letyndr opened a new issue #12537:
URL: https://github.com/apache/airflow/issues/12537
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**Apache Airflow version**: apache-airflow==1.10.12
**Kubernetes version (if you are using kubernetes)** (use `kubectl
version`): Does not apply
**Environment**:
- **Cloud provider or hardware configuration**:
- **OS** (e.g. from /etc/os-release): Ubuntu 18.04.5 LTS bionic
- **Kernel** (e.g. `uname -a`): Linux letyndr-letyndr 4.15.0-123-generic
#126-Ubuntu SMP Wed Oct 21 09:40:11 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux
- **Install tools**:
- **Others**:
**What happened**:
I'm trying to use the docker operator to automate the execution of some
scripts using airflow.
What I want to do is to "copy" all my project's files (with folders and
files) to the container using this code.
The following file ml-intermediate.py is in this directory
~/airflow/dags/ml-intermediate.py:
```
"""
Template to convert a Ploomber DAG to Airflow
"""
from airflow import DAG
from airflow.operators.bash_operator import BashOperator
from airflow.utils.dates import days_ago
from ploomber.spec import DAGSpec
from soopervisor.script.ScriptConfig import ScriptConfig
script_cfg =
ScriptConfig.from_path('/home/letyndr/airflow/dags/ml-intermediate')
# Replace the project root to reflect the new location - or maybe just
# write a soopervisor.yaml, then we can we rid of this line
script_cfg.paths.project = '/home/letyndr/airflow/dags/ml-intermediate'
# TODO: use lazy_import from script_cfg
dag_ploomber =
DAGSpec('/home/letyndr/airflow/dags/ml-intermediate/pipeline.yaml',
lazy_import=True).to_dag()
dag_ploomber.name = "ML Intermediate"
default_args = {
'start_date': days_ago(0),
}
dag_airflow = DAG(
dag_ploomber.name.replace(' ', '-'),
default_args=default_args,
description='Ploomber dag',
schedule_interval=None,
)
script_cfg.save_script()
from airflow.operators.docker_operator import DockerOperator
for task_name in dag_ploomber:
DockerOperator(task_id=task_name,
image="continuumio/miniconda3",
api_version="auto",
auto_remove=True,
# command="sh /home/letyndr/airflow/dags/ml-intermediate/script.sh",
command="sleep 600",
docker_url="unix://var/run/docker.sock",
volumes=[
"/home/letyndr/airflow/dags/ml-intermediate:/home/letyndr/airflow/dags/ml-intermediate:rw",
"/home/letyndr/airflow-data/ml-intermediate:/home/letyndr/airflow-data/ml-intermediate:rw"
],
working_dir=script_cfg.paths.project,
dag=dag_airflow,
container_name=task_name,
)
for task_name in dag_ploomber:
task_ploomber = dag_ploomber[task_name]
task_airflow = dag_airflow.get_task(task_name)
for upstream in task_ploomber.upstream:
task_airflow.set_upstream(dag_airflow.get_task(upstream))
dag = dag_airflow
```
When I execute this DAG using Airflow, I get the error that the docker does
not find the `/home/letyndr/airflow/dags/ml-intermediate/script.sh` script. I
changed the execution command of the docker operator `sleep 600` to enter to
the container and check the files in the container with the corrects paths.
**What you expected to happen**: Basically to share the files of the host
with the docker container to execute a shell script within the container.
When I'm in the container I can go to this path
/home/letyndr/airflow/dags/ml-intermediate/ for example, but I don't see the
files that are supposed to be there.
**What do you think went wrong?**
I tried to replicate how Airflow implements Docker SDK for Python
This is my one replication of the docker implementation:
```
import docker
client = docker.APIClient()
# binds = {
# "/home/letyndr/airflow/dags": {
# "bind": "/home/letyndr/airflow/dags",
# "mode": "rw"
# },
# "/home/letyndr/airflow-data/ml-intermediate": {
# "bind": "/home/letyndr/airflow-data/ml-intermediate",
# "mode": "rw"
# }
# }
binds = ["/home/letyndr/airflow/dags:/home/letyndr/airflow/dags:rw",
"/home/letyndr/airflow-data/ml-intermediate:/home/letyndr/airflow-data/ml-intermediate:rw"]
container = client.create_container(
image="continuumio/miniconda3",
command="sleep 600",
volumes=["/home/letyndr/airflow/dags",
"/home/letyndr/airflow-data/ml-intermediate"],
host_config=client.create_host_config(binds=binds),
working_dir="/home/letyndr/airflow/dags",
name="simple_example",
)
client.start(container=container.get("Id"))
```
What I found was that mounting volumes only works if it's set `host_config`
and `volumes`, the problem is that the implementation on Airflow just set
`host_config` but not `volumes`. I added the parameter on the method
`create_container`, it worked.
**How to reproduce it**:
Mount a volume from a host and use the files inside the directory in the
docker container.
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