noah-gil opened a new issue, #26718:
URL: https://github.com/apache/airflow/issues/26718
### Apache Airflow Provider(s)
docker
### Versions of Apache Airflow Providers
apache-airflow-providers-docker==3.1.0
### Apache Airflow version
2.4.0
### Operating System
Debian GNU/Linux 11 (bullseye)
### Deployment
Docker-Compose
### Deployment details
Client: Docker Engine - Community
Cloud integration: v1.0.28
Version: 20.10.17
API version: 1.41
Go version: go1.17.11
Git commit: 100c701
Built: Mon Jun 6 23:03:17 2022
OS/Arch: linux/amd64
Context: default
Experimental: true
Docker Compose: v2.7.0
Using a slightly modified version of the example docker-compose.yaml:
```yaml
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
# Basic Airflow cluster configuration for CeleryExecutor with Redis and
PostgreSQL.
#
# WARNING: This configuration is for local development. Do not use it in a
production deployment.
#
# This configuration supports basic configuration using environment
variables or an .env file
# The following variables are supported:
#
# AIRFLOW_IMAGE_NAME - Docker image name used to run Airflow.
# Default: apache/airflow:2.4.0
# AIRFLOW_UID - User ID in Airflow containers
# Default: 50000
# Those configurations are useful mostly in case of standalone
testing/running Airflow in test/try-out mode
#
# _AIRFLOW_WWW_USER_USERNAME - Username for the administrator account (if
requested).
# Default: airflow
# _AIRFLOW_WWW_USER_PASSWORD - Password for the administrator account (if
requested).
# Default: airflow
# _PIP_ADDITIONAL_REQUIREMENTS - Additional PIP requirements to add when
starting all containers.
# Default: ''
#
# Feel free to modify this file to suit your needs.
---
version: '3'
x-airflow-common:
&airflow-common
# In order to add custom dependencies or upgrade provider packages you can
use your extended image.
# Comment the image line, place your Dockerfile in the directory where you
placed the docker-compose.yaml
# and uncomment the "build" line below, Then run `docker-compose build` to
build the images.
image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.4.0}
# build: .
environment:
&airflow-common-env
AIRFLOW__CORE__EXECUTOR: LocalExecutor
AIRFLOW__DATABASE__SQL_ALCHEMY_CONN:
postgresql+psycopg2://airflow:airflow@postgres/airflow
# For backward compatibility, with Airflow <2.3
AIRFLOW__CORE__SQL_ALCHEMY_CONN:
postgresql+psycopg2://airflow:airflow@postgres/airflow
AIRFLOW__CORE__FERNET_KEY: ''
AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
AIRFLOW__CORE__LOAD_EXAMPLES: 'false'
AIRFLOW__API__AUTH_BACKENDS: 'airflow.api.auth.backend.basic_auth'
_PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
IS_LOCAL: 'true'
volumes:
- ./dags:/opt/airflow/dags
- ./logs:/opt/airflow/logs
- ./plugins:/opt/airflow/plugins
- ./kube.conf:/opt/airflow/kube.conf
- /var/run/docker.sock:/var/run/docker.sock
user: "${AIRFLOW_UID:-50000}:0"
group_add:
- '1001' # Add user to docker group. Change value depending on gid of
docker on your machine
depends_on:
&airflow-common-depends-on
redis:
condition: service_healthy
postgres:
condition: service_healthy
services:
postgres:
image: postgres:13
environment:
POSTGRES_USER: airflow
POSTGRES_PASSWORD: airflow
POSTGRES_DB: airflow
volumes:
- postgres-db-volume:/var/lib/postgresql/data
healthcheck:
test: ["CMD", "pg_isready", "-U", "airflow"]
interval: 5s
retries: 5
restart: always
redis:
image: redis:latest
expose:
- 6379
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 5s
timeout: 30s
retries: 50
restart: always
airflow-webserver:
<<: *airflow-common
command: webserver
ports:
- 8080:8080
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:8080/health";]
interval: 10s
timeout: 10s
retries: 5
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-scheduler:
<<: *airflow-common
command: scheduler
healthcheck:
test: ["CMD-SHELL", 'airflow jobs check --job-type SchedulerJob
--hostname "$${HOSTNAME}"']
interval: 10s
timeout: 10s
retries: 5
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-init:
<<: *airflow-common
entrypoint: /bin/bash
# yamllint disable rule:line-length
command:
- -c
- |
function ver() {
printf "%04d%04d%04d%04d" $${1//./ }
}
airflow_version=$$(AIRFLOW__LOGGING__LOGGING_LEVEL=INFO && gosu
airflow airflow version)
airflow_version_comparable=$$(ver $${airflow_version})
min_airflow_version=2.2.0
min_airflow_version_comparable=$$(ver $${min_airflow_version})
if (( airflow_version_comparable < min_airflow_version_comparable
)); then
echo
echo -e "\033[1;31mERROR!!!: Too old Airflow version
$${airflow_version}!\e[0m"
echo "The minimum Airflow version supported:
$${min_airflow_version}. Only use this or higher!"
echo
exit 1
fi
if [[ -z "${AIRFLOW_UID}" ]]; then
echo
echo -e "\033[1;33mWARNING!!!: AIRFLOW_UID not set!\e[0m"
echo "If you are on Linux, you SHOULD follow the instructions
below to set "
echo "AIRFLOW_UID environment variable, otherwise files will be
owned by root."
echo "For other operating systems you can get rid of the warning
with manually created .env file:"
echo " See:
https://airflow.apache.org/docs/apache-airflow/stable/howto/docker-compose/index.html#setting-the-right-airflow-user";
echo
fi
one_meg=1048576
mem_available=$$(($$(getconf _PHYS_PAGES) * $$(getconf PAGE_SIZE) /
one_meg))
cpus_available=$$(grep -cE 'cpu[0-9]+' /proc/stat)
disk_available=$$(df / | tail -1 | awk '{print $$4}')
warning_resources="false"
if (( mem_available < 4000 )) ; then
echo
echo -e "\033[1;33mWARNING!!!: Not enough memory available for
Docker.\e[0m"
echo "At least 4GB of memory required. You have $$(numfmt --to iec
$$((mem_available * one_meg)))"
echo
warning_resources="true"
fi
if (( cpus_available < 2 )); then
echo
echo -e "\033[1;33mWARNING!!!: Not enough CPUS available for
Docker.\e[0m"
echo "At least 2 CPUs recommended. You have $${cpus_available}"
echo
warning_resources="true"
fi
if (( disk_available < one_meg * 10 )); then
echo
echo -e "\033[1;33mWARNING!!!: Not enough Disk space available for
Docker.\e[0m"
echo "At least 10 GBs recommended. You have $$(numfmt --to iec
$$((disk_available * 1024 )))"
echo
warning_resources="true"
fi
if [[ $${warning_resources} == "true" ]]; then
echo
echo -e "\033[1;33mWARNING!!!: You have not enough resources to
run Airflow (see above)!\e[0m"
echo "Please follow the instructions to increase amount of
resources available:"
echo "
https://airflow.apache.org/docs/apache-airflow/stable/howto/docker-compose/index.html#before-you-begin";
echo
fi
mkdir -p /sources/logs /sources/dags /sources/plugins
chown -R "${AIRFLOW_UID}:0" /sources/{logs,dags,plugins}
exec /entrypoint airflow version
# yamllint enable rule:line-length
environment:
<<: *airflow-common-env
_AIRFLOW_DB_UPGRADE: 'true'
_AIRFLOW_WWW_USER_CREATE: 'true'
_AIRFLOW_WWW_USER_USERNAME: ${_AIRFLOW_WWW_USER_USERNAME:-airflow}
_AIRFLOW_WWW_USER_PASSWORD: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow}
_PIP_ADDITIONAL_REQUIREMENTS: ''
user: "0:0"
volumes:
- .:/sources
airflow-cli:
<<: *airflow-common
profiles:
- debug
environment:
<<: *airflow-common-env
CONNECTION_CHECK_MAX_COUNT: "0"
# Workaround for entrypoint issue. See:
https://github.com/apache/airflow/issues/16252
command:
- bash
- -c
- airflow
volumes:
postgres-db-volume:
```
### What happened
I was trying to test running a task using the `@task.docker` decorator, so I
set up the following DAG with a series of Docker tasks.
```python
from airflow import DAG
from airflow.decorators import task, dag
from docker.types import Mount
from datetime import datetime
@dag(
description='Run a series of Docker containers with outputs',
start_date=datetime(2022, 1, 1),
catchup=False,
schedule_interval=None,
)
def docker_parallel_decorator():
@task.docker(image="python:3.9-slim-bullseye", params={"expect_airflow":
False})
def container_a():
print("Hello from Container A")
return None
@task.docker(image="python:3.9-slim-bullseye", params={"expect_airflow":
False})
def container_b():
print("Hello from Container B")
return None
@task.docker(image="python:3.9-slim-bullseye", params={"expect_airflow":
False})
def container_c():
print("Hello from Container C")
return None
container_a() >> container_b() >> container_c()
docker_parallel_decorator()
```
In the past, I've had success with the DockerOperator, so I expected no
difference. However, I received the following error in the output log:
```
[2022-09-27, 17:37:03 UTC] {taskinstance.py:1851} ERROR - Task failed with
exception
Traceback (most recent call last):
File
"/home/airflow/.local/lib/python3.7/site-packages/airflow/providers/docker/decorators/docker.py",
line 111, in execute
filename=script_filename,
File
"/home/airflow/.local/lib/python3.7/site-packages/airflow/utils/python_virtualenv.py",
line 128, in write_python_script
template.stream(**jinja_context).dump(filename)
File
"/home/airflow/.local/lib/python3.7/site-packages/jinja2/environment.py", line
1618, in dump
fp.writelines(iterable)
File
"/home/airflow/.local/lib/python3.7/site-packages/jinja2/environment.py", line
1613, in <genexpr>
iterable = (x.encode(encoding, errors) for x in self) # type: ignore
File
"/home/airflow/.local/lib/python3.7/site-packages/jinja2/environment.py", line
1662, in __next__
return self._next() # type: ignore
File
"/home/airflow/.local/lib/python3.7/site-packages/jinja2/environment.py", line
1354, in generate
yield self.environment.handle_exception()
File
"/home/airflow/.local/lib/python3.7/site-packages/jinja2/environment.py", line
936, in handle_exception
raise rewrite_traceback_stack(source=source)
File
"/home/airflow/.local/lib/python3.7/site-packages/airflow/utils/python_virtualenv_script.jinja2",
line 23, in top-level template code
{% if expect_airflow %}
jinja2.exceptions.UndefinedError: 'expect_***' is undefined
```
### What you think should happen instead
I expected the Docker tasks to run the code in the provided Python function.
### How to reproduce
1. Deploy Airflow from the provided docker-compose.yaml file
2. Place the provided DAG into the `./dags` folder
3. Manually trigger the `docker_parallel_decorator` from the web UI
### Anything else
I have no experience with Jinja, so I don't know the specifics, but I
noticed that I was able to create a workaround by patching the
`/home/airflow/.local/lib/python3.7/site-packages/airflow/providers/docker/decorators/docker.py`
file in the `airflow-scheduler` service.
First, I copied the file out of the container.
```bash
docker compose cp
airflow-scheduler:/home/airflow/.local/lib/python3.7/site-packages/airflow/providers/docker/decorators/docker.py
./docker.py
```
Then I changed the following snippet starting on line 101:
```python
write_python_script(
jinja_context=dict(
op_args=self.op_args,
op_kwargs=self.op_kwargs,
pickling_library=self.pickling_library.__name__,
python_callable=self.python_callable.__name__,
python_callable_source=py_source,
string_args_global=False,
),
filename=script_filename,
)
```
To this:
```python
write_python_script(
jinja_context=dict(
op_args=self.op_args,
op_kwargs=self.op_kwargs,
pickling_library=self.pickling_library.__name__,
python_callable=self.python_callable.__name__,
python_callable_source=py_source,
string_args_global=False,
expect_airflow=False, # Added this line
),
filename=script_filename,
)
```
Then I copied the file back into the container.
```bash
docker compose cp ./docker.py
airflow-scheduler:/home/airflow/.local/lib/python3.7/site-packages/airflow/providers/docker/decorators/docker.py
```
After that, running the DAG resulted in no errors with the expected output
in the logs.
### Are you willing to submit PR?
- [ ] Yes I am willing to submit a PR!
### Code of Conduct
- [X] I agree to follow this project's [Code of
Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)
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