def init(datetime):
global articles,products,order_product_counts,cart_product_counts,tags
product_df=da.getDataFrame('product',datetime)
article_df=da.getDataFrame('article',datetime)
tags_df=da.getDataFrame('product_list',datetime)
products=da.rowGroupCount(product_df[pd.notnull(product_df['device_id'])],'values')
articles=da.rowGroupCount(article_df[pd.notnull(article_df['device_id'])],'values')
tags=da.rowGroupCount(tags_df[pd.notnull(tags_df['device_id'])],'values')
order_product_counts=da.getOrderCounts(datetime)
cart_product_counts=da.getCartCount(datetime)
def init(datetime):
global articles, products, order_product_counts, cart_product_counts, tags
product_df = da.getDataFrame('product', datetime)
article_df = da.getDataFrame('article', datetime)
tags_df = da.getDataFrame('product_list', datetime)
products = da.rowGroupCount(
product_df[pd.notnull(product_df['device_id'])], 'values')
articles = da.rowGroupCount(
article_df[pd.notnull(article_df['device_id'])], 'values')
tags = da.rowGroupCount(tags_df[pd.notnull(tags_df['device_id'])],
'values')
order_product_counts = da.getOrderCounts(datetime)
cart_product_counts = da.getCartCount(datetime)
def community_static(datetime):
global like_df,follow_df,view_df,reply_df
likes=da.rowGroupCount(like_df,'values')
follows=da.rowGroupCount(follow_df,'values')
views=da.rowGroupCount(view_df,'values')
replies=da.rowGroupCount(reply_df,'values')
result='\n'
result=result+pr_format.format('topic_id','view_count','like','follow','reply')
for topic_id in views.keys()[:50]:
result=result+pr_format.format(id_util.decode_topic(topic_id),views.get(topic_id,0),likes.get(topic_id,0),\
follows.get(topic_id,0),replies.get(topic_id,0))
result+='sum\n'
result+=pr_format.format(len(views.keys()),sum(views),sum(likes),sum(follows),sum(replies))
return result
def community_summarize(datetime):
global list_df,create_df,privateMsg_df
result=''
result+='private_message,'+str(len(privateMsg_df))+'\n\n'
lists=da.rowGroupCount(list_df,'values')
creates=da.rowGroupCount(create_df,'values')
users=da.getUniqueDevice(datetime,'topic_list','values')
result=result+sum_pr_format.format('node_id','node_pv','topic_create','user')
for node_id in lists.keys():
result=result+sum_pr_format.format(id_util.decode_node(node_id),lists[node_id],\
creates.get(node_id,0),users.get(node_id,0))
result=result+'sum\n'
result=result+sum_pr_format.format(len(lists.keys()),sum(lists),sum(creates),sum(users))
return result
def init(datetime):
global articles,products,order_product_counts,cart_product_counts,tags,\
product_unique_visitor,article_unique_visitor,tag_unique_visitor
product_df = da.getDataFrame('product', datetime)
article_df = da.getDataFrame('article', datetime)
tags_df = da.getDataFrame('product_list', datetime)
products = da.rowGroupCount(product_df, 'values')
articles = da.rowGroupCount(article_df, 'values')
tags = da.rowGroupCount(tags_df, 'values')
order_product_counts = da.getOrderCounts(datetime)
cart_product_counts = da.getCartCount(datetime)
product_unique_visitor = da.getDfUniqueDevice(product_df, 'values')
article_unique_visitor = da.getDfUniqueDevice(article_df, 'values')
tag_unique_visitor = da.getDfUniqueDevice(tags_df, 'values')
def init(datetime):
global articles,products,order_product_counts,cart_product_counts,tags,\
product_unique_visitor,article_unique_visitor,tag_unique_visitor
product_df=da.getDataFrame('product',datetime)
article_df=da.getDataFrame('article',datetime)
tags_df=da.getDataFrame('product_list',datetime)
products=da.rowGroupCount(product_df,'values')
articles=da.rowGroupCount(article_df,'values')
tags=da.rowGroupCount(tags_df,'values')
order_product_counts=da.getOrderCounts(datetime)
cart_product_counts=da.getCartCount(datetime)
product_unique_visitor=da.getDfUniqueDevice(product_df,'values')
article_unique_visitor=da.getDfUniqueDevice(article_df,'values')
tag_unique_visitor=da.getDfUniqueDevice(tags_df,'values')
def save_data(datetime,limit):
product_view_counts=da.rowGroupCount(da.getDataFrame('product',datetime),'values')
order_product_counts=da.getOrderCounts(datetime)
cart_product_counts=da.getCartCount(datetime)
result=da.rowGroupCount(da.getDataFrame('article',datetime),'values')
article_ids=result.keys()[:limit]
for article_id in article_ids:
product_ids=api_util.getProductIdInArticle(article_id)
if product_ids:
for product_id in product_ids:
db.save_article_data(datetime,id_util.decode_article(article_id),result[article_id],product_id,\
da.getProductCounts(product_view_counts,id_util.encode_product(product_id)),\
da.getProductCounts(cart_product_counts,id_util.encode_product(product_id)),\
da.getProductCounts(order_product_counts,id_util.encode_product(product_id)))
else:
db.save_article_data(datetime,id_util.decode_article(article_id),result[article_id],0,0,0,0)
def article_statics(datetime,limit):
print datetime
product_view_counts=da.rowGroupCount(da.getDataFrame('product',datetime),'values')
order_product_counts=da.getOrderCounts(datetime)
cart_product_counts=da.getCartCount(datetime)
result=da.rowGroupCount(da.getDataFrame('article',datetime),'values')
article_ids=result[:limit].keys()
article_unique_device_counts=da.getUniqueDevice(datetime,'article','values')
for article_id in article_ids:
product_ids=api_util.getProductIdInArticle(article_id)
unique_device_num=article_unique_device_counts.get(article_id,0)
if product_ids:
for product_id in product_ids:
print show_format.format(id_util.decode_article(article_id),result[article_id],product_id,\
da.getProductCounts(product_view_counts,id_util.encode_product(product_id)),\
da.getProductCounts(cart_product_counts,id_util.encode_product(product_id)),\
da.getProductCounts(order_product_counts,id_util.encode_product(product_id)),\
unique_device_num)
else:
print show_format.format(id_util.decode_article(article_id),result[article_id],0,0,0,0,unique_device_num)
def product_statics(datetime,limit):
print datetime
data=''
product_df=da.getDataFrame('product',datetime)
condition=pd.notnull(product_df['device_id'])
result=da.rowGroupCount(product_df[condition],'values')
order_product_counts=da.getOrderCounts(datetime)
cart_product_counts=da.getCartCount(datetime)
unique_visitor=da.getUniqueDevice(datetime,'product','values')
product_ids=result.keys()
data+=pr_format.format('date','product_id','product_pv','cart_count','order_count','unique_visitor')
for product_id in product_ids:
data+=pr_format.format(datetime,id_util.decode_product(product_id),result.get(product_id,0),\
cart_product_counts.get(product_id,0),\
order_product_counts.get(product_id,0),\
unique_visitor.get(product_id,0))
data+=all_pr_format.format('sum',len(result.keys()),sum(result),\
sum(cart_product_counts),\
sum(order_product_counts),\
da.getActiveUser(datetime),\
da.getAllUser(datetime),\
len(product_df['device_id'].unique()))
da.write2CsvFile(datetime,'product',data)
def product_statics(datetime, limit):
print datetime
data = ''
product_df = da.getDataFrame('product', datetime)
condition = pd.notnull(product_df['device_id'])
result = da.rowGroupCount(product_df[condition], 'values')
order_product_counts = da.getOrderCounts(datetime)
cart_product_counts = da.getCartCount(datetime)
unique_visitor = da.getUniqueDevice(datetime, 'product', 'values')
product_ids = result.keys()
data += pr_format.format('date', 'product_id', 'product_pv', 'cart_count',
'order_count', 'unique_visitor')
for product_id in product_ids:
data+=pr_format.format(datetime,id_util.decode_product(product_id),result.get(product_id,0),\
cart_product_counts.get(product_id,0),\
order_product_counts.get(product_id,0),\
unique_visitor.get(product_id,0))
data+=all_pr_format.format('sum',len(result.keys()),sum(result),\
sum(cart_product_counts),\
sum(order_product_counts),\
da.getActiveUser(datetime),\
da.getAllUser(datetime),\
len(product_df['device_id'].unique()))
da.write2CsvFile(datetime, 'product', data)
def product_list_record(date):
list_df = da.getDataFrame('product_list', str(date).replace('-', ''))
tags = da.rowGroupCount(list_df, 'values')
for tag in tags.keys()[:10]:
print tag, tags.get(tag, 0)
def product_list_record(date):
list_df=da.getDataFrame('product_list',str(date).replace('-',''))
tags=da.rowGroupCount(list_df,'values')
for tag in tags.keys()[:10]:
print tag,tags.get(tag,0)