datadog-api-client-python
This repository contains a Python API client for the Datadog API.
Requirements
Building and using the API client library requires Python 3.7+.
Installation
To install the API client library, simply execute:
pip install datadog-api-clientGetting Started
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)Authentication
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>"Unstable Endpoints
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>"] = Truewhere <OperationName> is the name of the method used to interact with that endpoint. For example: list_log_indexes, or get_logs_index
Changing Server
When talking to a different server, like the eu instance, change the server_variables on your configuration object:
configuration.server_variables["site"] = "datadoghq.eu"Disable compressed payloads
If you want to disable GZIP compressed responses, set the compress flag
on your configuration object:
configuration.compress = FalseEnable requests logging
If you want to enable requests logging, set the debug flag on your configuration object:
configuration.debug = TrueThreads support
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 import dashboards_api
configuration = Configuration()
with ThreadedApiClient(configuration) as api_client:
api_instance = dashboards_api.DashboardsApi(api_client)
result = api_instance.list_dashboards()
dashboards = result.get()
print(dashboards)Asyncio support
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 import dashboards_api
async def main():
configuration = Configuration()
async with AsyncApiClient(configuration) as api_client:
api_instance = dashboards_api.DashboardsApi(api_client)
dashbooards = await api_instance.list_dashboards()
print(dashbooards)
asyncio.run(main())Pagination
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
Documentation for API endpoints and models are available on readthedocs.
Documentation for Authorization
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"