repo stringlengths 7 54 | path stringlengths 4 223 | func_name stringlengths 1 134 | original_string stringlengths 75 104k | language stringclasses 1
value | code stringlengths 75 104k | code_tokens listlengths 20 28.4k | docstring stringlengths 1 46.3k | docstring_tokens listlengths 1 1.66k | sha stringlengths 40 40 | url stringlengths 87 315 | partition stringclasses 1
value | summary stringlengths 4 350 | obf_code stringlengths 7.85k 764k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._get_pod_uid | def _get_pod_uid(self, labels):
"""
Return the id of a pod
:param labels:
:return: str or None
"""
namespace = CadvisorPrometheusScraperMixin._get_container_label(labels, "namespace")
pod_name = CadvisorPrometheusScraperMixin._get_container_label(labels, "pod_name... | python | def _get_pod_uid(self, labels):
"""
Return the id of a pod
:param labels:
:return: str or None
"""
namespace = CadvisorPrometheusScraperMixin._get_container_label(labels, "namespace")
pod_name = CadvisorPrometheusScraperMixin._get_container_label(labels, "pod_name... | [
"def",
"_get_pod_uid",
"(",
"self",
",",
"labels",
")",
":",
"namespace",
"=",
"CadvisorPrometheusScraperMixin",
".",
"_get_container_label",
"(",
"labels",
",",
"\"namespace\"",
")",
"pod_name",
"=",
"CadvisorPrometheusScraperMixin",
".",
"_get_container_label",
"(",
... | Return the id of a pod
:param labels:
:return: str or None | [
"Return",
"the",
"id",
"of",
"a",
"pod",
":",
"param",
"labels",
":",
":",
"return",
":",
"str",
"or",
"None"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubelet/datadog_checks/kubelet/prometheus.py#L181-L189 | train | Get the pod uid from the pod_name and namespace | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._is_pod_host_networked | def _is_pod_host_networked(self, pod_uid):
"""
Return if the pod is on host Network
Return False if the Pod isn't in the pod list
:param pod_uid: str
:return: bool
"""
for pod in self.pod_list['items']:
if pod.get('metadata', {}).get('uid', '') == pod_... | python | def _is_pod_host_networked(self, pod_uid):
"""
Return if the pod is on host Network
Return False if the Pod isn't in the pod list
:param pod_uid: str
:return: bool
"""
for pod in self.pod_list['items']:
if pod.get('metadata', {}).get('uid', '') == pod_... | [
"def",
"_is_pod_host_networked",
"(",
"self",
",",
"pod_uid",
")",
":",
"for",
"pod",
"in",
"self",
".",
"pod_list",
"[",
"'items'",
"]",
":",
"if",
"pod",
".",
"get",
"(",
"'metadata'",
",",
"{",
"}",
")",
".",
"get",
"(",
"'uid'",
",",
"''",
")",... | Return if the pod is on host Network
Return False if the Pod isn't in the pod list
:param pod_uid: str
:return: bool | [
"Return",
"if",
"the",
"pod",
"is",
"on",
"host",
"Network",
"Return",
"False",
"if",
"the",
"Pod",
"isn",
"t",
"in",
"the",
"pod",
"list",
":",
"param",
"pod_uid",
":",
"str",
":",
"return",
":",
"bool"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubelet/datadog_checks/kubelet/prometheus.py#L201-L211 | train | Return True if the pod is on host Network
Return False if the pod is not in the pod list | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._get_pod_by_metric_label | def _get_pod_by_metric_label(self, labels):
"""
:param labels: metric labels: iterable
:return:
"""
pod_uid = self._get_pod_uid(labels)
return get_pod_by_uid(pod_uid, self.pod_list) | python | def _get_pod_by_metric_label(self, labels):
"""
:param labels: metric labels: iterable
:return:
"""
pod_uid = self._get_pod_uid(labels)
return get_pod_by_uid(pod_uid, self.pod_list) | [
"def",
"_get_pod_by_metric_label",
"(",
"self",
",",
"labels",
")",
":",
"pod_uid",
"=",
"self",
".",
"_get_pod_uid",
"(",
"labels",
")",
"return",
"get_pod_by_uid",
"(",
"pod_uid",
",",
"self",
".",
"pod_list",
")"
] | :param labels: metric labels: iterable
:return: | [
":",
"param",
"labels",
":",
"metric",
"labels",
":",
"iterable",
":",
"return",
":"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubelet/datadog_checks/kubelet/prometheus.py#L213-L219 | train | Get a pod by metric label | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._sum_values_by_context | def _sum_values_by_context(metric, uid_from_labels):
"""
Iterates over all metrics in a metric and sums the values
matching the same uid. Modifies the metric family in place.
:param metric: prometheus metric family
:param uid_from_labels: function mapping a metric.label to a uniq... | python | def _sum_values_by_context(metric, uid_from_labels):
"""
Iterates over all metrics in a metric and sums the values
matching the same uid. Modifies the metric family in place.
:param metric: prometheus metric family
:param uid_from_labels: function mapping a metric.label to a uniq... | [
"def",
"_sum_values_by_context",
"(",
"metric",
",",
"uid_from_labels",
")",
":",
"seen",
"=",
"{",
"}",
"for",
"sample",
"in",
"metric",
".",
"samples",
":",
"uid",
"=",
"uid_from_labels",
"(",
"sample",
"[",
"OpenMetricsBaseCheck",
".",
"SAMPLE_LABELS",
"]",... | Iterates over all metrics in a metric and sums the values
matching the same uid. Modifies the metric family in place.
:param metric: prometheus metric family
:param uid_from_labels: function mapping a metric.label to a unique context id
:return: dict with uid as keys, metric object refer... | [
"Iterates",
"over",
"all",
"metrics",
"in",
"a",
"metric",
"and",
"sums",
"the",
"values",
"matching",
"the",
"same",
"uid",
".",
"Modifies",
"the",
"metric",
"family",
"in",
"place",
".",
":",
"param",
"metric",
":",
"prometheus",
"metric",
"family",
":",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubelet/datadog_checks/kubelet/prometheus.py#L238-L265 | train | Sums the values of all the contexts in a metric. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._process_container_metric | def _process_container_metric(self, type, metric_name, metric, scraper_config):
"""
Takes a simple metric about a container, reports it as a rate or gauge.
If several series are found for a given container, values are summed before submission.
"""
if metric.type not in METRIC_TYP... | python | def _process_container_metric(self, type, metric_name, metric, scraper_config):
"""
Takes a simple metric about a container, reports it as a rate or gauge.
If several series are found for a given container, values are summed before submission.
"""
if metric.type not in METRIC_TYP... | [
"def",
"_process_container_metric",
"(",
"self",
",",
"type",
",",
"metric_name",
",",
"metric",
",",
"scraper_config",
")",
":",
"if",
"metric",
".",
"type",
"not",
"in",
"METRIC_TYPES",
":",
"self",
".",
"log",
".",
"error",
"(",
"\"Metric type %s unsupporte... | Takes a simple metric about a container, reports it as a rate or gauge.
If several series are found for a given container, values are summed before submission. | [
"Takes",
"a",
"simple",
"metric",
"about",
"a",
"container",
"reports",
"it",
"as",
"a",
"rate",
"or",
"gauge",
".",
"If",
"several",
"series",
"are",
"found",
"for",
"a",
"given",
"container",
"values",
"are",
"summed",
"before",
"submission",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubelet/datadog_checks/kubelet/prometheus.py#L267-L298 | train | Processes a metric about a container. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._process_pod_rate | def _process_pod_rate(self, metric_name, metric, scraper_config):
"""
Takes a simple metric about a pod, reports it as a rate.
If several series are found for a given pod, values are summed before submission.
"""
if metric.type not in METRIC_TYPES:
self.log.error("Met... | python | def _process_pod_rate(self, metric_name, metric, scraper_config):
"""
Takes a simple metric about a pod, reports it as a rate.
If several series are found for a given pod, values are summed before submission.
"""
if metric.type not in METRIC_TYPES:
self.log.error("Met... | [
"def",
"_process_pod_rate",
"(",
"self",
",",
"metric_name",
",",
"metric",
",",
"scraper_config",
")",
":",
"if",
"metric",
".",
"type",
"not",
"in",
"METRIC_TYPES",
":",
"self",
".",
"log",
".",
"error",
"(",
"\"Metric type %s unsupported for metric %s\"",
"%"... | Takes a simple metric about a pod, reports it as a rate.
If several series are found for a given pod, values are summed before submission. | [
"Takes",
"a",
"simple",
"metric",
"about",
"a",
"pod",
"reports",
"it",
"as",
"a",
"rate",
".",
"If",
"several",
"series",
"are",
"found",
"for",
"a",
"given",
"pod",
"values",
"are",
"summed",
"before",
"submission",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubelet/datadog_checks/kubelet/prometheus.py#L300-L316 | train | Processes a metric about a pod and reports it as a rate. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._process_usage_metric | def _process_usage_metric(self, m_name, metric, cache, scraper_config):
"""
Takes a metric object, a metric name, and a cache dict where it will store
container_name --> (value, tags) so that _process_limit_metric can compute usage_pct
it also submit said value and tags as a gauge.
... | python | def _process_usage_metric(self, m_name, metric, cache, scraper_config):
"""
Takes a metric object, a metric name, and a cache dict where it will store
container_name --> (value, tags) so that _process_limit_metric can compute usage_pct
it also submit said value and tags as a gauge.
... | [
"def",
"_process_usage_metric",
"(",
"self",
",",
"m_name",
",",
"metric",
",",
"cache",
",",
"scraper_config",
")",
":",
"# track containers that still exist in the cache",
"seen_keys",
"=",
"{",
"k",
":",
"False",
"for",
"k",
"in",
"cache",
"}",
"samples",
"="... | Takes a metric object, a metric name, and a cache dict where it will store
container_name --> (value, tags) so that _process_limit_metric can compute usage_pct
it also submit said value and tags as a gauge. | [
"Takes",
"a",
"metric",
"object",
"a",
"metric",
"name",
"and",
"a",
"cache",
"dict",
"where",
"it",
"will",
"store",
"container_name",
"--",
">",
"(",
"value",
"tags",
")",
"so",
"that",
"_process_limit_metric",
"can",
"compute",
"usage_pct",
"it",
"also",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubelet/datadog_checks/kubelet/prometheus.py#L318-L355 | train | Processes a usage metric. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin._process_limit_metric | def _process_limit_metric(self, m_name, metric, cache, scraper_config, pct_m_name=None):
"""
Reports limit metrics if m_name is not an empty string,
and optionally checks in the given cache if there's a usage
for each sample in the metric and reports the usage_pct
"""
sam... | python | def _process_limit_metric(self, m_name, metric, cache, scraper_config, pct_m_name=None):
"""
Reports limit metrics if m_name is not an empty string,
and optionally checks in the given cache if there's a usage
for each sample in the metric and reports the usage_pct
"""
sam... | [
"def",
"_process_limit_metric",
"(",
"self",
",",
"m_name",
",",
"metric",
",",
"cache",
",",
"scraper_config",
",",
"pct_m_name",
"=",
"None",
")",
":",
"samples",
"=",
"self",
".",
"_sum_values_by_context",
"(",
"metric",
",",
"self",
".",
"_get_entity_id_if... | Reports limit metrics if m_name is not an empty string,
and optionally checks in the given cache if there's a usage
for each sample in the metric and reports the usage_pct | [
"Reports",
"limit",
"metrics",
"if",
"m_name",
"is",
"not",
"an",
"empty",
"string",
"and",
"optionally",
"checks",
"in",
"the",
"given",
"cache",
"if",
"there",
"s",
"a",
"usage",
"for",
"each",
"sample",
"in",
"the",
"metric",
"and",
"reports",
"the",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubelet/datadog_checks/kubelet/prometheus.py#L357-L387 | train | Processes a limit metric. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin.container_fs_usage_bytes | def container_fs_usage_bytes(self, metric, scraper_config):
"""
Number of bytes that are consumed by the container on this filesystem.
"""
metric_name = scraper_config['namespace'] + '.filesystem.usage'
if metric.type not in METRIC_TYPES:
self.log.error("Metric type %... | python | def container_fs_usage_bytes(self, metric, scraper_config):
"""
Number of bytes that are consumed by the container on this filesystem.
"""
metric_name = scraper_config['namespace'] + '.filesystem.usage'
if metric.type not in METRIC_TYPES:
self.log.error("Metric type %... | [
"def",
"container_fs_usage_bytes",
"(",
"self",
",",
"metric",
",",
"scraper_config",
")",
":",
"metric_name",
"=",
"scraper_config",
"[",
"'namespace'",
"]",
"+",
"'.filesystem.usage'",
"if",
"metric",
".",
"type",
"not",
"in",
"METRIC_TYPES",
":",
"self",
".",... | Number of bytes that are consumed by the container on this filesystem. | [
"Number",
"of",
"bytes",
"that",
"are",
"consumed",
"by",
"the",
"container",
"on",
"this",
"filesystem",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubelet/datadog_checks/kubelet/prometheus.py#L453-L461 | train | This method is used to update the number of bytes that are consumed by the container on this filesystem. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubelet/datadog_checks/kubelet/prometheus.py | CadvisorPrometheusScraperMixin.container_fs_limit_bytes | def container_fs_limit_bytes(self, metric, scraper_config):
"""
Number of bytes that can be consumed by the container on this filesystem.
This method is used by container_fs_usage_bytes, it doesn't report any metric
"""
pct_m_name = scraper_config['namespace'] + '.filesystem.usag... | python | def container_fs_limit_bytes(self, metric, scraper_config):
"""
Number of bytes that can be consumed by the container on this filesystem.
This method is used by container_fs_usage_bytes, it doesn't report any metric
"""
pct_m_name = scraper_config['namespace'] + '.filesystem.usag... | [
"def",
"container_fs_limit_bytes",
"(",
"self",
",",
"metric",
",",
"scraper_config",
")",
":",
"pct_m_name",
"=",
"scraper_config",
"[",
"'namespace'",
"]",
"+",
"'.filesystem.usage_pct'",
"if",
"metric",
".",
"type",
"not",
"in",
"METRIC_TYPES",
":",
"self",
"... | Number of bytes that can be consumed by the container on this filesystem.
This method is used by container_fs_usage_bytes, it doesn't report any metric | [
"Number",
"of",
"bytes",
"that",
"can",
"be",
"consumed",
"by",
"the",
"container",
"on",
"this",
"filesystem",
".",
"This",
"method",
"is",
"used",
"by",
"container_fs_usage_bytes",
"it",
"doesn",
"t",
"report",
"any",
"metric"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubelet/datadog_checks/kubelet/prometheus.py#L463-L472 | train | This method is used by container_fs_usage_bytes to report the number of bytes that can be consumed by the container on this filesystem. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb._report_replica_set_state | def _report_replica_set_state(self, state, clean_server_name, replset_name):
"""
Report the member's replica set state
* Submit a service check.
* Create an event on state change.
"""
last_state = self._last_state_by_server.get(clean_server_name, -1)
self._last_st... | python | def _report_replica_set_state(self, state, clean_server_name, replset_name):
"""
Report the member's replica set state
* Submit a service check.
* Create an event on state change.
"""
last_state = self._last_state_by_server.get(clean_server_name, -1)
self._last_st... | [
"def",
"_report_replica_set_state",
"(",
"self",
",",
"state",
",",
"clean_server_name",
",",
"replset_name",
")",
":",
"last_state",
"=",
"self",
".",
"_last_state_by_server",
".",
"get",
"(",
"clean_server_name",
",",
"-",
"1",
")",
"self",
".",
"_last_state_b... | Report the member's replica set state
* Submit a service check.
* Create an event on state change. | [
"Report",
"the",
"member",
"s",
"replica",
"set",
"state",
"*",
"Submit",
"a",
"service",
"check",
".",
"*",
"Create",
"an",
"event",
"on",
"state",
"change",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L450-L459 | train | Report the state of a replica set. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb.hostname_for_event | def hostname_for_event(self, clean_server_name):
"""Return a reasonable hostname for a replset membership event to mention."""
uri = urlsplit(clean_server_name)
if '@' in uri.netloc:
hostname = uri.netloc.split('@')[1].split(':')[0]
else:
hostname = uri.netloc.spl... | python | def hostname_for_event(self, clean_server_name):
"""Return a reasonable hostname for a replset membership event to mention."""
uri = urlsplit(clean_server_name)
if '@' in uri.netloc:
hostname = uri.netloc.split('@')[1].split(':')[0]
else:
hostname = uri.netloc.spl... | [
"def",
"hostname_for_event",
"(",
"self",
",",
"clean_server_name",
")",
":",
"uri",
"=",
"urlsplit",
"(",
"clean_server_name",
")",
"if",
"'@'",
"in",
"uri",
".",
"netloc",
":",
"hostname",
"=",
"uri",
".",
"netloc",
".",
"split",
"(",
"'@'",
")",
"[",
... | Return a reasonable hostname for a replset membership event to mention. | [
"Return",
"a",
"reasonable",
"hostname",
"for",
"a",
"replset",
"membership",
"event",
"to",
"mention",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L461-L470 | train | Return a reasonable hostname for a replset membership event to mention. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb.create_event | def create_event(self, last_state, state, clean_server_name, replset_name):
"""Create an event with a message describing the replication
state of a mongo node"""
status = self.get_state_description(state)
short_status = self.get_state_name(state)
last_short_status = self.get... | python | def create_event(self, last_state, state, clean_server_name, replset_name):
"""Create an event with a message describing the replication
state of a mongo node"""
status = self.get_state_description(state)
short_status = self.get_state_name(state)
last_short_status = self.get... | [
"def",
"create_event",
"(",
"self",
",",
"last_state",
",",
"state",
",",
"clean_server_name",
",",
"replset_name",
")",
":",
"status",
"=",
"self",
".",
"get_state_description",
"(",
"state",
")",
"short_status",
"=",
"self",
".",
"get_state_name",
"(",
"stat... | Create an event with a message describing the replication
state of a mongo node | [
"Create",
"an",
"event",
"with",
"a",
"message",
"describing",
"the",
"replication",
"state",
"of",
"a",
"mongo",
"node"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L472-L498 | train | Create an event describing the replication
state of a mongo node. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb._build_metric_list_to_collect | def _build_metric_list_to_collect(self, additional_metrics):
"""
Build the metric list to collect based on the instance preferences.
"""
metrics_to_collect = {}
# Defaut metrics
for default_metrics in itervalues(self.DEFAULT_METRICS):
metrics_to_collect.updat... | python | def _build_metric_list_to_collect(self, additional_metrics):
"""
Build the metric list to collect based on the instance preferences.
"""
metrics_to_collect = {}
# Defaut metrics
for default_metrics in itervalues(self.DEFAULT_METRICS):
metrics_to_collect.updat... | [
"def",
"_build_metric_list_to_collect",
"(",
"self",
",",
"additional_metrics",
")",
":",
"metrics_to_collect",
"=",
"{",
"}",
"# Defaut metrics",
"for",
"default_metrics",
"in",
"itervalues",
"(",
"self",
".",
"DEFAULT_METRICS",
")",
":",
"metrics_to_collect",
".",
... | Build the metric list to collect based on the instance preferences. | [
"Build",
"the",
"metric",
"list",
"to",
"collect",
"based",
"on",
"the",
"instance",
"preferences",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L500-L527 | train | Build the metric list to collect based on the instance preferences. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb._get_metrics_to_collect | def _get_metrics_to_collect(self, instance_key, additional_metrics):
"""
Return and cache the list of metrics to collect.
"""
if instance_key not in self.metrics_to_collect_by_instance:
self.metrics_to_collect_by_instance[instance_key] = self._build_metric_list_to_collect(add... | python | def _get_metrics_to_collect(self, instance_key, additional_metrics):
"""
Return and cache the list of metrics to collect.
"""
if instance_key not in self.metrics_to_collect_by_instance:
self.metrics_to_collect_by_instance[instance_key] = self._build_metric_list_to_collect(add... | [
"def",
"_get_metrics_to_collect",
"(",
"self",
",",
"instance_key",
",",
"additional_metrics",
")",
":",
"if",
"instance_key",
"not",
"in",
"self",
".",
"metrics_to_collect_by_instance",
":",
"self",
".",
"metrics_to_collect_by_instance",
"[",
"instance_key",
"]",
"="... | Return and cache the list of metrics to collect. | [
"Return",
"and",
"cache",
"the",
"list",
"of",
"metrics",
"to",
"collect",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L529-L535 | train | Return the list of metrics to collect. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb._resolve_metric | def _resolve_metric(self, original_metric_name, metrics_to_collect, prefix=""):
"""
Return the submit method and the metric name to use.
The metric name is defined as follow:
* If available, the normalized metric name alias
* (Or) the normalized original metric name
"""
... | python | def _resolve_metric(self, original_metric_name, metrics_to_collect, prefix=""):
"""
Return the submit method and the metric name to use.
The metric name is defined as follow:
* If available, the normalized metric name alias
* (Or) the normalized original metric name
"""
... | [
"def",
"_resolve_metric",
"(",
"self",
",",
"original_metric_name",
",",
"metrics_to_collect",
",",
"prefix",
"=",
"\"\"",
")",
":",
"submit_method",
"=",
"(",
"metrics_to_collect",
"[",
"original_metric_name",
"]",
"[",
"0",
"]",
"if",
"isinstance",
"(",
"metri... | Return the submit method and the metric name to use.
The metric name is defined as follow:
* If available, the normalized metric name alias
* (Or) the normalized original metric name | [
"Return",
"the",
"submit",
"method",
"and",
"the",
"metric",
"name",
"to",
"use",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L537-L557 | train | Resolve the metric name to use. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb._normalize | def _normalize(self, metric_name, submit_method, prefix):
"""
Replace case-sensitive metric name characters, normalize the metric name,
prefix and suffix according to its type.
"""
metric_prefix = "mongodb." if not prefix else "mongodb.{0}.".format(prefix)
metric_suffix =... | python | def _normalize(self, metric_name, submit_method, prefix):
"""
Replace case-sensitive metric name characters, normalize the metric name,
prefix and suffix according to its type.
"""
metric_prefix = "mongodb." if not prefix else "mongodb.{0}.".format(prefix)
metric_suffix =... | [
"def",
"_normalize",
"(",
"self",
",",
"metric_name",
",",
"submit_method",
",",
"prefix",
")",
":",
"metric_prefix",
"=",
"\"mongodb.\"",
"if",
"not",
"prefix",
"else",
"\"mongodb.{0}.\"",
".",
"format",
"(",
"prefix",
")",
"metric_suffix",
"=",
"\"ps\"",
"if... | Replace case-sensitive metric name characters, normalize the metric name,
prefix and suffix according to its type. | [
"Replace",
"case",
"-",
"sensitive",
"metric",
"name",
"characters",
"normalize",
"the",
"metric",
"name",
"prefix",
"and",
"suffix",
"according",
"to",
"its",
"type",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L559-L576 | train | Normalize the metric name and wrap it in a new one. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb._authenticate | def _authenticate(self, database, username, password, use_x509, server_name, service_check_tags):
"""
Authenticate to the database.
Available mechanisms:
* Username & password
* X.509
More information:
https://api.mongodb.com/python/current/examples/authenticati... | python | def _authenticate(self, database, username, password, use_x509, server_name, service_check_tags):
"""
Authenticate to the database.
Available mechanisms:
* Username & password
* X.509
More information:
https://api.mongodb.com/python/current/examples/authenticati... | [
"def",
"_authenticate",
"(",
"self",
",",
"database",
",",
"username",
",",
"password",
",",
"use_x509",
",",
"server_name",
",",
"service_check_tags",
")",
":",
"authenticated",
"=",
"False",
"try",
":",
"# X.509",
"if",
"use_x509",
":",
"self",
".",
"log",... | Authenticate to the database.
Available mechanisms:
* Username & password
* X.509
More information:
https://api.mongodb.com/python/current/examples/authentication.html | [
"Authenticate",
"to",
"the",
"database",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L578-L608 | train | Authenticate to the database. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb._parse_uri | def _parse_uri(cls, server, sanitize_username=False):
"""
Parses a MongoDB-formatted URI (e.g. mongodb://user:pass@server/db) and returns parsed elements
and a sanitized URI.
"""
parsed = pymongo.uri_parser.parse_uri(server)
username = parsed.get('username')
pass... | python | def _parse_uri(cls, server, sanitize_username=False):
"""
Parses a MongoDB-formatted URI (e.g. mongodb://user:pass@server/db) and returns parsed elements
and a sanitized URI.
"""
parsed = pymongo.uri_parser.parse_uri(server)
username = parsed.get('username')
pass... | [
"def",
"_parse_uri",
"(",
"cls",
",",
"server",
",",
"sanitize_username",
"=",
"False",
")",
":",
"parsed",
"=",
"pymongo",
".",
"uri_parser",
".",
"parse_uri",
"(",
"server",
")",
"username",
"=",
"parsed",
".",
"get",
"(",
"'username'",
")",
"password",
... | Parses a MongoDB-formatted URI (e.g. mongodb://user:pass@server/db) and returns parsed elements
and a sanitized URI. | [
"Parses",
"a",
"MongoDB",
"-",
"formatted",
"URI",
"(",
"e",
".",
"g",
".",
"mongodb",
":",
"//",
"user",
":",
"pass"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L611-L634 | train | Parses a MongoDB - formatted URI and returns parsed elements
and a sanitized URI. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb._collect_indexes_stats | def _collect_indexes_stats(self, instance, db, tags):
"""
Collect indexes statistics for all collections in the configuration.
This use the "$indexStats" command.
"""
for coll_name in instance.get('collections', []):
try:
for stats in db[coll_name].agg... | python | def _collect_indexes_stats(self, instance, db, tags):
"""
Collect indexes statistics for all collections in the configuration.
This use the "$indexStats" command.
"""
for coll_name in instance.get('collections', []):
try:
for stats in db[coll_name].agg... | [
"def",
"_collect_indexes_stats",
"(",
"self",
",",
"instance",
",",
"db",
",",
"tags",
")",
":",
"for",
"coll_name",
"in",
"instance",
".",
"get",
"(",
"'collections'",
",",
"[",
"]",
")",
":",
"try",
":",
"for",
"stats",
"in",
"db",
"[",
"coll_name",
... | Collect indexes statistics for all collections in the configuration.
This use the "$indexStats" command. | [
"Collect",
"indexes",
"statistics",
"for",
"all",
"collections",
"in",
"the",
"configuration",
".",
"This",
"use",
"the",
"$indexStats",
"command",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L636-L651 | train | Collect indexes stats for all collections in the configuration. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | mongo/datadog_checks/mongo/mongo.py | MongoDb.check | def check(self, instance):
"""
Returns a dictionary that looks a lot like what's sent back by
db.serverStatus()
"""
def total_seconds(td):
"""
Returns total seconds of a timedelta in a way that's safe for
Python < 2.7
"""
... | python | def check(self, instance):
"""
Returns a dictionary that looks a lot like what's sent back by
db.serverStatus()
"""
def total_seconds(td):
"""
Returns total seconds of a timedelta in a way that's safe for
Python < 2.7
"""
... | [
"def",
"check",
"(",
"self",
",",
"instance",
")",
":",
"def",
"total_seconds",
"(",
"td",
")",
":",
"\"\"\"\n Returns total seconds of a timedelta in a way that's safe for\n Python < 2.7\n \"\"\"",
"if",
"hasattr",
"(",
"td",
",",
"'total_sec... | Returns a dictionary that looks a lot like what's sent back by
db.serverStatus() | [
"Returns",
"a",
"dictionary",
"that",
"looks",
"a",
"lot",
"like",
"what",
"s",
"sent",
"back",
"by",
"db",
".",
"serverStatus",
"()"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/mongo/datadog_checks/mongo/mongo.py#L653-L1045 | train | Check the status of a specific instance of a specific version of the database. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | ibm_mq/datadog_checks/ibm_mq/connection.py | get_normal_connection | def get_normal_connection(config):
"""
Get the connection either with a username and password or without
"""
if config.username and config.password:
log.debug("connecting with username and password")
queue_manager = pymqi.connect(
config.queue_manager_name, config.channel, co... | python | def get_normal_connection(config):
"""
Get the connection either with a username and password or without
"""
if config.username and config.password:
log.debug("connecting with username and password")
queue_manager = pymqi.connect(
config.queue_manager_name, config.channel, co... | [
"def",
"get_normal_connection",
"(",
"config",
")",
":",
"if",
"config",
".",
"username",
"and",
"config",
".",
"password",
":",
"log",
".",
"debug",
"(",
"\"connecting with username and password\"",
")",
"queue_manager",
"=",
"pymqi",
".",
"connect",
"(",
"conf... | Get the connection either with a username and password or without | [
"Get",
"the",
"connection",
"either",
"with",
"a",
"username",
"and",
"password",
"or",
"without"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/ibm_mq/datadog_checks/ibm_mq/connection.py#L25-L38 | train | Get the connection to the normal queue manager. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | ibm_mq/datadog_checks/ibm_mq/connection.py | get_ssl_connection | def get_ssl_connection(config):
"""
Get the connection with SSL
"""
cd = pymqi.CD()
cd.ChannelName = config.channel
cd.ConnectionName = config.host_and_port
cd.ChannelType = pymqi.CMQC.MQCHT_CLNTCONN
cd.TransportType = pymqi.CMQC.MQXPT_TCP
cd.SSLCipherSpec = config.ssl_cipher_spec
... | python | def get_ssl_connection(config):
"""
Get the connection with SSL
"""
cd = pymqi.CD()
cd.ChannelName = config.channel
cd.ConnectionName = config.host_and_port
cd.ChannelType = pymqi.CMQC.MQCHT_CLNTCONN
cd.TransportType = pymqi.CMQC.MQXPT_TCP
cd.SSLCipherSpec = config.ssl_cipher_spec
... | [
"def",
"get_ssl_connection",
"(",
"config",
")",
":",
"cd",
"=",
"pymqi",
".",
"CD",
"(",
")",
"cd",
".",
"ChannelName",
"=",
"config",
".",
"channel",
"cd",
".",
"ConnectionName",
"=",
"config",
".",
"host_and_port",
"cd",
".",
"ChannelType",
"=",
"pymq... | Get the connection with SSL | [
"Get",
"the",
"connection",
"with",
"SSL"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/ibm_mq/datadog_checks/ibm_mq/connection.py#L41-L58 | train | Get the connection with SSL
| Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/commands/env/check.py | check_run | def check_run(check, env, rate, times, pause, delay, log_level, as_json, break_point):
"""Run an Agent check."""
envs = get_configured_envs(check)
if not envs:
echo_failure('No active environments found for `{}`.'.format(check))
echo_info('See what is available to start via `ddev env ls {}`.... | python | def check_run(check, env, rate, times, pause, delay, log_level, as_json, break_point):
"""Run an Agent check."""
envs = get_configured_envs(check)
if not envs:
echo_failure('No active environments found for `{}`.'.format(check))
echo_info('See what is available to start via `ddev env ls {}`.... | [
"def",
"check_run",
"(",
"check",
",",
"env",
",",
"rate",
",",
"times",
",",
"pause",
",",
"delay",
",",
"log_level",
",",
"as_json",
",",
"break_point",
")",
":",
"envs",
"=",
"get_configured_envs",
"(",
"check",
")",
"if",
"not",
"envs",
":",
"echo_... | Run an Agent check. | [
"Run",
"an",
"Agent",
"check",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/commands/env/check.py#L33-L60 | train | Run an Agent check. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackScope.get_user_identity | def get_user_identity(cls, instance_config):
"""
Parse user identity out of init_config
To guarantee a uniquely identifiable user, expects
{"user": {"name": "my_username", "password": "my_password",
"domain": {"id": "my_domain_id"}
}
}
... | python | def get_user_identity(cls, instance_config):
"""
Parse user identity out of init_config
To guarantee a uniquely identifiable user, expects
{"user": {"name": "my_username", "password": "my_password",
"domain": {"id": "my_domain_id"}
}
}
... | [
"def",
"get_user_identity",
"(",
"cls",
",",
"instance_config",
")",
":",
"user",
"=",
"instance_config",
".",
"get",
"(",
"'user'",
")",
"if",
"not",
"(",
"user",
"and",
"user",
".",
"get",
"(",
"'name'",
")",
"and",
"user",
".",
"get",
"(",
"'passwor... | Parse user identity out of init_config
To guarantee a uniquely identifiable user, expects
{"user": {"name": "my_username", "password": "my_password",
"domain": {"id": "my_domain_id"}
}
} | [
"Parse",
"user",
"identity",
"out",
"of",
"init_config"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L171-L189 | train | Parse user identity out of init_config | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackScope.get_auth_scope | def get_auth_scope(cls, instance_config):
"""
Parse authorization scope out of init_config
To guarantee a uniquely identifiable scope, expects either:
{'project': {'name': 'my_project', 'domain': {'id': 'my_domain_id'}}}
OR
{'project': {'id': 'my_project_id'}}
""... | python | def get_auth_scope(cls, instance_config):
"""
Parse authorization scope out of init_config
To guarantee a uniquely identifiable scope, expects either:
{'project': {'name': 'my_project', 'domain': {'id': 'my_domain_id'}}}
OR
{'project': {'id': 'my_project_id'}}
""... | [
"def",
"get_auth_scope",
"(",
"cls",
",",
"instance_config",
")",
":",
"auth_scope",
"=",
"instance_config",
".",
"get",
"(",
"'auth_scope'",
")",
"if",
"not",
"auth_scope",
":",
"return",
"None",
"if",
"not",
"auth_scope",
".",
"get",
"(",
"'project'",
")",... | Parse authorization scope out of init_config
To guarantee a uniquely identifiable scope, expects either:
{'project': {'name': 'my_project', 'domain': {'id': 'my_domain_id'}}}
OR
{'project': {'id': 'my_project_id'}} | [
"Parse",
"authorization",
"scope",
"out",
"of",
"init_config"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L192-L217 | train | Parse authorization scope out of init_config and return it | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | KeystoneCatalog.get_neutron_endpoint | def get_neutron_endpoint(cls, json_resp):
"""
Parse the service catalog returned by the Identity API for an endpoint matching the Neutron service
Sends a CRITICAL service check when none are found registered in the Catalog
"""
catalog = json_resp.get('token', {}).get('catalog', [... | python | def get_neutron_endpoint(cls, json_resp):
"""
Parse the service catalog returned by the Identity API for an endpoint matching the Neutron service
Sends a CRITICAL service check when none are found registered in the Catalog
"""
catalog = json_resp.get('token', {}).get('catalog', [... | [
"def",
"get_neutron_endpoint",
"(",
"cls",
",",
"json_resp",
")",
":",
"catalog",
"=",
"json_resp",
".",
"get",
"(",
"'token'",
",",
"{",
"}",
")",
".",
"get",
"(",
"'catalog'",
",",
"[",
"]",
")",
"match",
"=",
"'neutron'",
"neutron_endpoint",
"=",
"N... | Parse the service catalog returned by the Identity API for an endpoint matching the Neutron service
Sends a CRITICAL service check when none are found registered in the Catalog | [
"Parse",
"the",
"service",
"catalog",
"returned",
"by",
"the",
"Identity",
"API",
"for",
"an",
"endpoint",
"matching",
"the",
"Neutron",
"service",
"Sends",
"a",
"CRITICAL",
"service",
"check",
"when",
"none",
"are",
"found",
"registered",
"in",
"the",
"Catalo... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L455-L479 | train | Parse the JSON response from the Neutron Identity API and return the endpoint that is available for the neutron service | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | KeystoneCatalog.get_nova_endpoint | def get_nova_endpoint(cls, json_resp, nova_api_version=None):
"""
Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog
"""
... | python | def get_nova_endpoint(cls, json_resp, nova_api_version=None):
"""
Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog
"""
... | [
"def",
"get_nova_endpoint",
"(",
"cls",
",",
"json_resp",
",",
"nova_api_version",
"=",
"None",
")",
":",
"nova_version",
"=",
"nova_api_version",
"or",
"DEFAULT_NOVA_API_VERSION",
"catalog",
"=",
"json_resp",
".",
"get",
"(",
"'token'",
",",
"{",
"}",
")",
".... | Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog | [
"Parse",
"the",
"service",
"catalog",
"returned",
"by",
"the",
"Identity",
"API",
"for",
"an",
"endpoint",
"matching",
"the",
"Nova",
"service",
"with",
"the",
"requested",
"version",
"Sends",
"a",
"CRITICAL",
"service",
"check",
"when",
"no",
"viable",
"candi... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L482-L507 | train | Parse the Nova service catalog and return the endpoint that is available for the requested version | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackCheck._make_request_with_auth_fallback | def _make_request_with_auth_fallback(self, url, headers=None, params=None):
"""
Generic request handler for OpenStack API requests
Raises specialized Exceptions for commonly encountered error codes
"""
self.log.debug("Request URL and Params: %s, %s", url, params)
try:
... | python | def _make_request_with_auth_fallback(self, url, headers=None, params=None):
"""
Generic request handler for OpenStack API requests
Raises specialized Exceptions for commonly encountered error codes
"""
self.log.debug("Request URL and Params: %s, %s", url, params)
try:
... | [
"def",
"_make_request_with_auth_fallback",
"(",
"self",
",",
"url",
",",
"headers",
"=",
"None",
",",
"params",
"=",
"None",
")",
":",
"self",
".",
"log",
".",
"debug",
"(",
"\"Request URL and Params: %s, %s\"",
",",
"url",
",",
"params",
")",
"try",
":",
... | Generic request handler for OpenStack API requests
Raises specialized Exceptions for commonly encountered error codes | [
"Generic",
"request",
"handler",
"for",
"OpenStack",
"API",
"requests",
"Raises",
"specialized",
"Exceptions",
"for",
"commonly",
"encountered",
"error",
"codes"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L576-L606 | train | This function is a generic request handler for OpenStack API requests Raises specialized Exceptions for commonly encountered error codes | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackCheck.get_network_stats | def get_network_stats(self, tags):
"""
Collect stats for all reachable networks
"""
# FIXME: (aaditya) Check all networks defaults to true
# until we can reliably assign agents to networks to monitor
if is_affirmative(self.init_config.get('check_all_networks', True)):
... | python | def get_network_stats(self, tags):
"""
Collect stats for all reachable networks
"""
# FIXME: (aaditya) Check all networks defaults to true
# until we can reliably assign agents to networks to monitor
if is_affirmative(self.init_config.get('check_all_networks', True)):
... | [
"def",
"get_network_stats",
"(",
"self",
",",
"tags",
")",
":",
"# FIXME: (aaditya) Check all networks defaults to true",
"# until we can reliably assign agents to networks to monitor",
"if",
"is_affirmative",
"(",
"self",
".",
"init_config",
".",
"get",
"(",
"'check_all_networ... | Collect stats for all reachable networks | [
"Collect",
"stats",
"for",
"all",
"reachable",
"networks"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L688-L714 | train | Collect stats for all reachable networks and add agents to the monitor. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackCheck._parse_uptime_string | def _parse_uptime_string(self, uptime):
""" Parse u' 16:53:48 up 1 day, 21:34, 3 users, load average: 0.04, 0.14, 0.19\n' """
uptime = uptime.strip()
load_averages = uptime[uptime.find('load average:') :].split(':')[1].split(',')
uptime_sec = uptime.split(',')[0]
return {'load... | python | def _parse_uptime_string(self, uptime):
""" Parse u' 16:53:48 up 1 day, 21:34, 3 users, load average: 0.04, 0.14, 0.19\n' """
uptime = uptime.strip()
load_averages = uptime[uptime.find('load average:') :].split(':')[1].split(',')
uptime_sec = uptime.split(',')[0]
return {'load... | [
"def",
"_parse_uptime_string",
"(",
"self",
",",
"uptime",
")",
":",
"uptime",
"=",
"uptime",
".",
"strip",
"(",
")",
"load_averages",
"=",
"uptime",
"[",
"uptime",
".",
"find",
"(",
"'load average:'",
")",
":",
"]",
".",
"split",
"(",
"':'",
")",
"[",... | Parse u' 16:53:48 up 1 day, 21:34, 3 users, load average: 0.04, 0.14, 0.19\n' | [
"Parse",
"u",
"16",
":",
"53",
":",
"48",
"up",
"1",
"day",
"21",
":",
"34",
"3",
"users",
"load",
"average",
":",
"0",
".",
"04",
"0",
".",
"14",
"0",
".",
"19",
"\\",
"n"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L759-L765 | train | Parse the uptime string into a dictionary of load average and uptime_sec. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackCheck.ensure_auth_scope | def ensure_auth_scope(self, instance):
"""
Guarantees a valid auth scope for this instance, and returns it
Communicates with the identity server and initializes a new scope when one is absent, or has been forcibly
removed due to token expiry
"""
instance_scope = None
... | python | def ensure_auth_scope(self, instance):
"""
Guarantees a valid auth scope for this instance, and returns it
Communicates with the identity server and initializes a new scope when one is absent, or has been forcibly
removed due to token expiry
"""
instance_scope = None
... | [
"def",
"ensure_auth_scope",
"(",
"self",
",",
"instance",
")",
":",
"instance_scope",
"=",
"None",
"custom_tags",
"=",
"instance",
".",
"get",
"(",
"'tags'",
",",
"[",
"]",
")",
"if",
"custom_tags",
"is",
"None",
":",
"custom_tags",
"=",
"[",
"]",
"try",... | Guarantees a valid auth scope for this instance, and returns it
Communicates with the identity server and initializes a new scope when one is absent, or has been forcibly
removed due to token expiry | [
"Guarantees",
"a",
"valid",
"auth",
"scope",
"for",
"this",
"instance",
"and",
"returns",
"it"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L1105-L1179 | train | Ensures that the auth token for this instance is valid and returns it | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackCheck.get_local_hypervisor | def get_local_hypervisor(self):
"""
Returns the hypervisor running on this host, and assumes a 1-1 between host and hypervisor
"""
# Look up hypervisors available filtered by my hostname
host = self.get_my_hostname()
hyp = self.get_all_hypervisor_ids(filter_by_host=host)
... | python | def get_local_hypervisor(self):
"""
Returns the hypervisor running on this host, and assumes a 1-1 between host and hypervisor
"""
# Look up hypervisors available filtered by my hostname
host = self.get_my_hostname()
hyp = self.get_all_hypervisor_ids(filter_by_host=host)
... | [
"def",
"get_local_hypervisor",
"(",
"self",
")",
":",
"# Look up hypervisors available filtered by my hostname",
"host",
"=",
"self",
".",
"get_my_hostname",
"(",
")",
"hyp",
"=",
"self",
".",
"get_all_hypervisor_ids",
"(",
"filter_by_host",
"=",
"host",
")",
"if",
... | Returns the hypervisor running on this host, and assumes a 1-1 between host and hypervisor | [
"Returns",
"the",
"hypervisor",
"running",
"on",
"this",
"host",
"and",
"assumes",
"a",
"1",
"-",
"1",
"between",
"host",
"and",
"hypervisor"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L1313-L1321 | train | Returns the local hypervisor running on this host and assumes a 1 - 1 between host and hypervisor | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackCheck.get_all_projects | def get_all_projects(self, scope):
"""
Returns all projects in the domain
"""
url = "{0}/{1}/{2}".format(self.keystone_server_url, DEFAULT_KEYSTONE_API_VERSION, "projects")
headers = {'X-Auth-Token': scope.auth_token}
try:
r = self._make_request_with_auth_fall... | python | def get_all_projects(self, scope):
"""
Returns all projects in the domain
"""
url = "{0}/{1}/{2}".format(self.keystone_server_url, DEFAULT_KEYSTONE_API_VERSION, "projects")
headers = {'X-Auth-Token': scope.auth_token}
try:
r = self._make_request_with_auth_fall... | [
"def",
"get_all_projects",
"(",
"self",
",",
"scope",
")",
":",
"url",
"=",
"\"{0}/{1}/{2}\"",
".",
"format",
"(",
"self",
".",
"keystone_server_url",
",",
"DEFAULT_KEYSTONE_API_VERSION",
",",
"\"projects\"",
")",
"headers",
"=",
"{",
"'X-Auth-Token'",
":",
"sco... | Returns all projects in the domain | [
"Returns",
"all",
"projects",
"in",
"the",
"domain"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L1323-L1337 | train | Returns all projects in the domain | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackCheck.get_scoped_project | def get_scoped_project(self, project_auth_scope):
"""
Returns the project that this instance of the check is scoped to
"""
filter_params = {}
url = "{0}/{1}/{2}".format(self.keystone_server_url, DEFAULT_KEYSTONE_API_VERSION, "projects")
if project_auth_scope.tenant_id:
... | python | def get_scoped_project(self, project_auth_scope):
"""
Returns the project that this instance of the check is scoped to
"""
filter_params = {}
url = "{0}/{1}/{2}".format(self.keystone_server_url, DEFAULT_KEYSTONE_API_VERSION, "projects")
if project_auth_scope.tenant_id:
... | [
"def",
"get_scoped_project",
"(",
"self",
",",
"project_auth_scope",
")",
":",
"filter_params",
"=",
"{",
"}",
"url",
"=",
"\"{0}/{1}/{2}\"",
".",
"format",
"(",
"self",
".",
"keystone_server_url",
",",
"DEFAULT_KEYSTONE_API_VERSION",
",",
"\"projects\"",
")",
"if... | Returns the project that this instance of the check is scoped to | [
"Returns",
"the",
"project",
"that",
"this",
"instance",
"of",
"the",
"check",
"is",
"scoped",
"to"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L1339-L1372 | train | Returns the project that this check is scoped to
| Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackCheck.get_my_hostname | def get_my_hostname(self, split_hostname_on_first_period=False):
"""
Returns a best guess for the hostname registered with OpenStack for this host
"""
hostname = self.init_config.get("os_host") or self.hostname
if split_hostname_on_first_period:
hostname = hostname.s... | python | def get_my_hostname(self, split_hostname_on_first_period=False):
"""
Returns a best guess for the hostname registered with OpenStack for this host
"""
hostname = self.init_config.get("os_host") or self.hostname
if split_hostname_on_first_period:
hostname = hostname.s... | [
"def",
"get_my_hostname",
"(",
"self",
",",
"split_hostname_on_first_period",
"=",
"False",
")",
":",
"hostname",
"=",
"self",
".",
"init_config",
".",
"get",
"(",
"\"os_host\"",
")",
"or",
"self",
".",
"hostname",
"if",
"split_hostname_on_first_period",
":",
"h... | Returns a best guess for the hostname registered with OpenStack for this host | [
"Returns",
"a",
"best",
"guess",
"for",
"the",
"hostname",
"registered",
"with",
"OpenStack",
"for",
"this",
"host"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L1374-L1383 | train | Returns a best guess for the hostname registered with OpenStack for this host. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack/datadog_checks/openstack/openstack.py | OpenStackCheck.get_external_host_tags | def get_external_host_tags(self):
""" Returns a list of tags for every guest server that is detected by the OpenStack
integration.
List of pairs (hostname, list_of_tags)
"""
self.log.debug("Collecting external_host_tags now")
external_host_tags = []
for k, v in it... | python | def get_external_host_tags(self):
""" Returns a list of tags for every guest server that is detected by the OpenStack
integration.
List of pairs (hostname, list_of_tags)
"""
self.log.debug("Collecting external_host_tags now")
external_host_tags = []
for k, v in it... | [
"def",
"get_external_host_tags",
"(",
"self",
")",
":",
"self",
".",
"log",
".",
"debug",
"(",
"\"Collecting external_host_tags now\"",
")",
"external_host_tags",
"=",
"[",
"]",
"for",
"k",
",",
"v",
"in",
"iteritems",
"(",
"self",
".",
"external_host_tags",
"... | Returns a list of tags for every guest server that is detected by the OpenStack
integration.
List of pairs (hostname, list_of_tags) | [
"Returns",
"a",
"list",
"of",
"tags",
"for",
"every",
"guest",
"server",
"that",
"is",
"detected",
"by",
"the",
"OpenStack",
"integration",
".",
"List",
"of",
"pairs",
"(",
"hostname",
"list_of_tags",
")"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack/datadog_checks/openstack/openstack.py#L1416-L1427 | train | Returns a list of pairs of hostname and list_of_tags | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon.check | def check(self, instance):
"""Run the Docker check for one instance."""
if not self.init_success:
# Initialization can fail if cgroups are not ready or docker daemon is down. So we retry if needed
# https://github.com/DataDog/dd-agent/issues/1896
self.init()
... | python | def check(self, instance):
"""Run the Docker check for one instance."""
if not self.init_success:
# Initialization can fail if cgroups are not ready or docker daemon is down. So we retry if needed
# https://github.com/DataDog/dd-agent/issues/1896
self.init()
... | [
"def",
"check",
"(",
"self",
",",
"instance",
")",
":",
"if",
"not",
"self",
".",
"init_success",
":",
"# Initialization can fail if cgroups are not ready or docker daemon is down. So we retry if needed",
"# https://github.com/DataDog/dd-agent/issues/1896",
"self",
".",
"init",
... | Run the Docker check for one instance. | [
"Run",
"the",
"Docker",
"check",
"for",
"one",
"instance",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L287-L357 | train | Run the Docker check for one instance. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._get_and_count_containers | def _get_and_count_containers(self, custom_cgroups=False, healthchecks=False):
"""List all the containers from the API, filter and count them."""
# Querying the size of containers is slow, we don't do it at each run
must_query_size = self.collect_container_size and self._latest_size_query == 0
... | python | def _get_and_count_containers(self, custom_cgroups=False, healthchecks=False):
"""List all the containers from the API, filter and count them."""
# Querying the size of containers is slow, we don't do it at each run
must_query_size = self.collect_container_size and self._latest_size_query == 0
... | [
"def",
"_get_and_count_containers",
"(",
"self",
",",
"custom_cgroups",
"=",
"False",
",",
"healthchecks",
"=",
"False",
")",
":",
"# Querying the size of containers is slow, we don't do it at each run",
"must_query_size",
"=",
"self",
".",
"collect_container_size",
"and",
... | List all the containers from the API, filter and count them. | [
"List",
"all",
"the",
"containers",
"from",
"the",
"API",
"filter",
"and",
"count",
"them",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L375-L442 | train | List all the containers from the API filter and count them. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._get_tags | def _get_tags(self, entity=None, tag_type=None):
"""Generate the tags for a given entity (container or image) according to a list of tag names."""
# Start with custom tags
tags = list(self.custom_tags)
# Collect pod names as tags on kubernetes
if Platform.is_k8s() and KubeUtil.P... | python | def _get_tags(self, entity=None, tag_type=None):
"""Generate the tags for a given entity (container or image) according to a list of tag names."""
# Start with custom tags
tags = list(self.custom_tags)
# Collect pod names as tags on kubernetes
if Platform.is_k8s() and KubeUtil.P... | [
"def",
"_get_tags",
"(",
"self",
",",
"entity",
"=",
"None",
",",
"tag_type",
"=",
"None",
")",
":",
"# Start with custom tags",
"tags",
"=",
"list",
"(",
"self",
".",
"custom_tags",
")",
"# Collect pod names as tags on kubernetes",
"if",
"Platform",
".",
"is_k8... | Generate the tags for a given entity (container or image) according to a list of tag names. | [
"Generate",
"the",
"tags",
"for",
"a",
"given",
"entity",
"(",
"container",
"or",
"image",
")",
"according",
"to",
"a",
"list",
"of",
"tag",
"names",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L452-L539 | train | Generate the tags for a given entity according to a list of tag names. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._extract_tag_value | def _extract_tag_value(self, entity, tag_name):
"""Extra tag information from the API result (containers or images).
Cache extracted tags inside the entity object.
"""
if tag_name not in TAG_EXTRACTORS:
self.warning("{0} isn't a supported tag".format(tag_name))
re... | python | def _extract_tag_value(self, entity, tag_name):
"""Extra tag information from the API result (containers or images).
Cache extracted tags inside the entity object.
"""
if tag_name not in TAG_EXTRACTORS:
self.warning("{0} isn't a supported tag".format(tag_name))
re... | [
"def",
"_extract_tag_value",
"(",
"self",
",",
"entity",
",",
"tag_name",
")",
":",
"if",
"tag_name",
"not",
"in",
"TAG_EXTRACTORS",
":",
"self",
".",
"warning",
"(",
"\"{0} isn't a supported tag\"",
".",
"format",
"(",
"tag_name",
")",
")",
"return",
"# Check... | Extra tag information from the API result (containers or images).
Cache extracted tags inside the entity object. | [
"Extra",
"tag",
"information",
"from",
"the",
"API",
"result",
"(",
"containers",
"or",
"images",
")",
".",
"Cache",
"extracted",
"tags",
"inside",
"the",
"entity",
"object",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L541-L556 | train | Extract the value of a tag from the API result. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._is_container_excluded | def _is_container_excluded(self, container):
"""Check if a container is excluded according to the filter rules.
Requires _filter_containers to run first.
"""
container_name = DockerUtil.container_name_extractor(container)[0]
return container_name in self._filtered_containers | python | def _is_container_excluded(self, container):
"""Check if a container is excluded according to the filter rules.
Requires _filter_containers to run first.
"""
container_name = DockerUtil.container_name_extractor(container)[0]
return container_name in self._filtered_containers | [
"def",
"_is_container_excluded",
"(",
"self",
",",
"container",
")",
":",
"container_name",
"=",
"DockerUtil",
".",
"container_name_extractor",
"(",
"container",
")",
"[",
"0",
"]",
"return",
"container_name",
"in",
"self",
".",
"_filtered_containers"
] | Check if a container is excluded according to the filter rules.
Requires _filter_containers to run first. | [
"Check",
"if",
"a",
"container",
"is",
"excluded",
"according",
"to",
"the",
"filter",
"rules",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L571-L577 | train | Check if a container is excluded according to the filter rules. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._send_container_healthcheck_sc | def _send_container_healthcheck_sc(self, containers_by_id):
"""Send health service checks for containers."""
for container in containers_by_id.itervalues():
healthcheck_tags = self._get_tags(container, HEALTHCHECK)
match = False
for tag in healthcheck_tags:
... | python | def _send_container_healthcheck_sc(self, containers_by_id):
"""Send health service checks for containers."""
for container in containers_by_id.itervalues():
healthcheck_tags = self._get_tags(container, HEALTHCHECK)
match = False
for tag in healthcheck_tags:
... | [
"def",
"_send_container_healthcheck_sc",
"(",
"self",
",",
"containers_by_id",
")",
":",
"for",
"container",
"in",
"containers_by_id",
".",
"itervalues",
"(",
")",
":",
"healthcheck_tags",
"=",
"self",
".",
"_get_tags",
"(",
"container",
",",
"HEALTHCHECK",
")",
... | Send health service checks for containers. | [
"Send",
"health",
"service",
"checks",
"for",
"containers",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L594-L608 | train | Send health service checks for containers. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._report_container_count | def _report_container_count(self, containers_by_id):
"""Report container count per state"""
m_func = FUNC_MAP[GAUGE][self.use_histogram]
per_state_count = defaultdict(int)
filterlambda = lambda ctr: not self._is_container_excluded(ctr)
containers = list(filter(filterlambda, con... | python | def _report_container_count(self, containers_by_id):
"""Report container count per state"""
m_func = FUNC_MAP[GAUGE][self.use_histogram]
per_state_count = defaultdict(int)
filterlambda = lambda ctr: not self._is_container_excluded(ctr)
containers = list(filter(filterlambda, con... | [
"def",
"_report_container_count",
"(",
"self",
",",
"containers_by_id",
")",
":",
"m_func",
"=",
"FUNC_MAP",
"[",
"GAUGE",
"]",
"[",
"self",
".",
"use_histogram",
"]",
"per_state_count",
"=",
"defaultdict",
"(",
"int",
")",
"filterlambda",
"=",
"lambda",
"ctr"... | Report container count per state | [
"Report",
"container",
"count",
"per",
"state"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L623-L637 | train | Report the number of containers in each state. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._report_volume_count | def _report_volume_count(self):
"""Report volume count per state (dangling or not)"""
m_func = FUNC_MAP[GAUGE][self.use_histogram]
attached_volumes = self.docker_util.client.volumes(filters={'dangling': False})
dangling_volumes = self.docker_util.client.volumes(filters={'dangling': True... | python | def _report_volume_count(self):
"""Report volume count per state (dangling or not)"""
m_func = FUNC_MAP[GAUGE][self.use_histogram]
attached_volumes = self.docker_util.client.volumes(filters={'dangling': False})
dangling_volumes = self.docker_util.client.volumes(filters={'dangling': True... | [
"def",
"_report_volume_count",
"(",
"self",
")",
":",
"m_func",
"=",
"FUNC_MAP",
"[",
"GAUGE",
"]",
"[",
"self",
".",
"use_histogram",
"]",
"attached_volumes",
"=",
"self",
".",
"docker_util",
".",
"client",
".",
"volumes",
"(",
"filters",
"=",
"{",
"'dang... | Report volume count per state (dangling or not) | [
"Report",
"volume",
"count",
"per",
"state",
"(",
"dangling",
"or",
"not",
")"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L639-L648 | train | Report volume count per state ( attached or not | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._report_net_metrics | def _report_net_metrics(self, container, tags):
"""Find container network metrics by looking at /proc/$PID/net/dev of the container process."""
if self._disable_net_metrics:
self.log.debug("Network metrics are disabled. Skipping")
return
proc_net_file = os.path.join(cont... | python | def _report_net_metrics(self, container, tags):
"""Find container network metrics by looking at /proc/$PID/net/dev of the container process."""
if self._disable_net_metrics:
self.log.debug("Network metrics are disabled. Skipping")
return
proc_net_file = os.path.join(cont... | [
"def",
"_report_net_metrics",
"(",
"self",
",",
"container",
",",
"tags",
")",
":",
"if",
"self",
".",
"_disable_net_metrics",
":",
"self",
".",
"log",
".",
"debug",
"(",
"\"Network metrics are disabled. Skipping\"",
")",
"return",
"proc_net_file",
"=",
"os",
".... | Find container network metrics by looking at /proc/$PID/net/dev of the container process. | [
"Find",
"container",
"network",
"metrics",
"by",
"looking",
"at",
"/",
"proc",
"/",
"$PID",
"/",
"net",
"/",
"dev",
"of",
"the",
"container",
"process",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L722-L764 | train | Report the network metrics for the container. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._get_events | def _get_events(self):
"""Get the list of events."""
events, changed_container_ids = self.docker_util.get_events()
if not self._disable_net_metrics:
self._invalidate_network_mapping_cache(events)
if changed_container_ids and self._service_discovery:
get_sd_backend... | python | def _get_events(self):
"""Get the list of events."""
events, changed_container_ids = self.docker_util.get_events()
if not self._disable_net_metrics:
self._invalidate_network_mapping_cache(events)
if changed_container_ids and self._service_discovery:
get_sd_backend... | [
"def",
"_get_events",
"(",
"self",
")",
":",
"events",
",",
"changed_container_ids",
"=",
"self",
".",
"docker_util",
".",
"get_events",
"(",
")",
"if",
"not",
"self",
".",
"_disable_net_metrics",
":",
"self",
".",
"_invalidate_network_mapping_cache",
"(",
"even... | Get the list of events. | [
"Get",
"the",
"list",
"of",
"events",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L799-L808 | train | Get the list of events. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._create_dd_event | def _create_dd_event(self, events, image, c_tags, priority='Normal'):
"""Create the actual event to submit from a list of similar docker events"""
if not events:
return
max_timestamp = 0
status = defaultdict(int)
status_change = []
for ev, c_name in events:
... | python | def _create_dd_event(self, events, image, c_tags, priority='Normal'):
"""Create the actual event to submit from a list of similar docker events"""
if not events:
return
max_timestamp = 0
status = defaultdict(int)
status_change = []
for ev, c_name in events:
... | [
"def",
"_create_dd_event",
"(",
"self",
",",
"events",
",",
"image",
",",
"c_tags",
",",
"priority",
"=",
"'Normal'",
")",
":",
"if",
"not",
"events",
":",
"return",
"max_timestamp",
"=",
"0",
"status",
"=",
"defaultdict",
"(",
"int",
")",
"status_change",... | Create the actual event to submit from a list of similar docker events | [
"Create",
"the",
"actual",
"event",
"to",
"submit",
"from",
"a",
"list",
"of",
"similar",
"docker",
"events"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L883-L928 | train | Create the actual event to submit from a list of similar docker events | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._report_disk_stats | def _report_disk_stats(self):
"""Report metrics about the volume space usage"""
stats = {
'docker.data.used': None,
'docker.data.total': None,
'docker.data.free': None,
'docker.metadata.used': None,
'docker.metadata.total': None,
'd... | python | def _report_disk_stats(self):
"""Report metrics about the volume space usage"""
stats = {
'docker.data.used': None,
'docker.data.total': None,
'docker.data.free': None,
'docker.metadata.used': None,
'docker.metadata.total': None,
'd... | [
"def",
"_report_disk_stats",
"(",
"self",
")",
":",
"stats",
"=",
"{",
"'docker.data.used'",
":",
"None",
",",
"'docker.data.total'",
":",
"None",
",",
"'docker.data.free'",
":",
"None",
",",
"'docker.metadata.used'",
":",
"None",
",",
"'docker.metadata.total'",
"... | Report metrics about the volume space usage | [
"Report",
"metrics",
"about",
"the",
"volume",
"space",
"usage"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L930-L968 | train | Report metrics about the disk usage | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._format_disk_metrics | def _format_disk_metrics(self, metrics):
"""Cast the disk stats to float and convert them to bytes"""
for name, raw_val in metrics.iteritems():
if raw_val:
match = DISK_STATS_RE.search(raw_val)
if match is None or len(match.groups()) != 2:
... | python | def _format_disk_metrics(self, metrics):
"""Cast the disk stats to float and convert them to bytes"""
for name, raw_val in metrics.iteritems():
if raw_val:
match = DISK_STATS_RE.search(raw_val)
if match is None or len(match.groups()) != 2:
... | [
"def",
"_format_disk_metrics",
"(",
"self",
",",
"metrics",
")",
":",
"for",
"name",
",",
"raw_val",
"in",
"metrics",
".",
"iteritems",
"(",
")",
":",
"if",
"raw_val",
":",
"match",
"=",
"DISK_STATS_RE",
".",
"search",
"(",
"raw_val",
")",
"if",
"match",... | Cast the disk stats to float and convert them to bytes | [
"Cast",
"the",
"disk",
"stats",
"to",
"float",
"and",
"convert",
"them",
"to",
"bytes"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L970-L987 | train | Cast the disk stats to float and convert them to bytes | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._calc_percent_disk_stats | def _calc_percent_disk_stats(self, stats):
"""Calculate a percentage of used disk space for data and metadata"""
mtypes = ['data', 'metadata']
percs = {}
for mtype in mtypes:
used = stats.get('docker.{0}.used'.format(mtype))
total = stats.get('docker.{0}.total'.fo... | python | def _calc_percent_disk_stats(self, stats):
"""Calculate a percentage of used disk space for data and metadata"""
mtypes = ['data', 'metadata']
percs = {}
for mtype in mtypes:
used = stats.get('docker.{0}.used'.format(mtype))
total = stats.get('docker.{0}.total'.fo... | [
"def",
"_calc_percent_disk_stats",
"(",
"self",
",",
"stats",
")",
":",
"mtypes",
"=",
"[",
"'data'",
",",
"'metadata'",
"]",
"percs",
"=",
"{",
"}",
"for",
"mtype",
"in",
"mtypes",
":",
"used",
"=",
"stats",
".",
"get",
"(",
"'docker.{0}.used'",
".",
... | Calculate a percentage of used disk space for data and metadata | [
"Calculate",
"a",
"percentage",
"of",
"used",
"disk",
"space",
"for",
"data",
"and",
"metadata"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L989-L1010 | train | Calculate a percentage of used disk space for data and metadata | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._get_cgroup_from_proc | def _get_cgroup_from_proc(self, cgroup, pid, filename):
"""Find a specific cgroup file, containing metrics to extract."""
params = {
"file": filename,
}
return DockerUtil.find_cgroup_from_proc(self._mountpoints, pid, cgroup, self.docker_util._docker_root) % (params) | python | def _get_cgroup_from_proc(self, cgroup, pid, filename):
"""Find a specific cgroup file, containing metrics to extract."""
params = {
"file": filename,
}
return DockerUtil.find_cgroup_from_proc(self._mountpoints, pid, cgroup, self.docker_util._docker_root) % (params) | [
"def",
"_get_cgroup_from_proc",
"(",
"self",
",",
"cgroup",
",",
"pid",
",",
"filename",
")",
":",
"params",
"=",
"{",
"\"file\"",
":",
"filename",
",",
"}",
"return",
"DockerUtil",
".",
"find_cgroup_from_proc",
"(",
"self",
".",
"_mountpoints",
",",
"pid",
... | Find a specific cgroup file, containing metrics to extract. | [
"Find",
"a",
"specific",
"cgroup",
"file",
"containing",
"metrics",
"to",
"extract",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L1013-L1018 | train | Find a specific cgroup file containing metrics to extract. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._parse_cgroup_file | def _parse_cgroup_file(self, stat_file):
"""Parse a cgroup pseudo file for key/values."""
self.log.debug("Opening cgroup file: %s" % stat_file)
try:
with open(stat_file, 'r') as fp:
if 'blkio' in stat_file:
return self._parse_blkio_metrics(fp.read(... | python | def _parse_cgroup_file(self, stat_file):
"""Parse a cgroup pseudo file for key/values."""
self.log.debug("Opening cgroup file: %s" % stat_file)
try:
with open(stat_file, 'r') as fp:
if 'blkio' in stat_file:
return self._parse_blkio_metrics(fp.read(... | [
"def",
"_parse_cgroup_file",
"(",
"self",
",",
"stat_file",
")",
":",
"self",
".",
"log",
".",
"debug",
"(",
"\"Opening cgroup file: %s\"",
"%",
"stat_file",
")",
"try",
":",
"with",
"open",
"(",
"stat_file",
",",
"'r'",
")",
"as",
"fp",
":",
"if",
"'blk... | Parse a cgroup pseudo file for key/values. | [
"Parse",
"a",
"cgroup",
"pseudo",
"file",
"for",
"key",
"/",
"values",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L1020-L1044 | train | Parse a cgroup pseudo file for key - value pairs. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._parse_blkio_metrics | def _parse_blkio_metrics(self, stats):
"""Parse the blkio metrics."""
metrics = {
'io_read': 0,
'io_write': 0,
}
for line in stats:
if 'Read' in line:
metrics['io_read'] += int(line.split()[2])
if 'Write' in line:
... | python | def _parse_blkio_metrics(self, stats):
"""Parse the blkio metrics."""
metrics = {
'io_read': 0,
'io_write': 0,
}
for line in stats:
if 'Read' in line:
metrics['io_read'] += int(line.split()[2])
if 'Write' in line:
... | [
"def",
"_parse_blkio_metrics",
"(",
"self",
",",
"stats",
")",
":",
"metrics",
"=",
"{",
"'io_read'",
":",
"0",
",",
"'io_write'",
":",
"0",
",",
"}",
"for",
"line",
"in",
"stats",
":",
"if",
"'Read'",
"in",
"line",
":",
"metrics",
"[",
"'io_read'",
... | Parse the blkio metrics. | [
"Parse",
"the",
"blkio",
"metrics",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L1046-L1057 | train | Parse the blkio metrics. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | docker_daemon/datadog_checks/docker_daemon/docker_daemon.py | DockerDaemon._crawl_container_pids | def _crawl_container_pids(self, container_dict, custom_cgroups=False):
"""Crawl `/proc` to find container PIDs and add them to `containers_by_id`."""
proc_path = os.path.join(self.docker_util._docker_root, 'proc')
pid_dirs = [_dir for _dir in os.listdir(proc_path) if _dir.isdigit()]
if ... | python | def _crawl_container_pids(self, container_dict, custom_cgroups=False):
"""Crawl `/proc` to find container PIDs and add them to `containers_by_id`."""
proc_path = os.path.join(self.docker_util._docker_root, 'proc')
pid_dirs = [_dir for _dir in os.listdir(proc_path) if _dir.isdigit()]
if ... | [
"def",
"_crawl_container_pids",
"(",
"self",
",",
"container_dict",
",",
"custom_cgroups",
"=",
"False",
")",
":",
"proc_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"self",
".",
"docker_util",
".",
"_docker_root",
",",
"'proc'",
")",
"pid_dirs",
"=",
... | Crawl `/proc` to find container PIDs and add them to `containers_by_id`. | [
"Crawl",
"/",
"proc",
"to",
"find",
"container",
"PIDs",
"and",
"add",
"them",
"to",
"containers_by_id",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/docker_daemon/datadog_checks/docker_daemon/docker_daemon.py#L1073-L1134 | train | Crawl proc to find container PIDs and add them to containers_by_id. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/commands/env/start.py | start | def start(ctx, check, env, agent, dev, base, env_vars):
"""Start an environment."""
if not file_exists(get_tox_file(check)):
abort('`{}` is not a testable check.'.format(check))
base_package = None
if base:
core_dir = os.path.expanduser(ctx.obj.get('core', ''))
if not dir_exists... | python | def start(ctx, check, env, agent, dev, base, env_vars):
"""Start an environment."""
if not file_exists(get_tox_file(check)):
abort('`{}` is not a testable check.'.format(check))
base_package = None
if base:
core_dir = os.path.expanduser(ctx.obj.get('core', ''))
if not dir_exists... | [
"def",
"start",
"(",
"ctx",
",",
"check",
",",
"env",
",",
"agent",
",",
"dev",
",",
"base",
",",
"env_vars",
")",
":",
"if",
"not",
"file_exists",
"(",
"get_tox_file",
"(",
"check",
")",
")",
":",
"abort",
"(",
"'`{}` is not a testable check.'",
".",
... | Start an environment. | [
"Start",
"an",
"environment",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/commands/env/start.py#L42-L208 | train | Start an environment. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack_controller/datadog_checks/openstack_controller/api.py | SimpleApi._make_request | def _make_request(self, url, headers, params=None):
"""
Generic request handler for OpenStack API requests
Raises specialized Exceptions for commonly encountered error codes
"""
self.logger.debug("Request URL, Headers and Params: %s, %s, %s", url, headers, params)
# Chec... | python | def _make_request(self, url, headers, params=None):
"""
Generic request handler for OpenStack API requests
Raises specialized Exceptions for commonly encountered error codes
"""
self.logger.debug("Request URL, Headers and Params: %s, %s, %s", url, headers, params)
# Chec... | [
"def",
"_make_request",
"(",
"self",
",",
"url",
",",
"headers",
",",
"params",
"=",
"None",
")",
":",
"self",
".",
"logger",
".",
"debug",
"(",
"\"Request URL, Headers and Params: %s, %s, %s\"",
",",
"url",
",",
"headers",
",",
"params",
")",
"# Checking if r... | Generic request handler for OpenStack API requests
Raises specialized Exceptions for commonly encountered error codes | [
"Generic",
"request",
"handler",
"for",
"OpenStack",
"API",
"requests",
"Raises",
"specialized",
"Exceptions",
"for",
"commonly",
"encountered",
"error",
"codes"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack_controller/datadog_checks/openstack_controller/api.py#L296-L331 | train | Generic request handler for OpenStack API requests
| Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack_controller/datadog_checks/openstack_controller/api.py | SimpleApi.get_projects | def get_projects(self):
"""
Returns all projects in the domain
"""
url = urljoin(self.keystone_endpoint, "{}/{}".format(DEFAULT_KEYSTONE_API_VERSION, "projects"))
try:
r = self._make_request(url, self.headers)
return r.get('projects', [])
except E... | python | def get_projects(self):
"""
Returns all projects in the domain
"""
url = urljoin(self.keystone_endpoint, "{}/{}".format(DEFAULT_KEYSTONE_API_VERSION, "projects"))
try:
r = self._make_request(url, self.headers)
return r.get('projects', [])
except E... | [
"def",
"get_projects",
"(",
"self",
")",
":",
"url",
"=",
"urljoin",
"(",
"self",
".",
"keystone_endpoint",
",",
"\"{}/{}\"",
".",
"format",
"(",
"DEFAULT_KEYSTONE_API_VERSION",
",",
"\"projects\"",
")",
")",
"try",
":",
"r",
"=",
"self",
".",
"_make_request... | Returns all projects in the domain | [
"Returns",
"all",
"projects",
"in",
"the",
"domain"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack_controller/datadog_checks/openstack_controller/api.py#L422-L433 | train | Returns all projects in the domain | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack_controller/datadog_checks/openstack_controller/api.py | Authenticator._get_user_identity | def _get_user_identity(user):
"""
Parse user identity out of init_config
To guarantee a uniquely identifiable user, expects
{"user": {"name": "my_username", "password": "my_password",
"domain": {"id": "my_domain_id"}
}
}
"""
if... | python | def _get_user_identity(user):
"""
Parse user identity out of init_config
To guarantee a uniquely identifiable user, expects
{"user": {"name": "my_username", "password": "my_password",
"domain": {"id": "my_domain_id"}
}
}
"""
if... | [
"def",
"_get_user_identity",
"(",
"user",
")",
":",
"if",
"not",
"(",
"user",
"and",
"user",
".",
"get",
"(",
"'name'",
")",
"and",
"user",
".",
"get",
"(",
"'password'",
")",
"and",
"user",
".",
"get",
"(",
"\"domain\"",
")",
"and",
"user",
".",
"... | Parse user identity out of init_config
To guarantee a uniquely identifiable user, expects
{"user": {"name": "my_username", "password": "my_password",
"domain": {"id": "my_domain_id"}
}
} | [
"Parse",
"user",
"identity",
"out",
"of",
"init_config"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack_controller/datadog_checks/openstack_controller/api.py#L556-L572 | train | Parse user identity out of init_config and return it as dict | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack_controller/datadog_checks/openstack_controller/api.py | Authenticator._get_neutron_endpoint | def _get_neutron_endpoint(cls, json_resp):
"""
Parse the service catalog returned by the Identity API for an endpoint matching the Neutron service
Sends a CRITICAL service check when none are found registered in the Catalog
"""
valid_endpoint = cls._get_valid_endpoint(json_resp, ... | python | def _get_neutron_endpoint(cls, json_resp):
"""
Parse the service catalog returned by the Identity API for an endpoint matching the Neutron service
Sends a CRITICAL service check when none are found registered in the Catalog
"""
valid_endpoint = cls._get_valid_endpoint(json_resp, ... | [
"def",
"_get_neutron_endpoint",
"(",
"cls",
",",
"json_resp",
")",
":",
"valid_endpoint",
"=",
"cls",
".",
"_get_valid_endpoint",
"(",
"json_resp",
",",
"'neutron'",
",",
"'network'",
")",
"if",
"valid_endpoint",
":",
"return",
"valid_endpoint",
"raise",
"MissingN... | Parse the service catalog returned by the Identity API for an endpoint matching the Neutron service
Sends a CRITICAL service check when none are found registered in the Catalog | [
"Parse",
"the",
"service",
"catalog",
"returned",
"by",
"the",
"Identity",
"API",
"for",
"an",
"endpoint",
"matching",
"the",
"Neutron",
"service",
"Sends",
"a",
"CRITICAL",
"service",
"check",
"when",
"none",
"are",
"found",
"registered",
"in",
"the",
"Catalo... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack_controller/datadog_checks/openstack_controller/api.py#L575-L583 | train | Parse the JSON response from the Neutron Identity API and return the endpoint that is valid | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack_controller/datadog_checks/openstack_controller/api.py | Authenticator._get_nova_endpoint | def _get_nova_endpoint(cls, json_resp):
"""
Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog
"""
valid_endpoint = c... | python | def _get_nova_endpoint(cls, json_resp):
"""
Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog
"""
valid_endpoint = c... | [
"def",
"_get_nova_endpoint",
"(",
"cls",
",",
"json_resp",
")",
":",
"valid_endpoint",
"=",
"cls",
".",
"_get_valid_endpoint",
"(",
"json_resp",
",",
"'nova'",
",",
"'compute'",
")",
"if",
"valid_endpoint",
":",
"return",
"valid_endpoint",
"raise",
"MissingNovaEnd... | Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog | [
"Parse",
"the",
"service",
"catalog",
"returned",
"by",
"the",
"Identity",
"API",
"for",
"an",
"endpoint",
"matching",
"the",
"Nova",
"service",
"with",
"the",
"requested",
"version",
"Sends",
"a",
"CRITICAL",
"service",
"check",
"when",
"no",
"viable",
"candi... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack_controller/datadog_checks/openstack_controller/api.py#L586-L595 | train | Parse the Nova service catalog response and return the endpoint that matches the requested version | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | openstack_controller/datadog_checks/openstack_controller/api.py | Authenticator._get_valid_endpoint | def _get_valid_endpoint(resp, name, entry_type):
"""
Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog
"""
catalog =... | python | def _get_valid_endpoint(resp, name, entry_type):
"""
Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog
"""
catalog =... | [
"def",
"_get_valid_endpoint",
"(",
"resp",
",",
"name",
",",
"entry_type",
")",
":",
"catalog",
"=",
"resp",
".",
"get",
"(",
"'token'",
",",
"{",
"}",
")",
".",
"get",
"(",
"'catalog'",
",",
"[",
"]",
")",
"for",
"entry",
"in",
"catalog",
":",
"if... | Parse the service catalog returned by the Identity API for an endpoint matching
the Nova service with the requested version
Sends a CRITICAL service check when no viable candidates are found in the Catalog | [
"Parse",
"the",
"service",
"catalog",
"returned",
"by",
"the",
"Identity",
"API",
"for",
"an",
"endpoint",
"matching",
"the",
"Nova",
"service",
"with",
"the",
"requested",
"version",
"Sends",
"a",
"CRITICAL",
"service",
"check",
"when",
"no",
"viable",
"candi... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack_controller/datadog_checks/openstack_controller/api.py#L598-L623 | train | Parse the response from the Identity API to find the endpoint that is valid for the requested version of the service | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/commands/validate/dep.py | dep | def dep():
"""
This command will:
* Verify the uniqueness of dependency versions across all checks.
* Verify all the dependencies are pinned.
* Verify the embedded Python environment defined in the base check and requirements
listed in every integration are compatible.
"""
failed = Fa... | python | def dep():
"""
This command will:
* Verify the uniqueness of dependency versions across all checks.
* Verify all the dependencies are pinned.
* Verify the embedded Python environment defined in the base check and requirements
listed in every integration are compatible.
"""
failed = Fa... | [
"def",
"dep",
"(",
")",
":",
"failed",
"=",
"False",
"catalog",
",",
"errors",
"=",
"make_catalog",
"(",
")",
"# Check unpinned",
"if",
"errors",
":",
"for",
"error",
"in",
"errors",
":",
"echo_failure",
"(",
"error",
")",
"failed",
"=",
"True",
"# Check... | This command will:
* Verify the uniqueness of dependency versions across all checks.
* Verify all the dependencies are pinned.
* Verify the embedded Python environment defined in the base check and requirements
listed in every integration are compatible. | [
"This",
"command",
"will",
":"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/commands/validate/dep.py#L31-L96 | train | This command checks if all the dependencies of the base check are compatible. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/commands/meta/prometheus.py | info | def info(endpoint):
"""Show metric info from a Prometheus endpoint.
\b
Example:
$ ddev meta prom info :8080/_status/vars
"""
endpoint = sanitize_endpoint(endpoint)
metrics = parse_metrics(endpoint)
num_metrics = len(metrics)
num_gauge = 0
num_counter = 0
num_histogram = 0
... | python | def info(endpoint):
"""Show metric info from a Prometheus endpoint.
\b
Example:
$ ddev meta prom info :8080/_status/vars
"""
endpoint = sanitize_endpoint(endpoint)
metrics = parse_metrics(endpoint)
num_metrics = len(metrics)
num_gauge = 0
num_counter = 0
num_histogram = 0
... | [
"def",
"info",
"(",
"endpoint",
")",
":",
"endpoint",
"=",
"sanitize_endpoint",
"(",
"endpoint",
")",
"metrics",
"=",
"parse_metrics",
"(",
"endpoint",
")",
"num_metrics",
"=",
"len",
"(",
"metrics",
")",
"num_gauge",
"=",
"0",
"num_counter",
"=",
"0",
"nu... | Show metric info from a Prometheus endpoint.
\b
Example:
$ ddev meta prom info :8080/_status/vars | [
"Show",
"metric",
"info",
"from",
"a",
"Prometheus",
"endpoint",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/commands/meta/prometheus.py#L66-L104 | train | Show metric info from a Prometheus endpoint. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/commands/meta/prometheus.py | parse | def parse(ctx, endpoint, check, here):
"""Interactively parse metric info from a Prometheus endpoint."""
if here:
output_dir = os.getcwd()
else:
output_dir = path_join(get_root(), check)
if not dir_exists(output_dir):
abort(
'Check `{check}` does not exist... | python | def parse(ctx, endpoint, check, here):
"""Interactively parse metric info from a Prometheus endpoint."""
if here:
output_dir = os.getcwd()
else:
output_dir = path_join(get_root(), check)
if not dir_exists(output_dir):
abort(
'Check `{check}` does not exist... | [
"def",
"parse",
"(",
"ctx",
",",
"endpoint",
",",
"check",
",",
"here",
")",
":",
"if",
"here",
":",
"output_dir",
"=",
"os",
".",
"getcwd",
"(",
")",
"else",
":",
"output_dir",
"=",
"path_join",
"(",
"get_root",
"(",
")",
",",
"check",
")",
"if",
... | Interactively parse metric info from a Prometheus endpoint. | [
"Interactively",
"parse",
"metric",
"info",
"from",
"a",
"Prometheus",
"endpoint",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/commands/meta/prometheus.py#L114-L251 | train | Interactively parse metric info from a Prometheus endpoint. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/operations.py | DeleteMany._add_to_bulk | def _add_to_bulk(self, bulkobj):
"""Add this operation to the _Bulk instance `bulkobj`."""
bulkobj.add_delete(self._filter, 0, collation=self._collation) | python | def _add_to_bulk(self, bulkobj):
"""Add this operation to the _Bulk instance `bulkobj`."""
bulkobj.add_delete(self._filter, 0, collation=self._collation) | [
"def",
"_add_to_bulk",
"(",
"self",
",",
"bulkobj",
")",
":",
"bulkobj",
".",
"add_delete",
"(",
"self",
".",
"_filter",
",",
"0",
",",
"collation",
"=",
"self",
".",
"_collation",
")"
] | Add this operation to the _Bulk instance `bulkobj`. | [
"Add",
"this",
"operation",
"to",
"the",
"_Bulk",
"instance",
"bulkobj",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/operations.py#L119-L121 | train | Add this operation to the _Bulk instance bulkobj. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/operations.py | ReplaceOne._add_to_bulk | def _add_to_bulk(self, bulkobj):
"""Add this operation to the _Bulk instance `bulkobj`."""
bulkobj.add_replace(self._filter, self._doc, self._upsert,
collation=self._collation) | python | def _add_to_bulk(self, bulkobj):
"""Add this operation to the _Bulk instance `bulkobj`."""
bulkobj.add_replace(self._filter, self._doc, self._upsert,
collation=self._collation) | [
"def",
"_add_to_bulk",
"(",
"self",
",",
"bulkobj",
")",
":",
"bulkobj",
".",
"add_replace",
"(",
"self",
".",
"_filter",
",",
"self",
".",
"_doc",
",",
"self",
".",
"_upsert",
",",
"collation",
"=",
"self",
".",
"_collation",
")"
] | Add this operation to the _Bulk instance `bulkobj`. | [
"Add",
"this",
"operation",
"to",
"the",
"_Bulk",
"instance",
"bulkobj",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/operations.py#L192-L195 | train | Add this operation to the _Bulk instance bulkobj. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/operations.py | UpdateOne._add_to_bulk | def _add_to_bulk(self, bulkobj):
"""Add this operation to the _Bulk instance `bulkobj`."""
bulkobj.add_update(self._filter, self._doc, False, self._upsert,
collation=self._collation) | python | def _add_to_bulk(self, bulkobj):
"""Add this operation to the _Bulk instance `bulkobj`."""
bulkobj.add_update(self._filter, self._doc, False, self._upsert,
collation=self._collation) | [
"def",
"_add_to_bulk",
"(",
"self",
",",
"bulkobj",
")",
":",
"bulkobj",
".",
"add_update",
"(",
"self",
".",
"_filter",
",",
"self",
".",
"_doc",
",",
"False",
",",
"self",
".",
"_upsert",
",",
"collation",
"=",
"self",
".",
"_collation",
")"
] | Add this operation to the _Bulk instance `bulkobj`. | [
"Add",
"this",
"operation",
"to",
"the",
"_Bulk",
"instance",
"bulkobj",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/operations.py#L222-L225 | train | Add this operation to the _Bulk instance bulkobj. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/ssl_context.py | SSLContext.load_cert_chain | def load_cert_chain(self, certfile, keyfile=None):
"""Load a private key and the corresponding certificate. The certfile
string must be the path to a single file in PEM format containing the
certificate as well as any number of CA certificates needed to
establish the certificate's authen... | python | def load_cert_chain(self, certfile, keyfile=None):
"""Load a private key and the corresponding certificate. The certfile
string must be the path to a single file in PEM format containing the
certificate as well as any number of CA certificates needed to
establish the certificate's authen... | [
"def",
"load_cert_chain",
"(",
"self",
",",
"certfile",
",",
"keyfile",
"=",
"None",
")",
":",
"self",
".",
"_certfile",
"=",
"certfile",
"self",
".",
"_keyfile",
"=",
"keyfile"
] | Load a private key and the corresponding certificate. The certfile
string must be the path to a single file in PEM format containing the
certificate as well as any number of CA certificates needed to
establish the certificate's authenticity. The keyfile string, if
present, must point to ... | [
"Load",
"a",
"private",
"key",
"and",
"the",
"corresponding",
"certificate",
".",
"The",
"certfile",
"string",
"must",
"be",
"the",
"path",
"to",
"a",
"single",
"file",
"in",
"PEM",
"format",
"containing",
"the",
"certificate",
"as",
"well",
"as",
"any",
"... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/ssl_context.py#L65-L74 | train | Load a private key and the corresponding certificate. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/ssl_context.py | SSLContext.wrap_socket | def wrap_socket(self, sock, server_side=False,
do_handshake_on_connect=True,
suppress_ragged_eofs=True, dummy=None):
"""Wrap an existing Python socket sock and return an ssl.SSLSocket
object.
"""
return ssl.wrap_socket(sock, keyfile=self._keyfile,
... | python | def wrap_socket(self, sock, server_side=False,
do_handshake_on_connect=True,
suppress_ragged_eofs=True, dummy=None):
"""Wrap an existing Python socket sock and return an ssl.SSLSocket
object.
"""
return ssl.wrap_socket(sock, keyfile=self._keyfile,
... | [
"def",
"wrap_socket",
"(",
"self",
",",
"sock",
",",
"server_side",
"=",
"False",
",",
"do_handshake_on_connect",
"=",
"True",
",",
"suppress_ragged_eofs",
"=",
"True",
",",
"dummy",
"=",
"None",
")",
":",
"return",
"ssl",
".",
"wrap_socket",
"(",
"sock",
... | Wrap an existing Python socket sock and return an ssl.SSLSocket
object. | [
"Wrap",
"an",
"existing",
"Python",
"socket",
"sock",
"and",
"return",
"an",
"ssl",
".",
"SSLSocket",
"object",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/ssl_context.py#L83-L96 | train | Wrap an existing Python socket sock and return an ssl. SSLSocket object. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_base/datadog_checks/base/utils/prometheus/functions.py | parse_metric_family | def parse_metric_family(buf):
"""
Parse the binary buffer in input, searching for Prometheus messages
of type MetricFamily [0] delimited by a varint32 [1].
[0] https://github.com/prometheus/client_model/blob/086fe7ca28bde6cec2acd5223423c1475a362858/metrics.proto#L76-%20%20L81 # noqa: E501
[1] http... | python | def parse_metric_family(buf):
"""
Parse the binary buffer in input, searching for Prometheus messages
of type MetricFamily [0] delimited by a varint32 [1].
[0] https://github.com/prometheus/client_model/blob/086fe7ca28bde6cec2acd5223423c1475a362858/metrics.proto#L76-%20%20L81 # noqa: E501
[1] http... | [
"def",
"parse_metric_family",
"(",
"buf",
")",
":",
"n",
"=",
"0",
"while",
"n",
"<",
"len",
"(",
"buf",
")",
":",
"msg_len",
",",
"new_pos",
"=",
"_DecodeVarint32",
"(",
"buf",
",",
"n",
")",
"n",
"=",
"new_pos",
"msg_buf",
"=",
"buf",
"[",
"n",
... | Parse the binary buffer in input, searching for Prometheus messages
of type MetricFamily [0] delimited by a varint32 [1].
[0] https://github.com/prometheus/client_model/blob/086fe7ca28bde6cec2acd5223423c1475a362858/metrics.proto#L76-%20%20L81 # noqa: E501
[1] https://developers.google.com/protocol-buffers... | [
"Parse",
"the",
"binary",
"buffer",
"in",
"input",
"searching",
"for",
"Prometheus",
"messages",
"of",
"type",
"MetricFamily",
"[",
"0",
"]",
"delimited",
"by",
"a",
"varint32",
"[",
"1",
"]",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/utils/prometheus/functions.py#L11-L28 | train | Parse the Prometheus metric family from the binary buffer buf. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | riakcs/datadog_checks/riakcs/riakcs.py | multidict | def multidict(ordered_pairs):
"""Convert duplicate keys values to lists."""
# read all values into lists
d = defaultdict(list)
for k, v in ordered_pairs:
d[k].append(v)
# unpack lists that have only 1 item
dict_copy = deepcopy(d)
for k, v in iteritems(dict_copy):
if len(v) ==... | python | def multidict(ordered_pairs):
"""Convert duplicate keys values to lists."""
# read all values into lists
d = defaultdict(list)
for k, v in ordered_pairs:
d[k].append(v)
# unpack lists that have only 1 item
dict_copy = deepcopy(d)
for k, v in iteritems(dict_copy):
if len(v) ==... | [
"def",
"multidict",
"(",
"ordered_pairs",
")",
":",
"# read all values into lists",
"d",
"=",
"defaultdict",
"(",
"list",
")",
"for",
"k",
",",
"v",
"in",
"ordered_pairs",
":",
"d",
"[",
"k",
"]",
".",
"append",
"(",
"v",
")",
"# unpack lists that have only ... | Convert duplicate keys values to lists. | [
"Convert",
"duplicate",
"keys",
"values",
"to",
"lists",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/riakcs/datadog_checks/riakcs/riakcs.py#L16-L27 | train | Convert duplicate keys values to lists. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/requirements.py | read_packages | def read_packages(reqs_file):
"""
Generator yielding one Package instance for every corresponing line in a
requirements file
"""
for line in stream_file_lines(reqs_file):
line = line.strip()
if not line.startswith(('#', '--hash')):
match = DEP_PATTERN.match(line)
... | python | def read_packages(reqs_file):
"""
Generator yielding one Package instance for every corresponing line in a
requirements file
"""
for line in stream_file_lines(reqs_file):
line = line.strip()
if not line.startswith(('#', '--hash')):
match = DEP_PATTERN.match(line)
... | [
"def",
"read_packages",
"(",
"reqs_file",
")",
":",
"for",
"line",
"in",
"stream_file_lines",
"(",
"reqs_file",
")",
":",
"line",
"=",
"line",
".",
"strip",
"(",
")",
"if",
"not",
"line",
".",
"startswith",
"(",
"(",
"'#'",
",",
"'--hash'",
")",
")",
... | Generator yielding one Package instance for every corresponing line in a
requirements file | [
"Generator",
"yielding",
"one",
"Package",
"instance",
"for",
"every",
"corresponing",
"line",
"in",
"a",
"requirements",
"file"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/requirements.py#L163-L174 | train | Generator yielding one Package instance for every corresponing line in a
requirements file | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/requirements.py | PackageCatalog.write_packages | def write_packages(self, reqs_file):
"""
Dump the packages in the catalog in a requirements file
"""
write_file_lines(reqs_file, ('{}\n'.format(package) for package in self.packages)) | python | def write_packages(self, reqs_file):
"""
Dump the packages in the catalog in a requirements file
"""
write_file_lines(reqs_file, ('{}\n'.format(package) for package in self.packages)) | [
"def",
"write_packages",
"(",
"self",
",",
"reqs_file",
")",
":",
"write_file_lines",
"(",
"reqs_file",
",",
"(",
"'{}\\n'",
".",
"format",
"(",
"package",
")",
"for",
"package",
"in",
"self",
".",
"packages",
")",
")"
] | Dump the packages in the catalog in a requirements file | [
"Dump",
"the",
"packages",
"in",
"the",
"catalog",
"in",
"a",
"requirements",
"file"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/requirements.py#L119-L123 | train | Dump the packages in the catalog in a requirements file | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_dev/datadog_checks/dev/tooling/requirements.py | PackageCatalog.add_package | def add_package(self, check_name, package):
"""
Add a Package to the catalog for the given check
"""
self._package_set.add(package)
package_data = self._packages[package.name]
self._checks_deps[check_name].append(package)
# Versions
if package.version:
... | python | def add_package(self, check_name, package):
"""
Add a Package to the catalog for the given check
"""
self._package_set.add(package)
package_data = self._packages[package.name]
self._checks_deps[check_name].append(package)
# Versions
if package.version:
... | [
"def",
"add_package",
"(",
"self",
",",
"check_name",
",",
"package",
")",
":",
"self",
".",
"_package_set",
".",
"add",
"(",
"package",
")",
"package_data",
"=",
"self",
".",
"_packages",
"[",
"package",
".",
"name",
"]",
"self",
".",
"_checks_deps",
"[... | Add a Package to the catalog for the given check | [
"Add",
"a",
"Package",
"to",
"the",
"catalog",
"for",
"the",
"given",
"check"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_dev/datadog_checks/dev/tooling/requirements.py#L125-L141 | train | Adds a Package to the catalog for the given check_name. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubernetes/datadog_checks/kubernetes/kubernetes.py | Kubernetes._update_container_metrics | def _update_container_metrics(self, instance, subcontainer, kube_labels):
"""Publish metrics for a subcontainer and handle filtering on tags"""
tags = list(instance.get('tags', [])) # add support for custom tags
if len(subcontainer.get('aliases', [])) >= 1:
# The first alias seems ... | python | def _update_container_metrics(self, instance, subcontainer, kube_labels):
"""Publish metrics for a subcontainer and handle filtering on tags"""
tags = list(instance.get('tags', [])) # add support for custom tags
if len(subcontainer.get('aliases', [])) >= 1:
# The first alias seems ... | [
"def",
"_update_container_metrics",
"(",
"self",
",",
"instance",
",",
"subcontainer",
",",
"kube_labels",
")",
":",
"tags",
"=",
"list",
"(",
"instance",
".",
"get",
"(",
"'tags'",
",",
"[",
"]",
")",
")",
"# add support for custom tags",
"if",
"len",
"(",
... | Publish metrics for a subcontainer and handle filtering on tags | [
"Publish",
"metrics",
"for",
"a",
"subcontainer",
"and",
"handle",
"filtering",
"on",
"tags"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubernetes/datadog_checks/kubernetes/kubernetes.py#L321-L391 | train | Update the tags for a container and handle filtering on tags | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubernetes/datadog_checks/kubernetes/kubernetes.py | Kubernetes._update_pods_metrics | def _update_pods_metrics(self, instance, pods):
"""
Reports the number of running pods on this node, tagged by service and creator
We go though all the pods, extract tags then count them by tag list, sorted and
serialized in a pipe-separated string (it is an illegar character for tags)
... | python | def _update_pods_metrics(self, instance, pods):
"""
Reports the number of running pods on this node, tagged by service and creator
We go though all the pods, extract tags then count them by tag list, sorted and
serialized in a pipe-separated string (it is an illegar character for tags)
... | [
"def",
"_update_pods_metrics",
"(",
"self",
",",
"instance",
",",
"pods",
")",
":",
"tags_map",
"=",
"defaultdict",
"(",
"int",
")",
"for",
"pod",
"in",
"pods",
"[",
"'items'",
"]",
":",
"pod_meta",
"=",
"pod",
".",
"get",
"(",
"'metadata'",
",",
"{",
... | Reports the number of running pods on this node, tagged by service and creator
We go though all the pods, extract tags then count them by tag list, sorted and
serialized in a pipe-separated string (it is an illegar character for tags) | [
"Reports",
"the",
"number",
"of",
"running",
"pods",
"on",
"this",
"node",
"tagged",
"by",
"service",
"and",
"creator"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubernetes/datadog_checks/kubernetes/kubernetes.py#L488-L512 | train | Update the metrics for running pods on this node. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubernetes/datadog_checks/kubernetes/kubernetes.py | Kubernetes._update_kube_events | def _update_kube_events(self, instance, pods_list, event_items):
"""
Process kube events and send ddog events
The namespace filtering is done here instead of KubeEventRetriever
to avoid interfering with service discovery
"""
node_ip, node_name = self.kubeutil.get_node_inf... | python | def _update_kube_events(self, instance, pods_list, event_items):
"""
Process kube events and send ddog events
The namespace filtering is done here instead of KubeEventRetriever
to avoid interfering with service discovery
"""
node_ip, node_name = self.kubeutil.get_node_inf... | [
"def",
"_update_kube_events",
"(",
"self",
",",
"instance",
",",
"pods_list",
",",
"event_items",
")",
":",
"node_ip",
",",
"node_name",
"=",
"self",
".",
"kubeutil",
".",
"get_node_info",
"(",
")",
"self",
".",
"log",
".",
"debug",
"(",
"'Processing events ... | Process kube events and send ddog events
The namespace filtering is done here instead of KubeEventRetriever
to avoid interfering with service discovery | [
"Process",
"kube",
"events",
"and",
"send",
"ddog",
"events",
"The",
"namespace",
"filtering",
"is",
"done",
"here",
"instead",
"of",
"KubeEventRetriever",
"to",
"avoid",
"interfering",
"with",
"service",
"discovery"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubernetes/datadog_checks/kubernetes/kubernetes.py#L514-L577 | train | Update the list of kube events and send ddog events | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | kubernetes/datadog_checks/kubernetes/kubernetes.py | Kubernetes.refresh_leader_status | def refresh_leader_status(self, instance):
"""
calls kubeutil.refresh_leader and compares the resulting
leader status with the previous one.
If it changed, update the event collection logic
"""
if not self.leader_candidate:
return
leader_status = self... | python | def refresh_leader_status(self, instance):
"""
calls kubeutil.refresh_leader and compares the resulting
leader status with the previous one.
If it changed, update the event collection logic
"""
if not self.leader_candidate:
return
leader_status = self... | [
"def",
"refresh_leader_status",
"(",
"self",
",",
"instance",
")",
":",
"if",
"not",
"self",
".",
"leader_candidate",
":",
"return",
"leader_status",
"=",
"self",
".",
"kubeutil",
".",
"is_leader",
"self",
".",
"kubeutil",
".",
"refresh_leader",
"(",
")",
"#... | calls kubeutil.refresh_leader and compares the resulting
leader status with the previous one.
If it changed, update the event collection logic | [
"calls",
"kubeutil",
".",
"refresh_leader",
"and",
"compares",
"the",
"resulting",
"leader",
"status",
"with",
"the",
"previous",
"one",
".",
"If",
"it",
"changed",
"update",
"the",
"event",
"collection",
"logic"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubernetes/datadog_checks/kubernetes/kubernetes.py#L579-L597 | train | Updates the leader status of the current instance. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | cacti/datadog_checks/cacti/cacti.py | Cacti._read_rrd | def _read_rrd(self, rrd_path, hostname, device_name, tags):
''' Main metric fetching method '''
metric_count = 0
try:
info = self._get_rrd_info(rrd_path)
except Exception:
# Unable to read RRD file, ignore it
self.log.exception("Unable to read RRD fil... | python | def _read_rrd(self, rrd_path, hostname, device_name, tags):
''' Main metric fetching method '''
metric_count = 0
try:
info = self._get_rrd_info(rrd_path)
except Exception:
# Unable to read RRD file, ignore it
self.log.exception("Unable to read RRD fil... | [
"def",
"_read_rrd",
"(",
"self",
",",
"rrd_path",
",",
"hostname",
",",
"device_name",
",",
"tags",
")",
":",
"metric_count",
"=",
"0",
"try",
":",
"info",
"=",
"self",
".",
"_get_rrd_info",
"(",
"rrd_path",
")",
"except",
"Exception",
":",
"# Unable to re... | Main metric fetching method | [
"Main",
"metric",
"fetching",
"method"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/cacti/datadog_checks/cacti/cacti.py#L114-L164 | train | Read the RRD file and return the number of metrics that were found. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | cacti/datadog_checks/cacti/cacti.py | Cacti._fetch_rrd_meta | def _fetch_rrd_meta(self, connection, rrd_path_root, whitelist, field_names, tags):
''' Fetch metadata about each RRD in this Cacti DB, returning a list of
tuples of (hostname, device_name, rrd_path)
'''
def _in_whitelist(rrd):
path = rrd.replace('<path_rra>/', '')
... | python | def _fetch_rrd_meta(self, connection, rrd_path_root, whitelist, field_names, tags):
''' Fetch metadata about each RRD in this Cacti DB, returning a list of
tuples of (hostname, device_name, rrd_path)
'''
def _in_whitelist(rrd):
path = rrd.replace('<path_rra>/', '')
... | [
"def",
"_fetch_rrd_meta",
"(",
"self",
",",
"connection",
",",
"rrd_path_root",
",",
"whitelist",
",",
"field_names",
",",
"tags",
")",
":",
"def",
"_in_whitelist",
"(",
"rrd",
")",
":",
"path",
"=",
"rrd",
".",
"replace",
"(",
"'<path_rra>/'",
",",
"''",
... | Fetch metadata about each RRD in this Cacti DB, returning a list of
tuples of (hostname, device_name, rrd_path) | [
"Fetch",
"metadata",
"about",
"each",
"RRD",
"in",
"this",
"Cacti",
"DB",
"returning",
"a",
"list",
"of",
"tuples",
"of",
"(",
"hostname",
"device_name",
"rrd_path",
")"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/cacti/datadog_checks/cacti/cacti.py#L166-L214 | train | Fetch metadata about each RRD in this Cacti DB returning a list of tuples of hostname device_name rrd_path. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | cacti/datadog_checks/cacti/cacti.py | Cacti._format_metric_name | def _format_metric_name(self, m_name, cfunc):
''' Format a cacti metric name into a Datadog-friendly name '''
try:
aggr = CFUNC_TO_AGGR[cfunc]
except KeyError:
aggr = cfunc.lower()
try:
m_name = CACTI_TO_DD[m_name]
if aggr != 'avg':
... | python | def _format_metric_name(self, m_name, cfunc):
''' Format a cacti metric name into a Datadog-friendly name '''
try:
aggr = CFUNC_TO_AGGR[cfunc]
except KeyError:
aggr = cfunc.lower()
try:
m_name = CACTI_TO_DD[m_name]
if aggr != 'avg':
... | [
"def",
"_format_metric_name",
"(",
"self",
",",
"m_name",
",",
"cfunc",
")",
":",
"try",
":",
"aggr",
"=",
"CFUNC_TO_AGGR",
"[",
"cfunc",
"]",
"except",
"KeyError",
":",
"aggr",
"=",
"cfunc",
".",
"lower",
"(",
")",
"try",
":",
"m_name",
"=",
"CACTI_TO... | Format a cacti metric name into a Datadog-friendly name | [
"Format",
"a",
"cacti",
"metric",
"name",
"into",
"a",
"Datadog",
"-",
"friendly",
"name"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/cacti/datadog_checks/cacti/cacti.py#L216-L229 | train | Format a cacti metric name into a Datadog - friendly name | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_base/datadog_checks/base/checks/win/wmi/counter_type.py | calculate_perf_100nsec_timer | def calculate_perf_100nsec_timer(previous, current, property_name):
"""
PERF_100NSEC_TIMER
https://technet.microsoft.com/en-us/library/cc728274(v=ws.10).aspx
"""
n0 = previous[property_name]
n1 = current[property_name]
d0 = previous["Timestamp_Sys100NS"]
d1 = current["Timestamp_Sys100NS... | python | def calculate_perf_100nsec_timer(previous, current, property_name):
"""
PERF_100NSEC_TIMER
https://technet.microsoft.com/en-us/library/cc728274(v=ws.10).aspx
"""
n0 = previous[property_name]
n1 = current[property_name]
d0 = previous["Timestamp_Sys100NS"]
d1 = current["Timestamp_Sys100NS... | [
"def",
"calculate_perf_100nsec_timer",
"(",
"previous",
",",
"current",
",",
"property_name",
")",
":",
"n0",
"=",
"previous",
"[",
"property_name",
"]",
"n1",
"=",
"current",
"[",
"property_name",
"]",
"d0",
"=",
"previous",
"[",
"\"Timestamp_Sys100NS\"",
"]",
... | PERF_100NSEC_TIMER
https://technet.microsoft.com/en-us/library/cc728274(v=ws.10).aspx | [
"PERF_100NSEC_TIMER"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/checks/win/wmi/counter_type.py#L96-L110 | train | Calculates the percentage of elapsed time between two previous and current objects. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_base/datadog_checks/base/checks/win/wmi/counter_type.py | calculate_perf_counter_bulk_count | def calculate_perf_counter_bulk_count(previous, current, property_name):
"""
PERF_COUNTER_BULK_COUNT
https://technet.microsoft.com/en-us/library/cc757486(v=ws.10).aspx
"""
n0 = previous[property_name]
n1 = current[property_name]
d0 = previous["Timestamp_Sys100NS"]
d1 = current["Timestam... | python | def calculate_perf_counter_bulk_count(previous, current, property_name):
"""
PERF_COUNTER_BULK_COUNT
https://technet.microsoft.com/en-us/library/cc757486(v=ws.10).aspx
"""
n0 = previous[property_name]
n1 = current[property_name]
d0 = previous["Timestamp_Sys100NS"]
d1 = current["Timestam... | [
"def",
"calculate_perf_counter_bulk_count",
"(",
"previous",
",",
"current",
",",
"property_name",
")",
":",
"n0",
"=",
"previous",
"[",
"property_name",
"]",
"n1",
"=",
"current",
"[",
"property_name",
"]",
"d0",
"=",
"previous",
"[",
"\"Timestamp_Sys100NS\"",
... | PERF_COUNTER_BULK_COUNT
https://technet.microsoft.com/en-us/library/cc757486(v=ws.10).aspx | [
"PERF_COUNTER_BULK_COUNT"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/checks/win/wmi/counter_type.py#L114-L129 | train | Calculates the bulk count of a given property in a given previous object. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | datadog_checks_base/datadog_checks/base/checks/win/wmi/counter_type.py | calculate_perf_counter_100ns_queuelen_type | def calculate_perf_counter_100ns_queuelen_type(previous, current, property_name):
"""
PERF_COUNTER_100NS_QUEUELEN_TYPE
Average length of a queue to a resource over time in 100 nanosecond units.
https://msdn.microsoft.com/en-us/library/aa392905(v=vs.85).aspx
Formula (n1 - n0) / (d1 - d0)
"""
... | python | def calculate_perf_counter_100ns_queuelen_type(previous, current, property_name):
"""
PERF_COUNTER_100NS_QUEUELEN_TYPE
Average length of a queue to a resource over time in 100 nanosecond units.
https://msdn.microsoft.com/en-us/library/aa392905(v=vs.85).aspx
Formula (n1 - n0) / (d1 - d0)
"""
... | [
"def",
"calculate_perf_counter_100ns_queuelen_type",
"(",
"previous",
",",
"current",
",",
"property_name",
")",
":",
"n0",
"=",
"previous",
"[",
"property_name",
"]",
"n1",
"=",
"current",
"[",
"property_name",
"]",
"d0",
"=",
"previous",
"[",
"\"Timestamp_Sys100... | PERF_COUNTER_100NS_QUEUELEN_TYPE
Average length of a queue to a resource over time in 100 nanosecond units.
https://msdn.microsoft.com/en-us/library/aa392905(v=vs.85).aspx
Formula (n1 - n0) / (d1 - d0) | [
"PERF_COUNTER_100NS_QUEUELEN_TYPE"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/datadog_checks_base/datadog_checks/base/checks/win/wmi/counter_type.py#L184-L201 | train | Calculates the 100ns queuelen type of the queue. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql._server_known | def _server_known(cls, host, port):
"""
Return whether the hostname and port combination was already seen
"""
with PostgreSql._known_servers_lock:
return (host, port) in PostgreSql._known_servers | python | def _server_known(cls, host, port):
"""
Return whether the hostname and port combination was already seen
"""
with PostgreSql._known_servers_lock:
return (host, port) in PostgreSql._known_servers | [
"def",
"_server_known",
"(",
"cls",
",",
"host",
",",
"port",
")",
":",
"with",
"PostgreSql",
".",
"_known_servers_lock",
":",
"return",
"(",
"host",
",",
"port",
")",
"in",
"PostgreSql",
".",
"_known_servers"
] | Return whether the hostname and port combination was already seen | [
"Return",
"whether",
"the",
"hostname",
"and",
"port",
"combination",
"was",
"already",
"seen"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L377-L382 | train | Return whether the hostname and port combination is already seen. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql._set_server_known | def _set_server_known(cls, host, port):
"""
Store the host/port combination for this server
"""
with PostgreSql._known_servers_lock:
PostgreSql._known_servers.add((host, port)) | python | def _set_server_known(cls, host, port):
"""
Store the host/port combination for this server
"""
with PostgreSql._known_servers_lock:
PostgreSql._known_servers.add((host, port)) | [
"def",
"_set_server_known",
"(",
"cls",
",",
"host",
",",
"port",
")",
":",
"with",
"PostgreSql",
".",
"_known_servers_lock",
":",
"PostgreSql",
".",
"_known_servers",
".",
"add",
"(",
"(",
"host",
",",
"port",
")",
")"
] | Store the host/port combination for this server | [
"Store",
"the",
"host",
"/",
"port",
"combination",
"for",
"this",
"server"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L385-L390 | train | Set the host and port combination for this server. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql._get_instance_metrics | def _get_instance_metrics(self, key, db, database_size_metrics, collect_default_db):
"""
Add NEWER_92_METRICS to the default set of COMMON_METRICS when server
version is 9.2 or later.
Store the list of metrics in the check instance to avoid rebuilding it at
every collection cycl... | python | def _get_instance_metrics(self, key, db, database_size_metrics, collect_default_db):
"""
Add NEWER_92_METRICS to the default set of COMMON_METRICS when server
version is 9.2 or later.
Store the list of metrics in the check instance to avoid rebuilding it at
every collection cycl... | [
"def",
"_get_instance_metrics",
"(",
"self",
",",
"key",
",",
"db",
",",
"database_size_metrics",
",",
"collect_default_db",
")",
":",
"metrics",
"=",
"self",
".",
"instance_metrics",
".",
"get",
"(",
"key",
")",
"if",
"metrics",
"is",
"None",
":",
"host",
... | Add NEWER_92_METRICS to the default set of COMMON_METRICS when server
version is 9.2 or later.
Store the list of metrics in the check instance to avoid rebuilding it at
every collection cycle.
In case we have multiple instances pointing to the same postgres server
monitoring di... | [
"Add",
"NEWER_92_METRICS",
"to",
"the",
"default",
"set",
"of",
"COMMON_METRICS",
"when",
"server",
"version",
"is",
"9",
".",
"2",
"or",
"later",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L467-L528 | train | Get the list of metrics for the current check instance. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql._get_bgw_metrics | def _get_bgw_metrics(self, key, db):
"""Use either COMMON_BGW_METRICS or COMMON_BGW_METRICS + NEWER_92_BGW_METRICS
depending on the postgres version.
Uses a dictionnary to save the result for each instance
"""
# Extended 9.2+ metrics if needed
metrics = self.bgw_metrics.g... | python | def _get_bgw_metrics(self, key, db):
"""Use either COMMON_BGW_METRICS or COMMON_BGW_METRICS + NEWER_92_BGW_METRICS
depending on the postgres version.
Uses a dictionnary to save the result for each instance
"""
# Extended 9.2+ metrics if needed
metrics = self.bgw_metrics.g... | [
"def",
"_get_bgw_metrics",
"(",
"self",
",",
"key",
",",
"db",
")",
":",
"# Extended 9.2+ metrics if needed",
"metrics",
"=",
"self",
".",
"bgw_metrics",
".",
"get",
"(",
"key",
")",
"if",
"metrics",
"is",
"None",
":",
"# Hack to make sure that if we have multiple... | Use either COMMON_BGW_METRICS or COMMON_BGW_METRICS + NEWER_92_BGW_METRICS
depending on the postgres version.
Uses a dictionnary to save the result for each instance | [
"Use",
"either",
"COMMON_BGW_METRICS",
"or",
"COMMON_BGW_METRICS",
"+",
"NEWER_92_BGW_METRICS",
"depending",
"on",
"the",
"postgres",
"version",
".",
"Uses",
"a",
"dictionnary",
"to",
"save",
"the",
"result",
"for",
"each",
"instance"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L530-L564 | train | Get the bgw metrics for the given key. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql._get_archiver_metrics | def _get_archiver_metrics(self, key, db):
"""Use COMMON_ARCHIVER_METRICS to read from pg_stat_archiver as
defined in 9.4 (first version to have this table).
Uses a dictionary to save the result for each instance
"""
# While there's only one set for now, prepare for future additio... | python | def _get_archiver_metrics(self, key, db):
"""Use COMMON_ARCHIVER_METRICS to read from pg_stat_archiver as
defined in 9.4 (first version to have this table).
Uses a dictionary to save the result for each instance
"""
# While there's only one set for now, prepare for future additio... | [
"def",
"_get_archiver_metrics",
"(",
"self",
",",
"key",
",",
"db",
")",
":",
"# While there's only one set for now, prepare for future additions to",
"# the table, mirroring _get_bgw_metrics()",
"metrics",
"=",
"self",
".",
"archiver_metrics",
".",
"get",
"(",
"key",
")",
... | Use COMMON_ARCHIVER_METRICS to read from pg_stat_archiver as
defined in 9.4 (first version to have this table).
Uses a dictionary to save the result for each instance | [
"Use",
"COMMON_ARCHIVER_METRICS",
"to",
"read",
"from",
"pg_stat_archiver",
"as",
"defined",
"in",
"9",
".",
"4",
"(",
"first",
"version",
"to",
"have",
"this",
"table",
")",
".",
"Uses",
"a",
"dictionary",
"to",
"save",
"the",
"result",
"for",
"each",
"in... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L566-L594 | train | Get the archiver metrics for the given key. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql._get_replication_metrics | def _get_replication_metrics(self, key, db):
""" Use either REPLICATION_METRICS_10, REPLICATION_METRICS_9_1, or
REPLICATION_METRICS_9_1 + REPLICATION_METRICS_9_2, depending on the
postgres version.
Uses a dictionnary to save the result for each instance
"""
metrics = self... | python | def _get_replication_metrics(self, key, db):
""" Use either REPLICATION_METRICS_10, REPLICATION_METRICS_9_1, or
REPLICATION_METRICS_9_1 + REPLICATION_METRICS_9_2, depending on the
postgres version.
Uses a dictionnary to save the result for each instance
"""
metrics = self... | [
"def",
"_get_replication_metrics",
"(",
"self",
",",
"key",
",",
"db",
")",
":",
"metrics",
"=",
"self",
".",
"replication_metrics",
".",
"get",
"(",
"key",
")",
"if",
"self",
".",
"_is_10_or_above",
"(",
"key",
",",
"db",
")",
"and",
"metrics",
"is",
... | Use either REPLICATION_METRICS_10, REPLICATION_METRICS_9_1, or
REPLICATION_METRICS_9_1 + REPLICATION_METRICS_9_2, depending on the
postgres version.
Uses a dictionnary to save the result for each instance | [
"Use",
"either",
"REPLICATION_METRICS_10",
"REPLICATION_METRICS_9_1",
"or",
"REPLICATION_METRICS_9_1",
"+",
"REPLICATION_METRICS_9_2",
"depending",
"on",
"the",
"postgres",
"version",
".",
"Uses",
"a",
"dictionnary",
"to",
"save",
"the",
"result",
"for",
"each",
"instan... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L596-L611 | train | Get the replication metrics for the given key. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql._get_activity_metrics | def _get_activity_metrics(self, key, db):
""" Use ACTIVITY_METRICS_LT_8_3 or ACTIVITY_METRICS_8_3 or ACTIVITY_METRICS_9_2
depending on the postgres version in conjunction with ACTIVITY_QUERY_10 or ACTIVITY_QUERY_LT_10.
Uses a dictionnary to save the result for each instance
"""
m... | python | def _get_activity_metrics(self, key, db):
""" Use ACTIVITY_METRICS_LT_8_3 or ACTIVITY_METRICS_8_3 or ACTIVITY_METRICS_9_2
depending on the postgres version in conjunction with ACTIVITY_QUERY_10 or ACTIVITY_QUERY_LT_10.
Uses a dictionnary to save the result for each instance
"""
m... | [
"def",
"_get_activity_metrics",
"(",
"self",
",",
"key",
",",
"db",
")",
":",
"metrics_data",
"=",
"self",
".",
"activity_metrics",
".",
"get",
"(",
"key",
")",
"if",
"metrics_data",
"is",
"None",
":",
"query",
"=",
"self",
".",
"ACTIVITY_QUERY_10",
"if",
... | Use ACTIVITY_METRICS_LT_8_3 or ACTIVITY_METRICS_8_3 or ACTIVITY_METRICS_9_2
depending on the postgres version in conjunction with ACTIVITY_QUERY_10 or ACTIVITY_QUERY_LT_10.
Uses a dictionnary to save the result for each instance | [
"Use",
"ACTIVITY_METRICS_LT_8_3",
"or",
"ACTIVITY_METRICS_8_3",
"or",
"ACTIVITY_METRICS_9_2",
"depending",
"on",
"the",
"postgres",
"version",
"in",
"conjunction",
"with",
"ACTIVITY_QUERY_10",
"or",
"ACTIVITY_QUERY_LT_10",
".",
"Uses",
"a",
"dictionnary",
"to",
"save",
... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L613-L637 | train | Get the activity metrics for the specified instance. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql._build_relations_config | def _build_relations_config(self, yamlconfig):
"""Builds a dictionary from relations configuration while maintaining compatibility
"""
config = {}
for element in yamlconfig:
if isinstance(element, str):
config[element] = {'relation_name': element, 'schemas': [... | python | def _build_relations_config(self, yamlconfig):
"""Builds a dictionary from relations configuration while maintaining compatibility
"""
config = {}
for element in yamlconfig:
if isinstance(element, str):
config[element] = {'relation_name': element, 'schemas': [... | [
"def",
"_build_relations_config",
"(",
"self",
",",
"yamlconfig",
")",
":",
"config",
"=",
"{",
"}",
"for",
"element",
"in",
"yamlconfig",
":",
"if",
"isinstance",
"(",
"element",
",",
"str",
")",
":",
"config",
"[",
"element",
"]",
"=",
"{",
"'relation_... | Builds a dictionary from relations configuration while maintaining compatibility | [
"Builds",
"a",
"dictionary",
"from",
"relations",
"configuration",
"while",
"maintaining",
"compatibility"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L639-L657 | train | Builds a dictionary from relations configuration while maintaining compatibility
| Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql._collect_stats | def _collect_stats(
self,
key,
db,
instance_tags,
relations,
custom_metrics,
collect_function_metrics,
collect_count_metrics,
collect_activity_metrics,
collect_database_size_metrics,
collect_default_db,
interface_error,
... | python | def _collect_stats(
self,
key,
db,
instance_tags,
relations,
custom_metrics,
collect_function_metrics,
collect_count_metrics,
collect_activity_metrics,
collect_database_size_metrics,
collect_default_db,
interface_error,
... | [
"def",
"_collect_stats",
"(",
"self",
",",
"key",
",",
"db",
",",
"instance_tags",
",",
"relations",
",",
"custom_metrics",
",",
"collect_function_metrics",
",",
"collect_count_metrics",
",",
"collect_activity_metrics",
",",
"collect_database_size_metrics",
",",
"collec... | Query pg_stat_* for various metrics
If relations is not an empty list, gather per-relation metrics
on top of that.
If custom_metrics is not an empty list, gather custom metrics defined in postgres.yaml | [
"Query",
"pg_stat_",
"*",
"for",
"various",
"metrics",
"If",
"relations",
"is",
"not",
"an",
"empty",
"list",
"gather",
"per",
"-",
"relation",
"metrics",
"on",
"top",
"of",
"that",
".",
"If",
"custom_metrics",
"is",
"not",
"an",
"empty",
"list",
"gather",... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L759-L834 | train | Query pg_stat_* for various metrics. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql.get_connection | def get_connection(self, key, host, port, user, password, dbname, ssl, connect_fct, tags, use_cached=True):
"""Get and memoize connections to instances"""
if key in self.dbs and use_cached:
return self.dbs[key]
elif host != "" and user != "":
try:
if host... | python | def get_connection(self, key, host, port, user, password, dbname, ssl, connect_fct, tags, use_cached=True):
"""Get and memoize connections to instances"""
if key in self.dbs and use_cached:
return self.dbs[key]
elif host != "" and user != "":
try:
if host... | [
"def",
"get_connection",
"(",
"self",
",",
"key",
",",
"host",
",",
"port",
",",
"user",
",",
"password",
",",
"dbname",
",",
"ssl",
",",
"connect_fct",
",",
"tags",
",",
"use_cached",
"=",
"True",
")",
":",
"if",
"key",
"in",
"self",
".",
"dbs",
"... | Get and memoize connections to instances | [
"Get",
"and",
"memoize",
"connections",
"to",
"instances"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L843-L876 | train | Get and memoize connections to instances | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | postgres/datadog_checks/postgres/postgres.py | PostgreSql._get_custom_queries | def _get_custom_queries(self, db, tags, custom_queries, programming_error):
"""
Given a list of custom_queries, execute each query and parse the result for metrics
"""
for custom_query in custom_queries:
metric_prefix = custom_query.get('metric_prefix')
if not met... | python | def _get_custom_queries(self, db, tags, custom_queries, programming_error):
"""
Given a list of custom_queries, execute each query and parse the result for metrics
"""
for custom_query in custom_queries:
metric_prefix = custom_query.get('metric_prefix')
if not met... | [
"def",
"_get_custom_queries",
"(",
"self",
",",
"db",
",",
"tags",
",",
"custom_queries",
",",
"programming_error",
")",
":",
"for",
"custom_query",
"in",
"custom_queries",
":",
"metric_prefix",
"=",
"custom_query",
".",
"get",
"(",
"'metric_prefix'",
")",
"if",... | Given a list of custom_queries, execute each query and parse the result for metrics | [
"Given",
"a",
"list",
"of",
"custom_queries",
"execute",
"each",
"query",
"and",
"parse",
"the",
"result",
"for",
"metrics"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/postgres/datadog_checks/postgres/postgres.py#L878-L970 | train | Execute each query and parse the result for metrics | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | ibm_was/datadog_checks/ibm_was/ibm_was.py | IbmWasCheck.process_stats | def process_stats(self, stats, prefix, metric_categories, nested_tags, tags, recursion_level=0):
"""
The XML will have Stat Nodes and Nodes that contain the metrics themselves
This code recursively goes through each Stat Node to properly setup tags
where each Stat will have a different t... | python | def process_stats(self, stats, prefix, metric_categories, nested_tags, tags, recursion_level=0):
"""
The XML will have Stat Nodes and Nodes that contain the metrics themselves
This code recursively goes through each Stat Node to properly setup tags
where each Stat will have a different t... | [
"def",
"process_stats",
"(",
"self",
",",
"stats",
",",
"prefix",
",",
"metric_categories",
",",
"nested_tags",
",",
"tags",
",",
"recursion_level",
"=",
"0",
")",
":",
"for",
"child",
"in",
"stats",
":",
"if",
"child",
".",
"tag",
"in",
"metrics",
".",
... | The XML will have Stat Nodes and Nodes that contain the metrics themselves
This code recursively goes through each Stat Node to properly setup tags
where each Stat will have a different tag key depending on the context. | [
"The",
"XML",
"will",
"have",
"Stat",
"Nodes",
"and",
"Nodes",
"that",
"contain",
"the",
"metrics",
"themselves",
"This",
"code",
"recursively",
"goes",
"through",
"each",
"Stat",
"Node",
"to",
"properly",
"setup",
"tags",
"where",
"each",
"Stat",
"will",
"h... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/ibm_was/datadog_checks/ibm_was/ibm_was.py#L81-L92 | train | This function processes the XML stats and submits the metrics to the tags list. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/monitoring.py | _to_micros | def _to_micros(dur):
"""Convert duration 'dur' to microseconds."""
if hasattr(dur, 'total_seconds'):
return int(dur.total_seconds() * 10e5)
# Python 2.6
return dur.microseconds + (dur.seconds + dur.days * 24 * 3600) * 1000000 | python | def _to_micros(dur):
"""Convert duration 'dur' to microseconds."""
if hasattr(dur, 'total_seconds'):
return int(dur.total_seconds() * 10e5)
# Python 2.6
return dur.microseconds + (dur.seconds + dur.days * 24 * 3600) * 1000000 | [
"def",
"_to_micros",
"(",
"dur",
")",
":",
"if",
"hasattr",
"(",
"dur",
",",
"'total_seconds'",
")",
":",
"return",
"int",
"(",
"dur",
".",
"total_seconds",
"(",
")",
"*",
"10e5",
")",
"# Python 2.6",
"return",
"dur",
".",
"microseconds",
"+",
"(",
"du... | Convert duration 'dur' to microseconds. | [
"Convert",
"duration",
"dur",
"to",
"microseconds",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/monitoring.py#L283-L288 | train | Convert duration 'dur' to microseconds. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/monitoring.py | _validate_event_listeners | def _validate_event_listeners(option, listeners):
"""Validate event listeners"""
if not isinstance(listeners, Sequence):
raise TypeError("%s must be a list or tuple" % (option,))
for listener in listeners:
if not isinstance(listener, _EventListener):
raise TypeError("Listeners fo... | python | def _validate_event_listeners(option, listeners):
"""Validate event listeners"""
if not isinstance(listeners, Sequence):
raise TypeError("%s must be a list or tuple" % (option,))
for listener in listeners:
if not isinstance(listener, _EventListener):
raise TypeError("Listeners fo... | [
"def",
"_validate_event_listeners",
"(",
"option",
",",
"listeners",
")",
":",
"if",
"not",
"isinstance",
"(",
"listeners",
",",
"Sequence",
")",
":",
"raise",
"TypeError",
"(",
"\"%s must be a list or tuple\"",
"%",
"(",
"option",
",",
")",
")",
"for",
"liste... | Validate event listeners | [
"Validate",
"event",
"listeners"
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/monitoring.py#L291-L300 | train | Validate event listeners. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
DataDog/integrations-core | tokumx/datadog_checks/tokumx/vendor/pymongo/monitoring.py | register | def register(listener):
"""Register a global event listener.
:Parameters:
- `listener`: A subclasses of :class:`CommandListener`,
:class:`ServerHeartbeatListener`, :class:`ServerListener`, or
:class:`TopologyListener`.
"""
if not isinstance(listener, _EventListener):
raise... | python | def register(listener):
"""Register a global event listener.
:Parameters:
- `listener`: A subclasses of :class:`CommandListener`,
:class:`ServerHeartbeatListener`, :class:`ServerListener`, or
:class:`TopologyListener`.
"""
if not isinstance(listener, _EventListener):
raise... | [
"def",
"register",
"(",
"listener",
")",
":",
"if",
"not",
"isinstance",
"(",
"listener",
",",
"_EventListener",
")",
":",
"raise",
"TypeError",
"(",
"\"Listeners for %s must be either a \"",
"\"CommandListener, ServerHeartbeatListener, \"",
"\"ServerListener, or TopologyList... | Register a global event listener.
:Parameters:
- `listener`: A subclasses of :class:`CommandListener`,
:class:`ServerHeartbeatListener`, :class:`ServerListener`, or
:class:`TopologyListener`. | [
"Register",
"a",
"global",
"event",
"listener",
"."
] | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd | https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/tokumx/datadog_checks/tokumx/vendor/pymongo/monitoring.py#L303-L322 | train | Registers a global event listener. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.