---
id: signalflow-client-python
version: "1.3.9"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# signalflow-client-python

License: permissive · Maintenance: active · Downloads: 80.8K/mo

## What it is and what it does

signalflow-client-python is a library for programmatically executing real-time analytics computations on Splunk Observability Cloud. It opens a persistent connection to SignalFx, sends SignalFlow programs (a domain-specific language for time-series analytics), and streams computed results back to your Python application. The library handles authentication via API token and manages the underlying connections through its runtime dependencies: certifi, six, sseclient-py, urllib3, and ws4py.

Typical usage involves instantiating a client with your API credentials, executing a SignalFlow program string, and iterating over the message stream to receive real-time metric data. It is designed for developers who want to embed SignalFx analytics directly into Python applications rather than relying solely on the Splunk UI, enabling programmatic access to the same computation engine that powers dashboards and alerts.

Use it for:

- Execute custom real-time analytics on metrics stored in Splunk Observability Cloud from a Python script or application.
- Stream live metric data into a Python monitoring or alerting system for custom post-processing or decision logic.
- Reuse SignalFlow programs written in the Splunk UI by executing them programmatically from Python code.
- Build automated data pipelines that fetch computed metrics from SignalFx on a schedule or in response to events.
- Integrate Splunk Observability analytics into Python-based observability or incident response workflows.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

A Python client library that connects to Splunk Observability Cloud to execute SignalFlow real-time streaming analytics computations and stream results back to your application.

Yes, if you use Splunk Observability Cloud and need to execute SignalFlow computations from Python. The package is actively maintained, has low install friction, carries a permissive Apache-2.0 license, and no known vulnerabilities. It is a straightforward client library with a clear use case: streaming real-time analytics from SignalFx. Install it only if you have a SignalFx account and an API token.

## Install

pip install signalflow-client-python
uv add signalflow-client-python
poetry add signalflow-client-python

## Installing signalflow-client-python

Before you install: Low friction: pure Python wheel with five lightweight runtime dependencies (certifi, six, sseclient-py, urllib3, ws4py). Active maintenance with a release 37 days ago; requires Python 3.10 or later.

License in practice: Apache-2.0 permissive license allows free use, modification, and distribution in both open-source and proprietary projects with minimal restrictions.

Quickstart:

pip install signalflow-client-python

from signalflow_client_python import SignalFlowClient

client = SignalFlowClient(token='your-api-token', endpoint='https://stream.signalfx.com')
computation = client.execute("data('sf.org.num.orguser').publish()")
for msg in computation.stream():
    print(msg)
client.close()

Requires a valid Splunk Observability Cloud API access token and network connectivity to the SignalFx stream endpoint.

Verify before relying:

- Whether the package supports streaming over WebSocket connections reliably in production environments.
- Performance characteristics and latency guarantees for high-frequency metric streams.
- Backward compatibility policy and deprecation timeline for older Python versions.
- Exact module and class names available in the public API beyond what the description excerpt shows.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 80.8K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

signalflow streaming analytics client, splunk observability real-time computation, signalflow python api, real-time metrics streaming, signalflow program execution, observability, streaming-analytics, signalflow

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