# -*- coding:utf-8 -*-

from typing import List, Dict

from dw_base.hive.hive_constants import COLUMN_NAME_TYPE_DICT, COLUMN_NAME_COMMENT_DICT


def get_hive_database_name(project: str, layer: str, env: str) -> str:
    """
    获取Hive数据库名称
    Args:
        project: 所属项目
        layer: 所属层次
        env: 所属环境
    Returns: Hive数据库名称
    """
    if project and project != '':
        if layer and layer != '':
            database = f'{project}_{layer}'
        else:
            database = f'{project}_ods'
    elif layer and layer != '':
        database = layer
    else:
        database = 'tmp'
    if database != 'tmp' and env and env != '':
        database = f'{database}_{env}'
    return database


def get_hive_table_prefix(project: str, layer: str, version: str) -> str:
    """
    获取表名前缀
    Args:
        project: 所属项目
        layer: 所属层次
        version: 所属版本
    Returns: 表名前缀
    """
    if layer and layer != '':
        if project and project != '':
            prefix = f'{layer}_{project}'
        else:
            prefix = layer
        if version and version != '':
            prefix = f'{prefix}_{version}'
    elif project and project != '':
        prefix = project
    else:
        prefix = 'tmp'
    return prefix


def get_hive_create_table_ddl(database: str,
                              table: str,
                              columns: List[str],
                              columns_with_types: Dict,
                              comment: str = '',
                              is_external: bool = False,
                              is_partitioned: bool = False):
    """
    生成Hive建表语句
    Args:
        database: 数据库名称
        table: 表名称
        columns: 字段
        comment: 表注释
        is_external: 是否是外部表
        is_partitioned: 是否是分区表
    Returns:
    """
    ddl = "DROP TABLE IF EXISTS {0};\nCREATE {1}TABLE IF NOT EXISTS {2}\n(\n{3}\n)\n\tCOMMENT '{4}'\n{5}\tSTORED AS ORC\n;"
    if is_external:
        argument1 = 'EXTERNAL '
    else:
        argument1 = ''
    if database is None:
        table_with_database = table
    else:
        table_with_database = f'{database}.{table}'
    max_column_length = max(map(len, columns))
    column_defs = []
    for col in columns:
        padded_col = col.ljust(max_column_length, ' ')
        if columns_with_types.__contains__(col):
            col_type = columns_with_types.get(col)
        else:
            col_type = COLUMN_NAME_TYPE_DICT.get(col, 'STRING')
        col_comment = COLUMN_NAME_COMMENT_DICT.get(col, '')
        column_defs.append(f"    {padded_col} {col_type} COMMENT '{col_comment}'")
    argument3 = ',\n'.join(column_defs)
    if is_partitioned:
        argument5 = '\tPARTITIONED BY (dt STRING)\n'
    else:
        argument5 = ''
    return ddl.format(table_with_database, argument1, table_with_database, argument3, comment, argument5)


def get_hive_create_table_ddl_sop(database: str,
                                  table: str,
                                  columns: List[str],
                                  columns_with_types: Dict,
                                  comment: str = '',
                                  is_external: bool = False,
                                  is_partitioned: bool = False):
    """
    生成Hive建表语句
    Args:
        database: 数据库名称
        table: 表名称
        columns: 字段
        comment: 表注释
        is_external: 是否是外部表
        is_partitioned: 是否是分区表
    Returns:
    """
    ddl = "DROP TABLE IF EXISTS {0};\nCREATE {1}TABLE IF NOT EXISTS {2}\n(\n{3}\n)\n    COMMENT '{4}'\n{5}    STORED AS ORC\n;"
    if is_external:
        argument1 = 'EXTERNAL '
    else:
        argument1 = ''
    if database is None:
        table_with_database = table
    else:
        table_with_database = f'{database}.{table}'
    max_column_length = max(map(len, columns))
    column_defs = []
    for col in columns:
        padded_col = col.ljust(max_column_length, ' ')
        if columns_with_types.__contains__(col):
            col_type = columns_with_types.get(col)
        else:
            col_type = COLUMN_NAME_TYPE_DICT.get(col, 'STRING')
        col_comment = COLUMN_NAME_COMMENT_DICT.get(col, '')
        column_defs.append(f"    {padded_col} {col_type} COMMENT '{col_comment}'")
    argument3 = ',\n'.join(column_defs)
    if is_partitioned:
        argument5 = '    PARTITIONED BY (dt STRING)\n'
    else:
        argument5 = ''
    return ddl.format(table_with_database, argument1, table_with_database, argument3, comment, argument5)