Splunk Enterprise SDK for Python

The Splunk Enterprise Software Development Kit (SDK) for Python contains library code designed to enable developers to build applications using the Splunk platform.

Splunk is a search engine and analytic environment that uses a distributed map-reduce architecture to efficiently index, search, and process large time-varying data sets.

Getting started

Requirements

Python compatibility

Splunk Enterprise SDK for Python is tested only with Python 3.7, 3.9 and 3.13. Latest version is always recommended.

Splunk Enterprise

This SDK is only tested with Splunk versions supported in the Splunk Software Support Policy

Go here to get Splunk Enterprise.

For more information, see the Splunk Enterprise Installation Manual.

Installing the SDK

uv is our tool of choice for development. Usually that means creating a project with uv init and installing the SDK with uv add splunk-sdk. When in doubt, consult uv docs.

If you prefer not using uv, the standard Python package installation method still works:

python -m venv .venv
source .venv/bin/activate
python -m pip install splunk-sdk

Create an .env file (optional)

To connect to Splunk Enterprise, many of the SDK examples and unit tests take command-line arguments that specify values for the host, port, and authentication. For convenience during development, you can store these arguments as key-value pairs in a .env file.

A file called .env.template exists in the root of this repository. Duplicate it as .env, then adjust it to your match your environment.

WARNING: The .env file isn't part of the Splunk platform. This is not the place for production credentials!

SDK usage examples

The easiest and most effective way of learning how to use this library should be reading through the apps in our test suite, as well as the splunk-app-examples repository. They show how to programmatically interact with the Splunk platform in a variety of scenarios - from basic metadata retrieval, one-shot searching and managing saved searches to building complete applications with modular inputs and custom search commands.

For details, see the examples using the Splunk Enterprise SDK for Python on the Splunk Developer Portal, as well as the Splunk Enterprise SDK for Python Reference

Connecting to a Splunk Enterprise instance

Using a username/password combo

import splunklib.client as client

service = client.connect(host=<HOST_URL>, username=<USERNAME>, password=<PASSWORD>, autologin=True)

Using a bearer token

import splunklib.client as client

service = client.connect(host=<HOST_URL>, splunkToken=<BEARER_TOKEN>, autologin=True)

Using a session key

import splunklib.client as client

service = client.connect(host=<HOST_URL>, token=<SESSION_KEY>, autologin=True)

Customization

When working with custom search commands such as Custom Streaming Commands or Custom Generating Commands, we may need to add new fields to the records based on certain conditions. Structural changes like this may not be preserved. If you're having issues with field retention, make sure to use add_field(record, fieldname, value) method from SearchCommand to add a new field and value to the record.

Do

class CustomStreamingCommand(StreamingCommand):
    def stream(self, records):
        for index, record in enumerate(records):
            if index % 1 == 0:
                self.add_field(record, "odd_record", "true")
            yield record

Don't

class CustomStreamingCommand(StreamingCommand):
    def stream(self, records):
        for index, record in enumerate(records):
            if index % 1 == 0:
                record["odd_record"] = "true"
            yield record

Customization for Generating Custom Search Command

• Generating Custom Search Command is used to generate events using SDK code.
• Make sure to use gen_record() method from SearchCommand to add a new record and pass event data as comma-separated key=value pairs (mentioned in below example).

Do

@Configuration()
class GeneratorTest(GeneratingCommand):
    def generate(self):
        yield self.gen_record(_time=time.time(), one=1)
        yield self.gen_record(_time=time.time(), two=2)

Don't

@Configuration()
class GeneratorTest(GeneratingCommand):
    def generate(self):
        yield {'_time': time.time(), 'one': 1}
        yield {'_time': time.time(), 'two': 2}

Access metadata of Modular Inputs app example

• In stream_events() one can access modular input app metadata from InputDefinition object

• See GitHub Commit Modular Input App example for reference.

  def stream_events(self, inputs, ew):
    # [...] other code
  
    # Access metadata (like server_host, server_uri, etc) of modular inputs app from InputDefinition object
    # Here, an InputDefinition`object data is used
    server_host = inputs.metadata["server_host"]
    server_uri = inputs.metadata["server_uri"]
    checkpoint_dir = inputs.metadata["checkpoint_dir"]

Access service object in Custom Search Command & Modular Input apps

Custom Search Commands

• The service object is created from the splunkd URI and session key passed to the command invocation the search results info file.
• Service object can be accessed using self.service in generate/transform/stream/reduce methods depending on the Custom Search Command.

Getting Splunk instance metadata

def get_metadata(self):
    # [...] other code

    # Access service object that can be used to connect Splunk Service
    service = self.service
    # Getting Splunk Service Info
    info = service.info

Modular Inputs app

• The service object is created from the splunkd URI and session key passed to the command invocation on the modular input stream respectively.

• It is available as soon as the Script.stream_events method is called.

  def stream_events(self, inputs, ew):
      # other code
  
      # access service object that can be used to connect Splunk Service
      service = self.service
      # to get Splunk Service Info
      info = service.info

Running the test suite

This repo contains a collection of unit and integration tests.

Unit tests

To run both unit and integration tests:

make test

Integration tests

NOTE: Before running the integration tests, make sure the instance of Splunk you are testing against doesn't have new events being dumped continuously into it. Several of the tests rely on a stable event count. It's best to test against a clean install of Splunk but if you can't, you should at least disable the *NIX and Windows apps.

Do not run the test suite against a production instance of Splunk! It will run just fine with the free Splunk license.

Prerequisites

• docker/podman
• tox

SPLUNK_VERSION=latest && make start

Optional: Set up logging for splunklib

The default level is WARNING, which means that only events of this level and above will be visible To change a logging level we can call setup_logging() method and pass the logging level as an argument.

Optionally, you can also provide a custom log and date format string. When in doubt, always refer to the source code.

import logging
from splunklib import setup_logging

# To see debug and above level logs
setup_logging(logging.DEBUG)

Changelog

The CHANGELOG contains a description of changes for each version of the SDK. For the latest version, see the CHANGELOG.md on GitHub.

Branches

The master branch represents a stable and released version of the SDK. develop is where development between releases is happening.

To learn more about our branching model, see Branching Model on GitHub.

Documentation and resources

Resource	Description
Splunk Developer Portal	General developer documentation, tools, and examples
Integrate the Splunk platform using development tools for Python	Documentation for Python development
Splunk Enterprise SDK for Python Reference	SDK API reference documentation
REST API Reference Manual	Splunk REST API reference documentation
Splunk>Docs	General documentation for the Splunk platform
GitHub Wiki	Documentation for this SDK's repository on GitHub
Splunk Enterprise SDK for Python Examples	Examples for this SDK's repository

Community

Stay connected with other developers building on the Splunk platform.

• E-mail
• Issues and pull requests
• Community Slack
• Splunk Answers

Contributions

We welcome all contributions! If you would like to contribute to the SDK, see Contributing to Splunk. For additional guidelines, see CONTRIBUTING.

Support

• You will be granted support if you or your company are already covered under an existing maintenance/support agreement. Submit a new case in the Support Portal and include Splunk Enterprise SDK for Python in the subject line.

If you are not covered under an existing maintenance/support agreement, you can find help through the broader community at Splunk Answers.

• Splunk will NOT provide support for SDKs if the core library (the code in the /splunklib directory) has been modified. If you modify an SDK and want support, you can find help through the broader community and Splunk Answers.

  We would also like to know why you modified the core library, so please send feedback to mailto:devinfo@splunk.com.

• File any issues on GitHub.

Contact us

You can reach the Splunk Developer Platform team at mailto:devinfo@splunk.com.