docs: add parallel to executed docs

docs/docs/icechunk-python/parallel.md

@@ -16,7 +16,7 @@ including those executed remotely in a multi-processing or any other remote exec
 Here is how you can execute such writes with Icechunk, illustrate with a `ThreadPoolExecutor`.
 First read some example data, and create an Icechunk Repository.
 
-```python
+```python exec="on" session="parallel" source="material-block"
 import xarray as xr
 import tempfile
 from icechunk import Repository, local_filesystem_storage
@@ -29,25 +29,25 @@ session = repo.writable_session("main")
 We will orchestrate so that each task writes one timestep.
 This is an arbitrary choice but determines what we set for the Zarr chunk size.
 
-```python
+```python exec="on" session="parallel" source="material-block"
 chunks = {1 if dim == "time" else ds.sizes[dim] for dim in ds.Tair.dims}
 ```
 
 Initialize the dataset using [`Dataset.to_zarr`](https://docs.xarray.dev/en/stable/generated/xarray.Dataset.to_zarr.html)
 and `compute=False`, this will NOT write any chunked array data, but will write all array metadata, and any
 in-memory arrays (only `time` in this case).
 
-```python
+```python exec="on" session="parallel" source="material-block"
 ds.to_zarr(session.store, compute=False, encoding={"Tair": {"chunks": chunks}}, mode="w")
 # this commit is optional, but may be useful in your workflow
-session.commit("initialize store")
+print(session.commit("initialize store"))
 ```
 
 ## Multi-threading
 
 First define a function that constitutes one "write task".
 
-```python
+```python exec="on" session="parallel" source="material-block"
 from icechunk import Session
 
 def write_timestamp(*, itime: int, session: Session) -> None:
@@ -59,7 +59,7 @@ def write_timestamp(*, itime: int, session: Session) -> None:
 
 Now execute the writes.
 
-```python
+```python exec="on" session="parallel" source="material-block"
 from concurrent.futures import ThreadPoolExecutor, wait
 from icechunk.distributed import merge_sessions
 
@@ -69,12 +69,12 @@ with ThreadPoolExecutor() as executor:
     futures = [executor.submit(write_timestamp, itime=i, session=session) for i in range(ds.sizes["time"])]
     wait(futures)
 
-session.commit("finished writes")
+print(session.commit("finished writes"))
 ```
 
 Verify that the writes worked as expected:
 
-```python
+```python exec="on" session="parallel" source="material-block"
 ondisk = xr.open_zarr(repo.readonly_session("main").store, consolidated=False)
 xr.testing.assert_identical(ds, ondisk)
 ```
@@ -96,7 +96,7 @@ There are three key points to keep in mind:
 
 First we modify `write_task` to return the `Session`:
 
-```python
+```python exec="on" session="parallel" source="material-block"
 from icechunk import Session
 
 def write_timestamp(*, itime: int, session: Session) -> Session:
@@ -110,7 +110,7 @@ def write_timestamp(*, itime: int, session: Session) -> Session:
 Now we issue write tasks within the [`session.allow_pickling()`](./reference/md#icechunk.Session.allow_pickling) context, gather the Sessions from individual tasks,
 merge them, and make a successful commit.
 
-```python
+```python exec="on" session="parallel" source="material-block"
 from concurrent.futures import ProcessPoolExecutor
 from icechunk.distributed import merge_sessions
 
@@ -128,12 +128,12 @@ with ProcessPoolExecutor() as executor:
 
 # manually merge the remote sessions in to the local session
 session = merge_sessions(session, *sessions)
-session.commit("finished writes")
+print(session.commit("finished writes"))
 ```
 
 Verify that the writes worked as expected:
 
-```python
+```python exec="on" session="parallel" source="material-block"
 ondisk = xr.open_zarr(repo.readonly_session("main").store, consolidated=False)
 xr.testing.assert_identical(ds, ondisk)
 ```