DataCenterGame/app/etl/MaterialLibrary/MaterialDataClean.py

"""
desc : 素材库数据清洗
每日运行一次

"""
from model.DataBaseUtils import MysqlUtils

db = MysqlUtils()


def title():
    sql = """select REPLACE(REPLACE(title, CHAR(10), ''), CHAR(13), '') content,
        cast(sum(cost) as float) consume_amount,
        sum(click_count) click_times,
        sum(view_count) view_times,
        cast(count(*) as decimal(10,2)) use_times,
        group_concat(distinct book) novels,
        max(dt) end_date,min(dt) start_date 
        from dw_image_cost_day where title!='' and title is not null  GROUP BY REPLACE(REPLACE(title, CHAR(10), ''), CHAR(13), '')
				"""

    df = db.dm.pd_data_sql(sql)

    df["data_type"] = 'all'
    df['type'] = '1'
    df['create_by'] = '0'

    key = ["content", "type"]
    tag = ["view_times", "click_times", "novels", "start_date", "end_date", "create_by", 'data_type',
           'consume_amount']
    table = "t_ads_content"
    db.zx_ads.dfsave2mysql(df, table, key, tag)


def description():
    sql = """select REPLACE(REPLACE(description, CHAR(10), ''), CHAR(13), '') content,
            sum(cost) consume_amount,
            sum(click_count) click_times,
            sum(view_count) view_times,
            cast(count(*) as decimal(10,2)) use_times,
            group_concat(distinct book) novels,
            max(dt) end_date,min(dt) start_date
            from dw_image_cost_day where description!='' and description is not null  GROUP BY REPLACE(REPLACE(description, CHAR(10), ''), CHAR(13), '')
    				"""

    df = db.dm.pd_data_sql(sql)

    # print(df)

    df["data_type"] = 'all'
    df['type'] = '2'
    df['create_by'] = '0'
    key = ["content", "type"]
    tag = ['use_times', "view_times", "click_times", "novels", "start_date", "end_date", "create_by", 'data_type',
           'consume_amount']
    table = "t_ads_content"

    db.zx_ads.dfsave2mysql(df, table, key, tag)


def image():

    sql = """select signature,sum(consume_amount) consume_amount,
            sum(click_times) click_times,
            sum(view_times) view_times,
            sum(use_times) use_times,
            group_concat(distinct novels) novels ,
            max(end_date) end_date,
            min(start_date) start_date,
            min(content) content,
            min(type) type,  
            if(locate(',',signature)>0,0,1) single_img,
            min(width ) width ,
            min(height ) height ,
            min(media_size) media_size ,
            min(media_format) media_format,
            min(video_length) video_length,
            min(video_bit_rate) video_bit_rate,
            0 max_media_size 
        from (select replace(signature,' ,','') as signature ,
            sum(cost) consume_amount,
            sum(click_count) click_times,
            sum(use_times) use_times,
            sum(view_count) view_times,
            group_concat(distinct book) novels ,
            max(dt) end_date,
            min(dt) start_date,
            replace (min(preview_url),' ,','') as content,
            if(is_video=1,2,1) type,  
            if(locate(',',signature)>0,0,1) single_img,
            min(replace(if(left (width ,2)='0,',substring(width ,3),width) ,',0','')) width ,
			min(replace(if(left (height ,2)='0,',substring(height ,3),height) ,',0','')) height,
			min(replace(if(left (size ,2)='0,',substring(size ,3),size) ,',0','')) media_size ,
            min(replace(format ,' ,','')) media_format,
            min(video_length) video_length,
            min(video_bit_rate) video_bit_rate
            from dw_image_cost_day  
            where signature is not null and signature !=''  
            and length (replace (replace (signature,',',''),' ',''))>0
            GROUP BY  signature,is_video) as foo
            group by signature   
            """

    # df = db.dm.getData_pd(sql)
    df = db.dm.pd_data_sql(sql)
    # print(df)
    # 进行数据转换-----添加max_media_size
    for i in range(len(df['media_size'])):
        if not df['media_size'][i]:
            continue
        size_list = df['media_size'][i].split(',')
        max_size = 0
        for size_data in size_list:
            if size_data != 'None':
                if float(size_data) > max_size:
                    max_size = str(size_data)
        df['max_media_size'][i] = max_size

    df['create_by'] = '0'
    df["data_type"] = 'all'

    key = ["signature"]
    tag = ['media_size', 'media_format', 'video_length', 'video_bit_rate', 'use_times', "view_times", "click_times", "novels", "start_date", "end_date", "create_by", "single_img",
           "content", 'consume_amount', 'type', 'width', 'height']
    table = "t_ads_media"

    db.zx_ads.dfsave2mysql(df, table, key, tag)


def adcreative():
    sql = """select  signature,title,article,
sum(click_times) click_times,
sum(view_times) view_times,
sum(use_times) use_times,
sum(consume_amount) consume_amount,
group_concat(distinct novels) novels,
min(start_date) start_date,
max(end_date) end_date,
min(media) media,
min(channel) channel ,
min(type) type,
if(locate(',',signature)>0,0,1) single_img,
min(width) width ,
min(height) height,
min(media_size) media_size ,
min(media_format) media_format,
min(video_length) video_length,
min(video_bit_rate) video_bit_rate,
0 max_media_size 
from 
 (select replace(signature ,' ,','') as signature,title,description article,
sum(click_count) click_times,
sum(view_count) view_times,
sum(use_times) use_times,
sum(cost) consume_amount,
group_concat(distinct book) novels,
min(dt) start_date,max(dt) end_date,
min(replace(preview_url ,' ,','')) media,
min(replace(if(left (width ,2)='0,',substring(width ,3),width) ,',0','')) width ,
min(replace(if(left (height ,2)='0,',substring(height ,3),height) ,',0','')) height ,
min(replace(if(left (size ,2)='0,',substring(size ,3),size) ,',0','')) media_size ,
min(replace(format ,' ,','')) media_format,
min(video_length) video_length,
min(video_bit_rate) video_bit_rate,
type channel,
if(is_video=1,2,1) type,
if(locate(',',signature)>0,0,1) single_img
from dw_image_cost_day where signature is not null and signature!=''   
GROUP BY  signature,title,description,type,is_video) as foo
group by signature ,title,article  """

    # df = db.dm.getData_pd(sql)
    df = db.dm.pd_data_sql(sql)
    # 进行数据转换-----添加max_media_size
    for i in range(len(df['media_size'])):
        if not df['media_size'][i]:
            continue
        size_list = df['media_size'][i].split(',')
        max_size = 0
        for size_data in size_list:
            if size_data != 'None':
                if float(size_data) > max_size:
                    max_size = str(size_data)
        df['max_media_size'][i] = max_size

    key = ["signature", 'title', 'article']
    tag = ['media_size', 'media_format', 'video_length', 'video_bit_rate', 'max_media_size', 'use_times', "view_times",
           "click_times", "novels", "start_date", "end_date", "type", "channel",
           'consume_amount', 'single_img', 'media', 'width', 'height']
    table = "t_ads_idea"

    db.zx_ads.dfsave2mysql(df, table, key, tag)


def run():
    title()
    description()
    image()
    adcreative()


if __name__ == '__main__':
    run()
    # title()
    # description()
    # image()
    # adcreative()