switch from positional to names args in dataframe construction

dlt-hub · Feb 29, 2024 · 1d12f21 · 1d12f21
1 parent 49e6aff
commit 1d12f21
Showing 1 changed file with 22 additions and 23 deletions.
diff --git a/sources/arrow_pandas/example_resources.py b/sources/arrow_pandas/example_resources.py
@@ -6,31 +6,23 @@
 import pandas as pd
 import pyarrow as pa
 
-# this is example data, you will get this from somewhere on your resource function
-EXAMPLE_ORDERS_DATA_FRAME = pd.DataFrame(
-    {
-        "order_id": [1, 2, 3],
-        "customer_id": [1, 2, 3],
-        "ordered_at": [
-            pendulum.DateTime(2021, 1, 1, 4, 5, 6),
-            pendulum.DateTime(2021, 1, 3, 4, 5, 6),
-            pendulum.DateTime(2021, 1, 6, 4, 5, 6),
-        ],
-        "order_amount": [100.0, 200.0, 300.0],
-    }
-)
-
-EXAMPLE_CUSTOMERS_DATA_FRAME = pd.DataFrame(
-    {
-        "customer_id": [1, 2, 3],
-        "name": ["Alice", "Bob", "Charlie"],
-        "age": [25, 30, 35],
-    }
-)
-
 
 @dlt.resource(name="orders", write_disposition="append")
 def orders() -> Generator[pd.DataFrame, None, None]:
+    # this is example data, you will get this from somewhere on your resource function
+    EXAMPLE_ORDERS_DATA_FRAME = pd.DataFrame(
+        data={
+            "order_id": [1, 2, 3],
+            "customer_id": [1, 2, 3],
+            "ordered_at": [
+                pendulum.DateTime(2021, 1, 1, 4, 5, 6),
+                pendulum.DateTime(2021, 1, 3, 4, 5, 6),
+                pendulum.DateTime(2021, 1, 6, 4, 5, 6),
+            ],
+            "order_amount": [100.0, 200.0, 300.0],
+        }
+    )
+
     # we can yield dataframes here, you will usually read them from a file or
     # receive them from another library
     yield EXAMPLE_ORDERS_DATA_FRAME
@@ -45,7 +37,14 @@ def orders() -> Generator[pd.DataFrame, None, None]:
 def customers() -> Generator[pd.DataFrame, None, None]:
     # we can yield arrow tables here, you will usually read them from a file or
     # receive them from another library
+    EXAMPLE_CUSTOMERS_DATA_FRAME = pd.DataFrame(
+        data={
+            "customer_id": [1, 2, 3],
+            "name": ["Alice", "Bob", "Charlie"],
+            "age": [25, 30, 35],
+        }
+    )
 
     # here we convert our dataframe to an arrow table, usually you would just yield the
     # dataframe if you have it, this is for demonstration purposes
-    yield pa.Table.from_pandas(EXAMPLE_ORDERS_DATA_FRAME)
+    yield pa.Table.from_pandas(EXAMPLE_CUSTOMERS_DATA_FRAME)