turbaszek commented on pull request #8805:
URL: https://github.com/apache/airflow/pull/8805#issuecomment-636334773
I did some simple test:
```python
from datetime import datetime
from airflow import DAG
from airflow.operators.dummy_operator import DummyOperator
from airflow.utils.decorators import apply_defaults
from scripts.perf.perf_kit import python, memory, repeat_and_time
fields = [f"field{i}" for i in range(30)]
class CustomOp(DummyOperator):
template_fields = fields
@apply_defaults
def __init__(self, *args, **kwargs):
super().__init__(*args, task_id=kwargs["task_id"])
for key in kwargs:
if key.startswith("field"):
setattr(self, key, kwargs[key])
if __name__ == '__main__':
N = 10
DAG_N = 100
@repeat_and_time.timing(N)
@repeat_and_time.repeat(N)
def case():
with DAG("xcomargs_test", default_args={"start_date":
datetime.today()}):
op1 = DummyOperator(task_id="op1")
for i in range(DAG_N):
kwargs = {k: op1.output for k in fields}
CustomOp(task_id=f"task_{i}", **kwargs)
print("DAGs: ", DAG_N)
case()
```
Results for 100 DAGs:
- metaclass: 492.990 ms
- setattr + if: 7072.531 ms
- setattr: 7208.424 ms
So using setattr is **14** slower than metaclass...
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