GitHub user christianalberto added a comment to the discussion: Serialization
issues with external_python decorator
Here is the straight-to-the-point explanation: when you use
@task.external_python, Airflow tries to pickle your function to send it over to
a separate Python environment. If the function tries to grab variables,
helpers, or imports from outside its scope, pickling breaks.
To fix it, treat your task as a self-contained box. Everything it needs must
live inside the function.
❌ Code that fails
```Python
from tasks.connections import get_connection # ❌ Import outside task
def my_dag():
def get_config(): # ❌ Local nested function outside task
return {"env": "prod"}
@task.external_python(python="/path/to/venv/bin/python")
def my_task():
cfg = get_config() # 💥 Fails: cannot pickle local function
conn = get_connection() # 💥 Fails: module import mismatch across venvs
```
✅ Code fixed
```Python
def my_dag():
@task.external_python(python="/path/to/venv/bin/python")
def my_task():
# ✅ Imports go INSIDE the task
from tasks.connections import get_connection
# ✅ Helper logic goes INSIDE the task
cfg = {"env": "prod"}
conn = get_connection()
```
3 golden rules to keep in mind:
1. Imports inside: Put any imports needed by the task directly inside the
decorated function.
2. No nested functions: Don't reference helper functions defined inside
my_dag().
3. Simple XComs: If you use .expand() or pass data between tasks, stick to
plain data structures (strings, numbers, dicts, lists)—avoid passing complex
custom objects or classes.
Moving the imports and helper logic inside the function will resolve both
pickling errors right away.
GitHub link:
https://github.com/apache/airflow/discussions/71281#discussioncomment-17940221
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