def setUpClass(cls):
mdb, datastore = run_environment(
config,
apis=['mysql'],
override_integration_config={
'default_clickhouse': {
'publish': True
}
},
override_api_config={'mysql': {
'ssl': False
}},
mindsdb_database=MINDSDB_DATABASE)
cls.mdb = mdb
models = cls.mdb.get_models()
models = [x['name'] for x in models]
if TEST_PREDICTOR_NAME in models:
cls.mdb.delete_model(TEST_PREDICTOR_NAME)
query('create database if not exists test_data')
if not USE_EXTERNAL_DB_SERVER:
test_csv_path = Path(DATASETS_PATH).joinpath(
TEST_DATASET).joinpath('data.csv')
if TEST_DATA_TABLE not in cls.get_tables_in(cls, 'test_data'):
print('creating test data table...')
upload_csv(
query=query,
columns_map=DATASETS_COLUMN_TYPES[TEST_DATASET],
db_types_map=DB_TYPES_MAP,
table_name=TEST_DATA_TABLE,
csv_path=test_csv_path,
template=
'create table test_data.%s (%s) ENGINE = MergeTree() ORDER BY days_on_market PARTITION BY location'
)
ds = datastore.get_datasource(EXTERNAL_DS_NAME)
if ds is not None:
datastore.delete_datasource(EXTERNAL_DS_NAME)
data = fetch(f'select * from test_data.{TEST_DATA_TABLE} limit 50')
external_datasource_csv = make_test_csv(EXTERNAL_DS_NAME, data)
datastore.save_datasource(EXTERNAL_DS_NAME, 'file', 'test.csv',
external_datasource_csv)
def setUpClass(cls):
mdb, datastore = run_environment(config,
apis=['mysql', 'http'],
mindsdb_database=MINDSDB_DATABASE)
cls.mdb = mdb
query('create database if not exists test_data')
if not USE_EXTERNAL_DB_SERVER:
test_csv_path = Path(DATASETS_PATH).joinpath(
TEST_DATASET).joinpath('data.csv')
if TEST_DATA_TABLE not in cls.get_tables_in(cls, 'test_data'):
print('creating test data table...')
upload_csv(query=query,
columns_map=DATASETS_COLUMN_TYPES[TEST_DATASET],
db_types_map=DB_TYPES_MAP,
table_name=TEST_DATA_TABLE,
csv_path=test_csv_path)
data = fetch(f'select * from test_data.{TEST_DATA_TABLE} limit 50',
as_dict=True)
cls.external_datasource_csv_path = make_test_csv(
EXTERNAL_DS_NAME, data)
def setUpClass(cls):
mdb, datastore = run_environment(
config,
apis=['http', 'mysql'],
override_integration_config={'default_mariadb': {
'publish': True
}},
mindsdb_database=MINDSDB_DATABASE)
cls.mdb = mdb
models = cls.mdb.get_models()
models = [x['name'] for x in models]
if TEST_PREDICTOR_NAME in models:
cls.mdb.delete_model(TEST_PREDICTOR_NAME)
if not USE_EXTERNAL_DB_SERVER:
query('create database if not exists test_data')
test_tables = fetch('show tables from test_data', as_dict=False)
test_tables = [x[0] for x in test_tables]
if TEST_DATA_TABLE not in test_tables:
test_csv_path = Path(DATASETS_PATH).joinpath(
TEST_DATASET).joinpath('data.csv')
upload_csv(query=query,
columns_map=DATASETS_COLUMN_TYPES[TEST_DATASET],
db_types_map=DB_TYPES_MAP,
table_name=TEST_DATA_TABLE,
csv_path=test_csv_path)
ds = datastore.get_datasource(EXTERNAL_DS_NAME)
if ds is not None:
datastore.delete_datasource(EXTERNAL_DS_NAME)
data = fetch(f'select * from test_data.{TEST_DATA_TABLE} limit 50')
external_datasource_csv = make_test_csv(EXTERNAL_DS_NAME, data)
datastore.save_datasource(EXTERNAL_DS_NAME, 'file', 'test.csv',
external_datasource_csv)
print(msg)
if __name__ == "__main__":
# Create the workspace.
print(f'creating workspace "{WORKSPACE}"...')
result = create_workspace(WORKSPACE)
response = result.json()
if response["errors"]:
print("errors encountered:\n", *response["errors"], sep="\n")
sys.exit(1)
else:
print("created succesfully")
# Upload the data tables.
for table in ["members", "clubs", "membership"]:
print(f"uploading {table}...")
result = upload_csv(f"data/{table}.csv", WORKSPACE, table)
if result.status_code != 200:
error_message(result.json())
sys.exit(1)
print("tables uploaded successfully")
# Create the graph.
print("creating graph...")
graph = create_graph(WORKSPACE, "boston", ["members", "clubs"],
"membership")
pprint(graph.json())