New Gherkin Step Definitions per Release

Discover the latest features and enhancements in pytest-bdd-ewx for an improved testing experience.

New steps in pytest-bdd-ewx in Release 25.02

Statement File Location	Type	Step Definition	What Is It Used For?
channel_classifier/steps.py	Then	I view the list of channel classifiers, I expect the channel "{channel_name}" to have the attribute "{attr_name}" with the value "{attr_value}"	Checks that the channel classifier has the expected attribute when Browse the list of channels.
channel_classifier/steps.py	Then	I view the list of channel classifiers, I expect the channel "{channel_name}" to have the datapoint attribute "{dpa_name}" of type "{dpa_type}"	Checks that the channel classifier has the expected DPA when Browse the list of channels.
channel_classifier/steps.py	Then	I view the list of channel classifiers, I expect the channel "{channel_name}" the datapoint attribute "{dpa_name}" to include enum values "{enum_values}"	Checks that the channel classifier has the expected list of enums in the DPA.
datasource/steps.py	Given	I expect no channels for the datasource with id "{datasource_id}"	Checks that a datasource has no channels.
datasource/steps.py	Then	I expect no channels for the datasource with id "{datasource_id}"	Checks that a datasource has no channels.
datasource/steps.py	Then	I expect response containing "{ds_ids}" when I search for datasources with query "{search_filter}" and filter by the datasource classifier "{ds_classifier_name}"	Queries datasources and filters by the datasource classifier. Verifies the required IDs are returned.
datasource/steps.py	Then	I expect response containing "{ds_ids}" when I search for datasources with query "{search_filter}"	Queries datasources, verifies the required IDs are returned.
datasource/steps.py	Then	I expect response containing "{ds_ids}" when I search for datasources with no query and filter by the datasource classifier "{ds_classifier_name}"	Search for datasources, filter by the datasource classifier. Verifies the required IDs are returned.
datasource/steps.py	Then	I expect response containing "{ds_ids}" when I search for datasources with no filters	Search for datasources without filters, verifies the required IDs are returned.
datasource/steps.py	Then	I do not expect response to contain "{unexpected_ds_ids}" when I search for datasources with query "{search_filter}" and filter by the datasource classifier "{ds_classifier_name}"	Verifies that datasources from the list are not returned by search with query and datasource classifier.
datasource/steps.py	Then	I do not expect response to contain "{unexpected_ds_ids}" when I search for datasources with query "{search_filter}"	Verifies that datasources from the list are not returned by search with query.
datasource/steps.py	Then	I do not expect response to contain "{unexpected_ds_ids}" when I search for datasources with no query and filter by the datasource classifier "{ds_classifier_name}"	Verifies that datasources from the list are not returned by search by datasource classifier filter.
datasource/steps.py	Then	I expect response to contain only datasources with id "{expected_ds_ids}" when I search for datasources with query "{query}"	Verifies that only expected datasources are returned by search with query.
datasource/steps.py	Then	I expect response to contain only datasources with id "{expected_ds_ids}" when I search for datasources with query "{query}" and filter by the datasource classifier "{ds_classifier_name}"	Verifies that only expected datasources are returned by search with query and filter by datasource classifier.
tag/steps.py	When	I create a tag with the name "{tag_name}" with a property "{property_name}" and a value "{property_value}" for datasource "{datasource_id}"	Creates a tag on the specified datasource. Valid from and version are set to 2000-01-01T00:00:00Z.
tag/steps.py	When	I create a tag with the name "{tag_name}" with a property "{property_name}" and a value "{property_value}" for datasource "{datasource_id}" and version "{version}"	Creates a tag on the specified datasource with specific version. Valid from is set to 2000-01-01T00:00:00Z.
tag/steps.py	When	I create a tag with the name "{tag_name}" with a property "{property_name}", valid from "{valid_from}" and a value "{property_value}" for datasource "{datasource_id}" and version "{version}"	Creates a tag on the specified datasource with specific version and valid from values.
tag/steps.py	When	I expect no tags for datasource "{datasource_id}"	Verifies no tags for the given datasource id
time_series/steps.py	Then	I expect in datasource with id "{datasource_id}" channel "{channel_classifier}" to have "{amount:d}" values from "{start_date}" for "{years}" years	Validates a timeseries data point is present in a channel classifier.
time_series/steps.py	Then	I expect in channel "{channel_classifier}" an annotation on index "{timestamp}" for property "{annotation_key}" with value "{annotation_value}" for datasource with ID "{datasource_id}"	Validates data point attribute values in a channel classifier.
time_series/steps.py	Then	I expect in datasource with id "{datasource_id}" in channel "{channel_classifier}" data point "{timestamp}", "{value}"	Validates a timeseries data point is present in a channel classifier.
time_series/steps.py	Then	I expect in datasource with id "{datasource_id}" for the last flow on the destination channel "{destination_classifier}" in channel "{channel_classifier}" data point "{timestamp}", "{value}"	Validates a timeseries data point is present in a channel classifier for the last flow run.
time_series/steps.py	Then	I expect no annotation for property "{annotation_key}" with value "{annotation_value}" in channel "{channel_classifier}" for the last flow on the destination channel "{destination_classifier}" on index "{timestamp}" for datasource with ID "{datasource_id}"	Validates data point attribute values in a channel classifier.
time_series/steps.py	Then	I expect on datasource with id "{datasource_id}" channel "{channel_classifier}" to have exactly "{amount:d}" values between "{start_date}" and "{end_date}"	Validates if exact amount of timeseries data point is present in a channel classifier.
time_series/steps.py	Then	I expect on datasource with id "{datasource_id}" for the last flow on the destination channel "{destination_classifier}" in channel "{channel_classifier}" to have exactly "{amount:d}" values between "{start_date}" and "{end_date}"	Validates if exact amount of timeseries data point is present in a channel classifier for the last flow run.
time_series/steps.py	Then	I expect the datapoint attribute-value pairs "{dpa_name}" and "{dpa_value}" in datasource with id "{datasource_id}" in channel "{channel_classifier}" on timestamp "{timestamp}"	Validates data point attribute values in a channel classifier.
time_series/steps.py	Then	I expect the following datapoint attribute-value pairs in datasource with id "{datasource_id}" in channel "{channel_classifier}" on timestamp "{timestamp}":\n{dpa_value_table}	Validates data point attribute values in a channel classifier.
time_series/steps.py	Then	I verify the timeseries datapoint version of channel "{channel_classifier}" in ds id "{datasource_id}" with timestamp "{timestamp}" got updated with new datapoint version value after ingestion	Verify DP version value got updated after ingestion.
time_series/steps.py	Then	I expect on datasource with id "{datasource_id}" channel "{channel_classifier}" to have exactly "{amount:d} datapoint attribute values with the name "{dpa_name}" between "{start_date}" and "{end_date}"	Validates if exact amount of specified datapoint attribute is present in a channel classifier.
time_series/steps.py	Then	I expect on datasource with id "{datasource_id}" channel "{channel_classifier}" to have exactly "{amount:d}" annotations with the name "{annotation_name}" and the property "{annotation_prop_name}" between "{start_date}" and "{end_date}"	Validates if exact amount of annotations is present in a channel classifier.
time_series/steps.py	Then	I expect channels with the names "{channel_list}" to have timeseries data between "{start_date}" and "{end_date}" on the datasource with id "{datasource_id}" when using "{view}" view for version depth "{version_depth}"	Verify that each channel from a given list contains timeseries data within a specified date range for the given datasource id with the requested view and specific version depth.
time_series/steps.py	Then	I expect channels with the names "{channel_list}" to have timeseries data between "{start_date}" and "{end_date}" on the datasource with id "{datasource_id}"	Verify that each channel from a given list contains timeseries data within a specified date range for the given datasource id.
time_series/steps.py	Then	I expect channels with the names "{channel_list}" to have timeseries data between "{start_date}" and "{end_date}" for channel family "{channel_family}" on the datasource with id "{datasource_id}" when using "{view}" view for version depth "{version_depth}"	Verify that each channel from a given list contains timeseries data within a specified date range and channel family filter for the given datasource id with the requested view and specific version depth.
time_series/steps.py	Then	I expect channels with the names "{channel_list}" to have timeseries data between "{start_date}" and "{end_date}" for channel family "{channel_family}" on the datasource with id "{datasource_id}"	Verify that each channel from a given list contains timeseries data within a specified date range and channel family filter for the given datasource id.
time_series/steps.py	Then	I expect on datasource with id "{datasource_id}" channel "{channel_classifier}" to have exactly "{amount:d}" annotations with the name "{annotation_name}" and the property "{annotation_prop_name}" between "{start_date}" and "{end_date}" when using "{view}" view for version depth "{version_depth}"	Validates if exact amount of annotations is present in a channel classifier with the requested view and specific version depth.
time_series/steps.py	Then	I expect on datasource with id "{datasource_id}" channel "{channel_classifier}" to have exactly "{amount:d}" annotations with the name "{annotation_name}" and the property "{annotation_prop_name}" between "{start_date}" and "{end_date}"	Validates if exact amount of annotations is present in a channel classifier.
time_series/steps.py	Then	I expect on datasource with id "{datasource_id}" channel "{channel_classifier}" to have exactly "{amount:d}" datapoint attribute values with the name "{dpa_name}" between "{start_date}" and "{end_date}" when using "{view}" view for version depth "{version_depth}"	Validates if exact amount of specified datapoint attribute is present in a channel classifier with the requested view and specific version depth.
time_series/steps.py	Then	I expect on datasource with id "{datasource_id}" channel "{channel_classifier}" to have exactly "{amount:d}" datapoint attribute values with the name "{dpa_name}" between "{start_date}" and "{end_date}"	Validates if exact amount of specified datapoint attribute is present in a channel classifier.
time_series/steps.py	Then	I expect no timeseries data for the datasource with id "{datasource_id}"	Checks the datasource has no timeseries data.
time_series/steps.py	Then	I expect on datasource with id "{datasource_id}" channel "{channel_classifier}" to have exactly "{amount:d}" flags with the name "{flag_name}" between "{start_date}" and "{end_date}" when using "{view}" view for version depth "{version_depth:d}"	Validates if exact amount of specified flag is present in a channel classifier with the requested view and specific version depth.
tag/steps.py	Then	I expect the tag with name "{tag_name}" to have property "{property_name}" with value "{property_value}" for datasource "{datasource_id}" and for a given version	Checks that a tag has a specific value for a given version.
tag/steps.py	Then	I expect the tag with name "{tag_name}" for datasource with id "{datasource_id}" to have value "{tag_value}" in the tag attribute	Verifies the tag has the specified value.
time_series/steps.py	Given	I expect the datapoint with timestamp "{timestamp}" has a version_ts between "{start_date}" and "{end_date}" for channel "{channel_classifier}" in datasource with id "{datasource_id}"	Validates that the datapoint has the correct version timestamp.

New steps in pytest-bdd-ewx in Release 25.03

Statement File Location	Type	Step Definition	What Is It Used For?
time_series/steps.py	Then	I expect a datapoint on timestamp "{timestamp}" to have a new version for continuous flow channel "{channel_name}" on datasource with id "{datasource_id}" after datapoint editing	Checks that the datapoint version is updated after editing for continuous flow channel.
time_series/steps.py	Then	I expect a datapoint on timestamp "{timestamp}" to have the same version for scenario flow channel "{channel_name}" on datasource with id "{datasource_id}" after datapoint editing	Checks that the datapoint version is not updated after editing for a scenario flow channel.
time_series/steps.py	Then	I expect the annotation "{annotation_name}" previous value to be equal to "{value}" for the timestamp "{timestamp}" on the channel "{annotation_channel}" in the edits history for the datasource with id "{datasource_id}"(?: with edit reason "{edit_reason}" and user email "{user_email}")?	Checks that the previous value of an annotation is as expected in the edits history. Optionally, edit reason and user email can be verified in the edits history.
time_series/steps.py	Then	I expect the datapoint attribute "{dpa_name}" previous value to be equal to "{value}" for the timestamp "{timestamp}" on the channel "{channel_name}" in the edits history for the datasource with id "{datasource_id}"(?: with edit reason "{edit_reason}" and user email "{user_email}")?	Checks that the previous value of a datapoint attribute is as expected in the edits history. Optionally, edit reason and user email can be verified in the edits history.
time_series/steps.py	Then	I expect the datapoint previous value to be equal to "{value}" for the timestamp "{timestamp}" on the channel "{channel_name}" in the edits history for the datasource with id "{datasource_id}"(?: with edit reason "{edit_reason}" and user email "{user_email}")?	Checks that the previous value of a datapoint is as expected in the edits history. Optionally, edit reason and user email can be verified in the edits history.
datapoint/steps.py	When	I edit on datasource "{datasource_id}" for channel "{channel_classifier}" at "{timestamp}" the annotation with the name "{annotation_key}" to the value "{value}" with edit reason "{edit_reason}"	Edits a single annotation value for a specified timestamp.
datapoint/steps.py	When	I edit on datasource "{datasource_id}" for channel "{channel_classifier}" at "{timestamp}" the datapoint attribute with the name "{dpa_name}" to the value "{value}" with edit reason "{edit_reason}"	Edits a single datapoint value for a specified timestamp.
datapoint/steps.py	When	I edit on datasource "{datasource_id}" for channel "{channel_classifier}" at "{timestamp}" the value to "{value}" with edit reason "{edit_reason}"	Edits a single datapoint value for a specified timestamp.
datapoint/steps.py	When	I edit on datasource "{datasource_id}" the following annotations with edit reason "{edit_reason}":\n{datatable}	Edits multiple annotations for a specified datasource using a datatable.
datapoint/steps.py	When	I edit on datasource "{datasource_id}" the following datapoint attributes with edit reason "{edit_reason}":\n{datatable}	Edits multiple datapoint attributes for a specified datasource using a datatable.
datapoint/steps.py	When	I edit on datasource "{datasource_id}" the following datapoint values with edit reason "{edit_reason}":\n{datatable}	Edits multiple datapoint values for a specified datasource using a datatable.

New steps in pytest-bdd-ewx in Release 25.04

Clients

Statement File Location	Type	Step Definition	What Is It Used For?
clients.py	Given	I use the namespace with the name "{nsp_name}"	This step is used to get the namespace id by name and set it for the test run.

Datasource

Statement File Location	Type	Step Definition	What Is It Used For?
datasource/steps.py	Given	I expect a new flow with config name "{flow_name}" and status "{flow_status}" with channel classifier "{channel_classifier}" on datasource "{datasource_id}" within "{timeout:d}" minutes with a poll frequency of "{freq:d}" seconds	Checks if amount of new successful or failed flows with channel classifier is as expected.
datasource/steps.py	Then	I expect a new flow with config name "{flow_name}" and status "{flow_status}" with channel classifier "{channel_classifier}" on datasource "{datasource_id}" within "{timeout:d}" minutes with a poll frequency of "{freq:d}" seconds	Checks if amount of new successful or failed flows with channel classifier is as expected.

Query

Statement File Location	Type	Step Definition	What Is It Used For?
query/steps.py	Then	I use advanced search to check the annotation "{annotation_name}" with the key "{annotation_key}" on the sequence id "{sequence_id}" has a value "{value}" for the timestamp "{timestamp}" for the channel "{channel_name}" on a datasource with id "{datasource_id}" after (?:flow execution|ingestion)	Uses advanced search to check the annotation value of a datapoint after ingestion.
query/steps.py	Then	I use advanced search to check the datapoint attribute "{dpa_name}" value is "{value}" for the timestamp "{timestamp}" for the channel "{channel_name}" on a datasource with id "{datasource_id}" after (?:flow execution|ingestion)	Uses advanced search to check the DPA value of a datapoint.
query/steps.py	Then	I use advanced search to check the datapoint value is "{value}" for the timestamp "{timestamp}" for the channel "{channel_name}" on a datasource with id "{datasource_id}" after (?:flow execution|ingestion)	Uses advanced search to check the datapoint value of a datapoint after ingestion.

Tasks

Statement File Location	Type	Step Definition	What Is It Used For?
tasks/steps.py	Then	I expect "{amount:d}" task(s) with the title "{title}" within "{time_limit_in_minutes:d}" minutes with a poll frequency of "{polling_frequency_in_seconds:d}" seconds	Poll to check if the expected amount of tasks with given title exist.
tasks/steps.py	When	I expect "{amount:d}" task(s) with the title "{title}" within "{time_limit_in_minutes:d}" minutes with a poll frequency of "{polling_frequency_in_seconds:d}" seconds	Poll to check if the expected amount of tasks with given title exist.