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Database containers

Allows to spin up docker database images such as MySQL, PostgreSQL, MariaDB, Oracle XE and MongoDb.

MySQL example

def test_docker_run_mysql():
    config = MySqlContainer('mysql:5.7.17')
    with config as mysql:
        e = sqlalchemy.create_engine(mysql.get_connection_url())
        result = e.execute("select version()")

It will spin up MySQL version 5.7. Then you can connect to database with credentials passed in constructor or just

call get_connection_url() method which returns sqlalchemy compatible url in format dialect+driver://username:password@host:port/database.

PostgresSQL

Example of PostgresSQL database usage:

def test_docker_run_postgress():
    postgres_container = PostgresContainer("postgres:9.5")
    with postgres_container as postgres:
        e = sqlalchemy.create_engine(postgres.get_connection_url())
        result = e.execute("select version()")

Connection set by using raw python psycopg2 driver for Postgres.

MariaDB

Maria DB is a fork of MySQL database, so the only difference with MySQL is the name of Docker container.

def test_docker_run_mariadb():
    mariadb_container = MariaDbContainer("mariadb:latest")
    with mariadb_container as mariadb:
        e = sqlalchemy.create_engine(mariadb.get_connection_url())
        result = e.execute("select version()")

Oracle XE

oracle = OracleDbContainer()

with oracle:
    e = sqlalchemy.create_engine(oracle.get_connection_url())
    result = e.execute("select 1 from dual")

It uses https://hub.docker.com/r/wnameless/oracle-xe-11g-r2/ docker image.

Necessary to use it:

hostname: localhost port: 49161 sid: xe username: system password: oracle

Elasticsearch

es = ElasticSearchContainer()
with es:
    es.get_url()  # gives you the http URL to connect to Elasticsearch

MongoDb

Example of MongoDb database usage:

def test_docker_run_mongodb():
    mongo_container = MongoDbContainer("mongo:latest")
    with mongo_container as mongo:
        db = mongo.get_connection_client().test
        result = db.restaurants.insert_one(
            {
                "address": {
                    "street": "2 Avenue",
                    "zipcode": "10075",
                    "building": "1480",
                    "coord": [-73.9557413, 40.7720266]
                },
                "borough": "Manhattan",
                "cuisine": "Italian",
                "name": "Vella",
                "restaurant_id": "41704620"
            }
        )
        print(result.inserted_id)
        cursor = db.restaurants.find({"borough": "Manhattan"})
        for document in cursor:
            print(document)

Connection is made using pymongo package and MongoClient class. Alternatively, you can use get_connection_url method to use the driver that better fits for your use case.