def workflow_update_lusers(user_id, workflow_id, log_id):
"""
Recalculate the elements in field lusers of the workflow based on the fields
luser_email_column and luser_email_column_MD5
:param user_id: Id of User object that is executing the action
:param workflow_id: Id of workflow being processed
:param log_id: Id of the log object where the status has to be reflected
:return: Nothing, the result is stored in the log with log_id
"""
# First get the log item to make sure we can record diagnostics
log_item = get_log_item(log_id)
if not log_item:
return False
to_return = True
try:
user, wflow, __ = get_execution_items(user_id=user_id,
workflow_id=workflow_id)
workflow.ops.do_workflow_update_lusers(wflow, log_item)
# Reflect status in the log event
log_item.payload['status'] = 'Execution finished successfully'
log_item.save()
except Exception as e:
log_item.payload['status'] = \
ugettext('Error: {0}').format(e)
log_item.save()
to_return = False
return to_return
def run_plugin_task(user_id, workflow_id, plugin_id, input_column_names,
output_column_names, output_suffix, merge_key, parameters,
log_id):
"""
Execute the run method in a plugin with the dataframe from the given
workflow
:param user_id: Id of User object that is executing the action
:param workflow_id: Id of workflow being processed
:param plugin_id: Id of the plugin being executed
:param input_column_names: List of input column names
:param output_column_names: List of output column names
:param output_suffix: Suffix that is added to the output column names
:param merge_key: Key column to use in the merge
:param parameters: Dictionary with the parameters to execute the plug in
:param log_id: Id of the log object where the status has to be reflected
:return: Nothing, the result is stored in the log with log_id
"""
# First get the log item to make sure we can record diagnostics
log_item = get_log_item(log_id)
if not log_item:
return False
to_return = True
try:
user, workflow, __ = get_execution_items(user_id=user_id,
workflow_id=workflow_id)
plugin_info = Plugin.objects.filter(pk=plugin_id).first()
if not plugin_info:
raise Exception(
ugettext('Unable to load plugin with id {pid}').format(
plugin_id), )
# Set the status to "executing" before calling the function
log_item.payload['status'] = 'Executing'
log_item.save()
# Invoke plugin execution
run_plugin(workflow, plugin_info, input_column_names,
output_column_names, output_suffix, merge_key, parameters)
# Reflect status in the log event
log_item.payload['status'] = 'Execution finished successfully'
log_item.save()
except Exception as exc:
log_item.payload['status'] = ugettext('Error: {0}').format(str(exc))
log_item.save()
to_return = False
return to_return
def send_canvas_email_messages(user_id: int, log_id: int,
action_info: CanvasEmailPayload) -> bool:
"""
This function invokes send_messages in action, gets the message
that may be sent as a result, and records the appropriate events.
:param user_id: Id of User object that is executing the action
:param action_id: Id of Action object from where the messages are taken
:param subject: String for the email subject
:param email_column: Name of the column to extract email addresses
:param exclude_values: List of values to exclude from the mailing
:param target_url: The name of the server to use to send email
:param log_id: Id of the log object where the status has to be reflected
:return: bool stating if execution has been correct
"""
# First get the log item to make sure we can record diagnostics
log_item = get_log_item(log_id)
if not log_item:
return False
try:
user, __, action = get_execution_items(
user_id=user_id, action_id=action_info['action_id'])
# Set the status to "executing" before calling the function
log_item.payload['status'] = 'Executing'
log_item.save()
send_canvas_emails(
user,
action,
log_item,
action_info,
)
# Reflect status in the log event
log_item.payload['status'] = 'Execution finished successfully'
log_item.save()
except Exception as e:
log_item.payload['status'] = \
ugettext('Error: {0}').format(e)
log_item.save()
return False
return True
def send_json_objects(
user_id: int,
log_id: Log,
action_info: JSONPayload,
) -> bool:
"""Invokes send_json in action
Gets the JSON objects that may be sent as a result, and records the
appropriate events.
:param user_id: Id of User object that is executing the action
:param action_id: Id of Action object from where the messages are taken
:param token: String to include as authorisation token
:param key_column: Key column name to use to exclude elements (if needed)
:param exclude_values: List of values to exclude from the mailing
:param log_id: Id of the log object where the status has to be reflected
:return: Nothing
"""
# First get the log item to make sure we can record diagnostics
log_item = get_log_item(log_id)
if not log_item:
return False
to_return = True
try:
user, __, action = get_execution_items(
user_id=user_id,
action_id=action_info['action_id'])
# Set the status to "executing" before calling the function
log_item.payload['status'] = 'Executing'
log_item.save()
send_json(user, action, log_item, action_info)
# Reflect status in the log event
log_item.payload['status'] = 'Execution finished successfully'
log_item.save()
except Exception as e:
log_item.payload['status'] = \
ugettext('Error: {0}').format(e)
log_item.save()
to_return = False
return to_return
def athena_dataupload_task(user_id, workflow_id, conn_id, params, log_id):
"""Upload or merge data in the current workflow using an Athena connection.
:param user_id: Id of User object that is executing the action
:param workflow_id: Workflow to upload the data
:param conn_id: Athena connection ID
:param params: Dictionary with additional parameters or the operation
:param log_id: Id of the log object where the status has to be reflected
:return: Nothing, the result is stored in the log with log_id
"""
# First get the log item to make sure we can record diagnostics
log_item = get_log_item(log_id)
if not log_item:
return
try:
user, workflow, __ = get_execution_items(user_id=user_id,
workflow_id=workflow_id)
conn = AthenaConnection.objects.filter(enabled=True).filter(
pk=conn_id).first()
if not conn:
raise Exception(
ugettext('Unable to find connection with id {0}').format(
conn_id))
ontask.dataops.forms.dataframeupload.batch_load_df_from_athenaconnection(
workflow, conn, params, log_item)
# Reflect status in the log event
log_item.payload['status'] = 'Execution finished successfully'
log_item.payload['datetime'] = str(
datetime.datetime.now(pytz.timezone(settings.TIME_ZONE)))
log_item.save()
except Exception as e:
log_item.payload['status'] = \
ugettext('Error: {0}').format(e)
log_item.save()
return