from utils.pg_client import PostgresClient
from decouple import config
from utils.df_utils import _process_pg_response
import numpy as np


def get_training_database(projectId, max_timestamp=None, favorites=False):
    """
    Gets training database using projectId, max_timestamp [optional] and favorites (if true adds favorites)
    Params:
        projectId: project id of all sessions to be selected.
        max_timestamp: max timestamp that a not seen session can have in order to be considered not interesting.
        favorites: True to use favorite sessions as interesting sessions reference.
    Output: Tuple (Set of features, set of labels, dict of indexes of each project_id, session_id, user_id in the set)
    """
    args = {"projectId": projectId, "max_timestamp": max_timestamp, "limit": 20}
    with PostgresClient() as conn:
        x1 = signals_features(conn, **args)
        if favorites:
            x2 = user_favorite_sessions(args['projectId'], conn)
        if max_timestamp is not None:
            x3 = user_not_seen_sessions(args['projectId'], args['limit'], conn)

    X_project_ids = dict()
    X_users_ids = dict()
    X_sessions_ids = dict()

    _X = list()
    _Y = list()
    _process_pg_response(x1, _X, _Y, X_project_ids, X_users_ids, X_sessions_ids, label=None)
    if favorites:
        _process_pg_response(x2, _X, _Y, X_project_ids, X_users_ids, X_sessions_ids, label=1)
    if max_timestamp:
        _process_pg_response(x3, _X, _Y, X_project_ids, X_users_ids, X_sessions_ids, label=0)
    return np.array(_X), np.array(_Y), \
           {'project_id': X_project_ids,
            'user_id': X_users_ids,
            'session_id': X_sessions_ids}


def signals_features(conn, **kwargs):
    """
    Selects features from frontend_signals table and mark as interesting given the following conditions:
        * If number of events is greater than events_threshold (default=10). (env value)
        * If session has been replayed more than once.
    """
    assert 'projectId' in kwargs.keys(), 'projectId should be provided in kwargs'
    projectId = kwargs['projectId']
    events_threshold = config('events_threshold', default=10, cast=int)
    query = conn.mogrify("""SELECT T.project_id,
                                   T.session_id,
                                   T.user_id,
                                   T2.viewer_id,
                                   T.events_count,
                                   T.errors_count,
                                   T.duration,
                                   T.country,
                                   T.issue_score,
                                   T.device_type,
                                   T2.interesting as train_label
                            FROM (SELECT project_id,
                                         user_id                                                            as viewer_id,
                                         session_id,
                                         count(CASE WHEN source = 'replay' THEN 1 END) > 1 OR COUNT(1) > %(events_threshold)s as interesting
                                  FROM frontend_signals
                                  WHERE project_id = %(projectId)s
                                    AND session_id is not null
                                  GROUP BY project_id, viewer_id, session_id) as T2
                                     INNER JOIN (SELECT project_id,
                                                        session_id,
                                                        user_id          as viewer_id,
                                                        user_id,
                                                        events_count,
                                                        errors_count,
                                                        duration,
                                                        user_country     as country,
                                                        issue_score,
                                                        user_device_type as device_type
                                                 FROM sessions
                                                 WHERE project_id = %(projectId)s
                                                   AND duration IS NOT NULL) as T
                                                USING (session_id);""",
                         {"projectId": projectId, "events_threshold": events_threshold})
    conn.execute(query)
    res = conn.fetchall()
    return res


def user_favorite_sessions(projectId, conn):
    """
    Selects features from user_favorite_sessions table.
    """
    query = """SELECT project_id,
                       session_id,
                       T1.user_id,
                       events_count,
                       errors_count,
                       duration,
                       user_country     as country,
                       issue_score,
                       user_device_type as device_type,
                       T2.user_id       AS viewer_id
                FROM sessions AS T1
                         INNER JOIN user_favorite_sessions as T2
                                    USING (session_id)
                WHERE project_id = %(projectId)s;"""
    conn.execute(
        conn.mogrify(query, {"projectId": projectId})
    )
    res = conn.fetchall()
    return res


def user_not_seen_sessions(projectId, limit, conn):
    """
    Selects features from user_viewed_sessions table.
    """
    # TODO: fetch un-viewed sessions alone, and the users list alone, then cross join them in python
    # and ignore deleted users (WHERE users.deleted_at ISNULL)
    query = """SELECT project_id, session_id, user_id, viewer_id, events_count, errors_count, duration, user_country as country, issue_score, user_device_type as device_type
FROM (
         (SELECT sessions.*
         FROM sessions LEFT JOIN user_viewed_sessions USING(session_id)
         WHERE project_id = %(projectId)s  
            AND duration IS NOT NULL
            AND user_viewed_sessions.session_id ISNULL
         LIMIT %(limit)s) AS T1
             LEFT JOIN
         (SELECT user_id as viewer_id
         FROM users
         WHERE tenant_id = (SELECT tenant_id FROM projects WHERE project_id = %(projectId)s)) AS T2 ON true
     )"""
    conn.execute(
        conn.mogrify(query, {"projectId": projectId, "limit": limit})
    )
    res = conn.fetchall()
    return res