chore: import upstream snapshot with attribution

2026-07-13 13:33:56 +08:00
commit 461bf6fd40
1313 changed files with 1079898 additions and 0 deletions
@@ -0,0 +1,37 @@
+import click
+from deltalake import DeltaTable
+
+
+@click.command()
+@click.option("--table-uri", type=str)
+def run_check(table_uri):
+    print(f"Checking contents of table at {table_uri}")
+    delta_table = DeltaTable(
+        table_uri=table_uri,
+    )
+
+    df = delta_table.to_pandas()
+    EXPECTED_ROWS = 5
+    EXPECTED_COLUMNS = 19
+    print(f"Number of rows in table vs expected: {len(df)}/{EXPECTED_ROWS}")
+    print(f"Number of columns in table vs expected: {len(df.columns)}/{EXPECTED_COLUMNS}")
+    number_of_rows = len(df)
+    assert number_of_rows == EXPECTED_ROWS, (
+        f"number of rows in generated table ({number_of_rows}) "
+        f"doesn't match expected value: {EXPECTED_ROWS}"
+    )
+
+    """
+    The number of columns is associated with the flattened JSON structure of the partition output.
+    If this changes, it's most likely due to the metadata changing in the output.
+    """
+    number_of_columns = len(df.columns)
+    assert number_of_columns == EXPECTED_COLUMNS, (
+        f"number of columns in generated table ({number_of_columns}) doesn't "
+        f"match expected value: {EXPECTED_COLUMNS}"
+    )
+    print("table check complete")
+
+
+if __name__ == "__main__":
+    run_check()