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Requirements

docker-compose>=1.29.2, envsubst

Install

sudo useradd airflow
sudo usermod -aG docker airflow
AIRFLOW_UID=`id -u airflow` DOCKER_GID=`cut -d: -f3 < <(getent group docker)` envsubst < airflow/.env.template > airflow/.env

Set REVERSE_PROXY_HOST value in airflow/.env to desired public hostname or ip address (current host should be accessible by it over http).

If you want to use GPU during training edit airflow/.env:

TRAIN_ON_GPU=true

Run pipeline

cd airflow
docker-compose up

Run tests:

pip install -r test-requirements
# generate python client for airflow 2.3.0 using OpenAPI Generator
git clone git@github.com:apache/airflow-client-python.git
cd airflow-client-python
rm -r airflow_client/*
git clone git@github.com:apache/airflow
cd airflow/clients
git checkout tags/2.3.0
# use patched specification
cp ../../../airflow/v1.yaml ../airflow/api_connexion/openapi/v1.yaml
python ../../../add_auth_to_openapi.py --config ../airflow/api_connexion/openapi/v1.yaml --auth_options Basic
./gen/python.sh ../airflow/api_connexion/openapi/v1.yaml ../../airflow_client/
cd ../../..
pip install attrs==20.3.0
pip install cattrs==1.1.1
pip install ./airflow-client-python --no-cache --force
rm -r airflow-client-python

pytest tests/unit_tests
pytest tests/functional_tests

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Integration pipeline for neural network-based TPC model

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