line.
line_by_line: yield each time a callback has returned True
move_end: start from the last line of the log"""
try:
self._open_file(move_end=move_end)
while True:
... | [
"Read",
"line",
"-",
"by",
"-",
"line",
"and",
"run",
"callback",
"on",
"each",
"line",
".",
"line_by_line",
":",
"yield",
"each",
"time",
"a",
"callback",
"has",
"returned",
"True",
"move_end",
":",
"start",
"from",
"the",
"last",
"line",
"of",
"the",
... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/utils/tailfile.py#L78-L107 | [
"def",
"tail",
"(",
"self",
",",
"line_by_line",
"=",
"True",
",",
"move_end",
"=",
"True",
")",
":",
"try",
":",
"self",
".",
"_open_file",
"(",
"move_end",
"=",
"move_end",
")",
"while",
"True",
":",
"pos",
"=",
"self",
".",
"_f",
".",
"tell",
"(... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | environment_run | This utility provides a convenient way to safely set up and tear down arbitrary types of environments.
:param up: A custom setup callable.
:type up: ``callable``
:param down: A custom tear down callable.
:type down: ``callable``
:param sleep: Number of seconds to wait before yielding.
:type sle... | datadog_checks_dev/datadog_checks/dev/env.py | def environment_run(up, down, sleep=None, endpoints=None, conditions=None, env_vars=None, wrapper=None):
"""This utility provides a convenient way to safely set up and tear down arbitrary types of environments.
:param up: A custom setup callable.
:type up: ``callable``
:param down: A custom tear down c... | def environment_run(up, down, sleep=None, endpoints=None, conditions=None, env_vars=None, wrapper=None):
"""This utility provides a convenient way to safely set up and tear down arbitrary types of environments.
:param up: A custom setup callable.
:type up: ``callable``
:param down: A custom tear down c... | [
"This",
"utility",
"provides",
"a",
"convenient",
"way",
"to",
"safely",
"set",
"up",
"and",
"tear",
"down",
"arbitrary",
"types",
"of",
"environments",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/env.py#L14-L60 | [
"def",
"environment_run",
"(",
"up",
",",
"down",
",",
"sleep",
"=",
"None",
",",
"endpoints",
"=",
"None",
",",
"conditions",
"=",
"None",
",",
"env_vars",
"=",
"None",
",",
"wrapper",
"=",
"None",
")",
":",
"if",
"not",
"callable",
"(",
"up",
")",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | config_proxy_skip | Returns an amended copy of the proxies dictionary - used by `requests`,
it will disable the proxy if the uri provided is to be reached directly.
:param proxies A dict with existing proxies: `https`, `http`, and `no` are potential keys.
:param uri URI to determine if a proxy is necessary or not.
:param s... | datadog_checks_base/datadog_checks/base/utils/proxy.py | def config_proxy_skip(proxies, uri, skip_proxy=False):
"""
Returns an amended copy of the proxies dictionary - used by `requests`,
it will disable the proxy if the uri provided is to be reached directly.
:param proxies A dict with existing proxies: `https`, `http`, and `no` are potential keys.
:para... | def config_proxy_skip(proxies, uri, skip_proxy=False):
"""
Returns an amended copy of the proxies dictionary - used by `requests`,
it will disable the proxy if the uri provided is to be reached directly.
:param proxies A dict with existing proxies: `https`, `http`, and `no` are potential keys.
:para... | [
"Returns",
"an",
"amended",
"copy",
"of",
"the",
"proxies",
"dictionary",
"-",
"used",
"by",
"requests",
"it",
"will",
"disable",
"the",
"proxy",
"if",
"the",
"uri",
"provided",
"is",
"to",
"be",
"reached",
"directly",
".",
":",
"param",
"proxies",
"A",
... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/utils/proxy.py#L8-L35 | [
"def",
"config_proxy_skip",
"(",
"proxies",
",",
"uri",
",",
"skip_proxy",
"=",
"False",
")",
":",
"parsed_uri",
"=",
"urlparse",
"(",
"uri",
")",
"# disable proxy if necessary",
"if",
"skip_proxy",
":",
"proxies",
"[",
"'http'",
"]",
"=",
"''",
"proxies",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Server.close | Clear the connection pool and stop the monitor.
Reconnect with open(). | tokumx/datadog_checks/tokumx/vendor/pymongo/server.py | def close(self):
"""Clear the connection pool and stop the monitor.
Reconnect with open().
"""
if self._publish:
self._events.put((self._listener.publish_server_closed,
(self._description.address, self._topology_id)))
self._monitor.close... | def close(self):
"""Clear the connection pool and stop the monitor.
Reconnect with open().
"""
if self._publish:
self._events.put((self._listener.publish_server_closed,
(self._description.address, self._topology_id)))
self._monitor.close... | [
"Clear",
"the",
"connection",
"pool",
"and",
"stop",
"the",
"monitor",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/server.py#L52-L61 | [
"def",
"close",
"(",
"self",
")",
":",
"if",
"self",
".",
"_publish",
":",
"self",
".",
"_events",
".",
"put",
"(",
"(",
"self",
".",
"_listener",
".",
"publish_server_closed",
",",
"(",
"self",
".",
"_description",
".",
"address",
",",
"self",
".",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Server.send_message | Send an unacknowledged message to MongoDB.
Can raise ConnectionFailure.
:Parameters:
- `message`: (request_id, data).
- `all_credentials`: dict, maps auth source to MongoCredential. | tokumx/datadog_checks/tokumx/vendor/pymongo/server.py | def send_message(self, message, all_credentials):
"""Send an unacknowledged message to MongoDB.
Can raise ConnectionFailure.
:Parameters:
- `message`: (request_id, data).
- `all_credentials`: dict, maps auth source to MongoCredential.
"""
_, data, max_doc_si... | def send_message(self, message, all_credentials):
"""Send an unacknowledged message to MongoDB.
Can raise ConnectionFailure.
:Parameters:
- `message`: (request_id, data).
- `all_credentials`: dict, maps auth source to MongoCredential.
"""
_, data, max_doc_si... | [
"Send",
"an",
"unacknowledged",
"message",
"to",
"MongoDB",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/server.py#L67-L78 | [
"def",
"send_message",
"(",
"self",
",",
"message",
",",
"all_credentials",
")",
":",
"_",
",",
"data",
",",
"max_doc_size",
"=",
"self",
".",
"_split_message",
"(",
"message",
")",
"with",
"self",
".",
"get_socket",
"(",
"all_credentials",
")",
"as",
"soc... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Server.send_message_with_response | Send a message to MongoDB and return a Response object.
Can raise ConnectionFailure.
:Parameters:
- `operation`: A _Query or _GetMore object.
- `set_slave_okay`: Pass to operation.get_message.
- `all_credentials`: dict, maps auth source to MongoCredential.
- `li... | tokumx/datadog_checks/tokumx/vendor/pymongo/server.py | def send_message_with_response(
self,
operation,
set_slave_okay,
all_credentials,
listeners,
exhaust=False):
"""Send a message to MongoDB and return a Response object.
Can raise ConnectionFailure.
:Parameters:
- ... | def send_message_with_response(
self,
operation,
set_slave_okay,
all_credentials,
listeners,
exhaust=False):
"""Send a message to MongoDB and return a Response object.
Can raise ConnectionFailure.
:Parameters:
- ... | [
"Send",
"a",
"message",
"to",
"MongoDB",
"and",
"return",
"a",
"Response",
"object",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/server.py#L80-L164 | [
"def",
"send_message_with_response",
"(",
"self",
",",
"operation",
",",
"set_slave_okay",
",",
"all_credentials",
",",
"listeners",
",",
"exhaust",
"=",
"False",
")",
":",
"with",
"self",
".",
"get_socket",
"(",
"all_credentials",
",",
"exhaust",
")",
"as",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Server._split_message | Return request_id, data, max_doc_size.
:Parameters:
- `message`: (request_id, data, max_doc_size) or (request_id, data) | tokumx/datadog_checks/tokumx/vendor/pymongo/server.py | def _split_message(self, message):
"""Return request_id, data, max_doc_size.
:Parameters:
- `message`: (request_id, data, max_doc_size) or (request_id, data)
"""
if len(message) == 3:
return message
else:
# get_more and kill_cursors messages don... | def _split_message(self, message):
"""Return request_id, data, max_doc_size.
:Parameters:
- `message`: (request_id, data, max_doc_size) or (request_id, data)
"""
if len(message) == 3:
return message
else:
# get_more and kill_cursors messages don... | [
"Return",
"request_id",
"data",
"max_doc_size",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/server.py#L184-L195 | [
"def",
"_split_message",
"(",
"self",
",",
"message",
")",
":",
"if",
"len",
"(",
"message",
")",
"==",
"3",
":",
"return",
"message",
"else",
":",
"# get_more and kill_cursors messages don't include BSON documents.",
"request_id",
",",
"data",
"=",
"message",
"re... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | BulkWriteResult.upserted_ids | A map of operation index to the _id of the upserted document. | tokumx/datadog_checks/tokumx/vendor/pymongo/results.py | def upserted_ids(self):
"""A map of operation index to the _id of the upserted document."""
self._raise_if_unacknowledged("upserted_ids")
if self.__bulk_api_result:
return dict((upsert["index"], upsert["_id"])
for upsert in self.bulk_api_result["upserted"]) | def upserted_ids(self):
"""A map of operation index to the _id of the upserted document."""
self._raise_if_unacknowledged("upserted_ids")
if self.__bulk_api_result:
return dict((upsert["index"], upsert["_id"])
for upsert in self.bulk_api_result["upserted"]) | [
"A",
"map",
"of",
"operation",
"index",
"to",
"the",
"_id",
"of",
"the",
"upserted",
"document",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/results.py#L221-L226 | [
"def",
"upserted_ids",
"(",
"self",
")",
":",
"self",
".",
"_raise_if_unacknowledged",
"(",
"\"upserted_ids\"",
")",
"if",
"self",
".",
"__bulk_api_result",
":",
"return",
"dict",
"(",
"(",
"upsert",
"[",
"\"index\"",
"]",
",",
"upsert",
"[",
"\"_id\"",
"]",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | show | Show the contents of the config file. | datadog_checks_dev/datadog_checks/dev/tooling/commands/config.py | def show(all_keys):
"""Show the contents of the config file."""
if not config_file_exists():
echo_info('No config file found! Please try `ddev config restore`.')
else:
if all_keys:
echo_info(read_config_file().rstrip())
else:
echo_info(read_config_file_scrubbe... | def show(all_keys):
"""Show the contents of the config file."""
if not config_file_exists():
echo_info('No config file found! Please try `ddev config restore`.')
else:
if all_keys:
echo_info(read_config_file().rstrip())
else:
echo_info(read_config_file_scrubbe... | [
"Show",
"the",
"contents",
"of",
"the",
"config",
"file",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/commands/config.py#L40-L48 | [
"def",
"show",
"(",
"all_keys",
")",
":",
"if",
"not",
"config_file_exists",
"(",
")",
":",
"echo_info",
"(",
"'No config file found! Please try `ddev config restore`.'",
")",
"else",
":",
"if",
"all_keys",
":",
"echo_info",
"(",
"read_config_file",
"(",
")",
".",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | set_value | Assigns values to config file entries. If the value is omitted,
you will be prompted, with the input hidden if it is sensitive.
\b
$ ddev config set github.user foo
New setting:
[github]
user = "foo" | datadog_checks_dev/datadog_checks/dev/tooling/commands/config.py | def set_value(ctx, key, value):
"""Assigns values to config file entries. If the value is omitted,
you will be prompted, with the input hidden if it is sensitive.
\b
$ ddev config set github.user foo
New setting:
[github]
user = "foo"
"""
scrubbing = False
if value is None:
... | def set_value(ctx, key, value):
"""Assigns values to config file entries. If the value is omitted,
you will be prompted, with the input hidden if it is sensitive.
\b
$ ddev config set github.user foo
New setting:
[github]
user = "foo"
"""
scrubbing = False
if value is None:
... | [
"Assigns",
"values",
"to",
"config",
"file",
"entries",
".",
"If",
"the",
"value",
"is",
"omitted",
"you",
"will",
"be",
"prompted",
"with",
"the",
"input",
"hidden",
"if",
"it",
"is",
"sensitive",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/commands/config.py#L69-L121 | [
"def",
"set_value",
"(",
"ctx",
",",
"key",
",",
"value",
")",
":",
"scrubbing",
"=",
"False",
"if",
"value",
"is",
"None",
":",
"scrubbing",
"=",
"key",
"in",
"SECRET_KEYS",
"value",
"=",
"click",
".",
"prompt",
"(",
"'Value for `{}`'",
".",
"format",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | _SocketManager.close | Return this instance's socket to the connection pool. | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def close(self):
"""Return this instance's socket to the connection pool.
"""
if not self.__closed:
self.__closed = True
self.pool.return_socket(self.sock)
self.sock, self.pool = None, None | def close(self):
"""Return this instance's socket to the connection pool.
"""
if not self.__closed:
self.__closed = True
self.pool.return_socket(self.sock)
self.sock, self.pool = None, None | [
"Return",
"this",
"instance",
"s",
"socket",
"to",
"the",
"connection",
"pool",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L92-L98 | [
"def",
"close",
"(",
"self",
")",
":",
"if",
"not",
"self",
".",
"__closed",
":",
"self",
".",
"__closed",
"=",
"True",
"self",
".",
"pool",
".",
"return_socket",
"(",
"self",
".",
"sock",
")",
"self",
".",
"sock",
",",
"self",
".",
"pool",
"=",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.rewind | Rewind this cursor to its unevaluated state.
Reset this cursor if it has been partially or completely evaluated.
Any options that are present on the cursor will remain in effect.
Future iterating performed on this cursor will cause new queries to
be sent to the server, even if the resul... | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def rewind(self):
"""Rewind this cursor to its unevaluated state.
Reset this cursor if it has been partially or completely evaluated.
Any options that are present on the cursor will remain in effect.
Future iterating performed on this cursor will cause new queries to
be sent to ... | def rewind(self):
"""Rewind this cursor to its unevaluated state.
Reset this cursor if it has been partially or completely evaluated.
Any options that are present on the cursor will remain in effect.
Future iterating performed on this cursor will cause new queries to
be sent to ... | [
"Rewind",
"this",
"cursor",
"to",
"its",
"unevaluated",
"state",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L227-L242 | [
"def",
"rewind",
"(",
"self",
")",
":",
"self",
".",
"__data",
"=",
"deque",
"(",
")",
"self",
".",
"__id",
"=",
"None",
"self",
".",
"__address",
"=",
"None",
"self",
".",
"__retrieved",
"=",
"0",
"self",
".",
"__killed",
"=",
"False",
"return",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor._clone | Internal clone helper. | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def _clone(self, deepcopy=True):
"""Internal clone helper."""
clone = self._clone_base()
values_to_clone = ("spec", "projection", "skip", "limit",
"max_time_ms", "max_await_time_ms", "comment",
"max", "min", "ordering", "explain", "hint",
... | def _clone(self, deepcopy=True):
"""Internal clone helper."""
clone = self._clone_base()
values_to_clone = ("spec", "projection", "skip", "limit",
"max_time_ms", "max_await_time_ms", "comment",
"max", "min", "ordering", "explain", "hint",
... | [
"Internal",
"clone",
"helper",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L254-L267 | [
"def",
"_clone",
"(",
"self",
",",
"deepcopy",
"=",
"True",
")",
":",
"clone",
"=",
"self",
".",
"_clone_base",
"(",
")",
"values_to_clone",
"=",
"(",
"\"spec\"",
",",
"\"projection\"",
",",
"\"skip\"",
",",
"\"limit\"",
",",
"\"max_time_ms\"",
",",
"\"max... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.__die | Closes this cursor. | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def __die(self, synchronous=False):
"""Closes this cursor.
"""
if self.__id and not self.__killed:
if self.__exhaust and self.__exhaust_mgr:
# If this is an exhaust cursor and we haven't completely
# exhausted the result set we *must* close the socket
... | def __die(self, synchronous=False):
"""Closes this cursor.
"""
if self.__id and not self.__killed:
if self.__exhaust and self.__exhaust_mgr:
# If this is an exhaust cursor and we haven't completely
# exhausted the result set we *must* close the socket
... | [
"Closes",
"this",
"cursor",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L274-L294 | [
"def",
"__die",
"(",
"self",
",",
"synchronous",
"=",
"False",
")",
":",
"if",
"self",
".",
"__id",
"and",
"not",
"self",
".",
"__killed",
":",
"if",
"self",
".",
"__exhaust",
"and",
"self",
".",
"__exhaust_mgr",
":",
"# If this is an exhaust cursor and we h... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.__query_spec | Get the spec to use for a query. | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def __query_spec(self):
"""Get the spec to use for a query.
"""
operators = self.__modifiers.copy()
if self.__ordering:
operators["$orderby"] = self.__ordering
if self.__explain:
operators["$explain"] = True
if self.__hint:
operators["$... | def __query_spec(self):
"""Get the spec to use for a query.
"""
operators = self.__modifiers.copy()
if self.__ordering:
operators["$orderby"] = self.__ordering
if self.__explain:
operators["$explain"] = True
if self.__hint:
operators["$... | [
"Get",
"the",
"spec",
"to",
"use",
"for",
"a",
"query",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L301-L355 | [
"def",
"__query_spec",
"(",
"self",
")",
":",
"operators",
"=",
"self",
".",
"__modifiers",
".",
"copy",
"(",
")",
"if",
"self",
".",
"__ordering",
":",
"operators",
"[",
"\"$orderby\"",
"]",
"=",
"self",
".",
"__ordering",
"if",
"self",
".",
"__explain"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.add_option | Set arbitrary query flags using a bitmask.
To set the tailable flag:
cursor.add_option(2) | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def add_option(self, mask):
"""Set arbitrary query flags using a bitmask.
To set the tailable flag:
cursor.add_option(2)
"""
if not isinstance(mask, int):
raise TypeError("mask must be an int")
self.__check_okay_to_chain()
if mask & _QUERY_OPTIONS["e... | def add_option(self, mask):
"""Set arbitrary query flags using a bitmask.
To set the tailable flag:
cursor.add_option(2)
"""
if not isinstance(mask, int):
raise TypeError("mask must be an int")
self.__check_okay_to_chain()
if mask & _QUERY_OPTIONS["e... | [
"Set",
"arbitrary",
"query",
"flags",
"using",
"a",
"bitmask",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L363-L382 | [
"def",
"add_option",
"(",
"self",
",",
"mask",
")",
":",
"if",
"not",
"isinstance",
"(",
"mask",
",",
"int",
")",
":",
"raise",
"TypeError",
"(",
"\"mask must be an int\"",
")",
"self",
".",
"__check_okay_to_chain",
"(",
")",
"if",
"mask",
"&",
"_QUERY_OPT... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.remove_option | Unset arbitrary query flags using a bitmask.
To unset the tailable flag:
cursor.remove_option(2) | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def remove_option(self, mask):
"""Unset arbitrary query flags using a bitmask.
To unset the tailable flag:
cursor.remove_option(2)
"""
if not isinstance(mask, int):
raise TypeError("mask must be an int")
self.__check_okay_to_chain()
if mask & _QUERY_... | def remove_option(self, mask):
"""Unset arbitrary query flags using a bitmask.
To unset the tailable flag:
cursor.remove_option(2)
"""
if not isinstance(mask, int):
raise TypeError("mask must be an int")
self.__check_okay_to_chain()
if mask & _QUERY_... | [
"Unset",
"arbitrary",
"query",
"flags",
"using",
"a",
"bitmask",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L384-L398 | [
"def",
"remove_option",
"(",
"self",
",",
"mask",
")",
":",
"if",
"not",
"isinstance",
"(",
"mask",
",",
"int",
")",
":",
"raise",
"TypeError",
"(",
"\"mask must be an int\"",
")",
"self",
".",
"__check_okay_to_chain",
"(",
")",
"if",
"mask",
"&",
"_QUERY_... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.limit | Limits the number of results to be returned by this cursor.
Raises :exc:`TypeError` if `limit` is not an integer. Raises
:exc:`~pymongo.errors.InvalidOperation` if this :class:`Cursor`
has already been used. The last `limit` applied to this cursor
takes precedence. A limit of ``0`` is e... | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def limit(self, limit):
"""Limits the number of results to be returned by this cursor.
Raises :exc:`TypeError` if `limit` is not an integer. Raises
:exc:`~pymongo.errors.InvalidOperation` if this :class:`Cursor`
has already been used. The last `limit` applied to this cursor
take... | def limit(self, limit):
"""Limits the number of results to be returned by this cursor.
Raises :exc:`TypeError` if `limit` is not an integer. Raises
:exc:`~pymongo.errors.InvalidOperation` if this :class:`Cursor`
has already been used. The last `limit` applied to this cursor
take... | [
"Limits",
"the",
"number",
"of",
"results",
"to",
"be",
"returned",
"by",
"this",
"cursor",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L400-L421 | [
"def",
"limit",
"(",
"self",
",",
"limit",
")",
":",
"if",
"not",
"isinstance",
"(",
"limit",
",",
"integer_types",
")",
":",
"raise",
"TypeError",
"(",
"\"limit must be an integer\"",
")",
"if",
"self",
".",
"__exhaust",
":",
"raise",
"InvalidOperation",
"(... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.skip | Skips the first `skip` results of this cursor.
Raises :exc:`TypeError` if `skip` is not an integer. Raises
:exc:`ValueError` if `skip` is less than ``0``. Raises
:exc:`~pymongo.errors.InvalidOperation` if this :class:`Cursor` has
already been used. The last `skip` applied to this cursor... | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def skip(self, skip):
"""Skips the first `skip` results of this cursor.
Raises :exc:`TypeError` if `skip` is not an integer. Raises
:exc:`ValueError` if `skip` is less than ``0``. Raises
:exc:`~pymongo.errors.InvalidOperation` if this :class:`Cursor` has
already been used. The l... | def skip(self, skip):
"""Skips the first `skip` results of this cursor.
Raises :exc:`TypeError` if `skip` is not an integer. Raises
:exc:`ValueError` if `skip` is less than ``0``. Raises
:exc:`~pymongo.errors.InvalidOperation` if this :class:`Cursor` has
already been used. The l... | [
"Skips",
"the",
"first",
"skip",
"results",
"of",
"this",
"cursor",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L451-L470 | [
"def",
"skip",
"(",
"self",
",",
"skip",
")",
":",
"if",
"not",
"isinstance",
"(",
"skip",
",",
"integer_types",
")",
":",
"raise",
"TypeError",
"(",
"\"skip must be an integer\"",
")",
"if",
"skip",
"<",
"0",
":",
"raise",
"ValueError",
"(",
"\"skip must ... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.max_time_ms | Specifies a time limit for a query operation. If the specified
time is exceeded, the operation will be aborted and
:exc:`~pymongo.errors.ExecutionTimeout` is raised. If `max_time_ms`
is ``None`` no limit is applied.
Raises :exc:`TypeError` if `max_time_ms` is not an integer or ``None``.... | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def max_time_ms(self, max_time_ms):
"""Specifies a time limit for a query operation. If the specified
time is exceeded, the operation will be aborted and
:exc:`~pymongo.errors.ExecutionTimeout` is raised. If `max_time_ms`
is ``None`` no limit is applied.
Raises :exc:`TypeError` ... | def max_time_ms(self, max_time_ms):
"""Specifies a time limit for a query operation. If the specified
time is exceeded, the operation will be aborted and
:exc:`~pymongo.errors.ExecutionTimeout` is raised. If `max_time_ms`
is ``None`` no limit is applied.
Raises :exc:`TypeError` ... | [
"Specifies",
"a",
"time",
"limit",
"for",
"a",
"query",
"operation",
".",
"If",
"the",
"specified",
"time",
"is",
"exceeded",
"the",
"operation",
"will",
"be",
"aborted",
"and",
":",
"exc",
":",
"~pymongo",
".",
"errors",
".",
"ExecutionTimeout",
"is",
"ra... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L472-L491 | [
"def",
"max_time_ms",
"(",
"self",
",",
"max_time_ms",
")",
":",
"if",
"(",
"not",
"isinstance",
"(",
"max_time_ms",
",",
"integer_types",
")",
"and",
"max_time_ms",
"is",
"not",
"None",
")",
":",
"raise",
"TypeError",
"(",
"\"max_time_ms must be an integer or N... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.max_await_time_ms | Specifies a time limit for a getMore operation on a
:attr:`~pymongo.cursor.CursorType.TAILABLE_AWAIT` cursor. For all other
types of cursor max_await_time_ms is ignored.
Raises :exc:`TypeError` if `max_await_time_ms` is not an integer or
``None``. Raises :exc:`~pymongo.errors.InvalidOpe... | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def max_await_time_ms(self, max_await_time_ms):
"""Specifies a time limit for a getMore operation on a
:attr:`~pymongo.cursor.CursorType.TAILABLE_AWAIT` cursor. For all other
types of cursor max_await_time_ms is ignored.
Raises :exc:`TypeError` if `max_await_time_ms` is not an integer o... | def max_await_time_ms(self, max_await_time_ms):
"""Specifies a time limit for a getMore operation on a
:attr:`~pymongo.cursor.CursorType.TAILABLE_AWAIT` cursor. For all other
types of cursor max_await_time_ms is ignored.
Raises :exc:`TypeError` if `max_await_time_ms` is not an integer o... | [
"Specifies",
"a",
"time",
"limit",
"for",
"a",
"getMore",
"operation",
"on",
"a",
":",
"attr",
":",
"~pymongo",
".",
"cursor",
".",
"CursorType",
".",
"TAILABLE_AWAIT",
"cursor",
".",
"For",
"all",
"other",
"types",
"of",
"cursor",
"max_await_time_ms",
"is",... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L493-L519 | [
"def",
"max_await_time_ms",
"(",
"self",
",",
"max_await_time_ms",
")",
":",
"if",
"(",
"not",
"isinstance",
"(",
"max_await_time_ms",
",",
"integer_types",
")",
"and",
"max_await_time_ms",
"is",
"not",
"None",
")",
":",
"raise",
"TypeError",
"(",
"\"max_await_t... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.max | Adds `max` operator that specifies upper bound for specific index.
:Parameters:
- `spec`: a list of field, limit pairs specifying the exclusive
upper bound for all keys of a specific index in order.
.. versionadded:: 2.7 | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def max(self, spec):
"""Adds `max` operator that specifies upper bound for specific index.
:Parameters:
- `spec`: a list of field, limit pairs specifying the exclusive
upper bound for all keys of a specific index in order.
.. versionadded:: 2.7
"""
if not ... | def max(self, spec):
"""Adds `max` operator that specifies upper bound for specific index.
:Parameters:
- `spec`: a list of field, limit pairs specifying the exclusive
upper bound for all keys of a specific index in order.
.. versionadded:: 2.7
"""
if not ... | [
"Adds",
"max",
"operator",
"that",
"specifies",
"upper",
"bound",
"for",
"specific",
"index",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L604-L618 | [
"def",
"max",
"(",
"self",
",",
"spec",
")",
":",
"if",
"not",
"isinstance",
"(",
"spec",
",",
"(",
"list",
",",
"tuple",
")",
")",
":",
"raise",
"TypeError",
"(",
"\"spec must be an instance of list or tuple\"",
")",
"self",
".",
"__check_okay_to_chain",
"(... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.min | Adds `min` operator that specifies lower bound for specific index.
:Parameters:
- `spec`: a list of field, limit pairs specifying the inclusive
lower bound for all keys of a specific index in order.
.. versionadded:: 2.7 | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def min(self, spec):
"""Adds `min` operator that specifies lower bound for specific index.
:Parameters:
- `spec`: a list of field, limit pairs specifying the inclusive
lower bound for all keys of a specific index in order.
.. versionadded:: 2.7
"""
if not ... | def min(self, spec):
"""Adds `min` operator that specifies lower bound for specific index.
:Parameters:
- `spec`: a list of field, limit pairs specifying the inclusive
lower bound for all keys of a specific index in order.
.. versionadded:: 2.7
"""
if not ... | [
"Adds",
"min",
"operator",
"that",
"specifies",
"lower",
"bound",
"for",
"specific",
"index",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L620-L634 | [
"def",
"min",
"(",
"self",
",",
"spec",
")",
":",
"if",
"not",
"isinstance",
"(",
"spec",
",",
"(",
"list",
",",
"tuple",
")",
")",
":",
"raise",
"TypeError",
"(",
"\"spec must be an instance of list or tuple\"",
")",
"self",
".",
"__check_okay_to_chain",
"(... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.sort | Sorts this cursor's results.
Pass a field name and a direction, either
:data:`~pymongo.ASCENDING` or :data:`~pymongo.DESCENDING`::
for doc in collection.find().sort('field', pymongo.ASCENDING):
print(doc)
To sort by multiple fields, pass a list of (key, direction) ... | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def sort(self, key_or_list, direction=None):
"""Sorts this cursor's results.
Pass a field name and a direction, either
:data:`~pymongo.ASCENDING` or :data:`~pymongo.DESCENDING`::
for doc in collection.find().sort('field', pymongo.ASCENDING):
print(doc)
To s... | def sort(self, key_or_list, direction=None):
"""Sorts this cursor's results.
Pass a field name and a direction, either
:data:`~pymongo.ASCENDING` or :data:`~pymongo.DESCENDING`::
for doc in collection.find().sort('field', pymongo.ASCENDING):
print(doc)
To s... | [
"Sorts",
"this",
"cursor",
"s",
"results",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L636-L678 | [
"def",
"sort",
"(",
"self",
",",
"key_or_list",
",",
"direction",
"=",
"None",
")",
":",
"self",
".",
"__check_okay_to_chain",
"(",
")",
"keys",
"=",
"helpers",
".",
"_index_list",
"(",
"key_or_list",
",",
"direction",
")",
"self",
".",
"__ordering",
"=",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.count | Get the size of the results set for this query.
Returns the number of documents in the results set for this query. Does
not take :meth:`limit` and :meth:`skip` into account by default - set
`with_limit_and_skip` to ``True`` if that is the desired behavior.
Raises :class:`~pymongo.errors... | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def count(self, with_limit_and_skip=False):
"""Get the size of the results set for this query.
Returns the number of documents in the results set for this query. Does
not take :meth:`limit` and :meth:`skip` into account by default - set
`with_limit_and_skip` to ``True`` if that is the d... | def count(self, with_limit_and_skip=False):
"""Get the size of the results set for this query.
Returns the number of documents in the results set for this query. Does
not take :meth:`limit` and :meth:`skip` into account by default - set
`with_limit_and_skip` to ``True`` if that is the d... | [
"Get",
"the",
"size",
"of",
"the",
"results",
"set",
"for",
"this",
"query",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L680-L727 | [
"def",
"count",
"(",
"self",
",",
"with_limit_and_skip",
"=",
"False",
")",
":",
"validate_boolean",
"(",
"\"with_limit_and_skip\"",
",",
"with_limit_and_skip",
")",
"cmd",
"=",
"SON",
"(",
"[",
"(",
"\"count\"",
",",
"self",
".",
"__collection",
".",
"name",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.distinct | Get a list of distinct values for `key` among all documents
in the result set of this query.
Raises :class:`TypeError` if `key` is not an instance of
:class:`basestring` (:class:`str` in python 3).
The :meth:`distinct` method obeys the
:attr:`~pymongo.collection.Collection.read... | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def distinct(self, key):
"""Get a list of distinct values for `key` among all documents
in the result set of this query.
Raises :class:`TypeError` if `key` is not an instance of
:class:`basestring` (:class:`str` in python 3).
The :meth:`distinct` method obeys the
:attr:... | def distinct(self, key):
"""Get a list of distinct values for `key` among all documents
in the result set of this query.
Raises :class:`TypeError` if `key` is not an instance of
:class:`basestring` (:class:`str` in python 3).
The :meth:`distinct` method obeys the
:attr:... | [
"Get",
"a",
"list",
"of",
"distinct",
"values",
"for",
"key",
"among",
"all",
"documents",
"in",
"the",
"result",
"set",
"of",
"this",
"query",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L729-L756 | [
"def",
"distinct",
"(",
"self",
",",
"key",
")",
":",
"options",
"=",
"{",
"}",
"if",
"self",
".",
"__spec",
":",
"options",
"[",
"\"query\"",
"]",
"=",
"self",
".",
"__spec",
"if",
"self",
".",
"__max_time_ms",
"is",
"not",
"None",
":",
"options",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.explain | Returns an explain plan record for this cursor.
.. mongodoc:: explain | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def explain(self):
"""Returns an explain plan record for this cursor.
.. mongodoc:: explain
"""
c = self.clone()
c.__explain = True
# always use a hard limit for explains
if c.__limit:
c.__limit = -abs(c.__limit)
return next(c) | def explain(self):
"""Returns an explain plan record for this cursor.
.. mongodoc:: explain
"""
c = self.clone()
c.__explain = True
# always use a hard limit for explains
if c.__limit:
c.__limit = -abs(c.__limit)
return next(c) | [
"Returns",
"an",
"explain",
"plan",
"record",
"for",
"this",
"cursor",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L758-L769 | [
"def",
"explain",
"(",
"self",
")",
":",
"c",
"=",
"self",
".",
"clone",
"(",
")",
"c",
".",
"__explain",
"=",
"True",
"# always use a hard limit for explains",
"if",
"c",
".",
"__limit",
":",
"c",
".",
"__limit",
"=",
"-",
"abs",
"(",
"c",
".",
"__l... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.where | Adds a $where clause to this query.
The `code` argument must be an instance of :class:`basestring`
(:class:`str` in python 3) or :class:`~bson.code.Code`
containing a JavaScript expression. This expression will be
evaluated for each document scanned. Only those documents
for whi... | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def where(self, code):
"""Adds a $where clause to this query.
The `code` argument must be an instance of :class:`basestring`
(:class:`str` in python 3) or :class:`~bson.code.Code`
containing a JavaScript expression. This expression will be
evaluated for each document scanned. On... | def where(self, code):
"""Adds a $where clause to this query.
The `code` argument must be an instance of :class:`basestring`
(:class:`str` in python 3) or :class:`~bson.code.Code`
containing a JavaScript expression. This expression will be
evaluated for each document scanned. On... | [
"Adds",
"a",
"$where",
"clause",
"to",
"this",
"query",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L823-L848 | [
"def",
"where",
"(",
"self",
",",
"code",
")",
":",
"self",
".",
"__check_okay_to_chain",
"(",
")",
"if",
"not",
"isinstance",
"(",
"code",
",",
"Code",
")",
":",
"code",
"=",
"Code",
"(",
"code",
")",
"self",
".",
"__spec",
"[",
"\"$where\"",
"]",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.collation | Adds a :class:`~pymongo.collation.Collation` to this query.
This option is only supported on MongoDB 3.4 and above.
Raises :exc:`TypeError` if `collation` is not an instance of
:class:`~pymongo.collation.Collation` or a ``dict``. Raises
:exc:`~pymongo.errors.InvalidOperation` if this :... | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def collation(self, collation):
"""Adds a :class:`~pymongo.collation.Collation` to this query.
This option is only supported on MongoDB 3.4 and above.
Raises :exc:`TypeError` if `collation` is not an instance of
:class:`~pymongo.collation.Collation` or a ``dict``. Raises
:exc:`... | def collation(self, collation):
"""Adds a :class:`~pymongo.collation.Collation` to this query.
This option is only supported on MongoDB 3.4 and above.
Raises :exc:`TypeError` if `collation` is not an instance of
:class:`~pymongo.collation.Collation` or a ``dict``. Raises
:exc:`... | [
"Adds",
"a",
":",
"class",
":",
"~pymongo",
".",
"collation",
".",
"Collation",
"to",
"this",
"query",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L850-L866 | [
"def",
"collation",
"(",
"self",
",",
"collation",
")",
":",
"self",
".",
"__check_okay_to_chain",
"(",
")",
"self",
".",
"__collation",
"=",
"validate_collation_or_none",
"(",
"collation",
")",
"return",
"self"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.__send_message | Send a query or getmore operation and handles the response.
If operation is ``None`` this is an exhaust cursor, which reads
the next result batch off the exhaust socket instead of
sending getMore messages to the server.
Can raise ConnectionFailure. | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def __send_message(self, operation):
"""Send a query or getmore operation and handles the response.
If operation is ``None`` this is an exhaust cursor, which reads
the next result batch off the exhaust socket instead of
sending getMore messages to the server.
Can raise Connecti... | def __send_message(self, operation):
"""Send a query or getmore operation and handles the response.
If operation is ``None`` this is an exhaust cursor, which reads
the next result batch off the exhaust socket instead of
sending getMore messages to the server.
Can raise Connecti... | [
"Send",
"a",
"query",
"or",
"getmore",
"operation",
"and",
"handles",
"the",
"response",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L868-L1031 | [
"def",
"__send_message",
"(",
"self",
",",
"operation",
")",
":",
"client",
"=",
"self",
".",
"__collection",
".",
"database",
".",
"client",
"listeners",
"=",
"client",
".",
"_event_listeners",
"publish",
"=",
"listeners",
".",
"enabled_for_commands",
"from_com... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor._refresh | Refreshes the cursor with more data from Mongo.
Returns the length of self.__data after refresh. Will exit early if
self.__data is already non-empty. Raises OperationFailure when the
cursor cannot be refreshed due to an error on the query. | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def _refresh(self):
"""Refreshes the cursor with more data from Mongo.
Returns the length of self.__data after refresh. Will exit early if
self.__data is already non-empty. Raises OperationFailure when the
cursor cannot be refreshed due to an error on the query.
"""
if l... | def _refresh(self):
"""Refreshes the cursor with more data from Mongo.
Returns the length of self.__data after refresh. Will exit early if
self.__data is already non-empty. Raises OperationFailure when the
cursor cannot be refreshed due to an error on the query.
"""
if l... | [
"Refreshes",
"the",
"cursor",
"with",
"more",
"data",
"from",
"Mongo",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L1033-L1080 | [
"def",
"_refresh",
"(",
"self",
")",
":",
"if",
"len",
"(",
"self",
".",
"__data",
")",
"or",
"self",
".",
"__killed",
":",
"return",
"len",
"(",
"self",
".",
"__data",
")",
"if",
"self",
".",
"__id",
"is",
"None",
":",
"# Query",
"self",
".",
"_... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor.next | Advance the cursor. | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def next(self):
"""Advance the cursor."""
if self.__empty:
raise StopIteration
if len(self.__data) or self._refresh():
if self.__manipulate:
_db = self.__collection.database
return _db._fix_outgoing(self.__data.popleft(),
... | def next(self):
"""Advance the cursor."""
if self.__empty:
raise StopIteration
if len(self.__data) or self._refresh():
if self.__manipulate:
_db = self.__collection.database
return _db._fix_outgoing(self.__data.popleft(),
... | [
"Advance",
"the",
"cursor",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L1128-L1140 | [
"def",
"next",
"(",
"self",
")",
":",
"if",
"self",
".",
"__empty",
":",
"raise",
"StopIteration",
"if",
"len",
"(",
"self",
".",
"__data",
")",
"or",
"self",
".",
"_refresh",
"(",
")",
":",
"if",
"self",
".",
"__manipulate",
":",
"_db",
"=",
"self... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Cursor._deepcopy | Deepcopy helper for the data dictionary or list.
Regular expressions cannot be deep copied but as they are immutable we
don't have to copy them when cloning. | tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py | def _deepcopy(self, x, memo=None):
"""Deepcopy helper for the data dictionary or list.
Regular expressions cannot be deep copied but as they are immutable we
don't have to copy them when cloning.
"""
if not hasattr(x, 'items'):
y, is_list, iterator = [], True, enumer... | def _deepcopy(self, x, memo=None):
"""Deepcopy helper for the data dictionary or list.
Regular expressions cannot be deep copied but as they are immutable we
don't have to copy them when cloning.
"""
if not hasattr(x, 'items'):
y, is_list, iterator = [], True, enumer... | [
"Deepcopy",
"helper",
"for",
"the",
"data",
"dictionary",
"or",
"list",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/cursor.py#L1164-L1194 | [
"def",
"_deepcopy",
"(",
"self",
",",
"x",
",",
"memo",
"=",
"None",
")",
":",
"if",
"not",
"hasattr",
"(",
"x",
",",
"'items'",
")",
":",
"y",
",",
"is_list",
",",
"iterator",
"=",
"[",
"]",
",",
"True",
",",
"enumerate",
"(",
"x",
")",
"else"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | trace_method | Decorator to catch and print the exceptions that happen within async tasks.
Note: this should be applied to methods of VSphereCheck only! | vsphere/datadog_checks/vsphere/vsphere.py | def trace_method(method):
"""
Decorator to catch and print the exceptions that happen within async tasks.
Note: this should be applied to methods of VSphereCheck only!
"""
def wrapper(*args, **kwargs):
try:
method(*args, **kwargs)
except Exception:
args[0].pr... | def trace_method(method):
"""
Decorator to catch and print the exceptions that happen within async tasks.
Note: this should be applied to methods of VSphereCheck only!
"""
def wrapper(*args, **kwargs):
try:
method(*args, **kwargs)
except Exception:
args[0].pr... | [
"Decorator",
"to",
"catch",
"and",
"print",
"the",
"exceptions",
"that",
"happen",
"within",
"async",
"tasks",
".",
"Note",
":",
"this",
"should",
"be",
"applied",
"to",
"methods",
"of",
"VSphereCheck",
"only!"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L68-L80 | [
"def",
"trace_method",
"(",
"method",
")",
":",
"def",
"wrapper",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"try",
":",
"method",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
"except",
"Exception",
":",
"args",
"[",
"0",
"]",
".",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck.print_exception | Print exceptions happening in separate threads
Prevent from logging a ton of them if a potentially big number of them fail the same way | vsphere/datadog_checks/vsphere/vsphere.py | def print_exception(self, msg):
""" Print exceptions happening in separate threads
Prevent from logging a ton of them if a potentially big number of them fail the same way
"""
if self.exception_printed < 10:
self.log.error(msg)
self.exception_printed += 1 | def print_exception(self, msg):
""" Print exceptions happening in separate threads
Prevent from logging a ton of them if a potentially big number of them fail the same way
"""
if self.exception_printed < 10:
self.log.error(msg)
self.exception_printed += 1 | [
"Print",
"exceptions",
"happening",
"in",
"separate",
"threads",
"Prevent",
"from",
"logging",
"a",
"ton",
"of",
"them",
"if",
"a",
"potentially",
"big",
"number",
"of",
"them",
"fail",
"the",
"same",
"way"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L143-L149 | [
"def",
"print_exception",
"(",
"self",
",",
"msg",
")",
":",
"if",
"self",
".",
"exception_printed",
"<",
"10",
":",
"self",
".",
"log",
".",
"error",
"(",
"msg",
")",
"self",
".",
"exception_printed",
"+=",
"1"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck._compute_needed_metrics | Compare the available metrics for one MOR we have computed and intersect them
with the set of metrics we want to report | vsphere/datadog_checks/vsphere/vsphere.py | def _compute_needed_metrics(self, instance, available_metrics):
""" Compare the available metrics for one MOR we have computed and intersect them
with the set of metrics we want to report
"""
i_key = self._instance_key(instance)
if self.in_compatibility_mode(instance):
... | def _compute_needed_metrics(self, instance, available_metrics):
""" Compare the available metrics for one MOR we have computed and intersect them
with the set of metrics we want to report
"""
i_key = self._instance_key(instance)
if self.in_compatibility_mode(instance):
... | [
"Compare",
"the",
"available",
"metrics",
"for",
"one",
"MOR",
"we",
"have",
"computed",
"and",
"intersect",
"them",
"with",
"the",
"set",
"of",
"metrics",
"we",
"want",
"to",
"report"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L288-L317 | [
"def",
"_compute_needed_metrics",
"(",
"self",
",",
"instance",
",",
"available_metrics",
")",
":",
"i_key",
"=",
"self",
".",
"_instance_key",
"(",
"instance",
")",
"if",
"self",
".",
"in_compatibility_mode",
"(",
"instance",
")",
":",
"if",
"instance",
".",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck.get_external_host_tags | Returns a list of tags for every host that is detected by the vSphere
integration.
Returns a list of pairs (hostname, {'SOURCE_TYPE: list_of_tags},) | vsphere/datadog_checks/vsphere/vsphere.py | def get_external_host_tags(self):
"""
Returns a list of tags for every host that is detected by the vSphere
integration.
Returns a list of pairs (hostname, {'SOURCE_TYPE: list_of_tags},)
"""
self.log.debug("Sending external_host_tags now")
external_host_tags = []... | def get_external_host_tags(self):
"""
Returns a list of tags for every host that is detected by the vSphere
integration.
Returns a list of pairs (hostname, {'SOURCE_TYPE: list_of_tags},)
"""
self.log.debug("Sending external_host_tags now")
external_host_tags = []... | [
"Returns",
"a",
"list",
"of",
"tags",
"for",
"every",
"host",
"that",
"is",
"detected",
"by",
"the",
"vSphere",
"integration",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L319-L340 | [
"def",
"get_external_host_tags",
"(",
"self",
")",
":",
"self",
".",
"log",
".",
"debug",
"(",
"\"Sending external_host_tags now\"",
")",
"external_host_tags",
"=",
"[",
"]",
"for",
"instance",
"in",
"self",
".",
"instances",
":",
"i_key",
"=",
"self",
".",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck._get_all_objs | Explore vCenter infrastructure to discover hosts, virtual machines, etc.
and compute their associated tags.
Start at the vCenter `rootFolder`, so as to collect every objet.
Example topology:
```
rootFolder
- datacenter1
- compute_resou... | vsphere/datadog_checks/vsphere/vsphere.py | def _get_all_objs(
self, server_instance, regexes=None, include_only_marked=False, tags=None, use_guest_hostname=False
):
"""
Explore vCenter infrastructure to discover hosts, virtual machines, etc.
and compute their associated tags.
Start at the vCenter `rootFolder`, so as t... | def _get_all_objs(
self, server_instance, regexes=None, include_only_marked=False, tags=None, use_guest_hostname=False
):
"""
Explore vCenter infrastructure to discover hosts, virtual machines, etc.
and compute their associated tags.
Start at the vCenter `rootFolder`, so as t... | [
"Explore",
"vCenter",
"infrastructure",
"to",
"discover",
"hosts",
"virtual",
"machines",
"etc",
".",
"and",
"compute",
"their",
"associated",
"tags",
".",
"Start",
"at",
"the",
"vCenter",
"rootFolder",
"so",
"as",
"to",
"collect",
"every",
"objet",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L436-L535 | [
"def",
"_get_all_objs",
"(",
"self",
",",
"server_instance",
",",
"regexes",
"=",
"None",
",",
"include_only_marked",
"=",
"False",
",",
"tags",
"=",
"None",
",",
"use_guest_hostname",
"=",
"False",
")",
":",
"start",
"=",
"time",
".",
"time",
"(",
")",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck._is_excluded | Return `True` if the given host or virtual machine is excluded by the user configuration,
i.e. violates any of the following rules:
* Do not match the corresponding `*_include_only` regular expressions
* Is "non-labeled" while `include_only_marked` is enabled (virtual machine only) | vsphere/datadog_checks/vsphere/vsphere.py | def _is_excluded(obj, properties, regexes, include_only_marked):
"""
Return `True` if the given host or virtual machine is excluded by the user configuration,
i.e. violates any of the following rules:
* Do not match the corresponding `*_include_only` regular expressions
* Is "non... | def _is_excluded(obj, properties, regexes, include_only_marked):
"""
Return `True` if the given host or virtual machine is excluded by the user configuration,
i.e. violates any of the following rules:
* Do not match the corresponding `*_include_only` regular expressions
* Is "non... | [
"Return",
"True",
"if",
"the",
"given",
"host",
"or",
"virtual",
"machine",
"is",
"excluded",
"by",
"the",
"user",
"configuration",
"i",
".",
"e",
".",
"violates",
"any",
"of",
"the",
"following",
"rules",
":",
"*",
"Do",
"not",
"match",
"the",
"correspo... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L538-L571 | [
"def",
"_is_excluded",
"(",
"obj",
",",
"properties",
",",
"regexes",
",",
"include_only_marked",
")",
":",
"# Host",
"if",
"isinstance",
"(",
"obj",
",",
"vim",
".",
"HostSystem",
")",
":",
"# Based on `host_include_only_regex`",
"if",
"regexes",
"and",
"regexe... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck._cache_morlist_raw | Fill the Mor objects queue that will be asynchronously processed later.
Resolve the vCenter `rootFolder` and initiate hosts and virtual machines
discovery. | vsphere/datadog_checks/vsphere/vsphere.py | def _cache_morlist_raw(self, instance):
"""
Fill the Mor objects queue that will be asynchronously processed later.
Resolve the vCenter `rootFolder` and initiate hosts and virtual machines
discovery.
"""
i_key = self._instance_key(instance)
self.log.debug("Caching... | def _cache_morlist_raw(self, instance):
"""
Fill the Mor objects queue that will be asynchronously processed later.
Resolve the vCenter `rootFolder` and initiate hosts and virtual machines
discovery.
"""
i_key = self._instance_key(instance)
self.log.debug("Caching... | [
"Fill",
"the",
"Mor",
"objects",
"queue",
"that",
"will",
"be",
"asynchronously",
"processed",
"later",
".",
"Resolve",
"the",
"vCenter",
"rootFolder",
"and",
"initiate",
"hosts",
"and",
"virtual",
"machines",
"discovery",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L573-L608 | [
"def",
"_cache_morlist_raw",
"(",
"self",
",",
"instance",
")",
":",
"i_key",
"=",
"self",
".",
"_instance_key",
"(",
"instance",
")",
"self",
".",
"log",
".",
"debug",
"(",
"\"Caching the morlist for vcenter instance {}\"",
".",
"format",
"(",
"i_key",
")",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck._process_mor_objects_queue_async | Process a batch of items popped from the objects queue by querying the available
metrics for these MORs and then putting them in the Mor cache | vsphere/datadog_checks/vsphere/vsphere.py | def _process_mor_objects_queue_async(self, instance, mors):
"""
Process a batch of items popped from the objects queue by querying the available
metrics for these MORs and then putting them in the Mor cache
"""
t = time.time()
i_key = self._instance_key(instance)
... | def _process_mor_objects_queue_async(self, instance, mors):
"""
Process a batch of items popped from the objects queue by querying the available
metrics for these MORs and then putting them in the Mor cache
"""
t = time.time()
i_key = self._instance_key(instance)
... | [
"Process",
"a",
"batch",
"of",
"items",
"popped",
"from",
"the",
"objects",
"queue",
"by",
"querying",
"the",
"available",
"metrics",
"for",
"these",
"MORs",
"and",
"then",
"putting",
"them",
"in",
"the",
"Mor",
"cache"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L611-L636 | [
"def",
"_process_mor_objects_queue_async",
"(",
"self",
",",
"instance",
",",
"mors",
")",
":",
"t",
"=",
"time",
".",
"time",
"(",
")",
"i_key",
"=",
"self",
".",
"_instance_key",
"(",
"instance",
")",
"server_instance",
"=",
"self",
".",
"_get_server_insta... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck._process_mor_objects_queue | Pops `batch_morlist_size` items from the mor objects queue and run asynchronously
the _process_mor_objects_queue_async method to fill the Mor cache. | vsphere/datadog_checks/vsphere/vsphere.py | def _process_mor_objects_queue(self, instance):
"""
Pops `batch_morlist_size` items from the mor objects queue and run asynchronously
the _process_mor_objects_queue_async method to fill the Mor cache.
"""
i_key = self._instance_key(instance)
self.mor_cache.init_instance(i... | def _process_mor_objects_queue(self, instance):
"""
Pops `batch_morlist_size` items from the mor objects queue and run asynchronously
the _process_mor_objects_queue_async method to fill the Mor cache.
"""
i_key = self._instance_key(instance)
self.mor_cache.init_instance(i... | [
"Pops",
"batch_morlist_size",
"items",
"from",
"the",
"mor",
"objects",
"queue",
"and",
"run",
"asynchronously",
"the",
"_process_mor_objects_queue_async",
"method",
"to",
"fill",
"the",
"Mor",
"cache",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L638-L678 | [
"def",
"_process_mor_objects_queue",
"(",
"self",
",",
"instance",
")",
":",
"i_key",
"=",
"self",
".",
"_instance_key",
"(",
"instance",
")",
"self",
".",
"mor_cache",
".",
"init_instance",
"(",
"i_key",
")",
"if",
"not",
"self",
".",
"mor_objects_queue",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck._cache_metrics_metadata | Get all the performance counters metadata meaning name/group/description...
from the server instance, attached with the corresponding ID | vsphere/datadog_checks/vsphere/vsphere.py | def _cache_metrics_metadata(self, instance):
"""
Get all the performance counters metadata meaning name/group/description...
from the server instance, attached with the corresponding ID
"""
# ## <TEST-INSTRUMENTATION>
t = Timer()
# ## </TEST-INSTRUMENTATION>
... | def _cache_metrics_metadata(self, instance):
"""
Get all the performance counters metadata meaning name/group/description...
from the server instance, attached with the corresponding ID
"""
# ## <TEST-INSTRUMENTATION>
t = Timer()
# ## </TEST-INSTRUMENTATION>
... | [
"Get",
"all",
"the",
"performance",
"counters",
"metadata",
"meaning",
"name",
"/",
"group",
"/",
"description",
"...",
"from",
"the",
"server",
"instance",
"attached",
"with",
"the",
"corresponding",
"ID"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L680-L721 | [
"def",
"_cache_metrics_metadata",
"(",
"self",
",",
"instance",
")",
":",
"# ## <TEST-INSTRUMENTATION>",
"t",
"=",
"Timer",
"(",
")",
"# ## </TEST-INSTRUMENTATION>",
"i_key",
"=",
"self",
".",
"_instance_key",
"(",
"instance",
")",
"self",
".",
"metadata_cache",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck._transform_value | Given the counter_id, look up for the metrics metadata to check the vsphere
type of the counter and apply pre-reporting transformation if needed. | vsphere/datadog_checks/vsphere/vsphere.py | def _transform_value(self, instance, counter_id, value):
""" Given the counter_id, look up for the metrics metadata to check the vsphere
type of the counter and apply pre-reporting transformation if needed.
"""
i_key = self._instance_key(instance)
try:
metadata = self... | def _transform_value(self, instance, counter_id, value):
""" Given the counter_id, look up for the metrics metadata to check the vsphere
type of the counter and apply pre-reporting transformation if needed.
"""
i_key = self._instance_key(instance)
try:
metadata = self... | [
"Given",
"the",
"counter_id",
"look",
"up",
"for",
"the",
"metrics",
"metadata",
"to",
"check",
"the",
"vsphere",
"type",
"of",
"the",
"counter",
"and",
"apply",
"pre",
"-",
"reporting",
"transformation",
"if",
"needed",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L753-L766 | [
"def",
"_transform_value",
"(",
"self",
",",
"instance",
",",
"counter_id",
",",
"value",
")",
":",
"i_key",
"=",
"self",
".",
"_instance_key",
"(",
"instance",
")",
"try",
":",
"metadata",
"=",
"self",
".",
"metadata_cache",
".",
"get_metadata",
"(",
"i_k... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck._collect_metrics_async | Task that collects the metrics listed in the morlist for one MOR | vsphere/datadog_checks/vsphere/vsphere.py | def _collect_metrics_async(self, instance, query_specs):
""" Task that collects the metrics listed in the morlist for one MOR
"""
# ## <TEST-INSTRUMENTATION>
t = Timer()
# ## </TEST-INSTRUMENTATION>
i_key = self._instance_key(instance)
server_instance = self._get_... | def _collect_metrics_async(self, instance, query_specs):
""" Task that collects the metrics listed in the morlist for one MOR
"""
# ## <TEST-INSTRUMENTATION>
t = Timer()
# ## </TEST-INSTRUMENTATION>
i_key = self._instance_key(instance)
server_instance = self._get_... | [
"Task",
"that",
"collects",
"the",
"metrics",
"listed",
"in",
"the",
"morlist",
"for",
"one",
"MOR"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L769-L834 | [
"def",
"_collect_metrics_async",
"(",
"self",
",",
"instance",
",",
"query_specs",
")",
":",
"# ## <TEST-INSTRUMENTATION>",
"t",
"=",
"Timer",
"(",
")",
"# ## </TEST-INSTRUMENTATION>",
"i_key",
"=",
"self",
".",
"_instance_key",
"(",
"instance",
")",
"server_instanc... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | VSphereCheck.collect_metrics | Calls asynchronously _collect_metrics_async on all MORs, as the
job queue is processed the Aggregator will receive the metrics. | vsphere/datadog_checks/vsphere/vsphere.py | def collect_metrics(self, instance):
"""
Calls asynchronously _collect_metrics_async on all MORs, as the
job queue is processed the Aggregator will receive the metrics.
"""
i_key = self._instance_key(instance)
if not self.mor_cache.contains(i_key):
self.log.de... | def collect_metrics(self, instance):
"""
Calls asynchronously _collect_metrics_async on all MORs, as the
job queue is processed the Aggregator will receive the metrics.
"""
i_key = self._instance_key(instance)
if not self.mor_cache.contains(i_key):
self.log.de... | [
"Calls",
"asynchronously",
"_collect_metrics_async",
"on",
"all",
"MORs",
"as",
"the",
"job",
"queue",
"is",
"processed",
"the",
"Aggregator",
"will",
"receive",
"the",
"metrics",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/vsphere/datadog_checks/vsphere/vsphere.py#L837-L883 | [
"def",
"collect_metrics",
"(",
"self",
",",
"instance",
")",
":",
"i_key",
"=",
"self",
".",
"_instance_key",
"(",
"instance",
")",
"if",
"not",
"self",
".",
"mor_cache",
".",
"contains",
"(",
"i_key",
")",
":",
"self",
".",
"log",
".",
"debug",
"(",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer._check_db_exists | Check if the database we're targeting actually exists
If not then we won't do any checks
This allows the same config to be installed on many servers but fail gracefully | sqlserver/datadog_checks/sqlserver/sqlserver.py | def _check_db_exists(self, instance):
"""
Check if the database we're targeting actually exists
If not then we won't do any checks
This allows the same config to be installed on many servers but fail gracefully
"""
dsn, host, username, password, database, driver = self._... | def _check_db_exists(self, instance):
"""
Check if the database we're targeting actually exists
If not then we won't do any checks
This allows the same config to be installed on many servers but fail gracefully
"""
dsn, host, username, password, database, driver = self._... | [
"Check",
"if",
"the",
"database",
"we",
"re",
"targeting",
"actually",
"exists",
"If",
"not",
"then",
"we",
"won",
"t",
"do",
"any",
"checks",
"This",
"allows",
"the",
"same",
"config",
"to",
"be",
"installed",
"on",
"many",
"servers",
"but",
"fail",
"gr... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L178-L202 | [
"def",
"_check_db_exists",
"(",
"self",
",",
"instance",
")",
":",
"dsn",
",",
"host",
",",
"username",
",",
"password",
",",
"database",
",",
"driver",
"=",
"self",
".",
"_get_access_info",
"(",
"instance",
",",
"self",
".",
"DEFAULT_DB_KEY",
")",
"contex... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer._make_metric_list_to_collect | Store the list of metrics to collect by instance_key.
Will also create and cache cursors to query the db. | sqlserver/datadog_checks/sqlserver/sqlserver.py | def _make_metric_list_to_collect(self, instance, custom_metrics):
"""
Store the list of metrics to collect by instance_key.
Will also create and cache cursors to query the db.
"""
metrics_to_collect = []
for name, counter_name, instance_name in self.METRICS:
t... | def _make_metric_list_to_collect(self, instance, custom_metrics):
"""
Store the list of metrics to collect by instance_key.
Will also create and cache cursors to query the db.
"""
metrics_to_collect = []
for name, counter_name, instance_name in self.METRICS:
t... | [
"Store",
"the",
"list",
"of",
"metrics",
"to",
"collect",
"by",
"instance_key",
".",
"Will",
"also",
"create",
"and",
"cache",
"cursors",
"to",
"query",
"the",
"db",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L204-L286 | [
"def",
"_make_metric_list_to_collect",
"(",
"self",
",",
"instance",
",",
"custom_metrics",
")",
":",
"metrics_to_collect",
"=",
"[",
"]",
"for",
"name",
",",
"counter_name",
",",
"instance_name",
"in",
"self",
".",
"METRICS",
":",
"try",
":",
"sql_type",
",",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer.typed_metric | Create the appropriate SqlServerMetric object, each implementing its method to
fetch the metrics properly.
If a `type` was specified in the config, it is used to report the value
directly fetched from SQLServer. Otherwise, it is decided based on the
sql_type, according to microsoft's doc... | sqlserver/datadog_checks/sqlserver/sqlserver.py | def typed_metric(self, instance, cfg_inst, table, base_name, user_type, sql_type, column):
'''
Create the appropriate SqlServerMetric object, each implementing its method to
fetch the metrics properly.
If a `type` was specified in the config, it is used to report the value
direct... | def typed_metric(self, instance, cfg_inst, table, base_name, user_type, sql_type, column):
'''
Create the appropriate SqlServerMetric object, each implementing its method to
fetch the metrics properly.
If a `type` was specified in the config, it is used to report the value
direct... | [
"Create",
"the",
"appropriate",
"SqlServerMetric",
"object",
"each",
"implementing",
"its",
"method",
"to",
"fetch",
"the",
"metrics",
"properly",
".",
"If",
"a",
"type",
"was",
"specified",
"in",
"the",
"config",
"it",
"is",
"used",
"to",
"report",
"the",
"... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L288-L319 | [
"def",
"typed_metric",
"(",
"self",
",",
"instance",
",",
"cfg_inst",
",",
"table",
",",
"base_name",
",",
"user_type",
",",
"sql_type",
",",
"column",
")",
":",
"if",
"table",
"==",
"DEFAULT_PERFORMANCE_TABLE",
":",
"metric_type_mapping",
"=",
"{",
"PERF_COUN... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer._get_access_info | Convenience method to extract info from instance | sqlserver/datadog_checks/sqlserver/sqlserver.py | def _get_access_info(self, instance, db_key, db_name=None):
''' Convenience method to extract info from instance
'''
dsn = instance.get('dsn')
host = instance.get('host')
username = instance.get('username')
password = instance.get('password')
database = instance.g... | def _get_access_info(self, instance, db_key, db_name=None):
''' Convenience method to extract info from instance
'''
dsn = instance.get('dsn')
host = instance.get('host')
username = instance.get('username')
password = instance.get('password')
database = instance.g... | [
"Convenience",
"method",
"to",
"extract",
"info",
"from",
"instance"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L341-L357 | [
"def",
"_get_access_info",
"(",
"self",
",",
"instance",
",",
"db_key",
",",
"db_name",
"=",
"None",
")",
":",
"dsn",
"=",
"instance",
".",
"get",
"(",
"'dsn'",
")",
"host",
"=",
"instance",
".",
"get",
"(",
"'host'",
")",
"username",
"=",
"instance",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer._conn_key | Return a key to use for the connection cache | sqlserver/datadog_checks/sqlserver/sqlserver.py | def _conn_key(self, instance, db_key, db_name=None):
''' Return a key to use for the connection cache
'''
dsn, host, username, password, database, driver = self._get_access_info(instance, db_key, db_name)
return '{}:{}:{}:{}:{}:{}'.format(dsn, host, username, password, database, driver) | def _conn_key(self, instance, db_key, db_name=None):
''' Return a key to use for the connection cache
'''
dsn, host, username, password, database, driver = self._get_access_info(instance, db_key, db_name)
return '{}:{}:{}:{}:{}:{}'.format(dsn, host, username, password, database, driver) | [
"Return",
"a",
"key",
"to",
"use",
"for",
"the",
"connection",
"cache"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L359-L363 | [
"def",
"_conn_key",
"(",
"self",
",",
"instance",
",",
"db_key",
",",
"db_name",
"=",
"None",
")",
":",
"dsn",
",",
"host",
",",
"username",
",",
"password",
",",
"database",
",",
"driver",
"=",
"self",
".",
"_get_access_info",
"(",
"instance",
",",
"d... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer._conn_string_odbc | Return a connection string to use with odbc | sqlserver/datadog_checks/sqlserver/sqlserver.py | def _conn_string_odbc(self, db_key, instance=None, conn_key=None, db_name=None):
''' Return a connection string to use with odbc
'''
if instance:
dsn, host, username, password, database, driver = self._get_access_info(instance, db_key, db_name)
elif conn_key:
dsn,... | def _conn_string_odbc(self, db_key, instance=None, conn_key=None, db_name=None):
''' Return a connection string to use with odbc
'''
if instance:
dsn, host, username, password, database, driver = self._get_access_info(instance, db_key, db_name)
elif conn_key:
dsn,... | [
"Return",
"a",
"connection",
"string",
"to",
"use",
"with",
"odbc"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L365-L389 | [
"def",
"_conn_string_odbc",
"(",
"self",
",",
"db_key",
",",
"instance",
"=",
"None",
",",
"conn_key",
"=",
"None",
",",
"db_name",
"=",
"None",
")",
":",
"if",
"instance",
":",
"dsn",
",",
"host",
",",
"username",
",",
"password",
",",
"database",
","... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer._conn_string_adodbapi | Return a connection string to use with adodbapi | sqlserver/datadog_checks/sqlserver/sqlserver.py | def _conn_string_adodbapi(self, db_key, instance=None, conn_key=None, db_name=None):
''' Return a connection string to use with adodbapi
'''
if instance:
_, host, username, password, database, _ = self._get_access_info(instance, db_key, db_name)
elif conn_key:
_, ... | def _conn_string_adodbapi(self, db_key, instance=None, conn_key=None, db_name=None):
''' Return a connection string to use with adodbapi
'''
if instance:
_, host, username, password, database, _ = self._get_access_info(instance, db_key, db_name)
elif conn_key:
_, ... | [
"Return",
"a",
"connection",
"string",
"to",
"use",
"with",
"adodbapi"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L391-L408 | [
"def",
"_conn_string_adodbapi",
"(",
"self",
",",
"db_key",
",",
"instance",
"=",
"None",
",",
"conn_key",
"=",
"None",
",",
"db_name",
"=",
"None",
")",
":",
"if",
"instance",
":",
"_",
",",
"host",
",",
"username",
",",
"password",
",",
"database",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer.get_cursor | Return a cursor to execute query against the db
Cursor are cached in the self.connections dict | sqlserver/datadog_checks/sqlserver/sqlserver.py | def get_cursor(self, instance, db_key, db_name=None):
'''
Return a cursor to execute query against the db
Cursor are cached in the self.connections dict
'''
conn_key = self._conn_key(instance, db_key, db_name)
try:
conn = self.connections[conn_key]['conn']
... | def get_cursor(self, instance, db_key, db_name=None):
'''
Return a cursor to execute query against the db
Cursor are cached in the self.connections dict
'''
conn_key = self._conn_key(instance, db_key, db_name)
try:
conn = self.connections[conn_key]['conn']
... | [
"Return",
"a",
"cursor",
"to",
"execute",
"query",
"against",
"the",
"db",
"Cursor",
"are",
"cached",
"in",
"the",
"self",
".",
"connections",
"dict"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L417-L430 | [
"def",
"get_cursor",
"(",
"self",
",",
"instance",
",",
"db_key",
",",
"db_name",
"=",
"None",
")",
":",
"conn_key",
"=",
"self",
".",
"_conn_key",
"(",
"instance",
",",
"db_key",
",",
"db_name",
")",
"try",
":",
"conn",
"=",
"self",
".",
"connections"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer.get_sql_type | Return the type of the performance counter so that we can report it to
Datadog correctly
If the sql_type is one that needs a base (PERF_RAW_LARGE_FRACTION and
PERF_AVERAGE_BULK), the name of the base counter will also be returned | sqlserver/datadog_checks/sqlserver/sqlserver.py | def get_sql_type(self, instance, counter_name):
'''
Return the type of the performance counter so that we can report it to
Datadog correctly
If the sql_type is one that needs a base (PERF_RAW_LARGE_FRACTION and
PERF_AVERAGE_BULK), the name of the base counter will also be returne... | def get_sql_type(self, instance, counter_name):
'''
Return the type of the performance counter so that we can report it to
Datadog correctly
If the sql_type is one that needs a base (PERF_RAW_LARGE_FRACTION and
PERF_AVERAGE_BULK), the name of the base counter will also be returne... | [
"Return",
"the",
"type",
"of",
"the",
"performance",
"counter",
"so",
"that",
"we",
"can",
"report",
"it",
"to",
"Datadog",
"correctly",
"If",
"the",
"sql_type",
"is",
"one",
"that",
"needs",
"a",
"base",
"(",
"PERF_RAW_LARGE_FRACTION",
"and",
"PERF_AVERAGE_BU... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L432-L462 | [
"def",
"get_sql_type",
"(",
"self",
",",
"instance",
",",
"counter_name",
")",
":",
"with",
"self",
".",
"get_managed_cursor",
"(",
"instance",
",",
"self",
".",
"DEFAULT_DB_KEY",
")",
"as",
"cursor",
":",
"cursor",
".",
"execute",
"(",
"COUNTER_TYPE_QUERY",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer.do_perf_counter_check | Fetch the metrics from the sys.dm_os_performance_counters table | sqlserver/datadog_checks/sqlserver/sqlserver.py | def do_perf_counter_check(self, instance):
"""
Fetch the metrics from the sys.dm_os_performance_counters table
"""
custom_tags = instance.get('tags', [])
if custom_tags is None:
custom_tags = []
instance_key = self._conn_key(instance, self.DEFAULT_DB_KEY)
... | def do_perf_counter_check(self, instance):
"""
Fetch the metrics from the sys.dm_os_performance_counters table
"""
custom_tags = instance.get('tags', [])
if custom_tags is None:
custom_tags = []
instance_key = self._conn_key(instance, self.DEFAULT_DB_KEY)
... | [
"Fetch",
"the",
"metrics",
"from",
"the",
"sys",
".",
"dm_os_performance_counters",
"table"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L474-L518 | [
"def",
"do_perf_counter_check",
"(",
"self",
",",
"instance",
")",
":",
"custom_tags",
"=",
"instance",
".",
"get",
"(",
"'tags'",
",",
"[",
"]",
")",
"if",
"custom_tags",
"is",
"None",
":",
"custom_tags",
"=",
"[",
"]",
"instance_key",
"=",
"self",
".",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer.do_stored_procedure_check | Fetch the metrics from the stored proc | sqlserver/datadog_checks/sqlserver/sqlserver.py | def do_stored_procedure_check(self, instance, proc):
"""
Fetch the metrics from the stored proc
"""
guardSql = instance.get('proc_only_if')
custom_tags = instance.get("tags", [])
if (guardSql and self.proc_check_guard(instance, guardSql)) or not guardSql:
se... | def do_stored_procedure_check(self, instance, proc):
"""
Fetch the metrics from the stored proc
"""
guardSql = instance.get('proc_only_if')
custom_tags = instance.get("tags", [])
if (guardSql and self.proc_check_guard(instance, guardSql)) or not guardSql:
se... | [
"Fetch",
"the",
"metrics",
"from",
"the",
"stored",
"proc"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L520-L564 | [
"def",
"do_stored_procedure_check",
"(",
"self",
",",
"instance",
",",
"proc",
")",
":",
"guardSql",
"=",
"instance",
".",
"get",
"(",
"'proc_only_if'",
")",
"custom_tags",
"=",
"instance",
".",
"get",
"(",
"\"tags\"",
",",
"[",
"]",
")",
"if",
"(",
"gua... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer.proc_check_guard | check to see if the guard SQL returns a single column containing 0 or 1
We return true if 1, else False | sqlserver/datadog_checks/sqlserver/sqlserver.py | def proc_check_guard(self, instance, sql):
"""
check to see if the guard SQL returns a single column containing 0 or 1
We return true if 1, else False
"""
self.open_db_connections(instance, self.PROC_GUARD_DB_KEY)
cursor = self.get_cursor(instance, self.PROC_GUARD_DB_KEY)... | def proc_check_guard(self, instance, sql):
"""
check to see if the guard SQL returns a single column containing 0 or 1
We return true if 1, else False
"""
self.open_db_connections(instance, self.PROC_GUARD_DB_KEY)
cursor = self.get_cursor(instance, self.PROC_GUARD_DB_KEY)... | [
"check",
"to",
"see",
"if",
"the",
"guard",
"SQL",
"returns",
"a",
"single",
"column",
"containing",
"0",
"or",
"1",
"We",
"return",
"true",
"if",
"1",
"else",
"False"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L566-L584 | [
"def",
"proc_check_guard",
"(",
"self",
",",
"instance",
",",
"sql",
")",
":",
"self",
".",
"open_db_connections",
"(",
"instance",
",",
"self",
".",
"PROC_GUARD_DB_KEY",
")",
"cursor",
"=",
"self",
".",
"get_cursor",
"(",
"instance",
",",
"self",
".",
"PR... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer.close_cursor | We close the cursor explicitly b/c we had proven memory leaks
We handle any exception from closing, although according to the doc:
"in adodbapi, it is NOT an error to re-close a closed cursor" | sqlserver/datadog_checks/sqlserver/sqlserver.py | def close_cursor(self, cursor):
"""
We close the cursor explicitly b/c we had proven memory leaks
We handle any exception from closing, although according to the doc:
"in adodbapi, it is NOT an error to re-close a closed cursor"
"""
try:
cursor.close()
... | def close_cursor(self, cursor):
"""
We close the cursor explicitly b/c we had proven memory leaks
We handle any exception from closing, although according to the doc:
"in adodbapi, it is NOT an error to re-close a closed cursor"
"""
try:
cursor.close()
... | [
"We",
"close",
"the",
"cursor",
"explicitly",
"b",
"/",
"c",
"we",
"had",
"proven",
"memory",
"leaks",
"We",
"handle",
"any",
"exception",
"from",
"closing",
"although",
"according",
"to",
"the",
"doc",
":",
"in",
"adodbapi",
"it",
"is",
"NOT",
"an",
"er... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L586-L595 | [
"def",
"close_cursor",
"(",
"self",
",",
"cursor",
")",
":",
"try",
":",
"cursor",
".",
"close",
"(",
")",
"except",
"Exception",
"as",
"e",
":",
"self",
".",
"log",
".",
"warning",
"(",
"\"Could not close adodbapi cursor\\n{}\"",
".",
"format",
"(",
"e",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer.close_db_connections | We close the db connections explicitly b/c when we don't they keep
locks on the db. This presents as issues such as the SQL Server Agent
being unable to stop. | sqlserver/datadog_checks/sqlserver/sqlserver.py | def close_db_connections(self, instance, db_key, db_name=None):
"""
We close the db connections explicitly b/c when we don't they keep
locks on the db. This presents as issues such as the SQL Server Agent
being unable to stop.
"""
conn_key = self._conn_key(instance, db_ke... | def close_db_connections(self, instance, db_key, db_name=None):
"""
We close the db connections explicitly b/c when we don't they keep
locks on the db. This presents as issues such as the SQL Server Agent
being unable to stop.
"""
conn_key = self._conn_key(instance, db_ke... | [
"We",
"close",
"the",
"db",
"connections",
"explicitly",
"b",
"/",
"c",
"when",
"we",
"don",
"t",
"they",
"keep",
"locks",
"on",
"the",
"db",
".",
"This",
"presents",
"as",
"issues",
"such",
"as",
"the",
"SQL",
"Server",
"Agent",
"being",
"unable",
"to... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L597-L611 | [
"def",
"close_db_connections",
"(",
"self",
",",
"instance",
",",
"db_key",
",",
"db_name",
"=",
"None",
")",
":",
"conn_key",
"=",
"self",
".",
"_conn_key",
"(",
"instance",
",",
"db_key",
",",
"db_name",
")",
"if",
"conn_key",
"not",
"in",
"self",
".",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SQLServer.open_db_connections | We open the db connections explicitly, so we can ensure they are open
before we use them, and are closable, once we are finished. Open db
connections keep locks on the db, presenting issues such as the SQL
Server Agent being unable to stop. | sqlserver/datadog_checks/sqlserver/sqlserver.py | def open_db_connections(self, instance, db_key, db_name=None):
"""
We open the db connections explicitly, so we can ensure they are open
before we use them, and are closable, once we are finished. Open db
connections keep locks on the db, presenting issues such as the SQL
Server ... | def open_db_connections(self, instance, db_key, db_name=None):
"""
We open the db connections explicitly, so we can ensure they are open
before we use them, and are closable, once we are finished. Open db
connections keep locks on the db, presenting issues such as the SQL
Server ... | [
"We",
"open",
"the",
"db",
"connections",
"explicitly",
"so",
"we",
"can",
"ensure",
"they",
"are",
"open",
"before",
"we",
"use",
"them",
"and",
"are",
"closable",
"once",
"we",
"are",
"finished",
".",
"Open",
"db",
"connections",
"keep",
"locks",
"on",
... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L620-L673 | [
"def",
"open_db_connections",
"(",
"self",
",",
"instance",
",",
"db_key",
",",
"db_name",
"=",
"None",
")",
":",
"conn_key",
"=",
"self",
".",
"_conn_key",
"(",
"instance",
",",
"db_key",
",",
"db_name",
")",
"timeout",
"=",
"int",
"(",
"instance",
".",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | SqlFractionMetric.fetch_metric | Because we need to query the metrics by matching pairs, we can't query
all of them together without having to perform some matching based on
the name afterwards so instead we query instance by instance.
We cache the list of instance so that we don't have to look it up every time | sqlserver/datadog_checks/sqlserver/sqlserver.py | def fetch_metric(self, cursor, results, tags):
'''
Because we need to query the metrics by matching pairs, we can't query
all of them together without having to perform some matching based on
the name afterwards so instead we query instance by instance.
We cache the list of insta... | def fetch_metric(self, cursor, results, tags):
'''
Because we need to query the metrics by matching pairs, we can't query
all of them together without having to perform some matching based on
the name afterwards so instead we query instance by instance.
We cache the list of insta... | [
"Because",
"we",
"need",
"to",
"query",
"the",
"metrics",
"by",
"matching",
"pairs",
"we",
"can",
"t",
"query",
"all",
"of",
"them",
"together",
"without",
"having",
"to",
"perform",
"some",
"matching",
"based",
"on",
"the",
"name",
"afterwards",
"so",
"in... | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/sqlserver/datadog_checks/sqlserver/sqlserver.py#L766-L818 | [
"def",
"fetch_metric",
"(",
"self",
",",
"cursor",
",",
"results",
",",
"tags",
")",
":",
"if",
"self",
".",
"sql_name",
"not",
"in",
"results",
":",
"self",
".",
"log",
".",
"warning",
"(",
"\"Couldn't find {} in results\"",
".",
"format",
"(",
"self",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | KubeDNSCheck.create_generic_instances | Transform each Kube DNS instance into a OpenMetricsBaseCheck instance | kube_dns/datadog_checks/kube_dns/kube_dns.py | def create_generic_instances(self, instances):
"""
Transform each Kube DNS instance into a OpenMetricsBaseCheck instance
"""
generic_instances = []
for instance in instances:
transformed_instance = self._create_kube_dns_instance(instance)
generic_instances... | def create_generic_instances(self, instances):
"""
Transform each Kube DNS instance into a OpenMetricsBaseCheck instance
"""
generic_instances = []
for instance in instances:
transformed_instance = self._create_kube_dns_instance(instance)
generic_instances... | [
"Transform",
"each",
"Kube",
"DNS",
"instance",
"into",
"a",
"OpenMetricsBaseCheck",
"instance"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kube_dns/datadog_checks/kube_dns/kube_dns.py#L45-L54 | [
"def",
"create_generic_instances",
"(",
"self",
",",
"instances",
")",
":",
"generic_instances",
"=",
"[",
"]",
"for",
"instance",
"in",
"instances",
":",
"transformed_instance",
"=",
"self",
".",
"_create_kube_dns_instance",
"(",
"instance",
")",
"generic_instances... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | KubeDNSCheck._create_kube_dns_instance | Set up kube_dns instance so it can be used in OpenMetricsBaseCheck | kube_dns/datadog_checks/kube_dns/kube_dns.py | def _create_kube_dns_instance(self, instance):
"""
Set up kube_dns instance so it can be used in OpenMetricsBaseCheck
"""
kube_dns_instance = deepcopy(instance)
# kube_dns uses 'prometheus_endpoint' and not 'prometheus_url', so we have to rename the key
kube_dns_instance... | def _create_kube_dns_instance(self, instance):
"""
Set up kube_dns instance so it can be used in OpenMetricsBaseCheck
"""
kube_dns_instance = deepcopy(instance)
# kube_dns uses 'prometheus_endpoint' and not 'prometheus_url', so we have to rename the key
kube_dns_instance... | [
"Set",
"up",
"kube_dns",
"instance",
"so",
"it",
"can",
"be",
"used",
"in",
"OpenMetricsBaseCheck"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kube_dns/datadog_checks/kube_dns/kube_dns.py#L56-L86 | [
"def",
"_create_kube_dns_instance",
"(",
"self",
",",
"instance",
")",
":",
"kube_dns_instance",
"=",
"deepcopy",
"(",
"instance",
")",
"# kube_dns uses 'prometheus_endpoint' and not 'prometheus_url', so we have to rename the key",
"kube_dns_instance",
"[",
"'prometheus_url'",
"]... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | KubeDNSCheck.submit_as_gauge_and_monotonic_count | submit a kube_dns metric both as a gauge (for compatibility) and as a monotonic_count | kube_dns/datadog_checks/kube_dns/kube_dns.py | def submit_as_gauge_and_monotonic_count(self, metric_suffix, metric, scraper_config):
"""
submit a kube_dns metric both as a gauge (for compatibility) and as a monotonic_count
"""
metric_name = scraper_config['namespace'] + metric_suffix
for sample in metric.samples:
... | def submit_as_gauge_and_monotonic_count(self, metric_suffix, metric, scraper_config):
"""
submit a kube_dns metric both as a gauge (for compatibility) and as a monotonic_count
"""
metric_name = scraper_config['namespace'] + metric_suffix
for sample in metric.samples:
... | [
"submit",
"a",
"kube_dns",
"metric",
"both",
"as",
"a",
"gauge",
"(",
"for",
"compatibility",
")",
"and",
"as",
"a",
"monotonic_count"
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kube_dns/datadog_checks/kube_dns/kube_dns.py#L88-L102 | [
"def",
"submit_as_gauge_and_monotonic_count",
"(",
"self",
",",
"metric_suffix",
",",
"metric",
",",
"scraper_config",
")",
":",
"metric_name",
"=",
"scraper_config",
"[",
"'namespace'",
"]",
"+",
"metric_suffix",
"for",
"sample",
"in",
"metric",
".",
"samples",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection._command | Internal command helper.
:Parameters:
- `sock_info` - A SocketInfo instance.
- `command` - The command itself, as a SON instance.
- `slave_ok`: whether to set the SlaveOkay wire protocol bit.
- `codec_options` (optional) - An instance of
:class:`~bson.codec_o... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def _command(self, sock_info, command, slave_ok=False,
read_preference=None,
codec_options=None, check=True, allowable_errors=None,
read_concern=DEFAULT_READ_CONCERN,
write_concern=None,
parse_write_concern_error=False,
... | def _command(self, sock_info, command, slave_ok=False,
read_preference=None,
codec_options=None, check=True, allowable_errors=None,
read_concern=DEFAULT_READ_CONCERN,
write_concern=None,
parse_write_concern_error=False,
... | [
"Internal",
"command",
"helper",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L188-L232 | [
"def",
"_command",
"(",
"self",
",",
"sock_info",
",",
"command",
",",
"slave_ok",
"=",
"False",
",",
"read_preference",
"=",
"None",
",",
"codec_options",
"=",
"None",
",",
"check",
"=",
"True",
",",
"allowable_errors",
"=",
"None",
",",
"read_concern",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection.with_options | Get a clone of this collection changing the specified settings.
>>> coll1.read_preference
Primary()
>>> from pymongo import ReadPreference
>>> coll2 = coll1.with_options(read_preference=ReadPreference.SECONDARY)
>>> coll1.read_preference
Primary()
>... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def with_options(
self, codec_options=None, read_preference=None,
write_concern=None, read_concern=None):
"""Get a clone of this collection changing the specified settings.
>>> coll1.read_preference
Primary()
>>> from pymongo import ReadPreference
... | def with_options(
self, codec_options=None, read_preference=None,
write_concern=None, read_concern=None):
"""Get a clone of this collection changing the specified settings.
>>> coll1.read_preference
Primary()
>>> from pymongo import ReadPreference
... | [
"Get",
"a",
"clone",
"of",
"this",
"collection",
"changing",
"the",
"specified",
"settings",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L300-L338 | [
"def",
"with_options",
"(",
"self",
",",
"codec_options",
"=",
"None",
",",
"read_preference",
"=",
"None",
",",
"write_concern",
"=",
"None",
",",
"read_concern",
"=",
"None",
")",
":",
"return",
"Collection",
"(",
"self",
".",
"__database",
",",
"self",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection.initialize_unordered_bulk_op | **DEPRECATED** - Initialize an unordered batch of write operations.
Operations will be performed on the server in arbitrary order,
possibly in parallel. All operations will be attempted.
:Parameters:
- `bypass_document_validation`: (optional) If ``True``, allows the
write... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def initialize_unordered_bulk_op(self, bypass_document_validation=False):
"""**DEPRECATED** - Initialize an unordered batch of write operations.
Operations will be performed on the server in arbitrary order,
possibly in parallel. All operations will be attempted.
:Parameters:
... | def initialize_unordered_bulk_op(self, bypass_document_validation=False):
"""**DEPRECATED** - Initialize an unordered batch of write operations.
Operations will be performed on the server in arbitrary order,
possibly in parallel. All operations will be attempted.
:Parameters:
... | [
"**",
"DEPRECATED",
"**",
"-",
"Initialize",
"an",
"unordered",
"batch",
"of",
"write",
"operations",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L340-L369 | [
"def",
"initialize_unordered_bulk_op",
"(",
"self",
",",
"bypass_document_validation",
"=",
"False",
")",
":",
"warnings",
".",
"warn",
"(",
"\"initialize_unordered_bulk_op is deprecated\"",
",",
"DeprecationWarning",
",",
"stacklevel",
"=",
"2",
")",
"return",
"BulkOpe... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection.initialize_ordered_bulk_op | **DEPRECATED** - Initialize an ordered batch of write operations.
Operations will be performed on the server serially, in the
order provided. If an error occurs all remaining operations
are aborted.
:Parameters:
- `bypass_document_validation`: (optional) If ``True``, allows t... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def initialize_ordered_bulk_op(self, bypass_document_validation=False):
"""**DEPRECATED** - Initialize an ordered batch of write operations.
Operations will be performed on the server serially, in the
order provided. If an error occurs all remaining operations
are aborted.
:Par... | def initialize_ordered_bulk_op(self, bypass_document_validation=False):
"""**DEPRECATED** - Initialize an ordered batch of write operations.
Operations will be performed on the server serially, in the
order provided. If an error occurs all remaining operations
are aborted.
:Par... | [
"**",
"DEPRECATED",
"**",
"-",
"Initialize",
"an",
"ordered",
"batch",
"of",
"write",
"operations",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L371-L401 | [
"def",
"initialize_ordered_bulk_op",
"(",
"self",
",",
"bypass_document_validation",
"=",
"False",
")",
":",
"warnings",
".",
"warn",
"(",
"\"initialize_ordered_bulk_op is deprecated\"",
",",
"DeprecationWarning",
",",
"stacklevel",
"=",
"2",
")",
"return",
"BulkOperati... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection.bulk_write | Send a batch of write operations to the server.
Requests are passed as a list of write operation instances (
:class:`~pymongo.operations.InsertOne`,
:class:`~pymongo.operations.UpdateOne`,
:class:`~pymongo.operations.UpdateMany`,
:class:`~pymongo.operations.ReplaceOne`,
... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def bulk_write(self, requests, ordered=True,
bypass_document_validation=False):
"""Send a batch of write operations to the server.
Requests are passed as a list of write operation instances (
:class:`~pymongo.operations.InsertOne`,
:class:`~pymongo.operations.UpdateOn... | def bulk_write(self, requests, ordered=True,
bypass_document_validation=False):
"""Send a batch of write operations to the server.
Requests are passed as a list of write operation instances (
:class:`~pymongo.operations.InsertOne`,
:class:`~pymongo.operations.UpdateOn... | [
"Send",
"a",
"batch",
"of",
"write",
"operations",
"to",
"the",
"server",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L403-L478 | [
"def",
"bulk_write",
"(",
"self",
",",
"requests",
",",
"ordered",
"=",
"True",
",",
"bypass_document_validation",
"=",
"False",
")",
":",
"if",
"not",
"isinstance",
"(",
"requests",
",",
"list",
")",
":",
"raise",
"TypeError",
"(",
"\"requests must be a list\... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection._insert | Internal insert helper. | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def _insert(self, sock_info, docs, ordered=True, check_keys=True,
manipulate=False, write_concern=None, op_id=None,
bypass_doc_val=False):
"""Internal insert helper."""
if isinstance(docs, collections.Mapping):
return self._insert_one(
sock_inf... | def _insert(self, sock_info, docs, ordered=True, check_keys=True,
manipulate=False, write_concern=None, op_id=None,
bypass_doc_val=False):
"""Internal insert helper."""
if isinstance(docs, collections.Mapping):
return self._insert_one(
sock_inf... | [
"Internal",
"insert",
"helper",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L568-L630 | [
"def",
"_insert",
"(",
"self",
",",
"sock_info",
",",
"docs",
",",
"ordered",
"=",
"True",
",",
"check_keys",
"=",
"True",
",",
"manipulate",
"=",
"False",
",",
"write_concern",
"=",
"None",
",",
"op_id",
"=",
"None",
",",
"bypass_doc_val",
"=",
"False",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection.insert_one | Insert a single document.
>>> db.test.count({'x': 1})
0
>>> result = db.test.insert_one({'x': 1})
>>> result.inserted_id
ObjectId('54f112defba522406c9cc208')
>>> db.test.find_one({'x': 1})
{u'x': 1, u'_id': ObjectId('54f112defba522406c9cc208')}
... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def insert_one(self, document, bypass_document_validation=False):
"""Insert a single document.
>>> db.test.count({'x': 1})
0
>>> result = db.test.insert_one({'x': 1})
>>> result.inserted_id
ObjectId('54f112defba522406c9cc208')
>>> db.test.find_one({'x... | def insert_one(self, document, bypass_document_validation=False):
"""Insert a single document.
>>> db.test.count({'x': 1})
0
>>> result = db.test.insert_one({'x': 1})
>>> result.inserted_id
ObjectId('54f112defba522406c9cc208')
>>> db.test.find_one({'x... | [
"Insert",
"a",
"single",
"document",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L632-L671 | [
"def",
"insert_one",
"(",
"self",
",",
"document",
",",
"bypass_document_validation",
"=",
"False",
")",
":",
"common",
".",
"validate_is_document_type",
"(",
"\"document\"",
",",
"document",
")",
"if",
"not",
"(",
"isinstance",
"(",
"document",
",",
"RawBSONDoc... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection.insert_many | Insert an iterable of documents.
>>> db.test.count()
0
>>> result = db.test.insert_many([{'x': i} for i in range(2)])
>>> result.inserted_ids
[ObjectId('54f113fffba522406c9cc20e'), ObjectId('54f113fffba522406c9cc20f')]
>>> db.test.count()
2
... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def insert_many(self, documents, ordered=True,
bypass_document_validation=False):
"""Insert an iterable of documents.
>>> db.test.count()
0
>>> result = db.test.insert_many([{'x': i} for i in range(2)])
>>> result.inserted_ids
[ObjectId('54f... | def insert_many(self, documents, ordered=True,
bypass_document_validation=False):
"""Insert an iterable of documents.
>>> db.test.count()
0
>>> result = db.test.insert_many([{'x': i} for i in range(2)])
>>> result.inserted_ids
[ObjectId('54f... | [
"Insert",
"an",
"iterable",
"of",
"documents",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L673-L725 | [
"def",
"insert_many",
"(",
"self",
",",
"documents",
",",
"ordered",
"=",
"True",
",",
"bypass_document_validation",
"=",
"False",
")",
":",
"if",
"not",
"isinstance",
"(",
"documents",
",",
"collections",
".",
"Iterable",
")",
"or",
"not",
"documents",
":",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection.replace_one | Replace a single document matching the filter.
>>> for doc in db.test.find({}):
... print(doc)
...
{u'x': 1, u'_id': ObjectId('54f4c5befba5220aa4d6dee7')}
>>> result = db.test.replace_one({'x': 1}, {'y': 1})
>>> result.matched_count
1
... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def replace_one(self, filter, replacement, upsert=False,
bypass_document_validation=False, collation=None):
"""Replace a single document matching the filter.
>>> for doc in db.test.find({}):
... print(doc)
...
{u'x': 1, u'_id': ObjectId('54f4c5bef... | def replace_one(self, filter, replacement, upsert=False,
bypass_document_validation=False, collation=None):
"""Replace a single document matching the filter.
>>> for doc in db.test.find({}):
... print(doc)
...
{u'x': 1, u'_id': ObjectId('54f4c5bef... | [
"Replace",
"a",
"single",
"document",
"matching",
"the",
"filter",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L787-L850 | [
"def",
"replace_one",
"(",
"self",
",",
"filter",
",",
"replacement",
",",
"upsert",
"=",
"False",
",",
"bypass_document_validation",
"=",
"False",
",",
"collation",
"=",
"None",
")",
":",
"common",
".",
"validate_is_mapping",
"(",
"\"filter\"",
",",
"filter",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection.update_one | Update a single document matching the filter.
>>> for doc in db.test.find():
... print(doc)
...
{u'x': 1, u'_id': 0}
{u'x': 1, u'_id': 1}
{u'x': 1, u'_id': 2}
>>> result = db.test.update_one({'x': 1}, {'$inc': {'x': 3}})
>>> result.mat... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def update_one(self, filter, update, upsert=False,
bypass_document_validation=False,
collation=None):
"""Update a single document matching the filter.
>>> for doc in db.test.find():
... print(doc)
...
{u'x': 1, u'_id': 0}
... | def update_one(self, filter, update, upsert=False,
bypass_document_validation=False,
collation=None):
"""Update a single document matching the filter.
>>> for doc in db.test.find():
... print(doc)
...
{u'x': 1, u'_id': 0}
... | [
"Update",
"a",
"single",
"document",
"matching",
"the",
"filter",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L852-L908 | [
"def",
"update_one",
"(",
"self",
",",
"filter",
",",
"update",
",",
"upsert",
"=",
"False",
",",
"bypass_document_validation",
"=",
"False",
",",
"collation",
"=",
"None",
")",
":",
"common",
".",
"validate_is_mapping",
"(",
"\"filter\"",
",",
"filter",
")"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection.delete_one | Delete a single document matching the filter.
>>> db.test.count({'x': 1})
3
>>> result = db.test.delete_one({'x': 1})
>>> result.deleted_count
1
>>> db.test.count({'x': 1})
2
:Parameters:
- `filter`: A query that matches the docum... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def delete_one(self, filter, collation=None):
"""Delete a single document matching the filter.
>>> db.test.count({'x': 1})
3
>>> result = db.test.delete_one({'x': 1})
>>> result.deleted_count
1
>>> db.test.count({'x': 1})
2
:Paramet... | def delete_one(self, filter, collation=None):
"""Delete a single document matching the filter.
>>> db.test.count({'x': 1})
3
>>> result = db.test.delete_one({'x': 1})
>>> result.deleted_count
1
>>> db.test.count({'x': 1})
2
:Paramet... | [
"Delete",
"a",
"single",
"document",
"matching",
"the",
"filter",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L1019-L1047 | [
"def",
"delete_one",
"(",
"self",
",",
"filter",
",",
"collation",
"=",
"None",
")",
":",
"with",
"self",
".",
"_socket_for_writes",
"(",
")",
"as",
"sock_info",
":",
"return",
"DeleteResult",
"(",
"self",
".",
"_delete",
"(",
"sock_info",
",",
"filter",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
train | Collection.delete_many | Delete one or more documents matching the filter.
>>> db.test.count({'x': 1})
3
>>> result = db.test.delete_many({'x': 1})
>>> result.deleted_count
3
>>> db.test.count({'x': 1})
0
:Parameters:
- `filter`: A query that matches the ... | tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py | def delete_many(self, filter, collation=None):
"""Delete one or more documents matching the filter.
>>> db.test.count({'x': 1})
3
>>> result = db.test.delete_many({'x': 1})
>>> result.deleted_count
3
>>> db.test.count({'x': 1})
0
:P... | def delete_many(self, filter, collation=None):
"""Delete one or more documents matching the filter.
>>> db.test.count({'x': 1})
3
>>> result = db.test.delete_many({'x': 1})
>>> result.deleted_count
3
>>> db.test.count({'x': 1})
0
:P... | [
"Delete",
"one",
"or",
"more",
"documents",
"matching",
"the",
"filter",
"."
] | DataDog/integrations-core | python | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/collection.py#L1049-L1077 | [
"def",
"delete_many",
"(",
"self",
",",
"filter",
",",
"collation",
"=",
"None",
")",
":",
"with",
"self",
".",
"_socket_for_writes",
"(",
")",
"as",
"sock_info",
":",
"return",
"DeleteResult",
"(",
"self",
".",
"_delete",
"(",
"sock_info",
",",
"filter",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.