This repository contains a Python API client for the Datadog API.
Building and using the API client library requires Python 3.7+.
To install the API client library, simply execute:
pip install datadog-api-client
Please follow the installation instruction and execute the following Python code:
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v1.api.monitors_api import MonitorsApi
from datadog_api_client.v1.model.monitor import Monitor
from datadog_api_client.v1.model.monitor_type import MonitorType
body = Monitor(
name="example",
type=MonitorType("log alert"),
query='logs("service:foo AND type:error").index("main").rollup("count").by("source").last("5m") > 2',
message="some message Notify: @hipchat-channel",
tags=["test:example", "env:ci"],
priority=3,
)
configuration = Configuration()
with ApiClient(configuration) as api_client:
api_instance = MonitorsApi(api_client)
response = api_instance.create_monitor(body=body)
print(response)
By default the library will use the DD_API_KEY
and DD_APP_KEY
environment variables to authenticate against the Datadog API.
To provide your own set of credentials, you need to set some keys on the configuration:
configuration.api_key["apiKeyAuth"] = "<API KEY>"
configuration.api_key["appKeyAuth"] = "<APPLICATION KEY>"
This client includes access to Datadog API endpoints while they are in an unstable state and may undergo breaking changes. An extra configuration step is required to enable these endpoints:
configuration.unstable_operations["<OperationName>"] = True
where <OperationName>
is the name of the method used to interact with that endpoint. For example: list_log_indexes
, or get_logs_index
When talking to a different server, like the eu
instance, change the server_variables
on your configuration object:
configuration.server_variables["site"] = "datadoghq.eu"
If you want to disable GZIP compressed responses, set the compress
flag
on your configuration object:
configuration.compress = False
If you want to enable requests logging, set the debug
flag on your configuration object:
configuration.debug = True
If you want to enable retry when getting status code 429
rate-limited, set enable_retry
to True
configuration.enable_retry = True
The default max retry is 3
, you can change it with max_retries
configuration.max_retries = 5
You can configure the client to use proxy by setting the proxy
key on configuration object:
configuration.proxy = "http://127.0.0.1:80"
You can run API calls in a thread by using ThreadedApiClient
in place of ApiClient
. API calls will then
return a AsyncResult
instance on which you can call get to retrieve the result:
from datadog_api_client import Configuration, ThreadedApiClient
from datadog_api_client.v1.api.dashboards_api import DashboardsApi
configuration = Configuration()
with ThreadedApiClient(configuration) as api_client:
api_instance = DashboardsApi(api_client)
result = api_instance.list_dashboards()
dashboards = result.get()
print(dashboards)
The library supports asynchronous operations when using AsyncApiClient
for the transport. When that client is used,
the API methods will then return coroutines that you can wait for.
To make async support available, you need to install the extra async
qualifiers during installation: pip install datadog-api-client[async]
.
import asyncio
from datadog_api_client import Configuration, AsyncApiClient
from datadog_api_client.v1.api.dashboards_api import DashboardsApi
async def main():
configuration = Configuration()
async with AsyncApiClient(configuration) as api_client:
api_instance = DashboardsApi(api_client)
dashboards = await api_instance.list_dashboards()
print(dashboards)
asyncio.run(main())
Several listing operations have a pagination method to help consume all the items available. For example, to retrieve all your incidents:
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.incidents_api import IncidentsApi
configuration = Configuration()
configuration.unstable_operations["list_incidents"] = True
with ApiClient(configuration) as api_client:
api_instance = IncidentsApi(api_client)
for incident in api_instance.list_incidents_with_pagination():
print(incident.id)
Documentation for API endpoints and models are available on readthedocs.
Authenticate with the API by providing your API and Application keys in the configuration:
configuration.api_key["apiKeyAuth"] = "YOUR_API_KEY"
configuration.api_key["appKeyAuth"] = "YOUR_APPLICATION_KEY"