"""Config."""
import os


env = os.environ.get('Environment')

FEED_NAME = 'label_spike_detector'

ACTIVITY_TYPE_NAME = 'spike_detector'

STATUS_PROCESSED = 'PROCESSED'
STATUS_PROCESSED_NOTIF_SENT = 'PROCESSED_NOTIF_SENT'

SWF_FLOW_NAME = ACTIVITY_TYPE_NAME
SWF_FLOW_VERSION = '1.0'

DEFAULT_SHIFT_DAYS = 2
DEFAULT_WINDOW_DAYS = 90
Z_SCORE_THRESHOLD = 4.5

MIN_TRACK_STREAMS = 1000
MAX_TRACKS_PER_ACCOUNT = 5000
MAX_SPIKES_PER_ACCOUNT = 10
MIN_STREAM_GAIN = 1000  # min value of (today - avg) to count a track a spike

# track's release_date <= CURRENT_DATE - MIN_RELEASE_DATE_SHIFT_DAYS
MIN_RELEASE_DATE_SHIFT_DAYS = 28

# number of days to look back for playlist placements
PLAYLIST_PLACEMENTS_SHIFT_DAYS = 7

# maximum number of playlists to retrieve for each spike
MAX_PLAYLISTS_TO_SHOW = 5

# fraction of total streams on target date playlist must have to be returned
PLAYLIST_STREAMS_THRESHOLD = 0.1

STORES = {
    286: 'spotify',
    1: 'apple music',
    1202: 'tiktok'
}

# spike detection in fact_analytics streams and for tiktok creations
TYPES = ['streams', 'tiktok']

TEMP_TABLE_NAME = 'TEMP_ACTIVITY_SPIKE_HISTORY_{type}'