docs: document that parallelized=True resources with add_limit(x) usually yield x-1

dlt/extract/resource.py

@@ -354,6 +354,7 @@ def add_limit(self: TDltResourceImpl, max_items: int) -> TDltResourceImpl:  # no
             1. Transformers won't be limited. They should process all the data they receive fully to avoid inconsistencies in generated datasets.
             2. Each yielded item may contain several records. `add_limit` only limits the "number of yields", not the total number of records.
             3. Async resources with a limit added may occasionally produce one item more than the limit on some runs. This behavior is not deterministic.
+            4. Parallelized sync resources with a limit added will usually produce one item less than the limit. This behavior is not deterministic.
 
         Args:
             max_items (int): The maximum number of items to yield

tests/pipeline/test_resources_evaluation.py

@@ -217,6 +217,19 @@ async def async_resource1():
     assert len(result) == 13
 
 
+@pytest.mark.parametrize("parallelized", [False, True])
+def test_limit_sync_resource(parallelized: bool) -> None:
+    @dlt.resource(parallelized=parallelized)
+    def sync_resource1():
+        for i in range(1, 10):
+            yield i
+
+    limit = 5
+    result = list(sync_resource1().add_limit(limit))
+    allowed_result_range = range(limit - int(parallelized), limit + 1)
+    assert len(result) in allowed_result_range
+
+
 @pytest.mark.parametrize("parallelized", [True, False])
 def test_parallelized_resource(parallelized: bool) -> None:
     os.environ["EXTRACT__NEXT_ITEM_MODE"] = "fifo"