Make the example's __main__ actually run

It claimed to run the pipeline with no engine involved, and could not: the
node bodies it called save and load artifacts, which raise outside a node by
design. Each node is now a thin wrapper over a plain function — make_rows,
train_curve, score — and __main__ calls those, which is the split the sandbox
already demonstrates and the one worth copying.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

examples/myresearch/train.py

@@ -9,6 +9,14 @@ import fluksio
 from fluksio import Port, node
 
 
+def train_curve(lr: float, epochs: int) -> list[float]:
+    """The loss per epoch, with no Fluksio in it."""
+    return [
+        math.exp(-lr * epoch * 10) * (1 + 0.05 * (epoch % 3)) / (1 + lr)
+        for epoch in range(epochs)
+    ]
+
+
 @node(
     requires=["dataset", Port("lr", "float")],
     provides=[
@@ -38,8 +46,7 @@ def fit(dataset, lr, epochs=25):
     """
     rows = json.loads(open(fluksio.load_artifact(dataset)).read())["rows"]
     loss = 1.0
-    for epoch in range(epochs):
-        loss = math.exp(-lr * epoch * 10) * (1 + 0.05 * (epoch % 3)) / (1 + lr)
+    for loss in train_curve(lr, epochs):
         yield {"loss": loss}
     weights = json.dumps({"lr": lr, "epochs": epochs, "n": len(rows)}).encode()
     return {