def _load_data(
connection_string: str,
dialect: str,
table_name: str = TAXI_DATA_TABLE_NAME,
random_table_suffix: bool = True,
) -> LoadedTable:
dialects_supporting_multiple_values_in_single_insert_clause: List[str] = [
"redshift"
]
to_sql_method: str = (
"multi" if dialect
in dialects_supporting_multiple_values_in_single_insert_clause else
None)
# Load the first 10 rows of each month of taxi data
return load_data_into_test_database(
table_name=table_name,
csv_paths=[
f"./data/ten_trips_from_each_month/yellow_tripdata_sample_10_trips_from_each_month.csv"
],
connection_string=connection_string,
convert_colnames_to_datetime=["pickup_datetime", "dropoff_datetime"],
load_full_dataset=True,
random_table_suffix=random_table_suffix,
to_sql_method=to_sql_method,
)
UserConfigurableProfiler, )
context = ge.get_context()
# </snippet>
# This utility is not for general use. It is only to support testing.
from tests.test_utils import load_data_into_test_database
# The following load & config blocks up until the batch requests are only to support testing.
MY_CONNECTION_STRING = "mysql+pymysql://root@localhost/test_ci"
PG_CONNECTION_STRING = "postgresql+psycopg2://postgres:@localhost/test_ci"
load_data_into_test_database(
table_name="taxi_data",
csv_path="./data/yellow_tripdata_sample_2019-01.csv",
connection_string=MY_CONNECTION_STRING,
)
load_data_into_test_database(
table_name="taxi_data",
csv_path="./data/yellow_tripdata_sample_2019-01.csv",
connection_string=PG_CONNECTION_STRING,
)
pg_datasource_config = {
"name": "my_postgresql_datasource",
"class_name": "Datasource",
"execution_engine": {
"class_name": "SqlAlchemyExecutionEngine",
"connection_string": f"{PG_CONNECTION_STRING}",
import os
from ruamel import yaml
import great_expectations as ge
CONNECTION_STRING = "postgresql+psycopg2://postgres:@localhost/test_ci"
# This utility is not for general use. It is only to support testing.
from tests.test_utils import load_data_into_test_database
load_data_into_test_database(
table_name="titanic",
csv_path="./data/Titanic.csv",
connection_string=CONNECTION_STRING,
load_full_dataset=True,
)
context = ge.get_context()
# parse great_expectations.yml for comparison
great_expectations_yaml_file_path = os.path.join(
context.root_directory, "great_expectations.yml"
)
with open(great_expectations_yaml_file_path) as f:
great_expectations_yaml = yaml.safe_load(f)
actual_datasource = great_expectations_yaml["datasources"]
# expected Datasource
expected_existing_datasource_yaml = r"""