feat(python): export recorded Function job timelines (#4946)

Function jobs can now export their recorded execution timeline with
`job.export_timeline(path)` or `await job.export_timeline(path)`. The
SDK fetches a fresh Chrome Trace Event recording that opens in Perfetto,
including worker split spans and timestamped job phases. Batch counts
and latency statistics remain details rather than invented batch
intervals.

```python
job = db.open_job(job_id)
job.export_timeline("refresh.trace.json")

async_job = await async_db.open_job(job_id)
await async_job.export_timeline("refresh.trace.json")
```

The export does not wait for completion or cancel the job. Running jobs
return partial recordings. Local operations and SQL query handles remain
unsupported, and servers must support the timeline endpoint. The
destination is touched only after a successful fetch; network and
filesystem errors propagate. Rust freshness wrappers forward the
operation without changing the submitting table's read baseline.

python/src/job.rs

@@ -152,6 +152,13 @@ impl Job {
         self.inner.description().map(JobDescription::from)
     }
 
+    pub fn timeline(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
+        let inner = self_.inner.clone();
+        future_into_py(self_.py(), async move {
+            Ok(inner.timeline().await.infer_error()?.to_string())
+        })
+    }
+
     #[pyo3(signature = (*, limit=None, filter=None))]
     pub fn events(
         self_: PyRef<'_, Self>,