fix snippets

dlt-hub · Nov 25, 2024 · 4f4ccd7 · 4f4ccd7
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diff --git a/docs/website/docs/general-usage/dataset-access/dataset.md b/docs/website/docs/general-usage/dataset-access/dataset.md
@@ -220,7 +220,7 @@ Since the `iter_arrow` and `iter_df` methods are generators that iterate over th
 limited_items_relation = dataset.items.limit(1_000_000)
 
 # Create a new pipeline
-other_pipeline = ...
+other_pipeline = dlt.pipeline(pipeline_name="other_pipeline", destination="duckdb")
 
 # We can now load these 1m rows into this pipeline in 10k chunks
 other_pipeline.run(limited_items_relation.iter_arrow(chunk_size=10_000), table_name="limited_items")

diff --git a/docs/website/docs/general-usage/dataset-access/sql-client.md b/docs/website/docs/general-usage/dataset-access/sql-client.md
@@ -36,7 +36,7 @@ The cursor returned by `execute_query` has several methods for retrieving the da
 The code below shows how to retrieve the data as a Pandas DataFrame and then manipulate it in memory:
 
 ```py
-pipeline = dlt.pipeline(...)
+pipeline = dlt.pipeline(pipeline_name="my_pipeline", destination="duckdb")
 with pipeline.sql_client() as client:
     with client.execute_query(
         'SELECT "reactions__+1", "reactions__-1", reactions__laugh, reactions__hooray, reactions__rocket FROM issues'