Python SDK for Gretl — control local services by name or port number
Project description
gretl
Python SDK for Gretl — control local services by name or port number.
Install
pip install gretl
Quick start
from gretl import gr
# List all monitored ports
ports = gr.ports()
# Start / stop by name or port number
gr.start("api")
gr.stop("3000")
# Start / stop an entire group
gr.start_group("backend")
gr.stop_group("backend")
# Wait for a service to come up (useful in tests)
gr.wait_for_active("postgres", timeout=30)
# Add a new port to monitoring
gr.add(7401, name="jobs-server", cmd="node jobs.js", group="backend")
API
| Method | Description |
|---|---|
gr.ports() |
Return all monitored ports |
gr.port(query) |
Find ports by name substring or exact port number |
gr.active() |
Only running ports |
gr.inactive() |
Only stopped ports |
gr.start(query) |
Start matching service(s) |
gr.stop(query) |
Stop matching service(s) |
gr.remove(query) |
Remove from monitoring |
gr.start_group(group) |
Start all ports in a group |
gr.stop_group(group) |
Stop all ports in a group |
gr.status_group(group) |
List all ports in a group |
gr.wait_for_active(query, timeout, interval) |
Block until active |
gr.wait_for_inactive(query, timeout, interval) |
Block until inactive |
gr.add(port, name, cmd, group, cwd) |
Register a new port |
Kubernetes & cloud
gr.k8s exposes the Gretl cloud API for managing Kubernetes workloads. Set GR_TOKEN in your environment or pass token= to GretlClient.
from gretl import gr
# GR_TOKEN is read automatically from os.environ
clusters = gr.k8s.clusters()
workloads = gr.k8s.workloads(cluster_id=clusters[0]["id"])
# Sleep / wake a workload
gr.k8s.sleep(workloads[0]["id"])
gr.k8s.wake(workloads[0]["id"])
# Tether a container port to a public tunnel URL
tether = gr.k8s.tether(workloads[0]["id"], container_port=8000)
print(tether["tunnel_url"])
# Force a cluster sync
gr.k8s.sync(clusters[0]["id"])
# Configure auto-sleep
gr.k8s.set_auto_sleep(workloads[0]["id"], enabled=True, idle_timeout_minutes=30)
| Method | Description |
|---|---|
gr.k8s.clusters() |
List connected clusters |
gr.k8s.workloads(cluster_id=None) |
List workloads |
gr.k8s.sync(cluster_id) |
Force cluster sync |
gr.k8s.sleep(workload_id) |
Scale to zero |
gr.k8s.wake(workload_id) |
Restore replicas |
gr.k8s.tether(workload_id, container_port, label=None) |
Create public tunnel |
gr.k8s.detach(tether_id) |
Deactivate a tether |
gr.k8s.tethers() |
List active tethers |
gr.k8s.auto_sleep(workload_id) |
Get auto-sleep config |
gr.k8s.set_auto_sleep(workload_id, enabled, idle_timeout_minutes) |
Update auto-sleep config |
Requirements
The Gretl daemon must be running for local port methods. Download free at gretl.dev. K8s methods require a GR_TOKEN from your Gretl dashboard.
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