All URIs are relative to https://localhost
| Method | HTTP request | Description |
|---|---|---|
| query_api | GET /api/v2/chart/api | Perform a charting query against Wavefront servers that returns the appropriate points in the specified time window and granularity |
| query_raw | GET /api/v2/chart/raw | Perform a raw data query against Wavefront servers that returns second granularity points grouped by tags |
QueryResult query_api(q, s, g, n=n, e=e, p=p, i=i, auto_events=auto_events, summarization=summarization, list_mode=list_mode, strict=strict, include_obsolete_metrics=include_obsolete_metrics, sorted=sorted)
Perform a charting query against Wavefront servers that returns the appropriate points in the specified time window and granularity
Long time spans and small granularities can take a long time to calculate
from __future__ import print_function
import time
import wavefront_api_client
from wavefront_api_client.rest import ApiException
from pprint import pprint
# Configure API key authorization: api_key
configuration = wavefront_api_client.Configuration()
configuration.api_key['X-AUTH-TOKEN'] = 'YOUR_API_KEY'
# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['X-AUTH-TOKEN'] = 'Bearer'
# create an instance of the API class
api_instance = wavefront_api_client.QueryApi(wavefront_api_client.ApiClient(configuration))
q = 'q_example' # str | the query expression to execute
s = 's_example' # str | the start time of the query window in epoch milliseconds
g = 'g_example' # str | the granularity of the points returned
n = 'n_example' # str | name used to identify the query (optional)
e = 'e_example' # str | the end time of the query window in epoch milliseconds (null to use now) (optional)
p = 'p_example' # str | the approximate maximum number of points to return (may not limit number of points exactly) (optional)
i = true # bool | whether series with only points that are outside of the query window will be returned (defaults to true) (optional)
auto_events = true # bool | whether events for sources included in the query will be automatically returned by the query (optional)
summarization = 'summarization_example' # str | summarization strategy to use when bucketing points together (optional)
list_mode = true # bool | retrieve events more optimally displayed for a list (optional)
strict = true # bool | do not return points outside the query window [s;e), defaults to false (optional)
include_obsolete_metrics = true # bool | include metrics that have not been reporting recently, defaults to false (optional)
sorted = false # bool | sorts the output so that returned series are in order, defaults to false (optional) (default to false)
try:
# Perform a charting query against Wavefront servers that returns the appropriate points in the specified time window and granularity
api_response = api_instance.query_api(q, s, g, n=n, e=e, p=p, i=i, auto_events=auto_events, summarization=summarization, list_mode=list_mode, strict=strict, include_obsolete_metrics=include_obsolete_metrics, sorted=sorted)
pprint(api_response)
except ApiException as e:
print("Exception when calling QueryApi->query_api: %s\n" % e)| Name | Type | Description | Notes |
|---|---|---|---|
| q | str | the query expression to execute | |
| s | str | the start time of the query window in epoch milliseconds | |
| g | str | the granularity of the points returned | |
| n | str | name used to identify the query | [optional] |
| e | str | the end time of the query window in epoch milliseconds (null to use now) | [optional] |
| p | str | the approximate maximum number of points to return (may not limit number of points exactly) | [optional] |
| i | bool | whether series with only points that are outside of the query window will be returned (defaults to true) | [optional] |
| auto_events | bool | whether events for sources included in the query will be automatically returned by the query | [optional] |
| summarization | str | summarization strategy to use when bucketing points together | [optional] |
| list_mode | bool | retrieve events more optimally displayed for a list | [optional] |
| strict | bool | do not return points outside the query window [s;e), defaults to false | [optional] |
| include_obsolete_metrics | bool | include metrics that have not been reporting recently, defaults to false | [optional] |
| sorted | bool | sorts the output so that returned series are in order, defaults to false | [optional] [default to false] |
- Content-Type: Not defined
- Accept: application/json, application/x-javascript; charset=UTF-8, application/javascript; charset=UTF-8
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list[RawTimeseries] query_raw(metric, host=host, source=source, start_time=start_time, end_time=end_time)
Perform a raw data query against Wavefront servers that returns second granularity points grouped by tags
An API to check if ingested points are as expected. Points ingested within a single second are averaged when returned.
from __future__ import print_function
import time
import wavefront_api_client
from wavefront_api_client.rest import ApiException
from pprint import pprint
# Configure API key authorization: api_key
configuration = wavefront_api_client.Configuration()
configuration.api_key['X-AUTH-TOKEN'] = 'YOUR_API_KEY'
# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['X-AUTH-TOKEN'] = 'Bearer'
# create an instance of the API class
api_instance = wavefront_api_client.QueryApi(wavefront_api_client.ApiClient(configuration))
metric = 'metric_example' # str | metric to query ingested points for (cannot contain wildcards)
host = 'host_example' # str | host to query ingested points for (cannot contain wildcards). host or source is equivalent, only one should be used. (optional)
source = 'source_example' # str | source to query ingested points for (cannot contain wildcards). host or source is equivalent, only one should be used. (optional)
start_time = 789 # int | start time in epoch milliseconds (cannot be more than a day in the past) null to use an hour before endTime (optional)
end_time = 789 # int | end time in epoch milliseconds (cannot be more than a day in the past) null to use now (optional)
try:
# Perform a raw data query against Wavefront servers that returns second granularity points grouped by tags
api_response = api_instance.query_raw(metric, host=host, source=source, start_time=start_time, end_time=end_time)
pprint(api_response)
except ApiException as e:
print("Exception when calling QueryApi->query_raw: %s\n" % e)| Name | Type | Description | Notes |
|---|---|---|---|
| metric | str | metric to query ingested points for (cannot contain wildcards) | |
| host | str | host to query ingested points for (cannot contain wildcards). host or source is equivalent, only one should be used. | [optional] |
| source | str | source to query ingested points for (cannot contain wildcards). host or source is equivalent, only one should be used. | [optional] |
| start_time | int | start time in epoch milliseconds (cannot be more than a day in the past) null to use an hour before endTime | [optional] |
| end_time | int | end time in epoch milliseconds (cannot be more than a day in the past) null to use now | [optional] |
- Content-Type: Not defined
- Accept: application/json
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