From 4f4ccd751f7b1299be1331347558e33d91bc30d2 Mon Sep 17 00:00:00 2001 From: Dave Date: Mon, 25 Nov 2024 12:38:07 +0100 Subject: [PATCH] fix snippets --- docs/website/docs/general-usage/dataset-access/dataset.md | 2 +- docs/website/docs/general-usage/dataset-access/sql-client.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/website/docs/general-usage/dataset-access/dataset.md b/docs/website/docs/general-usage/dataset-access/dataset.md index d05887e4d9..68635383c5 100644 --- 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 index 05371ed4e5..bcd23cfd32 100644 --- 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'