REST API Documentation

Programmatic access to the orbital compute simulation engine. Self-host the Python backend to use these endpoints.

Quick Start

# Install and start the API server
git clone https://github.com/ShipItAndPray/orbital-compute.git
cd orbital-compute
pip install -r requirements.txt
python -m orbital_compute.api --port 8080

# Test it
curl http://localhost:8080/status
      

Endpoints

GET /status

Constellation overview — satellite count, running jobs, fleet utilization.

curl http://localhost:8080/status

Example Response

{
  "n_satellites": 12,
  "running_jobs": 3,
  "completed_jobs": 47,
  "fleet_utilization_pct": 23.5,
  "total_compute_hours": 22.54
}

GET /satellites

Per-satellite detail — orbit, power, thermal, compute utilization, contacts.

curl http://localhost:8080/satellites

GET /jobs

All jobs grouped by status: pending, running, completed.

curl http://localhost:8080/jobs

POST /jobs

Submit a new compute job. Specify workload type from the catalog.

curl -X POST http://localhost:8080/jobs \
  -H "Content-Type: application/json" \
  -d '{"workload": "image_classification"}'

Available Workloads

image_classification  — 200W, 120s, Earth Observation
change_detection      — 300W, 300s, Earth Observation
object_tracking       — 400W, 60s,  Earth Observation (realtime)
llm_inference         — 600W, 30s,  AI Inference (realtime)
image_generation      — 500W, 45s,  AI Inference
weather_model         — 800W, 3600s, Scientific (batch)
climate_analysis      — 700W, 7200s, Scientific (batch)
sar_processing        — 500W, 180s, Defense/ISR
signal_analysis       — 300W, 60s,  Defense/ISR (realtime)

GET /contacts

Upcoming ground station contact windows per satellite.

curl http://localhost:8080/contacts

GET /metrics

Fleet utilization, job throughput, power/thermal statistics.

curl http://localhost:8080/metrics

Python Library

# Use as a Python library
from orbital_compute.simulator import Simulation, SimulationConfig

config = SimulationConfig(
    n_satellites=12,
    sim_duration_hours=24,
    n_jobs=100,
    solar_panel_watts=2000,
    battery_capacity_wh=5000,
)
sim = Simulation(config)
sim.setup()
results = sim.run()
sim.print_report()

# Access results
print(f"Completed: {results['scheduler']['completed']}")
print(f"Utilization: {results['fleet_utilization_pct']}%")