# Pick your starting point

Setup differs depending on what you are here for. Pick the path that matches.

Pick the one that sounds like you. Everything past this section is the same for
both.

<div class="fluksio-lanes" markdown>

<div class="fluksio-lane fluksio-lane--science" markdown>

### Data science

*"I have a training script. I want to stop losing track of what I ran."*

One `pip install`, one command, and you are writing Python again. No Docker, no
database, no ports to open. Flows are files, runs are rows, and the metrics are
just the numbers your loop already produces.

[Set up for experiments →](data-science.md)

</div>

<div class="fluksio-lane fluksio-lane--facility" markdown>

### Facility automation

*"I have a homelab and a pile of sensors. I want them to do something."*

A stack you bring up once and leave running: the engine, a broker, a
time-series database, dashboards, alerting. Most of the work happens in the
browser, and it is worth doing properly because you will live in it.

[Set up a homelab instance →](facility-automation.md)

</div>

</div>

## Not sure?

Some rough tells:

| | Data science | Facility automation |
|---|---|---|
| **The flow** | starts, finishes, has a result | never ends |
| **You mostly** | write Python | wire nodes in the browser |
| **Time to first result** | a few minutes | an afternoon |
| **Runs on** | your laptop, or a login node | a box in a cupboard |
| **Data lives in** | SQLite beside the flows | InfluxDB, usually |
| **The thing you look at** | run history and loss curves | a dashboard, maybe on a wall |

If both describe you (a lab with instruments to drive *and* models to fit),
start with the data-science path. It is the smaller instance, and it
grows into the other one without being reinstalled: the same engine, the same
flows, just more of them running all the time.

## What is the same either way

Whichever door you came in:

- **Flows are files in a git repository.** Every save is a commit. You can read
  the history with ordinary git, and you can copy a flow between instances
  by copying a directory.
- **Editing is separate from running.** You edit a draft; the engine keeps
  running what was published until you publish.
- **Nodes are typed.** A port declares what it carries, and a mismatch is
  caught at edit time rather than at three in the morning.
- **Everything the browser does is an API call.** The dashboard is a client of
  the same REST API you can script against.