Metadata-Version: 2.4
Name: sssn
Version: 0.0.1
Summary: Simple System of Systems Network
Author: Productive Superintelligence
License-Expression: MIT
Project-URL: Homepage, https://github.com/Productive-Superintelligence/sssn
Project-URL: Repository, https://github.com/Productive-Superintelligence/sssn
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: fastapi>=0.110
Requires-Dist: pydantic>=2.0
Requires-Dist: PyJWT>=2.8
Requires-Dist: uvicorn>=0.29
Requires-Dist: aiosqlite>=0.20
Requires-Dist: httpx>=0.27
Provides-Extra: dev
Requires-Dist: pytest>=8.0; extra == "dev"
Requires-Dist: pytest-asyncio>=0.23; extra == "dev"
Provides-Extra: docs
Requires-Dist: mkdocs-material>=9.5; extra == "docs"
Requires-Dist: mkdocs-autorefs>=1.0; extra == "docs"
Requires-Dist: pymdown-extensions>=10.0; extra == "docs"
Dynamic: license-file

# SSSN — Simple System of Systems Network

[![PyPI version](https://img.shields.io/pypi/v/sssn.svg)](https://pypi.org/project/sssn/)
[![Python](https://img.shields.io/pypi/pyversions/sssn.svg)](https://pypi.org/project/sssn/)
[![License](https://img.shields.io/github/license/Productive-Superintelligence/sssn.svg)](LICENSE)
[![Docs](https://img.shields.io/badge/docs-sssn.one-indigo)](https://sssn.one)

A minimal Python framework for building composable, distributed AI agent networks.

Two abstractions. One graph.

```
System ──writes──► Channel ──reads──► System
```

A **Channel** is a typed, secured, persistent message store.
A **System** is an autonomous agent that owns channels, wires itself to the network, and runs a tick loop.

---

## Install

```bash
pip install sssn
```

Requires Python 3.10+.

---

## Quick start

```python
import asyncio
from sssn.channels.broadcast import BroadcastChannel
from sssn.core.system import BaseSystem

class Sensor(BaseSystem):
    async def setup(self):
        self.readings = BroadcastChannel(id="readings", name="Readings")
        self.add_channel(self.readings)

    async def step(self):
        await self.write_channel("readings", data={"celsius": 22.4})

class Monitor(BaseSystem):
    async def step(self):
        msgs = await self.read_channel("readings")
        for msg in msgs:
            print(msg.content)

async def main():
    sensor  = Sensor(id="sensor",  name="Sensor")
    monitor = Monitor(id="monitor", name="Monitor")
    await sensor.setup()
    sensor.add_subsystem(monitor, channels=["readings"])
    await asyncio.gather(sensor.launch())

asyncio.run(main())
```

---

## Channel types

| Channel | Pattern |
|---------|---------|
| `BroadcastChannel` | Fan-out — every consumer sees every message |
| `WorkQueueChannel` | Competing consumers — each message claimed once |
| `MailboxChannel` | Per-recipient inbox |
| `PeriodicChannel` | Active poll loop for external data sources |
| `DiscoveryChannel` | Service registry with TTL-based expiry |
| `PassthroughChannel` | Base class — inline write, no loop |

---

## Documentation

Full documentation at **[sssn.one](https://sssn.one)**:

- [Concepts](https://sssn.one/concepts/) — Channel, System, Security, Transport
- [Tutorials](https://sssn.one/tutorials/) — Step-by-step from first channel to secured multi-system network
- [Examples](https://sssn.one/examples/) — Data pipeline, request-response, service discovery

---

## Development setup

```bash
git clone https://github.com/Productive-Superintelligence/sssn.git
cd sssn
pip install -e ".[dev]"
pytest
```

Build and preview the docs locally:

```bash
pip install -e ".[docs]"
mkdocs serve          # http://127.0.0.1:8000
mkdocs build --strict # production build → site/
```

---

## Release

```bash
# 1. Bump version in pyproject.toml, then:
python -m build
python -m twine upload dist/*

# 2. Tag and push
git tag -a v0.0.1 -m "Release 0.0.1"
git push origin main --tags
```
