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Upgrade to SQLAlchemy 2.0.30 #73

Upgrade to SQLAlchemy 2.0.30

Upgrade to SQLAlchemy 2.0.30 #73

Workflow file for this run

name: Test Vertica-SQLAlchemy dialect
on:
push:
branches:
- main
pull_request:
branches:
- main
env:
DB_PWD: 'abc123'
jobs:
build:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.11']
steps:
- name: Check out repository
uses: actions/checkout@v3
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- name: Set up a VerticaDB server
timeout-minutes: 15
run: |
docker run -d -p 5433:5433 -p 5444:5444 \
--name vertica_docker \
vertica/vertica-ce:12.0.2-0
echo "Vertica startup ..."
until docker exec vertica_docker test -f /data/vertica/VMart/agent_start.out; do \
echo "..."; \
sleep 3; \
done;
echo "Vertica is up"
docker exec -u dbadmin vertica_docker /opt/vertica/bin/vsql -c "\l"
docker exec -u dbadmin vertica_docker /opt/vertica/bin/vsql -c "select version()"
- name: Add necessary schema into VerticaDB
timeout-minutes: 15
run: |
docker cp ddl.sql vertica_docker:/home/dbadmin/
docker exec vertica_docker sh -c "/opt/vertica/bin/vsql -w $DB_PWD -f /home/dbadmin/ddl.sql &&
sudo yum install git -y &&
cd /opt && sudo git clone https://github.com/vertica/Machine-Learning-Examples &&
sudo chmod -R a+rwx /opt/Machine-Learning-Examples &&
cd /opt/Machine-Learning-Examples/data && /opt/vertica/bin/vsql -w $DB_PWD -f load_ml_data.sql &&
cd .. &&
/opt/vertica/bin/vsql -w $DB_PWD -f naive_bayes/naive_bayes_data_preparation.sql &&
/opt/vertica/bin/vsql -w $DB_PWD -f naive_bayes/naivebayes_examples.sql &&
/opt/vertica/bin/vsql -w $DB_PWD -c 'select count(*) from v_catalog.tables'
"
- name: Install dependencies
run: |
python -m ensurepip --upgrade
python -m venv venv
source venv/bin/activate
python -m pip install setuptools wheel pytest pyodbc sqlalchemy==1.4.44
python setup.py install
- name: Run tests
# This step references the directory that contains the action.
uses: ./.github/actions/run-unit-test