turbaszek edited a comment on pull request #8805:
URL: https://github.com/apache/airflow/pull/8805#issuecomment-636334773
I did a 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 # 30 template 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
OP_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(OP_N):
kwargs = {k: op1.output for k in fields}
CustomOp(task_id=f"task_{i}", **kwargs)
print("OPs: ", OP_N)
case()
```
Average time for 100 OPs in single DAG:
- metaclass: 492.990 ms
- setattr + if: 7072.531 ms
- setattr: 7208.424 ms
So using setattr is **14** slower than metaclass...
But to make everything works smooth we can mix those two approaches:
```python
class BaseOperatorMeta(type):
def __call__(cls, *args, **kwargs):
obj: BaseOperator = type.__call__(cls, *args, **kwargs)
# Set upstream task defined by XComArgs passed to template fields of
an operator
obj.set_xcomargs_dependencies()
obj._instantiated = True
return obj
class BaseOperator(Operator, LoggingMixin, metaclass=BaseOperatorMeta):
_instantiated = False
def __setattr__(self, key, value):
super().__setattr__(key, value)
if self._instantiated and key in self.template_fields:
self.set_xcomargs_dependencies()
```
this gives the following result **471.381 ms**
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