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from typing import Any
import pandas as pd
# pandas can take several different types of database connection,
# and itself exposes its connection parameters as "Any".
# This alias might help things be a bit clearer in our documentation.
DB = Any
def app_counts_for_workflow(workflow_id: Any, db: DB) -> pd.DataFrame:
return pd.read_sql_query("""
SELECT task_func_name, count(*) as 'frequency'
FROM task
WHERE run_id='%s'
GROUP BY task_func_name;
""" % workflow_id, db)
def nodes_for_workflow(workflow_id: Any, db: Any) -> pd.DataFrame:
return pd.read_sql_query("""
SELECT *
FROM node
WHERE run_id='%s';
""" % (workflow_id), db)
def resources_for_workflow(workflow_id: Any, db: Any) -> pd.DataFrame:
return pd.read_sql_query("""
SELECT *
FROM resource
WHERE run_id='%s';
""" % (workflow_id), db)
def resources_for_task(workflow_id: Any, task_id: Any, db: Any) -> pd.DataFrame:
return pd.read_sql_query("""
SELECT *
FROM resource
WHERE run_id='%s' AND task_id='%s';
""" % (workflow_id, task_id), db)
def status_for_workflow(workflow_id: Any, db: Any) -> pd.DataFrame:
return pd.read_sql_query("""
SELECT run_id, task_id, task_status_name, timestamp
FROM status
WHERE run_id='%s';
""" % workflow_id, db)
def completion_times_for_workflow(workflow_id: Any, db: Any) -> pd.DataFrame:
return pd.read_sql_query("""
SELECT task_id, task_func_name, task_time_returned
FROM task
WHERE run_id='%s'
""" % (workflow_id), db)
def tasks_for_workflow(workflow_id: Any, db: Any) -> pd.DataFrame:
return pd.read_sql_query("""
SELECT *
FROM task
WHERE run_id='%s'
""" % (workflow_id), db)
def tries_for_workflow(workflow_id: Any, db: Any) -> pd.DataFrame:
return pd.read_sql_query("""
SELECT task.task_id, task_func_name, task_time_returned, task_try_time_running, task_try_time_returned
FROM task, try
WHERE task.task_id = try.task_id AND task.run_id='%s' AND try.run_id='%s'
""" % (workflow_id, workflow_id), db)
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