def test_DataContextConfig_with_FilesystemStoreBackendDefaults_and_simple_defaults_no_root_directory(
construct_data_context_config, default_pandas_datasource_config
):
"""
What does this test and why?
Ensure that a very simple DataContextConfig setup using FilesystemStoreBackendDefaults is created accurately
This test does not set the optional root_directory parameter
"""
data_context_config = DataContextConfig(
datasources={
"my_pandas_datasource": DatasourceConfig(
class_name="PandasDatasource",
batch_kwargs_generators={
"subdir_reader": {
"class_name": "SubdirReaderBatchKwargsGenerator",
"base_directory": "../data/",
}
},
)
},
store_backend_defaults=FilesystemStoreBackendDefaults(),
)
# Create desired config
data_context_id = data_context_config.anonymous_usage_statistics.data_context_id
desired_config = construct_data_context_config(
data_context_id=data_context_id, datasources=default_pandas_datasource_config
)
data_context_config_schema = DataContextConfigSchema()
assert data_context_config_schema.dump(data_context_config) == desired_config
assert DataContext.validate_config(project_config=data_context_config)
def test_DataContextConfig_with_BaseStoreBackendDefaults_and_simple_defaults(
construct_data_context_config, default_pandas_datasource_config
):
"""
What does this test and why?
Ensure that a very simple DataContextConfig setup with many defaults is created accurately
and produces a valid DataContextConfig
"""
data_context_config = DataContextConfig(
datasources={
"my_pandas_datasource": DatasourceConfig(
class_name="PandasDatasource",
batch_kwargs_generators={
"subdir_reader": {
"class_name": "SubdirReaderBatchKwargsGenerator",
"base_directory": "../data/",
}
},
)
},
store_backend_defaults=BaseStoreBackendDefaults(),
)
desired_config = construct_data_context_config(
data_context_id=data_context_config.anonymous_usage_statistics.data_context_id,
datasources=default_pandas_datasource_config,
)
data_context_config_schema = DataContextConfigSchema()
assert data_context_config_schema.dump(data_context_config) == desired_config
assert DataContext.validate_config(project_config=data_context_config)
def test_DataContextConfig_with_FilesystemStoreBackendDefaults_and_simple_defaults(
construct_data_context_config, default_pandas_datasource_config
):
"""
What does this test and why?
Ensure that a very simple DataContextConfig setup using FilesystemStoreBackendDefaults is created accurately
This test sets the root_dir parameter
"""
test_root_directory = "test_root_dir"
store_backend_defaults = FilesystemStoreBackendDefaults(
root_directory=test_root_directory
)
data_context_config = DataContextConfig(
datasources={
"my_pandas_datasource": DatasourceConfig(
class_name="PandasDatasource",
batch_kwargs_generators={
"subdir_reader": {
"class_name": "SubdirReaderBatchKwargsGenerator",
"base_directory": "../data/",
}
},
)
},
store_backend_defaults=store_backend_defaults,
)
# Create desired config
data_context_id = data_context_config.anonymous_usage_statistics.data_context_id
desired_config = construct_data_context_config(
data_context_id=data_context_id, datasources=default_pandas_datasource_config
)
# Add root_directory to stores and data_docs
desired_config["stores"][desired_config["expectations_store_name"]][
"store_backend"
]["root_directory"] = test_root_directory
desired_config["stores"][desired_config["validations_store_name"]]["store_backend"][
"root_directory"
] = test_root_directory
desired_config["stores"][desired_config["checkpoint_store_name"]]["store_backend"][
"root_directory"
] = test_root_directory
desired_config["data_docs_sites"]["local_site"]["store_backend"][
"root_directory"
] = test_root_directory
data_context_config_schema = DataContextConfigSchema()
assert filter_properties_dict(
properties=data_context_config_schema.dump(data_context_config)
) == filter_properties_dict(properties=desired_config)
assert DataContext.validate_config(project_config=data_context_config)
def test_override_general_defaults(
construct_data_context_config,
default_pandas_datasource_config,
default_spark_datasource_config,
):
"""
What does this test and why?
A DataContextConfig should be able to be created by passing items into the constructor that override any defaults.
It should also be able to handle multiple datasources, even if they are configured with a dictionary or a DatasourceConfig.
"""
data_context_config = DataContextConfig(
config_version=999,
plugins_directory="custom_plugins_directory",
config_variables_file_path="custom_config_variables_file_path",
datasources={
"my_spark_datasource": {
"data_asset_type": {
"class_name": "SparkDFDataset",
"module_name": "great_expectations.dataset",
},
"class_name": "SparkDFDatasource",
"module_name": "great_expectations.datasource",
"batch_kwargs_generators": {},
},
"my_pandas_datasource": DatasourceConfig(
class_name="PandasDatasource",
batch_kwargs_generators={
"subdir_reader": {
"class_name": "SubdirReaderBatchKwargsGenerator",
"base_directory": "../data/",
}
},
),
},
stores={
"expectations_S3_store": {
"class_name": "ExpectationsStore",
"store_backend": {
"class_name": "TupleS3StoreBackend",
"bucket": "REPLACE_ME",
"prefix": "REPLACE_ME",
},
},
"expectations_S3_store2": {
"class_name": "ExpectationsStore",
"store_backend": {
"class_name": "TupleS3StoreBackend",
"bucket": "REPLACE_ME",
"prefix": "REPLACE_ME",
},
},
"validations_S3_store": {
"class_name": "ValidationsStore",
"store_backend": {
"class_name": "TupleS3StoreBackend",
"bucket": "REPLACE_ME",
"prefix": "REPLACE_ME",
},
},
"validations_S3_store2": {
"class_name": "ValidationsStore",
"store_backend": {
"class_name": "TupleS3StoreBackend",
"bucket": "REPLACE_ME",
"prefix": "REPLACE_ME",
},
},
"custom_evaluation_parameter_store": {
"class_name": "EvaluationParameterStore"
},
},
expectations_store_name="custom_expectations_store_name",
validations_store_name="custom_validations_store_name",
evaluation_parameter_store_name="custom_evaluation_parameter_store_name",
data_docs_sites={
"s3_site": {
"class_name": "SiteBuilder",
"store_backend": {
"class_name": "TupleS3StoreBackend",
"bucket": "REPLACE_ME",
},
"site_index_builder": {
"class_name": "DefaultSiteIndexBuilder",
"show_cta_footer": True,
},
},
"local_site": {
"class_name": "SiteBuilder",
"show_how_to_buttons": True,
"site_index_builder": {
"class_name": "DefaultSiteIndexBuilder",
"show_cta_footer": True,
},
"store_backend": {
"base_directory": "uncommitted/data_docs/local_site/",
"class_name": "TupleFilesystemStoreBackend",
},
},
},
validation_operators={
"custom_action_list_operator": {
"class_name": "ActionListValidationOperator",
"action_list": [
{
"name": "custom_store_validation_result",
"action": {"class_name": "CustomStoreValidationResultAction"},
},
{
"name": "store_evaluation_params",
"action": {"class_name": "StoreEvaluationParametersAction"},
},
{
"name": "update_data_docs",
"action": {"class_name": "UpdateDataDocsAction"},
},
],
}
},
anonymous_usage_statistics={"enabled": True},
)
desired_stores = {
"custom_evaluation_parameter_store": {"class_name": "EvaluationParameterStore"},
"expectations_S3_store": {
"class_name": "ExpectationsStore",
"store_backend": {
"bucket": "REPLACE_ME",
"class_name": "TupleS3StoreBackend",
"prefix": "REPLACE_ME",
},
},
"expectations_S3_store2": {
"class_name": "ExpectationsStore",
"store_backend": {
"bucket": "REPLACE_ME",
"class_name": "TupleS3StoreBackend",
"prefix": "REPLACE_ME",
},
},
"validations_S3_store": {
"class_name": "ValidationsStore",
"store_backend": {
"bucket": "REPLACE_ME",
"class_name": "TupleS3StoreBackend",
"prefix": "REPLACE_ME",
},
},
"validations_S3_store2": {
"class_name": "ValidationsStore",
"store_backend": {
"bucket": "REPLACE_ME",
"class_name": "TupleS3StoreBackend",
"prefix": "REPLACE_ME",
},
},
}
desired_data_docs_sites_config = {
"local_site": {
"class_name": "SiteBuilder",
"show_how_to_buttons": True,
"site_index_builder": {
"class_name": "DefaultSiteIndexBuilder",
"show_cta_footer": True,
},
"store_backend": {
"base_directory": "uncommitted/data_docs/local_site/",
"class_name": "TupleFilesystemStoreBackend",
},
},
"s3_site": {
"class_name": "SiteBuilder",
"site_index_builder": {
"class_name": "DefaultSiteIndexBuilder",
"show_cta_footer": True,
},
"store_backend": {
"bucket": "REPLACE_ME",
"class_name": "TupleS3StoreBackend",
},
},
}
desired_validation_operators = {
"custom_action_list_operator": {
"class_name": "ActionListValidationOperator",
"action_list": [
{
"name": "custom_store_validation_result",
"action": {"class_name": "CustomStoreValidationResultAction"},
},
{
"name": "store_evaluation_params",
"action": {"class_name": "StoreEvaluationParametersAction"},
},
{
"name": "update_data_docs",
"action": {"class_name": "UpdateDataDocsAction"},
},
],
}
}
desired_config = construct_data_context_config(
data_context_id=data_context_config.anonymous_usage_statistics.data_context_id,
datasources={
**default_pandas_datasource_config,
**default_spark_datasource_config,
},
config_version=999.0,
expectations_store_name="custom_expectations_store_name",
validations_store_name="custom_validations_store_name",
evaluation_parameter_store_name="custom_evaluation_parameter_store_name",
stores=desired_stores,
validation_operators=desired_validation_operators,
data_docs_sites=desired_data_docs_sites_config,
plugins_directory="custom_plugins_directory",
)
desired_config["config_variables_file_path"] = "custom_config_variables_file_path"
data_context_config_schema = DataContextConfigSchema()
assert data_context_config_schema.dump(data_context_config) == desired_config
assert DataContext.validate_config(project_config=data_context_config)
def test_DataContextConfig_with_DatabaseStoreBackendDefaults_using_all_parameters(
construct_data_context_config, default_pandas_datasource_config
):
"""
What does this test and why?
Make sure that DatabaseStoreBackendDefaults parameters are handled appropriately
E.g. Make sure that default_credentials is ignored if individual store credentials are passed
"""
data_context_config = DataContextConfig(
datasources={
"my_pandas_datasource": DatasourceConfig(
class_name="PandasDatasource",
module_name="great_expectations.datasource",
data_asset_type={
"module_name": "great_expectations.dataset",
"class_name": "PandasDataset",
},
batch_kwargs_generators={
"subdir_reader": {
"class_name": "SubdirReaderBatchKwargsGenerator",
"base_directory": "../data/",
}
},
)
},
store_backend_defaults=DatabaseStoreBackendDefaults(
default_credentials={
"drivername": "postgresql",
"host": "localhost",
"port": "65432",
"username": "******",
"password": "******",
"database": "ge_tutorials",
},
expectations_store_credentials={
"drivername": "custom_expectations_store_drivername",
"host": "custom_expectations_store_host",
"port": "custom_expectations_store_port",
"username": "******",
"password": "******",
"database": "custom_expectations_store_database",
},
validations_store_credentials={
"drivername": "custom_validations_store_drivername",
"host": "custom_validations_store_host",
"port": "custom_validations_store_port",
"username": "******",
"password": "******",
"database": "custom_validations_store_database",
},
expectations_store_name="custom_expectations_database_store_name",
validations_store_name="custom_validations_database_store_name",
evaluation_parameter_store_name="custom_evaluation_parameter_store_name",
),
)
# Create desired config
desired_stores_config = {
"custom_evaluation_parameter_store_name": {
"class_name": "EvaluationParameterStore"
},
"custom_expectations_database_store_name": {
"class_name": "ExpectationsStore",
"store_backend": {
"class_name": "DatabaseStoreBackend",
"credentials": {
"database": "custom_expectations_store_database",
"drivername": "custom_expectations_store_drivername",
"host": "custom_expectations_store_host",
"password": "******",
"port": "custom_expectations_store_port",
"username": "******",
},
},
},
"custom_validations_database_store_name": {
"class_name": "ValidationsStore",
"store_backend": {
"class_name": "DatabaseStoreBackend",
"credentials": {
"database": "custom_validations_store_database",
"drivername": "custom_validations_store_drivername",
"host": "custom_validations_store_host",
"password": "******",
"port": "custom_validations_store_port",
"username": "******",
},
},
},
}
desired_data_docs_sites_config = {
"local_site": {
"class_name": "SiteBuilder",
"show_how_to_buttons": True,
"site_index_builder": {
"class_name": "DefaultSiteIndexBuilder",
"show_cta_footer": True,
},
"store_backend": {
"base_directory": "uncommitted/data_docs/local_site/",
"class_name": "TupleFilesystemStoreBackend",
},
}
}
desired_config = construct_data_context_config(
data_context_id=data_context_config.anonymous_usage_statistics.data_context_id,
datasources=default_pandas_datasource_config,
expectations_store_name="custom_expectations_database_store_name",
validations_store_name="custom_validations_database_store_name",
evaluation_parameter_store_name="custom_evaluation_parameter_store_name",
stores=desired_stores_config,
data_docs_sites=desired_data_docs_sites_config,
)
data_context_config_schema = DataContextConfigSchema()
assert data_context_config_schema.dump(data_context_config) == desired_config
assert DataContext.validate_config(project_config=data_context_config)
def test_DataContextConfig_with_DatabaseStoreBackendDefaults(
construct_data_context_config, default_pandas_datasource_config
):
"""
What does this test and why?
Make sure that using DatabaseStoreBackendDefaults as the store_backend_defaults applies appropriate
defaults, including default_credentials getting propagated to stores and not data_docs
"""
data_context_config = DataContextConfig(
datasources={
"my_pandas_datasource": DatasourceConfig(
class_name="PandasDatasource",
module_name="great_expectations.datasource",
data_asset_type={
"module_name": "great_expectations.dataset",
"class_name": "PandasDataset",
},
batch_kwargs_generators={
"subdir_reader": {
"class_name": "SubdirReaderBatchKwargsGenerator",
"base_directory": "../data/",
}
},
)
},
store_backend_defaults=DatabaseStoreBackendDefaults(
default_credentials={
"drivername": "postgresql",
"host": "localhost",
"port": "65432",
"username": "******",
"password": "******",
"database": "ge_tutorials",
},
),
)
# Create desired config
desired_stores_config = {
"evaluation_parameter_store": {"class_name": "EvaluationParameterStore"},
"expectations_database_store": {
"class_name": "ExpectationsStore",
"store_backend": {
"class_name": "DatabaseStoreBackend",
"credentials": {
"drivername": "postgresql",
"host": "localhost",
"port": "65432",
"username": "******",
"password": "******",
"database": "ge_tutorials",
},
},
},
"validations_database_store": {
"class_name": "ValidationsStore",
"store_backend": {
"class_name": "DatabaseStoreBackend",
"credentials": {
"drivername": "postgresql",
"host": "localhost",
"port": "65432",
"username": "******",
"password": "******",
"database": "ge_tutorials",
},
},
},
}
desired_data_docs_sites_config = {
"local_site": {
"class_name": "SiteBuilder",
"show_how_to_buttons": True,
"site_index_builder": {
"class_name": "DefaultSiteIndexBuilder",
"show_cta_footer": True,
},
"store_backend": {
"base_directory": "uncommitted/data_docs/local_site/",
"class_name": "TupleFilesystemStoreBackend",
},
}
}
desired_config = construct_data_context_config(
data_context_id=data_context_config.anonymous_usage_statistics.data_context_id,
datasources=default_pandas_datasource_config,
expectations_store_name="expectations_database_store",
validations_store_name="validations_database_store",
evaluation_parameter_store_name=DataContextConfigDefaults.DEFAULT_EVALUATION_PARAMETER_STORE_NAME.value,
stores=desired_stores_config,
data_docs_sites=desired_data_docs_sites_config,
)
data_context_config_schema = DataContextConfigSchema()
assert data_context_config_schema.dump(data_context_config) == desired_config
assert DataContext.validate_config(project_config=data_context_config)
def test_DataContextConfig_with_GCSStoreBackendDefaults_using_all_parameters(
construct_data_context_config, default_pandas_datasource_config
):
"""
What does this test and why?
Make sure that GCSStoreBackendDefaults parameters are handled appropriately
E.g. Make sure that default_bucket_name is ignored if individual bucket names are passed
"""
data_context_config = DataContextConfig(
datasources={
"my_pandas_datasource": DatasourceConfig(
class_name="PandasDatasource",
module_name="great_expectations.datasource",
data_asset_type={
"module_name": "great_expectations.dataset",
"class_name": "PandasDataset",
},
batch_kwargs_generators={
"subdir_reader": {
"class_name": "SubdirReaderBatchKwargsGenerator",
"base_directory": "../data/",
}
},
)
},
store_backend_defaults=GCSStoreBackendDefaults(
default_bucket_name="custom_default_bucket_name",
default_project_name="custom_default_project_name",
expectations_store_bucket_name="custom_expectations_store_bucket_name",
validations_store_bucket_name="custom_validations_store_bucket_name",
data_docs_bucket_name="custom_data_docs_store_bucket_name",
expectations_store_project_name="custom_expectations_store_project_name",
validations_store_project_name="custom_validations_store_project_name",
data_docs_project_name="custom_data_docs_store_project_name",
expectations_store_prefix="custom_expectations_store_prefix",
validations_store_prefix="custom_validations_store_prefix",
data_docs_prefix="custom_data_docs_prefix",
expectations_store_name="custom_expectations_GCS_store_name",
validations_store_name="custom_validations_GCS_store_name",
evaluation_parameter_store_name="custom_evaluation_parameter_store_name",
),
)
# Create desired config
desired_stores_config = {
"custom_evaluation_parameter_store_name": {
"class_name": "EvaluationParameterStore"
},
"custom_expectations_GCS_store_name": {
"class_name": "ExpectationsStore",
"store_backend": {
"bucket": "custom_expectations_store_bucket_name",
"project": "custom_expectations_store_project_name",
"class_name": "TupleGCSStoreBackend",
"prefix": "custom_expectations_store_prefix",
},
},
"custom_validations_GCS_store_name": {
"class_name": "ValidationsStore",
"store_backend": {
"bucket": "custom_validations_store_bucket_name",
"project": "custom_validations_store_project_name",
"class_name": "TupleGCSStoreBackend",
"prefix": "custom_validations_store_prefix",
},
},
}
desired_data_docs_sites_config = {
"gcs_site": {
"class_name": "SiteBuilder",
"show_how_to_buttons": True,
"site_index_builder": {
"class_name": "DefaultSiteIndexBuilder",
"show_cta_footer": True,
},
"store_backend": {
"bucket": "custom_data_docs_store_bucket_name",
"project": "custom_data_docs_store_project_name",
"class_name": "TupleGCSStoreBackend",
"prefix": "custom_data_docs_prefix",
},
}
}
desired_config = construct_data_context_config(
data_context_id=data_context_config.anonymous_usage_statistics.data_context_id,
datasources=default_pandas_datasource_config,
expectations_store_name="custom_expectations_GCS_store_name",
validations_store_name="custom_validations_GCS_store_name",
evaluation_parameter_store_name="custom_evaluation_parameter_store_name",
stores=desired_stores_config,
data_docs_sites=desired_data_docs_sites_config,
)
data_context_config_schema = DataContextConfigSchema()
assert data_context_config_schema.dump(data_context_config) == desired_config
assert DataContext.validate_config(project_config=data_context_config)
def test_DataContextConfig_with_GCSStoreBackendDefaults(
construct_data_context_config, default_pandas_datasource_config
):
"""
What does this test and why?
Make sure that using GCSStoreBackendDefaults as the store_backend_defaults applies appropriate
defaults, including default_bucket_name & default_project_name getting propagated
to all stores.
"""
data_context_config = DataContextConfig(
datasources={
"my_pandas_datasource": DatasourceConfig(
class_name="PandasDatasource",
module_name="great_expectations.datasource",
data_asset_type={
"module_name": "great_expectations.dataset",
"class_name": "PandasDataset",
},
batch_kwargs_generators={
"subdir_reader": {
"class_name": "SubdirReaderBatchKwargsGenerator",
"base_directory": "../data/",
}
},
)
},
store_backend_defaults=GCSStoreBackendDefaults(
default_bucket_name="my_default_bucket",
default_project_name="my_default_project",
),
)
# Create desired config
data_context_id = data_context_config.anonymous_usage_statistics.data_context_id
desired_stores_config = {
"evaluation_parameter_store": {"class_name": "EvaluationParameterStore"},
"expectations_GCS_store": {
"class_name": "ExpectationsStore",
"store_backend": {
"bucket": "my_default_bucket",
"project": "my_default_project",
"class_name": "TupleGCSStoreBackend",
"prefix": "expectations",
},
},
"validations_GCS_store": {
"class_name": "ValidationsStore",
"store_backend": {
"bucket": "my_default_bucket",
"project": "my_default_project",
"class_name": "TupleGCSStoreBackend",
"prefix": "validations",
},
},
}
desired_data_docs_sites_config = {
"gcs_site": {
"class_name": "SiteBuilder",
"show_how_to_buttons": True,
"site_index_builder": {
"class_name": "DefaultSiteIndexBuilder",
"show_cta_footer": True,
},
"store_backend": {
"bucket": "my_default_bucket",
"project": "my_default_project",
"class_name": "TupleGCSStoreBackend",
"prefix": "data_docs",
},
}
}
desired_config = construct_data_context_config(
data_context_id=data_context_id,
datasources=default_pandas_datasource_config,
expectations_store_name="expectations_GCS_store",
validations_store_name="validations_GCS_store",
evaluation_parameter_store_name=DataContextConfigDefaults.DEFAULT_EVALUATION_PARAMETER_STORE_NAME.value,
stores=desired_stores_config,
data_docs_sites=desired_data_docs_sites_config,
)
data_context_config_schema = DataContextConfigSchema()
assert data_context_config_schema.dump(data_context_config) == desired_config
assert DataContext.validate_config(project_config=data_context_config)
def test_DataContextConfig_with_S3StoreBackendDefaults_and_simple_defaults_with_variable_sub(
monkeypatch, construct_data_context_config, default_pandas_datasource_config
):
"""
What does this test and why?
Ensure that a very simple DataContextConfig setup with many defaults is created accurately
and produces a valid DataContextConfig
"""
monkeypatch.setenv("SUBSTITUTED_BASE_DIRECTORY", "../data/")
data_context_config = DataContextConfig(
datasources={
"my_pandas_datasource": DatasourceConfig(
class_name="PandasDatasource",
batch_kwargs_generators={
"subdir_reader": {
"class_name": "SubdirReaderBatchKwargsGenerator",
"base_directory": "${SUBSTITUTED_BASE_DIRECTORY}",
}
},
)
},
store_backend_defaults=S3StoreBackendDefaults(
default_bucket_name="my_default_bucket"
),
)
# Create desired config
desired_stores_config = {
"evaluation_parameter_store": {"class_name": "EvaluationParameterStore"},
"expectations_S3_store": {
"class_name": "ExpectationsStore",
"store_backend": {
"bucket": "my_default_bucket",
"class_name": "TupleS3StoreBackend",
"prefix": "expectations",
},
},
"validations_S3_store": {
"class_name": "ValidationsStore",
"store_backend": {
"bucket": "my_default_bucket",
"class_name": "TupleS3StoreBackend",
"prefix": "validations",
},
},
}
desired_data_docs_sites_config = {
"s3_site": {
"class_name": "SiteBuilder",
"show_how_to_buttons": True,
"site_index_builder": {
"class_name": "DefaultSiteIndexBuilder",
"show_cta_footer": True,
},
"store_backend": {
"bucket": "my_default_bucket",
"class_name": "TupleS3StoreBackend",
"prefix": "data_docs",
},
}
}
desired_config = construct_data_context_config(
data_context_id=data_context_config.anonymous_usage_statistics.data_context_id,
datasources=default_pandas_datasource_config,
expectations_store_name="expectations_S3_store",
validations_store_name="validations_S3_store",
evaluation_parameter_store_name=DataContextConfigDefaults.DEFAULT_EVALUATION_PARAMETER_STORE_NAME.value,
stores=desired_stores_config,
data_docs_sites=desired_data_docs_sites_config,
)
desired_config["datasources"]["my_pandas_datasource"]["batch_kwargs_generators"][
"subdir_reader"
]["base_directory"] = "${SUBSTITUTED_BASE_DIRECTORY}"
data_context_config_schema = DataContextConfigSchema()
assert data_context_config_schema.dump(data_context_config) == desired_config
assert DataContext.validate_config(project_config=data_context_config)
data_context = BaseDataContext(project_config=data_context_config)
assert (
data_context.datasources["my_pandas_datasource"]
.get_batch_kwargs_generator("subdir_reader")
._base_directory
== "../data/"
)
