"""Config for TikTok and Douyin Ingestion Workflow."""
import os

# Environment
environment = os.environ.get('Environment', 'dev')

# Feed configuration
store_id = 1202
feed_id = 45
feed_name = 'tiktok'
secrets_path = 'tiktok'
sme_secrets_path = 'swf-sme-ca-prod-partners-s3-access'

# Supported reports
reports = ['TikTok', 'Douyin']

DBT_REQUIRED_LICENSORS = ['theorchard', 'sme']

# orchard bucket for dropped data
drop_bucket = os.environ.get(
    'FEED_INGESTION_DROP_BUCKET',
    'dev-feed-drop')

# sme bucket for dropped data
sme_drop_bucket = os.environ.get(
    'SME_FEED_INGESTION_DROP_BUCKET',
    'sme-ca-prod-partners')

# altafonte bucket for dropped data
altafonte_drop_bucket = os.environ.get(
    'ALTAFONTE_FEED_INGESTION_DROP_BUCKET',
    'prod-orcd-ftp')

# bucket for archived data
data_bucket = os.environ.get(
    'FEED_INGESTION_DATA_BUCKET',
    'dev-cucumbers')

# drop and data buckets for different environments
if environment in ['dev']:
    drop_bucket = 'prod-orcd-ftp'
    data_bucket = 'dev-cucumbers'

if environment in ['qa']:
    drop_bucket = 'prod-orcd-ftp'
    data_bucket = 'qa-cucumbers'

if environment in ['production', 'prod']:
    drop_bucket = 'prod-orcd-ftp'
    data_bucket = 'cucumbers'

licensors = {
    'theorchard': {
        'reports': reports,
        's3': {
            'drop': 'ftp/data_feed/tiktok/',
            'archive': 'TikTok/archives/{date:%Y-%m-%d}/',
            'processed': 'TikTok/processed/{date:%Y-%m-%d}/',
            'filename': '{report}_Daily_Usage_Report_{date:%Y%m%d}.tsv.zip',
            'drop_bucket': drop_bucket
        },
        's3_sme': {
            'drop': 'tiktok/in/orchard/daily_trends/',
            'archive': 'TikTok/archives/{date:%Y-%m-%d}/',
            'processed': 'TikTok/processed/{date:%Y-%m-%d}/',
            'filename': '{report}_Daily_Usage_Report_{date:%Y%m%d}.tsv.zip',
            'drop_bucket': sme_drop_bucket
        },
    },
    'sme': {
        'reports': reports,
        's3': {
            'drop': 'tiktok/in/sme/daily_trends/',
            'archive': 'TikTok/archives_sme/{date:%Y-%m-%d}/',
            'processed': 'TikTok/archives_sme/{date:%Y-%m-%d}/',
            'filename': 'PLY3_D_{sme_report}_{date:%Y%m%d}.txt',
            'drop_bucket': sme_drop_bucket
        },
    },
    'smejp': {
        'reports': ['TikTok'],
        's3': {
            'drop': 'tiktok/in/smej/japan/',
            'archive': 'TikTok/archives_smejp/{date:%Y-%m-%d}/',
            'processed': 'TikTok/archives_smejp/{date:%Y-%m-%d}/',
            'filename': 'PLY3_D_{sme_report}_{date:%Y%m%d}.txt',
            'drop_bucket': sme_drop_bucket
        },
    },
    'smejpintl': {
        'reports': ['TikTok'],
        's3': {
            'drop': 'tiktok/in/smej/ww/',
            'archive': 'TikTok/archives_smejpintl/{date:%Y-%m-%d}/',
            'processed': 'TikTok/archives_smejpintl/{date:%Y-%m-%d}/',
            'filename': 'PLY3_D_{sme_report}_{date:%Y%m%d}.txt',
            'drop_bucket': sme_drop_bucket
        },
    },
    'altafonte': {
        'reports': reports,
        's3': {
            'drop': 'ftp/altafonte/merlin/tiktok/{date:%Y-%m-%d}/',
            'archive': 'TikTok/archives_altafonte/{date:%Y-%m-%d}/',
            'processed': 'TikTok/archives_altafonte/{date:%Y-%m-%d}/',
            'filename': ('altafonte-network-s-l_{report}_'
                         '{date:%Y%m%d}_Daily-Usage.tsv.zip'),
            'drop_bucket': altafonte_drop_bucket
        },
        'reports_new': ['TikTok'],
        's3_new': {
            'drop': 'tiktok/in/altafonte/daily_trends/',
            'archive': 'TikTok/archives_altafonte/{date:%Y-%m-%d}/',
            'processed': 'TikTok/archives_altafonte/{date:%Y-%m-%d}/',
            'filename': '{report}_Daily_Usage_Report_{date:%Y%m%d}.tsv.zip',
            'drop_bucket': sme_drop_bucket
        },
    }
}

# uses in filename template
sme_report_mapping = {
    'TikTok': 'ROW',
    'Douyin': 'CN'
}

altafonte_source_bucket_switch_date = '2024-10-30'

# Snowflake destination for the staging_raw and temp tables
# (separate from the default facts.prod used for dim tables)
consumer_sf = {
    'db': os.environ.get('CONSUMER_DB', 'consumer'),
    'schema': os.environ.get('CONSUMER_SCHEMA', 'tiktok'),
}

# Temp Staging Raw Table
temp_staging_raw_table = 'temp_staging_raw_{licensor}_{report}_{date:%Y%m%d}'

# Staging Raw Table
staging_raw_table = 'staging_raw_tiktok'

# The maximum allowed number of errors in the file
snowflake_error_limit = 10

# trigger DBT: dbt-scheduler-analytics-build-views
# MODEL=tag:tiktok_v2
# FORCE_MODEL_UPGRADE=True
jenkins_config = {
    'feeds_required_for_jenkins_build': [
        f'tiktok_{licensor}'
        for licensor in DBT_REQUIRED_LICENSORS
    ],
    'jenkins_username': os.environ.get('JENKINS_USER', 'jenkinsjobrunner'),
    'jenkins_secrets_path': 'swf-shared-jenkins',
    'jenkins_url': 'https://scheduler.theorchard.io',
    'jenkins_job': 'dbt-scheduler-analytics-parametrized-pipeline',
    'jenkins_job_params': {
        'MODELS': 'tag:tiktok_v2',
        'CLEAR_CACHE': True,
        'ENVIRONMENT': environment,
        'TRIGGER_TADAS': True,
    }
}