"""
Transform data from staging_raw table and load into fact tables.

Used by FlowLoadFactMixinSF mixin.
"""

from garcon import task

from feed_ingestion.conf.config import merge_configs
from feed_ingestion.flows import registered_executors
from feed_ingestion.flows.helpers import get_sf_config
from feed_ingestion.util import task_status


TASK_ID = 'load_fact_data'


@task.decorate(timeout=7200)
def create_staging_fact(
        activity, feed_name, date, sfdb_params, secrets_path=None,
        kwargs=None):
    """Create temp staging fact table for unloading fact and fact error data.

    Args:
        activity (ActivityWorker): The activity worker.
        feed_name (str): Name of the feed to get executor class.
        date (str): Date of the data being process (YYYY-MM-DD).
        sfdb_params (dict): Dict with params to optionally override default
            ones (Snowflake db and schema name).
        secrets_path (str): Secrets manager path of the flow.
    """
    # keyword arguments for the task
    kwargs = kwargs or {}

    # completion check
    if task_status.is_completed_task(feed_name, date, TASK_ID):
        activity.logger.info(
            'Task {task_id} of {feed_name} for {date} already complete, and '
            '"reload" flag was not passed, skipping...'.format(
                task_id=TASK_ID, feed_name=feed_name, date=date))
        return

    sf_config = get_sf_config(secrets_path)
    sf_config_custom = merge_configs(sf_config, sfdb_params)
    ExecutorFA = registered_executors.get(feed_name)
    with ExecutorFA(sf_config_custom) as sf_executor:
        sf_executor.drop_table(sf_executor.staging_fact_table(date))
        activity.logger.info('Staging fact table was dropped, if existed')
        sf_executor.create_staging_fact_table(date, **kwargs)
        activity.logger.info('Staging fact table was created')


@task.decorate(timeout=60*60*4)
def load_staging_fact(
        activity, feed_name, date,
        sfdb_params,
        secrets_path=None,
        kwargs=None):
    """Load staging fact_analytics table from staging_raw table.

    Args:
        activity (ActivityWorker): The activity worker.
        feed_name (str): Name of the feed to get executor class.
        date (str): Date of the data being process (YYYY-MM-DD).
        sfdb_params (dict): Dict with params to optionally override default
            ones (Snowflake db and schema name).
        secrets_path (str): Secrets manager path of the flow.
    """
    # keyword arguments for the task
    kwargs = kwargs or {}

    if task_status.is_completed_task(feed_name, date, TASK_ID):
        activity.logger.info(
            'Task {task_id} of {feed_name} for {date} already complete, and '
            '"reload" flag was not passed, skipping...'.format(
                task_id=TASK_ID, feed_name=feed_name, date=date))
        return

    sf_config = get_sf_config(secrets_path)
    sf_config_custom = merge_configs(sf_config, sfdb_params)
    ExecutorFA = registered_executors.get(feed_name)
    with ExecutorFA(sf_config_custom) as sf_executor:
        sf_executor.load_staging_fact_table(date, **kwargs)
    activity.logger.info(f'Data was loaded into staging fact table '
                         f'feed_name {feed_name} date {date}')


@task.decorate(timeout=14000)
def load_aggregated_skips_and_saves(activity, feed_name, date, sfdb_params,
                                    secrets_path=None, kwargs=None):
    """Load aggregated_skips_and_saves from staging fact_analytics table.

    Args:
        activity (ActivityWorker): The activity worker.
        feed_name (str): Name of the feed to get executor class.
        date (str): Date of the data being process (YYYY-MM-DD).
        sfdb_params (dict): Dict with params to optionally override default
            ones (Snowflake db and schema name).
        secrets_path (str): Secrets manager path of the flow.
        kwargs (dict): Custom activity params. Passed to snowflake_executor
    """
    task_id = 'load_aggregated_skips_and_saves'
    kwargs = kwargs or {}

    if task_status.is_completed_task(feed_name, date, task_id):
        activity.logger.info(
            'Task {task_id} of {feed_name} for {date} already complete, and '
            '"reload" flag was not passed, skipping...'.format(
                task_id=task_id, feed_name=feed_name, date=date))
        return

    sf_config = get_sf_config(secrets_path)
    sf_config_custom = merge_configs(sf_config, sfdb_params)
    ExecutorFA = registered_executors.get(feed_name)
    with ExecutorFA(sf_config_custom) as sf_executor:
        sf_executor.delete_from_aggregated_skips_and_saves(date, **kwargs)
        activity.logger.info(
            'Data was deleted from load_aggregated_skips_and_saves table')
        sf_executor.load_aggregated_skips_and_saves(date, **kwargs)
        activity.logger.info(
            'Data was loaded into load_aggregated_skips_and_saves table')

    task_status.mark_completed_task(feed_name, date, task_id)
    activity.logger.info(
        'Task {task_id} of {feed_name} for {date} completed'.format(
            task_id=task_id, feed_name=feed_name, date=date))


@task.decorate(timeout=60*60*5)
def load_fact_data(
        activity, feed_name, date, sfdb_params,
        secrets_path=None, kwargs=None):
    """Load data on fact_analytics & fact_analytics_error.

    Args:
        activity (ActivityWorker): The activity worker.
        feed_name (str): Name of the feed to get executor class.
        date (str): Date of the data being process (YYYY-MM-DD).
        sfdb_params (dict): Dict with params to optionally override default
            ones (Snowflake db and schema name).
        kwargs (dict): Custom activity params.
        secrets_path (str): Secrets manager path of the flow.
    """
    kwargs = kwargs or {}

    completed = task_status.is_completed_report(feed_name, date)
    if task_status.is_completed_task(feed_name, date, TASK_ID) and completed:
        activity.logger.info(
            'Task {task_id} of {feed_name} for {date} already complete, and '
            '"reload" flag was not passed, skipping...'.format(
                task_id=TASK_ID, feed_name=feed_name, date=date))
        return

    sf_config = get_sf_config(secrets_path)
    sf_config_custom = merge_configs(sf_config, sfdb_params)
    ExecutorFA = registered_executors.get(feed_name)
    with ExecutorFA(sf_config_custom) as sf_executor:
        message = 'Deleting rows for {date} from fact_analytics for feed ' \
                  '{feed_name} and kwargs {kwargs}'.format(date=date,
                                                           feed_name=feed_name,
                                                           kwargs=kwargs)
        activity.logger.info(message)
        sf_executor.delete_from_fact_table(date, **kwargs)

        activity.logger.info(
            'Loading fact_analytics for feed {}'.format(feed_name))
        sf_executor.load_fact_data(date, **kwargs)

    with ExecutorFA(sf_config_custom) as sf_executor:
        activity.logger.info(
            'Deleting rows for {date} from fact_analytics_error for feed '
            '{feed_name}'.format(date=date, feed_name=feed_name))
        sf_executor.delete_from_fact_error_table(date, **kwargs)

        activity.logger.info(
            'Loading fact_analytics_error for feed {}'.format(feed_name))
        sf_executor.load_fact_error_data(date, **kwargs)

        sf_executor.drop_table(sf_executor.staging_fact_table(date))
        activity.logger.info('Staging fact table was dropped')

    activity.logger.info(
        'Data was loaded into fact_analytics and fact_analytics_error')

    task_status.mark_completed_task(feed_name, date, TASK_ID)
    activity.logger.info(
        'Task {task_id} of {feed_name} for {date} completed'.format(
            task_id=TASK_ID, feed_name=feed_name, date=date))


@task.decorate(timeout=21600)
def update_dim_tables(
        activity, feed_name, date,
        sfdb_params, secrets_path=None, kwargs=None):
    """Update dimension tables.

    Args:
        activity (ActivityWorker): The activity worker.
        feed_name (str): Feed name of workflow execution for status updates.
        date (str): Reporting date (YYYY-MM-DD).
        sfdb_params (dict): Dict with params to optionally override default
            ones (Snowflake db and schema name).
        kwargs (dict): Custom activity params.
        secrets_path (str): Secrets manager path of the flow.
    """
    task_id = 'update_dim_tables'

    kwargs = kwargs or {}

    completed = task_status.is_completed_report(feed_name, date)
    if task_status.is_completed_task(feed_name, date, task_id) and completed:
        activity.logger.info(
            'Task {task_id} of {feed_name} for {date} already complete, and '
            '"reload" flag was not passed, skipping...'.format(
                task_id=task_id, feed_name=feed_name, date=date))
        return

    sf_config = get_sf_config(secrets_path)
    sf_config_custom = merge_configs(sf_config, sfdb_params)
    ExecutorFA = registered_executors.get(feed_name)
    with ExecutorFA(sf_config_custom) as sf_executor:
        sns_report = {}
        for table_name in kwargs['tables_to_update']:
            activity.logger.info('Updating {}...'.format(table_name))
            result = sf_executor.update_dimension_table(date, table_name)
            sns_report.update({table_name: result})
        activity.logger.info('All the dimension tables were updated.')

    changed_tables = [
        table_name for table_name in sns_report
        if sns_report[table_name].get(
            'number of rows inserted', 0) +
        sns_report[table_name].get('number of rows updated', 0)
        and table_name in kwargs['include_to_report']
    ]

    report_subject = '{feed_name} ETL for {date} update' \
                     ' following tables {tables}'.format(
                        date=date,
                        tables=', '.join(changed_tables),
                        feed_name=feed_name)

    if len(report_subject) > 100:
        report_subject = report_subject[0:96] + '...'

    context = {
        'sns_report_subject': report_subject,
        'sns_report_message':
            '\n'.join(
                '{table_name}: {inserted} rows inserted, '
                '{updated} rows updated'.format(
                    table_name=table_name,
                    inserted=sns_report[table_name].get(
                        'number of rows inserted', '0'),
                    updated=sns_report[table_name].get(
                        'number of rows updated', '0'))
                for table_name in changed_tables)
    }

    task_status.mark_completed_task(feed_name, date, task_id)
    activity.logger.info(
        'Task {task_id} of {feed_name} for {date} completed'.format(
            task_id=task_id, feed_name=feed_name, date=date))

    return context if context.get('sns_report_message') else {}