fix: DFS Arrow example datatypes (#160)

Co-authored-by: Paul Spangler <[email protected]>

Author: cameronwaterman

README.rst

@@ -36,13 +36,20 @@ To install **nisystemlink-clients**, use one of the following methods:
 
 Optional Arrow (pyarrow) Support
 --------------------------------
-The base install does not pull in ``pyarrow``. Install the optional extra if you
-plan to use Arrow RecordBatch ingestion with ``DataFrameClient.append_table_data``::
+The base install does not pull in ``pyarrow``. Arrow ``RecordBatch`` ingestion via
+``DataFrameClient.append_table_data`` is available starting in
+``nisystemlink-clients`` version 2.19.0. Install that version (or newer) with the
+optional extra:
 
-   $ python -m pip install "nisystemlink-clients[pyarrow]"
+   $ python -m pip install "nisystemlink-clients[pyarrow]>=2.19.0"
 
-Without the extra, Arrow-specific code paths will raise a ``RuntimeError`` when
-attempting to append ``pyarrow.RecordBatch`` instances.
+If you already have an older version installed, upgrade with:
+
+   $ python -m pip install --upgrade "nisystemlink-clients[pyarrow]>=2.19.0"
+
+Without the extra (or when using a package version earlier than 2.19.0),
+Arrow-specific code paths will raise a ``RuntimeError`` when attempting to
+append ``pyarrow.RecordBatch`` instances.
 
 .. _usage_section:
 

examples/dataframe/create_write_data.py

@@ -45,9 +45,9 @@
     # Append via single RecordBatch (Arrow)
     batch_single = pa.record_batch(
         [
-            pa.array([6, 7, 8]),
-            pa.array([0.1, 0.2, 0.3]),
-            pa.array([datetime.now().isoformat()] * 3),
+            pa.array([6, 7, 8], type=pa.int32()),
+            pa.array([0.1, 0.2, 0.3], type=pa.float32()),
+            pa.array([datetime.now() for _ in range(3)], pa.timestamp("ms")),
         ],
         names=["ix", "Float_Column", "Timestamp_Column"],
     )
@@ -57,9 +57,9 @@
     batch_list = [
         pa.record_batch(
             [
-                pa.array([9, 10]),
-                pa.array([0.4, 0.5]),
-                pa.array([datetime.now().isoformat(), datetime.now().isoformat()]),
+                pa.array([9, 10], type=pa.int32()),
+                pa.array([0.4, 0.5], type=pa.float32()),
+                pa.array([datetime.now() for _ in range(2)], pa.timestamp("ms")),
             ],
             names=["ix", "Float_Column", "Timestamp_Column"],
         )