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from elixir import *
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from sqlalchemy.sql import or_ ,func, asc, desc, and_
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from shop2020.config.client.ConfigClient import ConfigClient
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from shop2020.model.v1.catalog.impl import DataService
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from shop2020.model.v1.catalog.impl.DataService import Amazonlisted, Item, \
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Category, SourcePercentageMaster,SourceCategoryPercentage, SourceItemPercentage, AmazonPromotion, AmazonScrapingHistory, \
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ItemVatMaster, CategoryVatMaster
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from shop2020.thriftpy.model.v1.order.ttypes import OrderSource
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from shop2020.thriftpy.model.v1.catalog.ttypes import CompetitionCategory, \
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Decision, RunType, AmazonPromotionType
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from shop2020.model.v1.catalog.script import AmazonAsyncScraper
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from shop2020.clients.InventoryClient import InventoryClient
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from shop2020.clients.TransactionClient import TransactionClient
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import time
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from time import sleep
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from datetime import date, datetime, timedelta
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import math
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import simplejson as json
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import xlwt
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import optparse
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import sys
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from operator import itemgetter
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config_client = ConfigClient()
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host = config_client.get_property('staging_hostname')
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syncPrice=config_client.get_property('sync_price_on_marketplace')
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amazonAsinPrice={}
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amazonLongTermActivePromotions = {}
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amazonShortTermActivePromotions = {}
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saleMap = {}
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DataService.initialize(db_hostname=host)
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amScraper = AmazonAsyncScraper.Products("AKIAII3SGRXBJDPCHSGQ", "B92xTbNBTYygbGs98w01nFQUhbec1pNCkCsKVfpg", "AF6E3O0VE0X4D")
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class __AmazonItemInfo:
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def __init__(self, asin, nlc, courierCost, sku, product_group, brand, model_name, model_number, color, weight, parent_category, risky, vatRate, runType, parent_category_name, sourcePercentage, ourInventory, state_id, otherCost):
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self.asin = asin
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self.nlc = nlc
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self.courierCost = courierCost
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self.sku = sku
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self.product_group = product_group
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self.brand = brand
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self.model_name = model_name
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self.model_number = model_number
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self.color = color
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self.weight = weight
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self.parent_category = parent_category
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self.risky = risky
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self.vatRate = vatRate
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self.runType = runType
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self.parent_category_name = parent_category_name
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self.sourcePercentage = sourcePercentage
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self.ourInventory = ourInventory
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self.state_id = state_id
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self.otherCost = otherCost
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class __AmazonDetails:
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def __init__(self, sku, ourSp, ourRank, lowestSellerName,lowestSellerSp,secondLowestSellerName, secondLowestSellerSp, thirdLowestSellerName, thirdLowestSellerSp, totalSeller, multipleListings, \
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promoPrice, isPromotion, lowestSellerShippingTime, lowestSellerRating, secondLowestSellerShippingTime, secondLowestSellerRating, thirdLowestSellerShippingTime , \
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thirdLowestSellerRating, lowestSellerType, secondLowestSellerType, thirdLowestSellerType):
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self.sku =sku
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self.ourSp = ourSp
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self.ourRank = ourRank
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self.lowestSellerName = lowestSellerName
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self.lowestSellerSp = lowestSellerSp
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self.secondLowestSellerName = secondLowestSellerName
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self.secondLowestSellerSp = secondLowestSellerSp
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self.thirdLowestSellerName = thirdLowestSellerName
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self.thirdLowestSellerSp = thirdLowestSellerSp
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self.totalSeller = totalSeller
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self.multipleListings = multipleListings
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self.promoPrice = promoPrice
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self.isPromotion = isPromotion
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self.lowestSellerShippingTime =lowestSellerShippingTime
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self.lowestSellerRating = lowestSellerRating
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self.secondLowestSellerShippingTime = secondLowestSellerShippingTime
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self.secondLowestSellerRating = secondLowestSellerRating
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self.thirdLowestSellerShippingTime= thirdLowestSellerShippingTime
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self.thirdLowestSellerRating = thirdLowestSellerRating
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self.lowestSellerType = lowestSellerType
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self.secondLowestSellerType = secondLowestSellerType
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self.thirdLowestSellerType = thirdLowestSellerType
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class __AmazonPricing:
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def __init__(self, ourSp, lowestPossibleSp):
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self.ourSp = ourSp
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self.lowestPossibleSp = lowestPossibleSp
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class __Promotion:
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def __init__(self, promoPrice, subsidy, promotionType,expiryDate):
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self.promoPrice = promoPrice
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self.subsidy = subsidy
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self.promotionType = promotionType
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self.expiryDate = expiryDate
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def fetchItemsForAutoDecrease(time):
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successfulAutoDecrease = []
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autoDecrementItems = session.query(AmazonScrapingHistory).join((Amazonlisted,AmazonScrapingHistory.item_id==Amazonlisted.itemId))\
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.filter(AmazonScrapingHistory.timestamp==time).filter(or_(AmazonScrapingHistory.competitiveCategory==CompetitionCategory.AMONG_CHEAPEST_CAN_COMPETE,AmazonScrapingHistory.competitiveCategory==CompetitionCategory.COMPETITIVE, AmazonScrapingHistory.competitiveCategory==CompetitionCategory.ALMOST_COMPETE ))\
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.filter(Amazonlisted.autoDecrement==True).all()
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for autoDecrementItem in autoDecrementItems:
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if autoDecrementItem.warehouseLocation == 1:
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sku = 'FBA'+str(autoDecrementItem.item_id)
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else:
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sku = 'FBB'+str(autoDecrementItem.item_id)
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if amazonShortTermActivePromotions.has_key(sku):
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markReasonForItem(autoDecrementItem,'Item in short term promotion',Decision.AUTO_DECREMENT_FAILED)
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continue
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if math.ceil(autoDecrementItem.proposedSp) >= autoDecrementItem.ourSellingPrice:
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markReasonForItem(autoDecrementItem,'Proposed SP greater than or equal to current SP',Decision.AUTO_DECREMENT_FAILED)
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continue
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if autoDecrementItem.proposedSellingPrice < autoDecrementItem.lowestPossibleSp:
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markReasonForItem(autoDecrementItem,'Proposed SP less than lowest possible SP',Decision.AUTO_DECREMENT_FAILED)
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continue
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try:
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daysOfStock = (float(autoDecrementItem.ourInventory))/autoDecrementItem.avgSale
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except:
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daysOfStock = float("inf")
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if autoDecrementItem.competitiveCategory == CompetitionCategory.AMONG_CHEAPEST_CAN_COMPETE:
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if daysOfStock < 20:
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markReasonForItem(autoDecrementItem,'Days of stock less than 20',Decision.AUTO_DECREMENT_FAILED)
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continue
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if autoDecrementItem.competitiveCategory == CompetitionCategory.COMPETITIVE and not autoDecrementItem.isPromotion:
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if autoDecrementItem.parentCategoryId in [10006,10009,11001]:
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if daysOfStock < 1 :
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markReasonForItem(autoDecrementItem,'Days of stock less than 1',Decision.AUTO_DECREMENT_FAILED)
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continue
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else:
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if daysOfStock < 3:
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markReasonForItem(autoDecrementItem,'Days of stock less than 3',Decision.AUTO_DECREMENT_FAILED)
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continue
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if autoDecrementItem.competitiveCategory == CompetitionCategory.COMPETITIVE and autoDecrementItem.isPromotion:
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if autoDecrementItem.parentCategoryId in [10006,10009,11001]:
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if (amazonLongTermActivePromotions.get(sku).expiryDate - datetime.now()).days >2 and daysOfStock < 1 :
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markReasonForItem(autoDecrementItem,'Promo Item, expiry after 2 days or not enough stock',Decision.AUTO_DECREMENT_FAILED)
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continue
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else:
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if (amazonLongTermActivePromotions.get(sku).expiryDate - datetime.now()).days >2 and daysOfStock < 3:
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markReasonForItem(autoDecrementItem,'Promo Item, expiry after 2 days or not enough stock',Decision.AUTO_DECREMENT_FAILED)
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continue
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autoDecrementItem.ourEnoughStock=True
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autoDecrementItem.decision = Decision.AUTO_DECREMENT_SUCCESS
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autoDecrementItem.reason = 'All conditions for auto decrement true'
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successfulAutoDecrease.append(autoDecrementItem)
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session.commit()
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session.close()
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return successfulAutoDecrease
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def fetchItemsForAutoIncrease(time):
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successfulAutoIncrease = []
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autoIncrementItems = session.query(AmazonScrapingHistory).join((Amazonlisted,AmazonScrapingHistory.item_id==Amazonlisted.itemId))\
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.filter(AmazonScrapingHistory.timestamp==time).filter(AmazonScrapingHistory.competitiveCategory==CompetitionCategory.BUY_BOX)\
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.filter(Amazonlisted.autoIncrement==True).all()
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transaction_client = TransactionClient().get_client()
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for autoIncrementItem in autoIncrementItems:
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if autoIncrementItem.warehouseLocation == 1:
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sku = 'FBA'+str(autoIncrementItem.item_id)
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else:
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sku = 'FBB'+str(autoIncrementItem.item_id)
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if amazonShortTermActivePromotions.has_key(sku):
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markReasonForItem(autoIncrementItem,'Item in short term promotion',Decision.AUTO_INCREMENT_FAILED)
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continue
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if autoIncrementItem.totalSeller==1 and autoIncrementItem.ourRank==1:
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markReasonForItem(autoIncrementItem,'We are the only seller',Decision.AUTO_INCREMENT_FAILED)
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continue
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if autoIncrementItem.proposedSp <= autoIncrementItem.ourSellingPrice:
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markReasonForItem(autoIncrementItem,'Proposed SP less than current SP',Decision.AUTO_INCREMENT_FAILED)
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continue
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if autoIncrementItem.proposedSellingPrice >=10000 and autoIncrementItem.ourSellingPrice<10000:
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markReasonForItem(autoIncrementItem,'Proposed SP is greater than 10,000 and current sp is less than 10,000',Decision.AUTO_INCREMENT_FAILED)
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continue
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if autoIncrementItem.isPromotion and math.ceil(autoIncrementItem.promoPrice+max(10,.01*autoIncrementItem.promoPrice)) > (amazonLongTermActivePromotions.get(sku)).promoPrice:
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markReasonForItem(autoIncrementItem,'Proposed SP cant be greater than promo price',Decision.AUTO_INCREMENT_FAILED)
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continue
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if autoIncrementItem.avgSale==0:
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markReasonForItem(autoIncrementItem,'Avg sale is 0',Decision.AUTO_INCREMENT_FAILED)
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continue
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daysOfStock = (float(autoIncrementItem.ourInventory))/autoIncrementItem.avgSale
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if daysOfStock > 5:
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markReasonForItem(autoIncrementItem,'Days of stock greater than 5',Decision.AUTO_INCREMENT_FAILED)
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continue
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antecedentPrice = session.query(AmazonScrapingHistory.ourSellingPrice).filter(AmazonScrapingHistory.item_id==autoIncrementItem.item_id).filter(AmazonScrapingHistory.timestamp>time-timedelta(days=1)).order_by(asc(AmazonScrapingHistory.timestamp)).first()
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if antecedentPrice is not None:
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if float(math.ceil(autoIncrementItem.ourSellingPrice+max(10,.01*autoIncrementItem.ourSellingPrice))-math.ceil(antecedentPrice[0]+max(10,.01*antecedentPrice[0])))/math.ceil(antecedentPrice[0]+max(10,.01*antecedentPrice[0]))>.02:
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markReasonForItem(autoIncrementItem,'Maximum price increase in last 24 hours should be 2%',Decision.AUTO_INCREMENT_FAILED)
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continue
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fbaSaleSnapshot = transaction_client.getAmazonFbaSalesLatestSnapshotForItemLocationWise(autoIncrementItem.item_id,autoIncrementItem.warehouseLocation)
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if getLastDaySale(fbaSaleSnapshot,autoIncrementItem.warehouseLocation-1)<=2:
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markReasonForItem(autoIncrementItem,'Last day sale is less than 3',Decision.AUTO_INCREMENT_FAILED)
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continue
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autoIncrementItem.ourEnoughStock = False
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autoIncrementItem.decision = Decision.AUTO_INCREMENT_SUCCESS
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autoIncrementItem.reason = 'All conditions for auto increment true'
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successfulAutoIncrease.append(autoIncrementItem)
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session.commit()
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return successfulAutoIncrease
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def markReasonForItem(amHistory,reason,decision):
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amHistory.decision = decision
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amHistory.reason = reason
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def calculateAverageSale(sku):
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count,sale = 0,0
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oosStatus = saleMap.get(sku)
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for obj in oosStatus:
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if not obj.isOutOfStock:
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count+=1
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sale = sale+obj.totalOrderCount
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avgSalePerDay=0 if count==0 else (float(sale)/count)
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return round(avgSalePerDay,2)
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def getOosString(oosStatus):
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lastNdaySale=""
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for obj in oosStatus:
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if obj.isOutOfStock:
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lastNdaySale += "X-"
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else:
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lastNdaySale += str(obj.totalOrderCount) + "-"
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return lastNdaySale[:-1]
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def getLastDaySale(fbaSaleSnapshot):
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if fbaSaleSnapshot.item_id==0:
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return 0
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else:
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return fbaSaleSnapshot.totalOrderCount
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#def syncAsin():
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## notListedOnAmazon = []
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## diffAsins = []
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## login_url = "https://sellercentral.amazon.in/gp/homepage.html"
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## br = SellerCentralInventoryReport.login(login_url)
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## report_url = "https://sellercentral.amazon.in/gp/upload-download-utils/requestReport.html?type=OpenListingReport&marketplaceID=44571&Request+Report="
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## br = SellerCentralInventoryReport.requestReport(br,report_url)
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## status_url="https://sellercentral.amazon.in/gp/upload-download-utils/reportStatusData.html"
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## br, page = SellerCentralInventoryReport.checkStatus(br,status_url)
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## br, batchId = SellerCentralInventoryReport.getReportBatchId(br,page)
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## print "*********************************"
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## print "Batch Id for request is ",batchId
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## print "*********************************"
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## ready = False
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## retryCount = 0
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## while not ready:
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## if retryCount == 10:
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## print "File not available for download after multiple retries"
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## sys.exit(1)
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## br, download_link = SellerCentralInventoryReport.downloadReport(br,batchId,status_url)
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## if download_link is not None:
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## ready= True
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## continue
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## print "File not ready for download yet.Will try again after 30 seconds."
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## retryCount+=1
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## time.sleep(30)
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## fPath = SellerCentralInventoryReport.fetchFile(download_link['href'],br,batchId)
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# fPath = "/tmp/9940651090.txt"
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# global amazonAsinPrice
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# for line in open(fPath):
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|
276 |
# l = line.split('\t')
|
|
|
277 |
# if (str(l[0]).startswith('FBA') or str(l[0]).startswith('FBB')):
|
|
|
278 |
# obj = __AmazonAsinPrice(l[1],l[2])
|
|
|
279 |
# amazonAsinPrice[l[0]] = obj
|
|
|
280 |
##Can be used to sync asins, not doing due to multiple asins corresponding to one itemId
|
|
|
281 |
## systemAsins = session.query(Item,Amazonlisted).join((Amazonlisted,Item.id==Amazonlisted.itemId)).all()
|
|
|
282 |
## for systemAsin in systemAsins:
|
|
|
283 |
## item = systemAsin[0]
|
|
|
284 |
## amListed = systemAsin[1]
|
|
|
285 |
## if amazonAsinPrice.get('FBA'+str(item.id)) is None:
|
|
|
286 |
## temp=[]
|
|
|
287 |
## temp.append(item)
|
|
|
288 |
## temp.append(amListed)
|
|
|
289 |
## notListedOnAmazon.append(temp)
|
|
|
290 |
## continue
|
|
|
291 |
## else:
|
|
|
292 |
## temp=[]
|
|
|
293 |
## temp.append(item)
|
|
|
294 |
## temp.append(amListed)
|
|
|
295 |
## if item.asin!=((amazonAsinPrice.get('FBA'+str(item.id))).asin).strip():
|
|
|
296 |
## diffAsins.append(temp)
|
|
|
297 |
## continue
|
|
|
298 |
##
|
|
|
299 |
## for diffAsin in diffAsins:
|
|
|
300 |
## item = diffAsin[0]
|
|
|
301 |
## amListed = diffAsin[1]
|
|
|
302 |
## item.asin = ((amazonAsinPrice.get('FBA'+str(item.id))).asin).strip()
|
|
|
303 |
## amListed.asin = ((amazonAsinPrice.get('FBA'+str(item.id))).asin).strip()
|
|
|
304 |
## session.commit()
|
|
|
305 |
## session.close()
|
| 12363 |
kshitij.so |
306 |
|
|
|
307 |
def fetchFbaSale():
|
|
|
308 |
global saleMap
|
|
|
309 |
transaction_client = TransactionClient().get_client()
|
|
|
310 |
fbaSaleSnapshot = transaction_client.getAmazonFbaSalesSnapshotForDays(4)
|
|
|
311 |
for saleSnapshot in fbaSaleSnapshot:
|
|
|
312 |
if saleSnapshot.fcLocation == 0:
|
|
|
313 |
if saleMap.has_key('FBA'+str(saleSnapshot.item_id)):
|
|
|
314 |
temp = []
|
| 12367 |
kshitij.so |
315 |
val = saleMap.get('FBA'+str(saleSnapshot.item_id))
|
|
|
316 |
for l in val:
|
| 12363 |
kshitij.so |
317 |
temp.append(l)
|
|
|
318 |
temp.append(saleSnapshot)
|
| 12366 |
kshitij.so |
319 |
saleMap['FBA'+str(saleSnapshot.item_id)]=temp
|
| 12363 |
kshitij.so |
320 |
else:
|
| 12368 |
kshitij.so |
321 |
temp = []
|
|
|
322 |
temp.append(saleSnapshot)
|
|
|
323 |
saleMap['FBA'+str(saleSnapshot.item_id)] = temp
|
| 12363 |
kshitij.so |
324 |
else:
|
|
|
325 |
if saleMap.has_key('FBB'+str(saleSnapshot.item_id)):
|
|
|
326 |
temp = []
|
| 12367 |
kshitij.so |
327 |
val = saleMap.get('FBB'+str(saleSnapshot.item_id))
|
|
|
328 |
for l in val:
|
| 12363 |
kshitij.so |
329 |
temp.append(l)
|
| 12368 |
kshitij.so |
330 |
saleMap['FBB'+str(saleSnapshot.item_id)]=temp
|
| 12363 |
kshitij.so |
331 |
temp.append(saleSnapshot)
|
|
|
332 |
else:
|
| 12368 |
kshitij.so |
333 |
temp = []
|
|
|
334 |
temp.append(saleSnapshot)
|
|
|
335 |
saleMap['FBB'+str(saleSnapshot.item_id)] = temp
|
| 12363 |
kshitij.so |
336 |
|
| 12424 |
kshitij.so |
337 |
|
| 12363 |
kshitij.so |
338 |
def computeCourierCost(weight):
|
| 12378 |
kshitij.so |
339 |
try:
|
|
|
340 |
cCost = 10.0;
|
|
|
341 |
slabs = int((weight*1000)/500-.001)
|
|
|
342 |
for slab in range(0,slabs):
|
|
|
343 |
cCost = cCost + 10.0;
|
|
|
344 |
return cCost;
|
|
|
345 |
except:
|
|
|
346 |
return 10.0
|
| 12363 |
kshitij.so |
347 |
|
|
|
348 |
|
|
|
349 |
def populateStuff(time,runType):
|
|
|
350 |
global amazonLongTermActivePromotions
|
| 12396 |
kshitij.so |
351 |
global amazonShortTermActivePromotions
|
| 12363 |
kshitij.so |
352 |
itemInfo = []
|
|
|
353 |
inventory_client = InventoryClient().get_client()
|
|
|
354 |
fbaAvailableInventorySnapshot = inventory_client.getAllAvailableAmazonFbaItemInventory()
|
| 12387 |
kshitij.so |
355 |
print len(fbaAvailableInventorySnapshot)
|
| 12363 |
kshitij.so |
356 |
for fbaInventoryItem in fbaAvailableInventorySnapshot:
|
|
|
357 |
d_amazon_listed = Amazonlisted.get_by(itemId=fbaInventoryItem.item_id)
|
|
|
358 |
if d_amazon_listed is None:
|
|
|
359 |
continue
|
|
|
360 |
if d_amazon_listed.overrrideWanlc:
|
|
|
361 |
wanlc = d_amazon_listed.exceptionalWanlc
|
|
|
362 |
else:
|
|
|
363 |
wanlc = inventory_client.getWanNlcForSource(fbaInventoryItem.item_id,OrderSource.AMAZON)
|
|
|
364 |
it = Item.query.filter_by(id=fbaInventoryItem.item_id).one()
|
|
|
365 |
category = Category.query.filter_by(id=it.category).one()
|
|
|
366 |
parent_category = Category.query.filter_by(id=category.parent_category_id).first()
|
|
|
367 |
scp = SourceCategoryPercentage.query.filter(SourceCategoryPercentage.category_id==it.category).filter(SourceCategoryPercentage.source==OrderSource.AMAZON).filter(SourceCategoryPercentage.startDate<=time).filter(SourceCategoryPercentage.expiryDate>=time).first()
|
|
|
368 |
if scp is not None:
|
|
|
369 |
sourcePercentage = scp
|
|
|
370 |
else:
|
|
|
371 |
spm = SourcePercentageMaster.get_by(source=OrderSource.AMAZON)
|
|
|
372 |
sourcePercentage = spm
|
| 12375 |
kshitij.so |
373 |
if fbaInventoryItem.location==0:
|
| 12377 |
kshitij.so |
374 |
sku = 'FBA'+str(fbaInventoryItem.item_id)
|
| 12363 |
kshitij.so |
375 |
state_id = 1
|
| 12375 |
kshitij.so |
376 |
elif fbaInventoryItem.location==1:
|
| 12377 |
kshitij.so |
377 |
sku = 'FBB'+str(fbaInventoryItem.item_id)
|
| 12363 |
kshitij.so |
378 |
state_id = 2
|
|
|
379 |
else:
|
|
|
380 |
continue
|
|
|
381 |
cc = computeCourierCost(it.weight)
|
| 12379 |
kshitij.so |
382 |
|
| 12447 |
kshitij.so |
383 |
amazonItemInfo = __AmazonItemInfo(None, wanlc,cc, sku, it.product_group, it.brand, it.model_name, it.model_number, it.color, it.weight, category.parent_category_id, it.risky, None, runType, parent_category.display_name,sourcePercentage,fbaInventoryItem.availability,state_id,d_amazon_listed.otherCost)
|
| 12363 |
kshitij.so |
384 |
itemInfo.append(amazonItemInfo)
|
|
|
385 |
amPromotions = AmazonPromotion.query.filter(AmazonPromotion.startDate<=time).filter(AmazonPromotion.endDate>=time).filter(AmazonPromotion.promotionType==AmazonPromotionType.LONGTERM).filter(AmazonPromotion.promotionActive==True) \
|
|
|
386 |
.group_by(AmazonPromotion.sku).order_by(desc(AmazonPromotion.addedOn)).all()
|
|
|
387 |
for amPromotion in amPromotions:
|
| 12433 |
kshitij.so |
388 |
amazonLongTermActivePromotions[amPromotion.sku] = __Promotion(amPromotion.salePrice,amPromotion.subsidy,amPromotion.promotionType,amPromotion.endDate)
|
| 12396 |
kshitij.so |
389 |
amPromotions = AmazonPromotion.query.filter(AmazonPromotion.startDate<=time).filter(AmazonPromotion.endDate>=time).filter(AmazonPromotion.promotionType==AmazonPromotionType.SHORTTERM).filter(AmazonPromotion.promotionActive==True) \
|
|
|
390 |
.group_by(AmazonPromotion.sku).order_by(desc(AmazonPromotion.addedOn)).all()
|
|
|
391 |
for amPromotion in amPromotions:
|
| 12433 |
kshitij.so |
392 |
amazonShortTermActivePromotions[amPromotion.sku] = __Promotion(amPromotion.salePrice,amPromotion.subsidy,amPromotion.promotionType,amPromotion.endDate)
|
| 12363 |
kshitij.so |
393 |
session.close()
|
| 12450 |
kshitij.so |
394 |
print "No of items populated ",len(itemInfo)
|
| 12452 |
kshitij.so |
395 |
sleep(5)
|
| 12363 |
kshitij.so |
396 |
return itemInfo
|
|
|
397 |
|
| 12430 |
kshitij.so |
398 |
def getPriceAndAsin(itemInfo):
|
|
|
399 |
skus = []
|
|
|
400 |
for item in itemInfo:
|
|
|
401 |
skus.append(item.sku)
|
|
|
402 |
ourPricingForSku = amScraper.get_my_pricing_for_sku('A21TJRUUN4KGV', skus)
|
|
|
403 |
for item in itemInfo:
|
|
|
404 |
ourPricing = ourPricingForSku.get(item.sku)
|
| 12441 |
kshitij.so |
405 |
if ourPricing is None or len(ourPricing.keys())==0:
|
| 12430 |
kshitij.so |
406 |
item.ourSp = 0
|
|
|
407 |
item.promoPrice = 0
|
|
|
408 |
item.isPromotion = False
|
|
|
409 |
else:
|
|
|
410 |
item.ourSp = ourPricing.get('sellingPrice')
|
|
|
411 |
item.promoPrice = ourPricing.get('promoPrice')
|
|
|
412 |
item.isPromotion = ourPricing.get('promotion')
|
| 12450 |
kshitij.so |
413 |
|
| 12430 |
kshitij.so |
414 |
|
|
|
415 |
|
| 12363 |
kshitij.so |
416 |
def decideCategory(itemInfo):
|
|
|
417 |
exceptionList, negativeMargin, cheapest, amongCheapestAndCanCompete, canCompete, almostCompete, cantCompete = [],[],[],[],[],[],[]
|
| 12430 |
kshitij.so |
418 |
skus = []
|
| 12363 |
kshitij.so |
419 |
for item in itemInfo:
|
| 12430 |
kshitij.so |
420 |
skus.append(item.sku)
|
|
|
421 |
aggResponse = amScraper.get_competitive_pricing_for_sku('A21TJRUUN4KGV', skus)
|
|
|
422 |
ourPricingForSku = amScraper.get_my_pricing_for_sku('A21TJRUUN4KGV', skus)
|
| 12403 |
kshitij.so |
423 |
|
| 12363 |
kshitij.so |
424 |
for val in itemInfo:
|
| 12430 |
kshitij.so |
425 |
scrapInfo = aggResponse.get(val.sku)
|
| 12443 |
kshitij.so |
426 |
if scrapInfo is None or len(scrapInfo)==0 or val.nlc==0 or len(ourPricingForSku.get(val.sku).keys())==0:
|
| 12363 |
kshitij.so |
427 |
temp = []
|
|
|
428 |
temp.append(val)
|
|
|
429 |
if val.nlc==0 or val.nlc is None:
|
| 12456 |
kshitij.so |
430 |
print "WANLC is 0"
|
| 12363 |
kshitij.so |
431 |
temp.append("WANLC is 0")
|
| 12443 |
kshitij.so |
432 |
elif ourPricingForSku.get(val.sku) is None or ourPricingForSku.get(val.sku).keys()==0:
|
| 12456 |
kshitij.so |
433 |
print "Unable to fetch our price"
|
| 12430 |
kshitij.so |
434 |
temp.append("Unable to fetch our price")
|
| 12363 |
kshitij.so |
435 |
else:
|
| 12456 |
kshitij.so |
436 |
print "Unable to fetch competive pricing"
|
| 12430 |
kshitij.so |
437 |
temp.append("Unable to fetch competitive pricing")
|
| 12363 |
kshitij.so |
438 |
exceptionList.append(temp)
|
|
|
439 |
continue
|
| 12430 |
kshitij.so |
440 |
val.asin = ourPricingForSku.get(val.sku).get('asin')
|
|
|
441 |
val.ourSp = ourPricingForSku.get(val.sku).get('sellingPrice')
|
|
|
442 |
val.promoPrice = ourPricingForSku.get(val.sku).get('promoPrice')
|
|
|
443 |
val.isPromo = ourPricingForSku.get(val.sku).get('promotion')
|
| 12363 |
kshitij.so |
444 |
iterator = 0
|
|
|
445 |
sku, lowestSellerName,secondLowestSellerName, thirdLowestSellerName = ('',)*4
|
| 12432 |
kshitij.so |
446 |
ourSp, ourRank, lowestSellerSp, secondLowestSellerSp, thirdLowestSellerSp, lowestPossibleSp = (0,)*6
|
| 12430 |
kshitij.so |
447 |
lowestSellerShippingTime, lowestSellerRating, secondLowestSellerShippingTime, secondLowestSellerRating, thirdLowestSellerShippingTime , \
|
|
|
448 |
thirdLowestSellerRating, lowestSellerType, secondLowestSellerType, thirdLowestSellerType = (0,)*9
|
|
|
449 |
isPromo = False
|
| 12363 |
kshitij.so |
450 |
sku = val.sku
|
|
|
451 |
multipleListings = False
|
| 12430 |
kshitij.so |
452 |
ourSkuDetails = ourPricingForSku.get(val.sku)
|
| 12442 |
kshitij.so |
453 |
if not (ourSkuDetails.get('promotion') and (amazonLongTermActivePromotions.has_key(val.sku) or amazonShortTermActivePromotions.has_key(val.sku))):
|
| 12432 |
kshitij.so |
454 |
temp = []
|
|
|
455 |
temp.append(val)
|
| 12456 |
kshitij.so |
456 |
print "promo misconfigured"
|
| 12432 |
kshitij.so |
457 |
temp.append("Promo misconfigured")
|
| 12457 |
kshitij.so |
458 |
exceptionList.append(temp)
|
| 12432 |
kshitij.so |
459 |
continue
|
|
|
460 |
|
| 12430 |
kshitij.so |
461 |
scrapInfo.append(ourSkuDetails)
|
|
|
462 |
sortedScrapInfo = sorted(scrapInfo, key=itemgetter('promoPrice','notOurSku'))
|
|
|
463 |
for info in sortedScrapInfo:
|
| 12465 |
kshitij.so |
464 |
if not info['notOurSku']:
|
| 12442 |
kshitij.so |
465 |
ourSp = info['sellingPrice']
|
|
|
466 |
promoPrice = info['promoPrice']
|
|
|
467 |
isPromo = info['promotion']
|
| 12430 |
kshitij.so |
468 |
ourRank = iterator + 1
|
| 12363 |
kshitij.so |
469 |
|
|
|
470 |
if iterator == 0:
|
| 12430 |
kshitij.so |
471 |
lowestSellerSp = info['promoPrice']
|
|
|
472 |
lowestSellerShippingTime = info['shippingTime']
|
|
|
473 |
lowestSellerRating = info['rating']
|
|
|
474 |
lowestSellerType = info['fulfillmentChannel']
|
| 12363 |
kshitij.so |
475 |
|
|
|
476 |
if iterator == 1:
|
| 12430 |
kshitij.so |
477 |
secondLowestSellerSp = info['promoPrice']
|
|
|
478 |
secondLowestSellerShippingTime = info['shippingTime']
|
|
|
479 |
secondLowestSellerRating = info['rating']
|
|
|
480 |
secondLowestSellerType = info['fulfillmentChannel']
|
| 12363 |
kshitij.so |
481 |
|
|
|
482 |
if iterator == 2:
|
| 12430 |
kshitij.so |
483 |
thirdLowestSellerSp = info['promoPrice']
|
|
|
484 |
thirdLowestSellerShippingTime = info['shippingTime']
|
|
|
485 |
thirdLowestSellerRating = info['rating']
|
|
|
486 |
thirdLowestSellerType = info['fulfillmentChannel']
|
| 12363 |
kshitij.so |
487 |
|
|
|
488 |
iterator += 1
|
| 12401 |
kshitij.so |
489 |
print "terminating iterator"
|
| 12363 |
kshitij.so |
490 |
|
|
|
491 |
|
| 12408 |
kshitij.so |
492 |
print "Creating object am details",val.sku
|
| 12430 |
kshitij.so |
493 |
amDetails = __AmazonDetails(sku, float(ourSp), ourRank, lowestSellerName,float(lowestSellerSp),secondLowestSellerName, float(secondLowestSellerSp), thirdLowestSellerName, float(thirdLowestSellerSp),len(scrapInfo),multipleListings,promoPrice,isPromo, \
|
|
|
494 |
lowestSellerShippingTime ,lowestSellerRating, secondLowestSellerShippingTime, secondLowestSellerRating, thirdLowestSellerShippingTime , thirdLowestSellerRating, lowestSellerType, secondLowestSellerType, thirdLowestSellerType)
|
| 12414 |
kshitij.so |
495 |
print "am details obj created"
|
| 12363 |
kshitij.so |
496 |
try:
|
| 12414 |
kshitij.so |
497 |
print "inside val getter"
|
| 12418 |
kshitij.so |
498 |
itemVatMaster = ItemVatMaster.query.filter(and_(ItemVatMaster.itemId==int(val.sku[3:]), ItemVatMaster.stateId==val.state_id)).first()
|
|
|
499 |
if itemVatMaster is None:
|
| 12419 |
kshitij.so |
500 |
d_item = Item.query.filter_by(id=int(val.sku[3:])).first()
|
|
|
501 |
if d_item is None:
|
|
|
502 |
raise
|
|
|
503 |
else:
|
| 12430 |
kshitij.so |
504 |
vatMaster = CategoryVatMaster.query.filter(and_(CategoryVatMaster.categoryId==d_item.category, CategoryVatMaster.minVal<=amDetails.promoPrice, CategoryVatMaster.maxVal>=amDetails.promoPrice, CategoryVatMaster.stateId == val.state_id)).first()
|
| 12419 |
kshitij.so |
505 |
if vatMaster is None:
|
| 12418 |
kshitij.so |
506 |
raise
|
| 12419 |
kshitij.so |
507 |
else:
|
|
|
508 |
val.vatRate = vatMaster.vatPercent
|
|
|
509 |
print "vat fetched"
|
| 12418 |
kshitij.so |
510 |
else:
|
|
|
511 |
val.vatRate = itemVatMaster.vatPercentage
|
| 12419 |
kshitij.so |
512 |
print "vat fetched"
|
| 12363 |
kshitij.so |
513 |
except:
|
| 12414 |
kshitij.so |
514 |
print "vat exception"
|
| 12363 |
kshitij.so |
515 |
temp = []
|
|
|
516 |
temp.append(val)
|
|
|
517 |
temp.append("Vat not available")
|
|
|
518 |
exceptionList.append(temp)
|
|
|
519 |
continue
|
|
|
520 |
|
|
|
521 |
lowestPossibleSp = getLowestPossibleSp(amDetails,val,val.sourcePercentage)
|
| 12408 |
kshitij.so |
522 |
print "Creating pricing obj"
|
| 12432 |
kshitij.so |
523 |
amPricing = __AmazonPricing(ourSp,lowestPossibleSp)
|
| 12363 |
kshitij.so |
524 |
|
| 12467 |
kshitij.so |
525 |
if amDetails.promoPrice < amPricing.lowestPossibleSp:
|
| 12363 |
kshitij.so |
526 |
temp = []
|
|
|
527 |
temp.append(val)
|
|
|
528 |
temp.append(amDetails)
|
|
|
529 |
temp.append(amPricing)
|
|
|
530 |
negativeMargin.append(temp)
|
|
|
531 |
continue
|
|
|
532 |
|
|
|
533 |
if amDetails.ourRank==1:
|
|
|
534 |
temp = []
|
|
|
535 |
temp.append(val)
|
|
|
536 |
temp.append(amDetails)
|
|
|
537 |
temp.append(amPricing)
|
|
|
538 |
cheapest.append(temp)
|
|
|
539 |
continue
|
|
|
540 |
|
| 12430 |
kshitij.so |
541 |
if (amDetails.lowestSellerSp > amPricing.lowestPossibleSp) and ((((float(amDetails.promoPrice - amDetails.lowestSellerSp))/amDetails.promoPrice)<=.01) or ((amDetails.promoPrice - amDetails.lowestSellerSp)<=25)):
|
| 12363 |
kshitij.so |
542 |
temp = []
|
|
|
543 |
temp.append(val)
|
|
|
544 |
temp.append(amDetails)
|
|
|
545 |
temp.append(amPricing)
|
|
|
546 |
amongCheapestAndCanCompete.append(temp)
|
|
|
547 |
continue
|
|
|
548 |
|
|
|
549 |
if (amDetails.lowestSellerSp > amPricing.lowestPossibleSp):
|
|
|
550 |
temp = []
|
|
|
551 |
temp.append(val)
|
|
|
552 |
temp.append(amDetails)
|
|
|
553 |
temp.append(amPricing)
|
|
|
554 |
canCompete.append(temp)
|
|
|
555 |
continue
|
|
|
556 |
|
| 12403 |
kshitij.so |
557 |
if amDetails.lowestSellerSp*(1+.01) >= amPricing.lowestPossibleSp:
|
| 12396 |
kshitij.so |
558 |
temp = []
|
|
|
559 |
temp.append(val)
|
|
|
560 |
temp.append(amDetails)
|
|
|
561 |
temp.append(amPricing)
|
|
|
562 |
almostCompete.append(temp)
|
|
|
563 |
continue
|
|
|
564 |
|
|
|
565 |
|
| 12363 |
kshitij.so |
566 |
temp = []
|
|
|
567 |
temp.append(val)
|
|
|
568 |
temp.append(amDetails)
|
|
|
569 |
temp.append(amPricing)
|
|
|
570 |
cantCompete.append(temp)
|
| 12414 |
kshitij.so |
571 |
print "Created category..."
|
| 12363 |
kshitij.so |
572 |
|
|
|
573 |
return exceptionList, negativeMargin, cheapest, amongCheapestAndCanCompete, canCompete, almostCompete, cantCompete
|
| 12396 |
kshitij.so |
574 |
|
| 12363 |
kshitij.so |
575 |
|
|
|
576 |
def getLowestPossibleSp(amazonDetails,val,spm):
|
| 12447 |
kshitij.so |
577 |
lowestPossibleSp = (val.nlc+(val.courierCost)*(1+(spm.serviceTax/100))*(1+(val.vatRate/100))+(15+val.otherCost)*(1+(val.vatRate)/100))/(1-(spm.commission/100+spm.emiFee/100)*(1+(spm.serviceTax/100))*(1+(val.vatRate)/100)-(spm.returnProvision/100)*(1+(val.vatRate)/100));
|
| 12432 |
kshitij.so |
578 |
if val.isPromo:
|
|
|
579 |
if amazonLongTermActivePromotions.has_key(val.sku):
|
| 12466 |
kshitij.so |
580 |
subsidy = (amazonLongTermActivePromotions.get(val.sku)).subsidy
|
| 12432 |
kshitij.so |
581 |
else:
|
| 12466 |
kshitij.so |
582 |
subsidy = (amazonShortTermActivePromotions.get(val.sku)).subsidy
|
| 12432 |
kshitij.so |
583 |
lowestPossibleSp = lowestPossibleSp - subsidy
|
| 12363 |
kshitij.so |
584 |
return round(lowestPossibleSp,2)
|
|
|
585 |
|
|
|
586 |
def getTargetTp(targetSp,spm,val):
|
| 12424 |
kshitij.so |
587 |
targetTp = targetSp- targetSp*(spm.commission/100+spm.emiFee/100)*(1+(spm.serviceTax/100))-(val.courierCost)*(1+(spm.serviceTax/100))
|
| 12363 |
kshitij.so |
588 |
return round(targetTp,2)
|
|
|
589 |
|
|
|
590 |
def commitExceptionList(exceptionList,timestamp,runType):
|
|
|
591 |
for exceptionItem in exceptionList:
|
|
|
592 |
val = exceptionItem[0]
|
|
|
593 |
reason = exceptionItem[1]
|
|
|
594 |
amazonScrapingHistory = AmazonScrapingHistory()
|
|
|
595 |
amazonScrapingHistory.item_id = val.sku[3:]
|
|
|
596 |
amazonScrapingHistory.warehouseLocation = val.state_id
|
| 12396 |
kshitij.so |
597 |
amazonScrapingHistory.parentCategoryId = val.parent_category
|
| 12363 |
kshitij.so |
598 |
amazonScrapingHistory.reason = reason
|
|
|
599 |
amazonScrapingHistory.runType = RunType._NAMES_TO_VALUES.get(runType)
|
|
|
600 |
amazonScrapingHistory.competitiveCategory = CompetitionCategory.EXCEPTION
|
|
|
601 |
amazonScrapingHistory.timestamp = timestamp
|
|
|
602 |
session.commit()
|
|
|
603 |
|
|
|
604 |
def commitNegativeMargin(negativeMargin,timestamp,runType):
|
|
|
605 |
for negativeMarginItem in negativeMargin:
|
|
|
606 |
val = negativeMarginItem[0]
|
|
|
607 |
amDetails = negativeMarginItem[1]
|
|
|
608 |
amPricing = negativeMarginItem[2]
|
|
|
609 |
spm = val.sourcePercentage
|
|
|
610 |
amazonScrapingHistory = AmazonScrapingHistory()
|
|
|
611 |
amazonScrapingHistory.item_id = val.sku[3:]
|
|
|
612 |
amazonScrapingHistory.warehouseLocation = val.state_id
|
| 12396 |
kshitij.so |
613 |
amazonScrapingHistory.parentCategoryId = val.parent_category
|
| 12363 |
kshitij.so |
614 |
amazonScrapingHistory.ourSellingPrice = amDetails.ourSp
|
| 12432 |
kshitij.so |
615 |
amazonScrapingHistory.promoPrice = amDetails.promoPrice
|
| 12363 |
kshitij.so |
616 |
amazonScrapingHistory.lowestPossibleSp = amPricing.lowestPossibleSp
|
|
|
617 |
amazonScrapingHistory.ourRank = amDetails.ourRank
|
|
|
618 |
amazonScrapingHistory.ourInventory = val.ourInventory
|
|
|
619 |
amazonScrapingHistory.lowestSellerSp = amDetails.lowestSellerSp
|
| 12468 |
kshitij.so |
620 |
amazonScrapingHistory.lowestSellerShippingTime = amDetails.lowestSellerShippingTime
|
|
|
621 |
amazonScrapingHistory.lowestSellerRating = amDetails.lowestSellerRating
|
|
|
622 |
amazonScrapingHistory.lowestSellerType = amDetails.lowestSellerType
|
| 12363 |
kshitij.so |
623 |
amazonScrapingHistory.secondLowestSellerSp = amDetails.secondLowestSellerSp
|
| 12468 |
kshitij.so |
624 |
amazonScrapingHistory.secondLowestSellerShippingTime = amDetails.secondLowestSellerShippingTime
|
|
|
625 |
amazonScrapingHistory.secondLowestSellerRating = amDetails.secondLowestSellerRating
|
|
|
626 |
amazonScrapingHistory.secondLowestSellerType = amDetails.secondLowestSellerType
|
| 12363 |
kshitij.so |
627 |
amazonScrapingHistory.thirdLowestSellerSp = amDetails.thirdLowestSellerSp
|
| 12468 |
kshitij.so |
628 |
amazonScrapingHistory.thirdLowestSellerShippingTime = amDetails.thirdLowestSellerShippingTime
|
|
|
629 |
amazonScrapingHistory.thirdLowestSellerRating = amDetails.thirdLowestSellerRating
|
|
|
630 |
amazonScrapingHistory.thirdLowestSellerType = amDetails.thirdLowestSellerType
|
| 12363 |
kshitij.so |
631 |
amazonScrapingHistory.wanlc = val.nlc
|
| 12447 |
kshitij.so |
632 |
amazonScrapingHistory.otherCost = val.otherCost
|
| 12363 |
kshitij.so |
633 |
amazonScrapingHistory.commission = spm.commission
|
| 12422 |
kshitij.so |
634 |
amazonScrapingHistory.competitorCommission = spm.competitorCommissionOther
|
| 12363 |
kshitij.so |
635 |
amazonScrapingHistory.returnProvision = spm.returnProvision
|
|
|
636 |
amazonScrapingHistory.courierCost = val.courierCost
|
|
|
637 |
amazonScrapingHistory.risky = val.risky
|
|
|
638 |
amazonScrapingHistory.runType = RunType._NAMES_TO_VALUES.get(runType)
|
|
|
639 |
amazonScrapingHistory.totalSeller = amDetails.totalSeller
|
|
|
640 |
amazonScrapingHistory.competitiveCategory = CompetitionCategory.NEGATIVE_MARGIN
|
|
|
641 |
amazonScrapingHistory.timestamp = timestamp
|
|
|
642 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
|
|
643 |
amazonScrapingHistory.avgSale = calculateAverageSale(val.sku) #Last five days
|
| 12432 |
kshitij.so |
644 |
amazonScrapingHistory.isPromotion = val.isPromo
|
| 12363 |
kshitij.so |
645 |
session.commit()
|
|
|
646 |
|
|
|
647 |
|
|
|
648 |
def commitCheapest(cheapest,timestamp,runType):
|
|
|
649 |
for cheapestItem in cheapest:
|
|
|
650 |
val = cheapestItem[0]
|
|
|
651 |
amDetails = cheapestItem[1]
|
|
|
652 |
amPricing = cheapestItem[2]
|
|
|
653 |
spm = val.sourcePercentage
|
|
|
654 |
amazonScrapingHistory = AmazonScrapingHistory()
|
|
|
655 |
amazonScrapingHistory.item_id = val.sku[3:]
|
|
|
656 |
amazonScrapingHistory.warehouseLocation = val.state_id
|
| 12396 |
kshitij.so |
657 |
amazonScrapingHistory.parentCategoryId = val.parent_category
|
| 12363 |
kshitij.so |
658 |
amazonScrapingHistory.ourSellingPrice = amDetails.ourSp
|
| 12432 |
kshitij.so |
659 |
amazonScrapingHistory.promoPrice = amDetails.promoPrice
|
| 12363 |
kshitij.so |
660 |
amazonScrapingHistory.lowestPossibleSp = amPricing.lowestPossibleSp
|
|
|
661 |
amazonScrapingHistory.ourRank = amDetails.ourRank
|
|
|
662 |
amazonScrapingHistory.ourInventory = val.ourInventory
|
|
|
663 |
amazonScrapingHistory.lowestSellerSp = amDetails.lowestSellerSp
|
| 12430 |
kshitij.so |
664 |
amazonScrapingHistory.lowestSellerShippingTime = amDetails.lowestSellerShippingTime
|
|
|
665 |
amazonScrapingHistory.lowestSellerRating = amDetails.lowestSellerRating
|
|
|
666 |
amazonScrapingHistory.lowestSellerType = amDetails.lowestSellerType
|
| 12363 |
kshitij.so |
667 |
amazonScrapingHistory.secondLowestSellerSp = amDetails.secondLowestSellerSp
|
| 12468 |
kshitij.so |
668 |
amazonScrapingHistory.secondLowestSellerShippingTime = amDetails.secondLowestSellerShippingTime
|
|
|
669 |
amazonScrapingHistory.secondLowestSellerRating = amDetails.secondLowestSellerRating
|
|
|
670 |
amazonScrapingHistory.secondLowestSellerType = amDetails.secondLowestSellerType
|
| 12363 |
kshitij.so |
671 |
amazonScrapingHistory.thirdLowestSellerSp = amDetails.thirdLowestSellerSp
|
| 12468 |
kshitij.so |
672 |
amazonScrapingHistory.thirdLowestSellerShippingTime = amDetails.thirdLowestSellerShippingTime
|
|
|
673 |
amazonScrapingHistory.thirdLowestSellerRating = amDetails.thirdLowestSellerRating
|
|
|
674 |
amazonScrapingHistory.thirdLowestSellerType = amDetails.thirdLowestSellerType
|
| 12447 |
kshitij.so |
675 |
amazonScrapingHistory.otherCost = val.otherCost
|
| 12363 |
kshitij.so |
676 |
amazonScrapingHistory.wanlc = val.nlc
|
|
|
677 |
amazonScrapingHistory.commission = spm.commission
|
| 12422 |
kshitij.so |
678 |
amazonScrapingHistory.competitorCommission = spm.competitorCommissionOther
|
| 12363 |
kshitij.so |
679 |
amazonScrapingHistory.returnProvision = spm.returnProvision
|
|
|
680 |
amazonScrapingHistory.courierCost = val.courierCost
|
|
|
681 |
amazonScrapingHistory.risky = val.risky
|
|
|
682 |
amazonScrapingHistory.runType = RunType._NAMES_TO_VALUES.get(runType)
|
|
|
683 |
amazonScrapingHistory.totalSeller = amDetails.totalSeller
|
|
|
684 |
amazonScrapingHistory.competitiveCategory = CompetitionCategory.BUY_BOX
|
|
|
685 |
amazonScrapingHistory.timestamp = timestamp
|
|
|
686 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
| 12430 |
kshitij.so |
687 |
proposed_sp = max(amDetails.secondLowestSellerSp - max((20, amDetails.secondLowestSellerSp*0.002)), amPricing.lowestPossibleSp)
|
| 12433 |
kshitij.so |
688 |
if amazonScrapingHistory.isPromotion:
|
|
|
689 |
if amazonLongTermActivePromotions.has_key(val.sku):
|
| 12466 |
kshitij.so |
690 |
proposed_sp = min(proposed_sp,(amazonLongTermActivePromotions.get(val.sku)).salePrice)
|
| 12433 |
kshitij.so |
691 |
else:
|
| 12466 |
kshitij.so |
692 |
proposed_sp = min(proposed_sp,(amazonShortTermActivePromotions.get(val.sku)).salePrice)
|
| 12468 |
kshitij.so |
693 |
#proposed_tp = getTargetTp(proposed_sp,spm,val)
|
| 12363 |
kshitij.so |
694 |
amazonScrapingHistory.proposedSp = proposed_sp
|
| 12468 |
kshitij.so |
695 |
#amazonScrapingHistory.proposedTp = proposed_tp
|
|
|
696 |
#amazonScrapingHistory.marginIncreasedPotential = proposed_tp - amPricing.ourTp
|
| 12363 |
kshitij.so |
697 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
|
|
698 |
amazonScrapingHistory.avgSale = calculateAverageSale(val.sku) #Last five days
|
| 12432 |
kshitij.so |
699 |
amazonScrapingHistory.isPromotion = val.isPromo
|
| 12363 |
kshitij.so |
700 |
session.commit()
|
|
|
701 |
|
|
|
702 |
|
|
|
703 |
|
|
|
704 |
def commitAmongCheapestAndCanCompete(amongCheapestAndCanCompete,timestamp,runType):
|
|
|
705 |
for amongCheapestAndCanCompeteItem in amongCheapestAndCanCompete:
|
|
|
706 |
val = amongCheapestAndCanCompeteItem[0]
|
|
|
707 |
amDetails = amongCheapestAndCanCompeteItem[1]
|
|
|
708 |
amPricing = amongCheapestAndCanCompeteItem[2]
|
|
|
709 |
spm = val.sourcePercentage
|
|
|
710 |
amazonScrapingHistory = AmazonScrapingHistory()
|
|
|
711 |
amazonScrapingHistory.item_id = val.sku[3:]
|
|
|
712 |
amazonScrapingHistory.warehouseLocation = val.state_id
|
| 12396 |
kshitij.so |
713 |
amazonScrapingHistory.parentCategoryId = val.parent_category
|
| 12363 |
kshitij.so |
714 |
amazonScrapingHistory.ourSellingPrice = amDetails.ourSp
|
| 12432 |
kshitij.so |
715 |
amazonScrapingHistory.promoPrice = amDetails.promoPrice
|
| 12363 |
kshitij.so |
716 |
amazonScrapingHistory.lowestPossibleSp = amPricing.lowestPossibleSp
|
|
|
717 |
amazonScrapingHistory.ourRank = amDetails.ourRank
|
|
|
718 |
amazonScrapingHistory.ourInventory = val.ourInventory
|
|
|
719 |
amazonScrapingHistory.lowestSellerSp = amDetails.lowestSellerSp
|
| 12430 |
kshitij.so |
720 |
amazonScrapingHistory.lowestSellerShippingTime = amDetails.lowestSellerShippingTime
|
|
|
721 |
amazonScrapingHistory.lowestSellerRating = amDetails.lowestSellerRating
|
|
|
722 |
amazonScrapingHistory.lowestSellerType = amDetails.lowestSellerType
|
| 12363 |
kshitij.so |
723 |
amazonScrapingHistory.secondLowestSellerSp = amDetails.secondLowestSellerSp
|
| 12468 |
kshitij.so |
724 |
amazonScrapingHistory.secondLowestSellerShippingTime = amDetails.secondLowestSellerShippingTime
|
|
|
725 |
amazonScrapingHistory.secondLowestSellerRating = amDetails.secondLowestSellerRating
|
|
|
726 |
amazonScrapingHistory.secondLowestSellerType = amDetails.secondLowestSellerType
|
|
|
727 |
amazonScrapingHistory.thirdLowestLowestSellerSp = amDetails.thirdLowestLowestSellerSp
|
|
|
728 |
amazonScrapingHistory.thirdLowestSellerShippingTime = amDetails.thirdLowestSellerShippingTime
|
|
|
729 |
amazonScrapingHistory.thirdLowestSellerRating = amDetails.thirdLowestSellerRating
|
|
|
730 |
amazonScrapingHistory.thirdLowestSellerType = amDetails.thirdLowestSellerType
|
| 12447 |
kshitij.so |
731 |
amazonScrapingHistory.otherCost = val.otherCost
|
| 12363 |
kshitij.so |
732 |
amazonScrapingHistory.wanlc = val.nlc
|
|
|
733 |
amazonScrapingHistory.commission = spm.commission
|
| 12422 |
kshitij.so |
734 |
amazonScrapingHistory.competitorCommission = spm.competitorCommissionOther
|
| 12363 |
kshitij.so |
735 |
amazonScrapingHistory.returnProvision = spm.returnProvision
|
|
|
736 |
amazonScrapingHistory.courierCost = val.courierCost
|
|
|
737 |
amazonScrapingHistory.risky = val.risky
|
|
|
738 |
amazonScrapingHistory.runType = RunType._NAMES_TO_VALUES.get(runType)
|
|
|
739 |
amazonScrapingHistory.totalSeller = amDetails.totalSeller
|
|
|
740 |
amazonScrapingHistory.competitiveCategory = CompetitionCategory.AMONG_CHEAPEST_CAN_COMPETE
|
|
|
741 |
amazonScrapingHistory.timestamp = timestamp
|
|
|
742 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
|
|
743 |
proposed_sp = max(amDetails.lowestSellerSp - max((5, amDetails.lowestSellerSp*0.001)), amPricing.lowestPossibleSp)
|
| 12468 |
kshitij.so |
744 |
#proposed_tp = getTargetTp(proposed_sp,spm,val)
|
| 12363 |
kshitij.so |
745 |
amazonScrapingHistory.proposedSp = proposed_sp
|
| 12468 |
kshitij.so |
746 |
#amazonScrapingHistory.proposedTp = proposed_tp
|
| 12363 |
kshitij.so |
747 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
|
|
748 |
amazonScrapingHistory.avgSale = calculateAverageSale(val.sku) #Last five days
|
| 12432 |
kshitij.so |
749 |
amazonScrapingHistory.isPromotion = val.isPromo
|
| 12363 |
kshitij.so |
750 |
session.commit()
|
|
|
751 |
|
|
|
752 |
def commitCanCompete(canCompete,timestamp,runType):
|
|
|
753 |
for canCompeteItem in canCompete:
|
|
|
754 |
val = canCompeteItem[0]
|
|
|
755 |
amDetails = canCompeteItem[1]
|
|
|
756 |
amPricing = canCompeteItem[2]
|
|
|
757 |
spm = val.sourcePercentage
|
|
|
758 |
amazonScrapingHistory = AmazonScrapingHistory()
|
|
|
759 |
amazonScrapingHistory.item_id = val.sku[3:]
|
|
|
760 |
amazonScrapingHistory.warehouseLocation = val.state_id
|
| 12396 |
kshitij.so |
761 |
amazonScrapingHistory.parentCategoryId = val.parent_category
|
| 12363 |
kshitij.so |
762 |
amazonScrapingHistory.ourSellingPrice = amDetails.ourSp
|
| 12432 |
kshitij.so |
763 |
amazonScrapingHistory.promoPrice = amDetails.promoPrice
|
| 12363 |
kshitij.so |
764 |
amazonScrapingHistory.lowestPossibleSp = amPricing.lowestPossibleSp
|
|
|
765 |
amazonScrapingHistory.ourRank = amDetails.ourRank
|
|
|
766 |
amazonScrapingHistory.ourInventory = val.ourInventory
|
|
|
767 |
amazonScrapingHistory.lowestSellerSp = amDetails.lowestSellerSp
|
| 12430 |
kshitij.so |
768 |
amazonScrapingHistory.lowestSellerShippingTime = amDetails.lowestSellerShippingTime
|
|
|
769 |
amazonScrapingHistory.lowestSellerRating = amDetails.lowestSellerRating
|
|
|
770 |
amazonScrapingHistory.lowestSellerType = amDetails.lowestSellerType
|
| 12363 |
kshitij.so |
771 |
amazonScrapingHistory.secondLowestSellerSp = amDetails.secondLowestSellerSp
|
| 12468 |
kshitij.so |
772 |
amazonScrapingHistory.secondLowestSellerShippingTime = amDetails.secondLowestSellerShippingTime
|
|
|
773 |
amazonScrapingHistory.secondLowestSellerRating = amDetails.secondLowestSellerRating
|
|
|
774 |
amazonScrapingHistory.secondLowestSellerType = amDetails.secondLowestSellerType
|
| 12363 |
kshitij.so |
775 |
amazonScrapingHistory.thirdLowestSellerSp = amDetails.thirdLowestSellerSp
|
| 12468 |
kshitij.so |
776 |
amazonScrapingHistory.thirdLowestSellerShippingTime = amDetails.thirdLowestSellerShippingTime
|
|
|
777 |
amazonScrapingHistory.thirdLowestSellerRating = amDetails.thirdLowestSellerRating
|
|
|
778 |
amazonScrapingHistory.thirdLowestSellerType = amDetails.thirdLowestSellerType
|
| 12447 |
kshitij.so |
779 |
amazonScrapingHistory.otherCost = val.otherCost
|
| 12363 |
kshitij.so |
780 |
amazonScrapingHistory.wanlc = val.nlc
|
|
|
781 |
amazonScrapingHistory.commission = spm.commission
|
| 12422 |
kshitij.so |
782 |
amazonScrapingHistory.competitorCommission = spm.competitorCommissionOther
|
| 12363 |
kshitij.so |
783 |
amazonScrapingHistory.returnProvision = spm.returnProvision
|
|
|
784 |
amazonScrapingHistory.courierCost = val.courierCost
|
|
|
785 |
amazonScrapingHistory.risky = val.risky
|
|
|
786 |
amazonScrapingHistory.runType = RunType._NAMES_TO_VALUES.get(runType)
|
|
|
787 |
amazonScrapingHistory.totalSeller = amDetails.totalSeller
|
|
|
788 |
amazonScrapingHistory.competitiveCategory = CompetitionCategory.COMPETITIVE
|
|
|
789 |
amazonScrapingHistory.timestamp = timestamp
|
|
|
790 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
|
|
791 |
proposed_sp = max(amDetails.lowestSellerSp - max((5, amDetails.lowestSellerSp*0.001)), amPricing.lowestPossibleSp)
|
| 12468 |
kshitij.so |
792 |
#proposed_tp = getTargetTp(proposed_sp,spm,val)
|
| 12363 |
kshitij.so |
793 |
amazonScrapingHistory.proposedSp = proposed_sp
|
| 12468 |
kshitij.so |
794 |
#amazonScrapingHistory.proposedTp = proposed_tp
|
| 12363 |
kshitij.so |
795 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
|
|
796 |
amazonScrapingHistory.avgSale = calculateAverageSale(val.sku) #Last five days
|
| 12432 |
kshitij.so |
797 |
amazonScrapingHistory.isPromotion = val.isPromo
|
| 12363 |
kshitij.so |
798 |
session.commit()
|
|
|
799 |
|
| 12383 |
kshitij.so |
800 |
def commitAlmostCompete(almostCompete,timestamp,runType):
|
| 12396 |
kshitij.so |
801 |
for almostCompeteItem in almostCompete:
|
|
|
802 |
val = almostCompeteItem[0]
|
|
|
803 |
amDetails = almostCompeteItem[1]
|
|
|
804 |
amPricing = almostCompeteItem[2]
|
|
|
805 |
spm = val.sourcePercentage
|
|
|
806 |
amazonScrapingHistory = AmazonScrapingHistory()
|
|
|
807 |
amazonScrapingHistory.item_id = val.sku[3:]
|
|
|
808 |
amazonScrapingHistory.warehouseLocation = val.state_id
|
|
|
809 |
amazonScrapingHistory.parentCategoryId = val.parent_category
|
|
|
810 |
amazonScrapingHistory.ourSellingPrice = amDetails.ourSp
|
| 12432 |
kshitij.so |
811 |
amazonScrapingHistory.promoPrice = amDetails.promoPrice
|
| 12396 |
kshitij.so |
812 |
amazonScrapingHistory.lowestPossibleSp = amPricing.lowestPossibleSp
|
|
|
813 |
amazonScrapingHistory.ourRank = amDetails.ourRank
|
|
|
814 |
amazonScrapingHistory.ourInventory = val.ourInventory
|
|
|
815 |
amazonScrapingHistory.lowestSellerSp = amDetails.lowestSellerSp
|
| 12430 |
kshitij.so |
816 |
amazonScrapingHistory.lowestSellerShippingTime = amDetails.lowestSellerShippingTime
|
|
|
817 |
amazonScrapingHistory.lowestSellerRating = amDetails.lowestSellerRating
|
|
|
818 |
amazonScrapingHistory.lowestSellerType = amDetails.lowestSellerType
|
| 12396 |
kshitij.so |
819 |
amazonScrapingHistory.secondLowestSellerSp = amDetails.secondLowestSellerSp
|
| 12468 |
kshitij.so |
820 |
amazonScrapingHistory.secondLowestSellerShippingTime = amDetails.secondLowestSellerShippingTime
|
|
|
821 |
amazonScrapingHistory.secondLowestSellerRating = amDetails.secondLowestSellerRating
|
|
|
822 |
amazonScrapingHistory.secondLowestSellerType = amDetails.secondLowestSellerType
|
| 12396 |
kshitij.so |
823 |
amazonScrapingHistory.thirdLowestSellerSp = amDetails.thirdLowestSellerSp
|
| 12468 |
kshitij.so |
824 |
amazonScrapingHistory.thirdLowestSellerShippingTime = amDetails.thirdLowestSellerShippingTime
|
|
|
825 |
amazonScrapingHistory.thirdLowestSellerRating = amDetails.thirdLowestSellerRating
|
|
|
826 |
amazonScrapingHistory.thirdLowestSellerType = amDetails.thirdLowestSellerType
|
| 12447 |
kshitij.so |
827 |
amazonScrapingHistory.otherCost = val.otherCost
|
| 12396 |
kshitij.so |
828 |
amazonScrapingHistory.wanlc = val.nlc
|
|
|
829 |
amazonScrapingHistory.commission = spm.commission
|
| 12422 |
kshitij.so |
830 |
amazonScrapingHistory.competitorCommission = spm.competitorCommissionOther
|
| 12396 |
kshitij.so |
831 |
amazonScrapingHistory.returnProvision = spm.returnProvision
|
|
|
832 |
amazonScrapingHistory.courierCost = val.courierCost
|
|
|
833 |
amazonScrapingHistory.risky = val.risky
|
|
|
834 |
amazonScrapingHistory.runType = RunType._NAMES_TO_VALUES.get(runType)
|
|
|
835 |
amazonScrapingHistory.totalSeller = amDetails.totalSeller
|
|
|
836 |
amazonScrapingHistory.competitiveCategory = CompetitionCategory.ALMOST_COMPETE
|
|
|
837 |
amazonScrapingHistory.timestamp = timestamp
|
|
|
838 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
| 12425 |
kshitij.so |
839 |
proposed_sp = min(amDetails.lowestSellerSp*(1+.01),amPricing.lowestPossibleSp)
|
| 12468 |
kshitij.so |
840 |
#proposed_tp = getTargetTp(proposed_sp,spm,val)
|
|
|
841 |
#target_nlc = proposed_tp - amPricing.lowestPossibleTp + val.nlc
|
| 12396 |
kshitij.so |
842 |
amazonScrapingHistory.proposedSp = proposed_sp
|
| 12468 |
kshitij.so |
843 |
#amazonScrapingHistory.proposedTp = proposed_tp
|
|
|
844 |
#amazonScrapingHistory.targetNlc = target_nlc
|
| 12396 |
kshitij.so |
845 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
|
|
846 |
amazonScrapingHistory.avgSale = calculateAverageSale(val.sku) #Last five days
|
| 12432 |
kshitij.so |
847 |
amazonScrapingHistory.isPromotion = val.isPromo
|
| 12396 |
kshitij.so |
848 |
session.commit()
|
| 12363 |
kshitij.so |
849 |
|
| 12396 |
kshitij.so |
850 |
|
| 12363 |
kshitij.so |
851 |
def commitCantCompete(cantCompete, timestamp,runType):
|
|
|
852 |
for cantCompeteItem in cantCompete:
|
|
|
853 |
val = cantCompeteItem[0]
|
|
|
854 |
amDetails = cantCompeteItem[1]
|
|
|
855 |
amPricing = cantCompeteItem[2]
|
|
|
856 |
spm = val.sourcePercentage
|
|
|
857 |
amazonScrapingHistory = AmazonScrapingHistory()
|
|
|
858 |
amazonScrapingHistory.item_id = val.sku[3:]
|
|
|
859 |
amazonScrapingHistory.warehouseLocation = val.state_id
|
| 12396 |
kshitij.so |
860 |
amazonScrapingHistory.parentCategoryId = val.parent_category
|
| 12363 |
kshitij.so |
861 |
amazonScrapingHistory.ourSellingPrice = amDetails.ourSp
|
| 12432 |
kshitij.so |
862 |
amazonScrapingHistory.promoPrice = amDetails.promoPrice
|
| 12363 |
kshitij.so |
863 |
amazonScrapingHistory.lowestPossibleSp = amPricing.lowestPossibleSp
|
|
|
864 |
amazonScrapingHistory.ourRank = amDetails.ourRank
|
|
|
865 |
amazonScrapingHistory.ourInventory = val.ourInventory
|
|
|
866 |
amazonScrapingHistory.lowestSellerSp = amDetails.lowestSellerSp
|
| 12430 |
kshitij.so |
867 |
amazonScrapingHistory.lowestSellerShippingTime = amDetails.lowestSellerShippingTime
|
|
|
868 |
amazonScrapingHistory.lowestSellerRating = amDetails.lowestSellerRating
|
|
|
869 |
amazonScrapingHistory.lowestSellerType = amDetails.lowestSellerType
|
| 12363 |
kshitij.so |
870 |
amazonScrapingHistory.secondLowestSellerSp = amDetails.secondLowestSellerSp
|
| 12468 |
kshitij.so |
871 |
amazonScrapingHistory.secondLowestSellerShippingTime = amDetails.secondLowestSellerShippingTime
|
|
|
872 |
amazonScrapingHistory.secondLowestSellerRating = amDetails.secondLowestSellerRating
|
|
|
873 |
amazonScrapingHistory.secondLowestSellerType = amDetails.secondLowestSellerType
|
| 12363 |
kshitij.so |
874 |
amazonScrapingHistory.thirdLowestSellerSp = amDetails.thirdLowestSellerSp
|
| 12468 |
kshitij.so |
875 |
amazonScrapingHistory.thirdLowestSellerShippingTime = amDetails.thirdLowestSellerShippingTime
|
|
|
876 |
amazonScrapingHistory.thirdLowestSellerRating = amDetails.thirdLowestSellerRating
|
|
|
877 |
amazonScrapingHistory.thirdLowestSellerType = amDetails.thirdLowestSellerType
|
| 12447 |
kshitij.so |
878 |
amazonScrapingHistory.otherCost = val.otherCost
|
| 12363 |
kshitij.so |
879 |
amazonScrapingHistory.wanlc = val.nlc
|
|
|
880 |
amazonScrapingHistory.commission = spm.commission
|
| 12422 |
kshitij.so |
881 |
amazonScrapingHistory.competitorCommission = spm.competitorCommissionOther
|
| 12363 |
kshitij.so |
882 |
amazonScrapingHistory.returnProvision = spm.returnProvision
|
|
|
883 |
amazonScrapingHistory.courierCost = val.courierCost
|
|
|
884 |
amazonScrapingHistory.risky = val.risky
|
|
|
885 |
amazonScrapingHistory.runType = RunType._NAMES_TO_VALUES.get(runType)
|
|
|
886 |
amazonScrapingHistory.totalSeller = amDetails.totalSeller
|
|
|
887 |
amazonScrapingHistory.competitiveCategory = CompetitionCategory.CANT_COMPETE
|
|
|
888 |
amazonScrapingHistory.timestamp = timestamp
|
|
|
889 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
|
|
890 |
proposed_sp = amDetails.lowestSellerSp - max(5, amDetails.lowestSellerSp*0.001)
|
| 12468 |
kshitij.so |
891 |
#proposed_tp = getTargetTp(proposed_sp,spm,val)
|
|
|
892 |
#target_nlc = proposed_tp - amPricing.lowestPossibleTp + val.nlc
|
| 12363 |
kshitij.so |
893 |
amazonScrapingHistory.proposedSp = proposed_sp
|
| 12468 |
kshitij.so |
894 |
#amazonScrapingHistory.proposedTp = proposed_tp
|
|
|
895 |
#amazonScrapingHistory.targetNlc = target_nlc
|
| 12363 |
kshitij.so |
896 |
amazonScrapingHistory.multipleListings = amDetails.multipleListings
|
|
|
897 |
amazonScrapingHistory.avgSale = calculateAverageSale(val.sku) #Last five days
|
| 12432 |
kshitij.so |
898 |
amazonScrapingHistory.isPromotion = val.isPromo
|
| 12363 |
kshitij.so |
899 |
session.commit()
|
|
|
900 |
|
| 12396 |
kshitij.so |
901 |
def markAutoFavourites(time):
|
|
|
902 |
nowAutoFav = []
|
|
|
903 |
previouslyAutoFav = []
|
|
|
904 |
stockList = []
|
|
|
905 |
saleList = []
|
|
|
906 |
items = session.query(func.sum(AmazonScrapingHistory.ourInventory),AmazonScrapingHistory.item_id).group_by(AmazonScrapingHistory.item_id).all()
|
|
|
907 |
allItems = session.query(Amazonlisted).all()
|
|
|
908 |
for item in items:
|
|
|
909 |
reason = ""
|
|
|
910 |
if item[0]>=5:
|
|
|
911 |
stockList.append(item[1])
|
|
|
912 |
|
|
|
913 |
for sku, val in saleMap.iteritems():
|
|
|
914 |
totalSale = 0
|
|
|
915 |
item_id = sku.replace('FBA','').replace('FBB','')
|
|
|
916 |
val =saleMap.get('FBA'+str(item_id))
|
|
|
917 |
if val is not None:
|
|
|
918 |
for sale in val:
|
|
|
919 |
totalSale += sale.totalOrderCount
|
|
|
920 |
val =saleMap.get('FBB'+str(item_id))
|
|
|
921 |
if val is not None:
|
|
|
922 |
for sale in val:
|
|
|
923 |
totalSale += sale.totalOrderCount
|
|
|
924 |
if totalSale > 0:
|
|
|
925 |
saleList.append(item_id)
|
|
|
926 |
|
|
|
927 |
for aItem in allItems:
|
|
|
928 |
reason = ""
|
|
|
929 |
toMark = False
|
|
|
930 |
if aItem.itemId in saleList:
|
|
|
931 |
toMark = True
|
|
|
932 |
reason+="Total FC sale is greater than 1 for last five days.."
|
|
|
933 |
if aItem.itemId in stockList:
|
|
|
934 |
toMark = True
|
|
|
935 |
reason+="Item is present in buy box in last 3 days"
|
|
|
936 |
if not aItem.autoFavourite:
|
|
|
937 |
print "Item is not under auto favourite"
|
|
|
938 |
if toMark:
|
|
|
939 |
temp=[]
|
|
|
940 |
temp.append(aItem.itemId)
|
|
|
941 |
temp.append(reason)
|
|
|
942 |
nowAutoFav.append(temp)
|
|
|
943 |
if (not toMark) and aItem.autoFavourite:
|
|
|
944 |
previouslyAutoFav.append(aItem.itemId)
|
|
|
945 |
aItem.autoFavourite = toMark
|
|
|
946 |
session.commit()
|
|
|
947 |
return previouslyAutoFav, nowAutoFav
|
|
|
948 |
|
| 12444 |
kshitij.so |
949 |
def writeReport(timestamp,autoDecreaseItems,autoIncreaseItems,previousAutoFav,nowAutoFav,runType):
|
| 12396 |
kshitij.so |
950 |
wbk = xlwt.Workbook()
|
|
|
951 |
sheet = wbk.add_sheet('Can\'t Compete')
|
|
|
952 |
xstr = lambda s: s or ""
|
|
|
953 |
heading_xf = xlwt.easyxf('font: bold on; align: wrap off, vert centre, horiz center')
|
|
|
954 |
|
|
|
955 |
excel_integer_format = '0'
|
|
|
956 |
integer_style = xlwt.XFStyle()
|
|
|
957 |
integer_style.num_format_str = excel_integer_format
|
|
|
958 |
|
|
|
959 |
sheet.write(0, 0, "Item Id", heading_xf)
|
|
|
960 |
sheet.write(0, 1, "Amazon Sku", heading_xf)
|
|
|
961 |
sheet.write(0, 2, "Asin", heading_xf)
|
|
|
962 |
sheet.write(0, 3, "Location", heading_xf)
|
|
|
963 |
sheet.write(0, 4, "Brand", heading_xf)
|
|
|
964 |
sheet.write(0, 5, "Product Name", heading_xf)
|
|
|
965 |
sheet.write(0, 6, "Weight", heading_xf)
|
|
|
966 |
sheet.write(0, 7, "Courier Cost", heading_xf)
|
|
|
967 |
sheet.write(0, 8, "Our SP", heading_xf)
|
| 12432 |
kshitij.so |
968 |
sheet.write(0, 9, "Promo Price", heading_xf)
|
|
|
969 |
sheet.write(0, 10, "Is Promotion", heading_xf)
|
|
|
970 |
sheet.write(0, 11, "Lowest Possible SP", heading_xf)
|
| 12396 |
kshitij.so |
971 |
sheet.write(0, 12, "Rank", heading_xf)
|
|
|
972 |
sheet.write(0, 13, "Our Inventory", heading_xf)
|
| 12432 |
kshitij.so |
973 |
sheet.write(0, 14, "Lowest Seller SP", heading_xf)
|
|
|
974 |
sheet.write(0, 15, "Lowest Seller Rating", heading_xf)
|
|
|
975 |
sheet.write(0, 16, "Lowest Seller Shipping Time", heading_xf)
|
| 12396 |
kshitij.so |
976 |
sheet.write(0, 17, "Second Lowest Seller SP", heading_xf)
|
| 12432 |
kshitij.so |
977 |
sheet.write(0, 18, "Second Lowest Seller Rating", heading_xf)
|
|
|
978 |
sheet.write(0, 19, "Second Lowest Seller Shipping Time", heading_xf)
|
|
|
979 |
sheet.write(0, 20, "Third Lowest Seller SP", heading_xf)
|
|
|
980 |
sheet.write(0, 21, "Third Lowest Seller Rating", heading_xf)
|
|
|
981 |
sheet.write(0, 22, "Third Lowest Seller Shipping Time", heading_xf)
|
| 12447 |
kshitij.so |
982 |
sheet.write(0, 23, "Other Cost", heading_xf)
|
|
|
983 |
sheet.write(0, 24, "WANLC", heading_xf)
|
|
|
984 |
sheet.write(0, 25, "Commission", heading_xf)
|
|
|
985 |
sheet.write(0, 26, "Competitor Commission", heading_xf)
|
|
|
986 |
sheet.write(0, 27, "Return Provision", heading_xf)
|
|
|
987 |
sheet.write(0, 28, "Margin", heading_xf)
|
|
|
988 |
sheet.write(0, 29, "Risky", heading_xf)
|
|
|
989 |
sheet.write(0, 30, "Proposed Sp", heading_xf)
|
| 12468 |
kshitij.so |
990 |
sheet.write(0, 31, "Avg Sale", heading_xf)
|
|
|
991 |
sheet.write(0, 32, "Sales History", heading_xf)
|
|
|
992 |
sheet.write(0, 33, "Decision", heading_xf)
|
|
|
993 |
sheet.write(0, 34, "Reason", heading_xf)
|
|
|
994 |
sheet.write(0, 35, "Updated Price", heading_xf)
|
| 12396 |
kshitij.so |
995 |
|
|
|
996 |
sheet_iterator = 1
|
|
|
997 |
cantCompeteItems = session.query(AmazonScrapingHistory,Item).join((Item,AmazonScrapingHistory.item_id==Item.id)).filter(AmazonScrapingHistory.competitiveCategory==CompetitionCategory.CANT_COMPETE).all()
|
|
|
998 |
for cantCompeteItem in cantCompeteItems:
|
|
|
999 |
amScraping = cantCompeteItem[0]
|
|
|
1000 |
item = cantCompeteItem[1]
|
|
|
1001 |
sheet.write(sheet_iterator, 0, amScraping.item_id)
|
|
|
1002 |
if amScraping.warehouseLocation == 1:
|
|
|
1003 |
sku = 'FBA'+str(amScraping.item_id)
|
|
|
1004 |
loc = 'MUMBAI'
|
|
|
1005 |
else:
|
|
|
1006 |
sku = 'FBB'+str(amScraping.item_id)
|
|
|
1007 |
loc = 'BANGLORE'
|
|
|
1008 |
sheet.write(sheet_iterator, 1, sku)
|
|
|
1009 |
sheet.write(sheet_iterator, 2, (amazonAsinPrice.get(sku).asin))
|
|
|
1010 |
sheet.write(sheet_iterator, 3, loc)
|
|
|
1011 |
sheet.write(sheet_iterator, 4, item.brand)
|
|
|
1012 |
sheet.write(sheet_iterator, 5, xstr(item.brand)+" "+xstr(item.model_name)+" "+xstr(item.model_number)+" "+xstr(item.color))
|
|
|
1013 |
sheet.write(sheet_iterator, 6, item.weight)
|
|
|
1014 |
sheet.write(sheet_iterator, 7, amScraping.courierCost)
|
|
|
1015 |
sheet.write(sheet_iterator, 8, amScraping.ourSellingPrice)
|
| 12432 |
kshitij.so |
1016 |
sheet.write(sheet_iterator, 9, amScraping.promoPrice)
|
|
|
1017 |
if amScraping.isPromotion:
|
|
|
1018 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1019 |
else:
|
|
|
1020 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1021 |
sheet.write(sheet_iterator, 11, amScraping.lowestPossibleSp)
|
| 12396 |
kshitij.so |
1022 |
if amScraping.ourRank > 3:
|
|
|
1023 |
sheet.write(sheet_iterator, 12, 'Greater than 3')
|
|
|
1024 |
else:
|
|
|
1025 |
sheet.write(sheet_iterator, 12, amScraping.ourRank)
|
|
|
1026 |
sheet.write(sheet_iterator, 13, amScraping.ourInventory)
|
| 12432 |
kshitij.so |
1027 |
sheet.write(sheet_iterator, 14, amScraping.lowestSellerSp)
|
|
|
1028 |
sheet.write(sheet_iterator, 15, amScraping.lowestSellerRating)
|
|
|
1029 |
sheet.write(sheet_iterator, 16, amScraping.lowestSellerShippingTime)
|
| 12396 |
kshitij.so |
1030 |
sheet.write(sheet_iterator, 17, amScraping.secondLowestSellerSp)
|
| 12432 |
kshitij.so |
1031 |
sheet.write(sheet_iterator, 18, amScraping.secondLowestSellerRating)
|
|
|
1032 |
sheet.write(sheet_iterator, 19, amScraping.secondLowestSellerShippingTime)
|
|
|
1033 |
sheet.write(sheet_iterator, 20, amScraping.thirdLowestSellerSp)
|
|
|
1034 |
sheet.write(sheet_iterator, 21, amScraping.thirdLowestSellerRating)
|
|
|
1035 |
sheet.write(sheet_iterator, 22, amScraping.thirdLowestSellerShippingTime)
|
| 12447 |
kshitij.so |
1036 |
sheet.write(sheet_iterator, 23, amScraping.otherCost)
|
|
|
1037 |
sheet.write(sheet_iterator, 24, amScraping.wanlc)
|
|
|
1038 |
sheet.write(sheet_iterator, 25, amScraping.commission)
|
|
|
1039 |
sheet.write(sheet_iterator, 26, amScraping.competitorCommission)
|
|
|
1040 |
sheet.write(sheet_iterator, 27, amScraping.returnProvision)
|
|
|
1041 |
sheet.write(sheet_iterator, 28, round(amScraping.ourSellingPrice - amScraping.lowestPossibleSp))
|
|
|
1042 |
sheet.write(sheet_iterator, 29, item.risky)
|
|
|
1043 |
sheet.write(sheet_iterator, 30, amScraping.proposedSp)
|
| 12468 |
kshitij.so |
1044 |
sheet.write(sheet_iterator, 31, amScraping.avgSale)
|
|
|
1045 |
sheet.write(sheet_iterator, 32, getOosString(saleMap.get(sku)))
|
| 12444 |
kshitij.so |
1046 |
if amScraping.decision is None:
|
| 12468 |
kshitij.so |
1047 |
sheet.write(sheet_iterator, 33, 'Auto Pricing Inactive')
|
| 12444 |
kshitij.so |
1048 |
sheet_iterator+=1
|
|
|
1049 |
continue
|
| 12468 |
kshitij.so |
1050 |
sheet.write(sheet_iterator, 33, Decision._VALUES_TO_NAMES.get(amScraping.decision))
|
|
|
1051 |
sheet.write(sheet_iterator, 34, amScraping.reason)
|
| 12444 |
kshitij.so |
1052 |
if Decision._VALUES_TO_NAMES.get(amScraping.decision) == "AUTO_DECREMENT_SUCCESS":
|
| 12468 |
kshitij.so |
1053 |
sheet.write(sheet_iterator, 35, math.ceil(amScraping.proposedSellingPrice))
|
| 12444 |
kshitij.so |
1054 |
if Decision._VALUES_TO_NAMES.get(amScraping.decision) == "AUTO_INCREMENT_SUCCESS":
|
| 12468 |
kshitij.so |
1055 |
sheet.write(sheet_iterator, 35, math.ceil(amScraping.ourSellingPrice+max(10,.01*amScraping.ourSellingPrice)))
|
| 12396 |
kshitij.so |
1056 |
sheet_iterator+=1
|
|
|
1057 |
|
|
|
1058 |
sheet = wbk.add_sheet('Competitive')
|
|
|
1059 |
xstr = lambda s: s or ""
|
|
|
1060 |
heading_xf = xlwt.easyxf('font: bold on; align: wrap off, vert centre, horiz center')
|
|
|
1061 |
|
|
|
1062 |
excel_integer_format = '0'
|
|
|
1063 |
integer_style = xlwt.XFStyle()
|
|
|
1064 |
integer_style.num_format_str = excel_integer_format
|
|
|
1065 |
|
|
|
1066 |
sheet.write(0, 0, "Item Id", heading_xf)
|
|
|
1067 |
sheet.write(0, 1, "Amazon Sku", heading_xf)
|
|
|
1068 |
sheet.write(0, 2, "Asin", heading_xf)
|
|
|
1069 |
sheet.write(0, 3, "Location", heading_xf)
|
|
|
1070 |
sheet.write(0, 4, "Brand", heading_xf)
|
|
|
1071 |
sheet.write(0, 5, "Product Name", heading_xf)
|
|
|
1072 |
sheet.write(0, 6, "Weight", heading_xf)
|
|
|
1073 |
sheet.write(0, 7, "Courier Cost", heading_xf)
|
|
|
1074 |
sheet.write(0, 8, "Our SP", heading_xf)
|
| 12432 |
kshitij.so |
1075 |
sheet.write(0, 9, "Promo Price", heading_xf)
|
|
|
1076 |
sheet.write(0, 10, "Is Promotion", heading_xf)
|
|
|
1077 |
sheet.write(0, 11, "Lowest Possible SP", heading_xf)
|
| 12396 |
kshitij.so |
1078 |
sheet.write(0, 12, "Rank", heading_xf)
|
|
|
1079 |
sheet.write(0, 13, "Our Inventory", heading_xf)
|
| 12432 |
kshitij.so |
1080 |
sheet.write(0, 14, "Lowest Seller SP", heading_xf)
|
|
|
1081 |
sheet.write(0, 15, "Lowest Seller Rating", heading_xf)
|
|
|
1082 |
sheet.write(0, 16, "Lowest Seller Shipping Time", heading_xf)
|
| 12396 |
kshitij.so |
1083 |
sheet.write(0, 17, "Second Lowest Seller SP", heading_xf)
|
| 12432 |
kshitij.so |
1084 |
sheet.write(0, 18, "Second Lowest Seller Rating", heading_xf)
|
|
|
1085 |
sheet.write(0, 19, "Second Lowest Seller Shipping Time", heading_xf)
|
|
|
1086 |
sheet.write(0, 20, "Third Lowest Seller SP", heading_xf)
|
|
|
1087 |
sheet.write(0, 21, "Third Lowest Seller Rating", heading_xf)
|
|
|
1088 |
sheet.write(0, 22, "Third Lowest Seller Shipping Time", heading_xf)
|
| 12447 |
kshitij.so |
1089 |
sheet.write(0, 23, "Other Cost", heading_xf)
|
|
|
1090 |
sheet.write(0, 24, "WANLC", heading_xf)
|
|
|
1091 |
sheet.write(0, 25, "Commission", heading_xf)
|
|
|
1092 |
sheet.write(0, 26, "Competitor Commission", heading_xf)
|
|
|
1093 |
sheet.write(0, 27, "Return Provision", heading_xf)
|
|
|
1094 |
sheet.write(0, 28, "Margin", heading_xf)
|
|
|
1095 |
sheet.write(0, 29, "Risky", heading_xf)
|
|
|
1096 |
sheet.write(0, 30, "Proposed Sp", heading_xf)
|
| 12468 |
kshitij.so |
1097 |
sheet.write(0, 31, "Avg Sale", heading_xf)
|
|
|
1098 |
sheet.write(0, 32, "Sales History", heading_xf)
|
|
|
1099 |
sheet.write(0, 33, "Decision", heading_xf)
|
|
|
1100 |
sheet.write(0, 34, "Reason", heading_xf)
|
|
|
1101 |
sheet.write(0, 35, "Updated Price", heading_xf)
|
| 12396 |
kshitij.so |
1102 |
|
|
|
1103 |
sheet_iterator = 1
|
|
|
1104 |
competitiveItems = session.query(AmazonScrapingHistory,Item).join((Item,AmazonScrapingHistory.item_id==Item.id)).filter(AmazonScrapingHistory.competitiveCategory==CompetitionCategory.COMPETITIVE).all()
|
|
|
1105 |
for competitiveItem in competitiveItems:
|
|
|
1106 |
amScraping = competitiveItem[0]
|
|
|
1107 |
item = competitiveItem[1]
|
|
|
1108 |
sheet.write(sheet_iterator, 0, amScraping.item_id)
|
|
|
1109 |
if amScraping.warehouseLocation == 1:
|
|
|
1110 |
sku = 'FBA'+str(amScraping.item_id)
|
|
|
1111 |
loc = 'MUMBAI'
|
|
|
1112 |
else:
|
|
|
1113 |
sku = 'FBB'+str(amScraping.item_id)
|
|
|
1114 |
loc = 'BANGLORE'
|
|
|
1115 |
sheet.write(sheet_iterator, 1, sku)
|
|
|
1116 |
sheet.write(sheet_iterator, 2, (amazonAsinPrice.get(sku).asin))
|
|
|
1117 |
sheet.write(sheet_iterator, 3, loc)
|
|
|
1118 |
sheet.write(sheet_iterator, 4, item.brand)
|
|
|
1119 |
sheet.write(sheet_iterator, 5, xstr(item.brand)+" "+xstr(item.model_name)+" "+xstr(item.model_number)+" "+xstr(item.color))
|
|
|
1120 |
sheet.write(sheet_iterator, 6, item.weight)
|
|
|
1121 |
sheet.write(sheet_iterator, 7, amScraping.courierCost)
|
|
|
1122 |
sheet.write(sheet_iterator, 8, amScraping.ourSellingPrice)
|
| 12432 |
kshitij.so |
1123 |
sheet.write(sheet_iterator, 9, amScraping.promoPrice)
|
|
|
1124 |
if amScraping.isPromotion:
|
|
|
1125 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1126 |
else:
|
|
|
1127 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1128 |
sheet.write(sheet_iterator, 11, amScraping.lowestPossibleSp)
|
| 12396 |
kshitij.so |
1129 |
if amScraping.ourRank > 3:
|
|
|
1130 |
sheet.write(sheet_iterator, 12, 'Greater than 3')
|
|
|
1131 |
else:
|
|
|
1132 |
sheet.write(sheet_iterator, 12, amScraping.ourRank)
|
|
|
1133 |
sheet.write(sheet_iterator, 13, amScraping.ourInventory)
|
| 12432 |
kshitij.so |
1134 |
sheet.write(sheet_iterator, 14, amScraping.lowestSellerSp)
|
|
|
1135 |
sheet.write(sheet_iterator, 15, amScraping.lowestSellerRating)
|
|
|
1136 |
sheet.write(sheet_iterator, 16, amScraping.lowestSellerShippingTime)
|
| 12396 |
kshitij.so |
1137 |
sheet.write(sheet_iterator, 17, amScraping.secondLowestSellerSp)
|
| 12432 |
kshitij.so |
1138 |
sheet.write(sheet_iterator, 18, amScraping.secondLowestSellerRating)
|
|
|
1139 |
sheet.write(sheet_iterator, 19, amScraping.secondLowestSellerShippingTime)
|
|
|
1140 |
sheet.write(sheet_iterator, 20, amScraping.thirdLowestSellerSp)
|
|
|
1141 |
sheet.write(sheet_iterator, 21, amScraping.thirdLowestSellerRating)
|
|
|
1142 |
sheet.write(sheet_iterator, 22, amScraping.thirdLowestSellerShippingTime)
|
| 12447 |
kshitij.so |
1143 |
sheet.write(sheet_iterator, 23, amScraping.otherCost)
|
|
|
1144 |
sheet.write(sheet_iterator, 24, amScraping.wanlc)
|
|
|
1145 |
sheet.write(sheet_iterator, 25, amScraping.commission)
|
|
|
1146 |
sheet.write(sheet_iterator, 26, amScraping.competitorCommission)
|
|
|
1147 |
sheet.write(sheet_iterator, 27, amScraping.returnProvision)
|
|
|
1148 |
sheet.write(sheet_iterator, 28, round(amScraping.ourSellingPrice - amScraping.lowestPossibleSp))
|
|
|
1149 |
sheet.write(sheet_iterator, 29, item.risky)
|
|
|
1150 |
sheet.write(sheet_iterator, 30, amScraping.proposedSp)
|
| 12468 |
kshitij.so |
1151 |
sheet.write(sheet_iterator, 31, amScraping.avgSale)
|
|
|
1152 |
sheet.write(sheet_iterator, 32, getOosString(saleMap.get(sku)))
|
| 12444 |
kshitij.so |
1153 |
if amScraping.decision is None:
|
| 12468 |
kshitij.so |
1154 |
sheet.write(sheet_iterator, 33, 'Auto Pricing Inactive')
|
| 12444 |
kshitij.so |
1155 |
sheet_iterator+=1
|
|
|
1156 |
continue
|
| 12468 |
kshitij.so |
1157 |
sheet.write(sheet_iterator, 33, Decision._VALUES_TO_NAMES.get(amScraping.decision))
|
|
|
1158 |
sheet.write(sheet_iterator, 34, amScraping.reason)
|
| 12444 |
kshitij.so |
1159 |
if Decision._VALUES_TO_NAMES.get(amScraping.decision) == "AUTO_DECREMENT_SUCCESS":
|
| 12468 |
kshitij.so |
1160 |
sheet.write(sheet_iterator, 35, math.ceil(amScraping.proposedSellingPrice))
|
| 12444 |
kshitij.so |
1161 |
if Decision._VALUES_TO_NAMES.get(amScraping.decision) == "AUTO_INCREMENT_SUCCESS":
|
| 12468 |
kshitij.so |
1162 |
sheet.write(sheet_iterator, 35, math.ceil(amScraping.ourSellingPrice+max(10,.01*amScraping.ourSellingPrice)))
|
| 12396 |
kshitij.so |
1163 |
sheet_iterator+=1
|
|
|
1164 |
|
|
|
1165 |
sheet = wbk.add_sheet('Almost Competitive')
|
|
|
1166 |
xstr = lambda s: s or ""
|
|
|
1167 |
heading_xf = xlwt.easyxf('font: bold on; align: wrap off, vert centre, horiz center')
|
|
|
1168 |
|
|
|
1169 |
excel_integer_format = '0'
|
|
|
1170 |
integer_style = xlwt.XFStyle()
|
|
|
1171 |
integer_style.num_format_str = excel_integer_format
|
|
|
1172 |
|
|
|
1173 |
sheet.write(0, 0, "Item Id", heading_xf)
|
|
|
1174 |
sheet.write(0, 1, "Amazon Sku", heading_xf)
|
|
|
1175 |
sheet.write(0, 2, "Asin", heading_xf)
|
|
|
1176 |
sheet.write(0, 3, "Location", heading_xf)
|
|
|
1177 |
sheet.write(0, 4, "Brand", heading_xf)
|
|
|
1178 |
sheet.write(0, 5, "Product Name", heading_xf)
|
|
|
1179 |
sheet.write(0, 6, "Weight", heading_xf)
|
|
|
1180 |
sheet.write(0, 7, "Courier Cost", heading_xf)
|
|
|
1181 |
sheet.write(0, 8, "Our SP", heading_xf)
|
| 12432 |
kshitij.so |
1182 |
sheet.write(0, 9, "Promo Price", heading_xf)
|
|
|
1183 |
sheet.write(0, 10, "Is Promotion", heading_xf)
|
|
|
1184 |
sheet.write(0, 11, "Lowest Possible SP", heading_xf)
|
| 12396 |
kshitij.so |
1185 |
sheet.write(0, 12, "Rank", heading_xf)
|
|
|
1186 |
sheet.write(0, 13, "Our Inventory", heading_xf)
|
| 12432 |
kshitij.so |
1187 |
sheet.write(0, 14, "Lowest Seller SP", heading_xf)
|
|
|
1188 |
sheet.write(0, 15, "Lowest Seller Rating", heading_xf)
|
|
|
1189 |
sheet.write(0, 16, "Lowest Seller Shipping Time", heading_xf)
|
| 12396 |
kshitij.so |
1190 |
sheet.write(0, 17, "Second Lowest Seller SP", heading_xf)
|
| 12432 |
kshitij.so |
1191 |
sheet.write(0, 18, "Second Lowest Seller Rating", heading_xf)
|
|
|
1192 |
sheet.write(0, 19, "Second Lowest Seller Shipping Time", heading_xf)
|
|
|
1193 |
sheet.write(0, 20, "Third Lowest Seller SP", heading_xf)
|
|
|
1194 |
sheet.write(0, 21, "Third Lowest Seller Rating", heading_xf)
|
|
|
1195 |
sheet.write(0, 22, "Third Lowest Seller Shipping Time", heading_xf)
|
| 12447 |
kshitij.so |
1196 |
sheet.write(0, 23, "Other Cost", heading_xf)
|
|
|
1197 |
sheet.write(0, 24, "WANLC", heading_xf)
|
|
|
1198 |
sheet.write(0, 25, "Commission", heading_xf)
|
|
|
1199 |
sheet.write(0, 26, "Competitor Commission", heading_xf)
|
|
|
1200 |
sheet.write(0, 27, "Return Provision", heading_xf)
|
|
|
1201 |
sheet.write(0, 28, "Margin", heading_xf)
|
|
|
1202 |
sheet.write(0, 29, "Risky", heading_xf)
|
|
|
1203 |
sheet.write(0, 30, "Proposed Sp", heading_xf)
|
| 12468 |
kshitij.so |
1204 |
sheet.write(0, 31, "Avg Sale", heading_xf)
|
|
|
1205 |
sheet.write(0, 32, "Sales History", heading_xf)
|
|
|
1206 |
sheet.write(0, 33, "Decision", heading_xf)
|
|
|
1207 |
sheet.write(0, 34, "Reason", heading_xf)
|
|
|
1208 |
sheet.write(0, 35, "Updated Price", heading_xf)
|
| 12396 |
kshitij.so |
1209 |
|
|
|
1210 |
sheet_iterator = 1
|
|
|
1211 |
almostCompetitiveItems = session.query(AmazonScrapingHistory,Item).join((Item,AmazonScrapingHistory.item_id==Item.id)).filter(AmazonScrapingHistory.competitiveCategory==CompetitionCategory.ALMOST_COMPETE).all()
|
|
|
1212 |
for almostCompetitiveItem in almostCompetitiveItems:
|
|
|
1213 |
amScraping = almostCompetitiveItem[0]
|
|
|
1214 |
item = almostCompetitiveItem[1]
|
|
|
1215 |
sheet.write(sheet_iterator, 0, amScraping.item_id)
|
|
|
1216 |
if amScraping.warehouseLocation == 1:
|
|
|
1217 |
sku = 'FBA'+str(amScraping.item_id)
|
|
|
1218 |
loc = 'MUMBAI'
|
|
|
1219 |
else:
|
|
|
1220 |
sku = 'FBB'+str(amScraping.item_id)
|
|
|
1221 |
loc = 'BANGLORE'
|
| 12432 |
kshitij.so |
1222 |
amScraping = competitiveItem[0]
|
|
|
1223 |
item = competitiveItem[1]
|
|
|
1224 |
sheet.write(sheet_iterator, 0, amScraping.item_id)
|
|
|
1225 |
if amScraping.warehouseLocation == 1:
|
|
|
1226 |
sku = 'FBA'+str(amScraping.item_id)
|
|
|
1227 |
loc = 'MUMBAI'
|
|
|
1228 |
else:
|
|
|
1229 |
sku = 'FBB'+str(amScraping.item_id)
|
|
|
1230 |
loc = 'BANGLORE'
|
| 12396 |
kshitij.so |
1231 |
sheet.write(sheet_iterator, 1, sku)
|
|
|
1232 |
sheet.write(sheet_iterator, 2, (amazonAsinPrice.get(sku).asin))
|
|
|
1233 |
sheet.write(sheet_iterator, 3, loc)
|
|
|
1234 |
sheet.write(sheet_iterator, 4, item.brand)
|
|
|
1235 |
sheet.write(sheet_iterator, 5, xstr(item.brand)+" "+xstr(item.model_name)+" "+xstr(item.model_number)+" "+xstr(item.color))
|
|
|
1236 |
sheet.write(sheet_iterator, 6, item.weight)
|
|
|
1237 |
sheet.write(sheet_iterator, 7, amScraping.courierCost)
|
|
|
1238 |
sheet.write(sheet_iterator, 8, amScraping.ourSellingPrice)
|
| 12432 |
kshitij.so |
1239 |
sheet.write(sheet_iterator, 9, amScraping.promoPrice)
|
|
|
1240 |
if amScraping.isPromotion:
|
|
|
1241 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1242 |
else:
|
|
|
1243 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1244 |
sheet.write(sheet_iterator, 11, amScraping.lowestPossibleSp)
|
| 12396 |
kshitij.so |
1245 |
if amScraping.ourRank > 3:
|
|
|
1246 |
sheet.write(sheet_iterator, 12, 'Greater than 3')
|
|
|
1247 |
else:
|
|
|
1248 |
sheet.write(sheet_iterator, 12, amScraping.ourRank)
|
|
|
1249 |
sheet.write(sheet_iterator, 13, amScraping.ourInventory)
|
| 12432 |
kshitij.so |
1250 |
sheet.write(sheet_iterator, 14, amScraping.lowestSellerSp)
|
|
|
1251 |
sheet.write(sheet_iterator, 15, amScraping.lowestSellerRating)
|
|
|
1252 |
sheet.write(sheet_iterator, 16, amScraping.lowestSellerShippingTime)
|
| 12396 |
kshitij.so |
1253 |
sheet.write(sheet_iterator, 17, amScraping.secondLowestSellerSp)
|
| 12432 |
kshitij.so |
1254 |
sheet.write(sheet_iterator, 18, amScraping.secondLowestSellerRating)
|
|
|
1255 |
sheet.write(sheet_iterator, 19, amScraping.secondLowestSellerShippingTime)
|
|
|
1256 |
sheet.write(sheet_iterator, 20, amScraping.thirdLowestSellerSp)
|
|
|
1257 |
sheet.write(sheet_iterator, 21, amScraping.thirdLowestSellerRating)
|
|
|
1258 |
sheet.write(sheet_iterator, 22, amScraping.thirdLowestSellerShippingTime)
|
| 12447 |
kshitij.so |
1259 |
sheet.write(sheet_iterator, 23, amScraping.otherCost)
|
|
|
1260 |
sheet.write(sheet_iterator, 24, amScraping.wanlc)
|
|
|
1261 |
sheet.write(sheet_iterator, 25, amScraping.commission)
|
|
|
1262 |
sheet.write(sheet_iterator, 26, amScraping.competitorCommission)
|
|
|
1263 |
sheet.write(sheet_iterator, 27, amScraping.returnProvision)
|
|
|
1264 |
sheet.write(sheet_iterator, 28, round(amScraping.ourSellingPrice - amScraping.lowestPossibleSp))
|
|
|
1265 |
sheet.write(sheet_iterator, 29, item.risky)
|
|
|
1266 |
sheet.write(sheet_iterator, 30, amScraping.proposedSp)
|
| 12468 |
kshitij.so |
1267 |
sheet.write(sheet_iterator, 31, amScraping.avgSale)
|
|
|
1268 |
sheet.write(sheet_iterator, 32, getOosString(saleMap.get(sku)))
|
| 12444 |
kshitij.so |
1269 |
if amScraping.decision is None:
|
| 12468 |
kshitij.so |
1270 |
sheet.write(sheet_iterator, 33, 'Auto Pricing Inactive')
|
| 12444 |
kshitij.so |
1271 |
sheet_iterator+=1
|
|
|
1272 |
continue
|
| 12468 |
kshitij.so |
1273 |
sheet.write(sheet_iterator, 33, Decision._VALUES_TO_NAMES.get(amScraping.decision))
|
|
|
1274 |
sheet.write(sheet_iterator, 34, amScraping.reason)
|
| 12444 |
kshitij.so |
1275 |
if Decision._VALUES_TO_NAMES.get(amScraping.decision) == "AUTO_DECREMENT_SUCCESS":
|
| 12468 |
kshitij.so |
1276 |
sheet.write(sheet_iterator, 35, math.ceil(amScraping.proposedSellingPrice))
|
| 12444 |
kshitij.so |
1277 |
if Decision._VALUES_TO_NAMES.get(amScraping.decision) == "AUTO_INCREMENT_SUCCESS":
|
| 12468 |
kshitij.so |
1278 |
sheet.write(sheet_iterator, 35, math.ceil(amScraping.ourSellingPrice+max(10,.01*amScraping.ourSellingPrice)))
|
| 12396 |
kshitij.so |
1279 |
sheet_iterator+=1
|
|
|
1280 |
|
|
|
1281 |
sheet = wbk.add_sheet('Among Cheapest')
|
|
|
1282 |
xstr = lambda s: s or ""
|
|
|
1283 |
heading_xf = xlwt.easyxf('font: bold on; align: wrap off, vert centre, horiz center')
|
|
|
1284 |
|
|
|
1285 |
excel_integer_format = '0'
|
|
|
1286 |
integer_style = xlwt.XFStyle()
|
|
|
1287 |
integer_style.num_format_str = excel_integer_format
|
|
|
1288 |
|
|
|
1289 |
sheet.write(0, 0, "Item Id", heading_xf)
|
|
|
1290 |
sheet.write(0, 1, "Amazon Sku", heading_xf)
|
|
|
1291 |
sheet.write(0, 2, "Asin", heading_xf)
|
|
|
1292 |
sheet.write(0, 3, "Location", heading_xf)
|
|
|
1293 |
sheet.write(0, 4, "Brand", heading_xf)
|
|
|
1294 |
sheet.write(0, 5, "Product Name", heading_xf)
|
|
|
1295 |
sheet.write(0, 6, "Weight", heading_xf)
|
|
|
1296 |
sheet.write(0, 7, "Courier Cost", heading_xf)
|
|
|
1297 |
sheet.write(0, 8, "Our SP", heading_xf)
|
| 12432 |
kshitij.so |
1298 |
sheet.write(0, 9, "Promo Price", heading_xf)
|
|
|
1299 |
sheet.write(0, 10, "Is Promotion", heading_xf)
|
|
|
1300 |
sheet.write(0, 11, "Lowest Possible SP", heading_xf)
|
| 12396 |
kshitij.so |
1301 |
sheet.write(0, 12, "Rank", heading_xf)
|
|
|
1302 |
sheet.write(0, 13, "Our Inventory", heading_xf)
|
| 12432 |
kshitij.so |
1303 |
sheet.write(0, 14, "Lowest Seller SP", heading_xf)
|
|
|
1304 |
sheet.write(0, 15, "Lowest Seller Rating", heading_xf)
|
|
|
1305 |
sheet.write(0, 16, "Lowest Seller Shipping Time", heading_xf)
|
| 12396 |
kshitij.so |
1306 |
sheet.write(0, 17, "Second Lowest Seller SP", heading_xf)
|
| 12432 |
kshitij.so |
1307 |
sheet.write(0, 18, "Second Lowest Seller Rating", heading_xf)
|
|
|
1308 |
sheet.write(0, 19, "Second Lowest Seller Shipping Time", heading_xf)
|
|
|
1309 |
sheet.write(0, 20, "Third Lowest Seller SP", heading_xf)
|
|
|
1310 |
sheet.write(0, 21, "Third Lowest Seller Rating", heading_xf)
|
|
|
1311 |
sheet.write(0, 22, "Third Lowest Seller Shipping Time", heading_xf)
|
| 12447 |
kshitij.so |
1312 |
sheet.write(0, 23, "Other Cost", heading_xf)
|
|
|
1313 |
sheet.write(0, 24, "WANLC", heading_xf)
|
|
|
1314 |
sheet.write(0, 25, "Commission", heading_xf)
|
|
|
1315 |
sheet.write(0, 26, "Competitor Commission", heading_xf)
|
|
|
1316 |
sheet.write(0, 27, "Return Provision", heading_xf)
|
|
|
1317 |
sheet.write(0, 28, "Margin", heading_xf)
|
|
|
1318 |
sheet.write(0, 29, "Risky", heading_xf)
|
|
|
1319 |
sheet.write(0, 30, "Proposed Sp", heading_xf)
|
| 12468 |
kshitij.so |
1320 |
sheet.write(0, 31, "Avg Sale", heading_xf)
|
|
|
1321 |
sheet.write(0, 32, "Sales History", heading_xf)
|
|
|
1322 |
sheet.write(0, 33, "Decision", heading_xf)
|
|
|
1323 |
sheet.write(0, 34, "Reason", heading_xf)
|
|
|
1324 |
sheet.write(0, 35, "Updated Price", heading_xf)
|
| 12396 |
kshitij.so |
1325 |
|
|
|
1326 |
sheet_iterator = 1
|
|
|
1327 |
amongCheapestItems = session.query(AmazonScrapingHistory,Item).join((Item,AmazonScrapingHistory.item_id==Item.id)).filter(AmazonScrapingHistory.competitiveCategory==CompetitionCategory.AMONG_CHEAPEST_CAN_COMPETE).all()
|
|
|
1328 |
for amongCheapestItem in amongCheapestItems:
|
|
|
1329 |
amScraping = amongCheapestItem[0]
|
|
|
1330 |
item = amongCheapestItem[1]
|
|
|
1331 |
sheet.write(sheet_iterator, 0, amScraping.item_id)
|
|
|
1332 |
if amScraping.warehouseLocation == 1:
|
|
|
1333 |
sku = 'FBA'+str(amScraping.item_id)
|
|
|
1334 |
loc = 'MUMBAI'
|
|
|
1335 |
else:
|
|
|
1336 |
sku = 'FBB'+str(amScraping.item_id)
|
|
|
1337 |
loc = 'BANGLORE'
|
|
|
1338 |
sheet.write(sheet_iterator, 1, sku)
|
|
|
1339 |
sheet.write(sheet_iterator, 2, (amazonAsinPrice.get(sku).asin))
|
|
|
1340 |
sheet.write(sheet_iterator, 3, loc)
|
|
|
1341 |
sheet.write(sheet_iterator, 4, item.brand)
|
|
|
1342 |
sheet.write(sheet_iterator, 5, xstr(item.brand)+" "+xstr(item.model_name)+" "+xstr(item.model_number)+" "+xstr(item.color))
|
|
|
1343 |
sheet.write(sheet_iterator, 6, item.weight)
|
|
|
1344 |
sheet.write(sheet_iterator, 7, amScraping.courierCost)
|
|
|
1345 |
sheet.write(sheet_iterator, 8, amScraping.ourSellingPrice)
|
| 12432 |
kshitij.so |
1346 |
sheet.write(sheet_iterator, 9, amScraping.promoPrice)
|
|
|
1347 |
if amScraping.isPromotion:
|
|
|
1348 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1349 |
else:
|
|
|
1350 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1351 |
sheet.write(sheet_iterator, 11, amScraping.lowestPossibleSp)
|
| 12396 |
kshitij.so |
1352 |
if amScraping.ourRank > 3:
|
|
|
1353 |
sheet.write(sheet_iterator, 12, 'Greater than 3')
|
|
|
1354 |
else:
|
|
|
1355 |
sheet.write(sheet_iterator, 12, amScraping.ourRank)
|
|
|
1356 |
sheet.write(sheet_iterator, 13, amScraping.ourInventory)
|
| 12432 |
kshitij.so |
1357 |
sheet.write(sheet_iterator, 14, amScraping.lowestSellerSp)
|
|
|
1358 |
sheet.write(sheet_iterator, 15, amScraping.lowestSellerRating)
|
|
|
1359 |
sheet.write(sheet_iterator, 16, amScraping.lowestSellerShippingTime)
|
| 12396 |
kshitij.so |
1360 |
sheet.write(sheet_iterator, 17, amScraping.secondLowestSellerSp)
|
| 12432 |
kshitij.so |
1361 |
sheet.write(sheet_iterator, 18, amScraping.secondLowestSellerRating)
|
|
|
1362 |
sheet.write(sheet_iterator, 19, amScraping.secondLowestSellerShippingTime)
|
|
|
1363 |
sheet.write(sheet_iterator, 20, amScraping.thirdLowestSellerSp)
|
|
|
1364 |
sheet.write(sheet_iterator, 21, amScraping.thirdLowestSellerRating)
|
|
|
1365 |
sheet.write(sheet_iterator, 22, amScraping.thirdLowestSellerShippingTime)
|
| 12447 |
kshitij.so |
1366 |
sheet.write(sheet_iterator, 23, amScraping.otherCost)
|
|
|
1367 |
sheet.write(sheet_iterator, 24, amScraping.wanlc)
|
|
|
1368 |
sheet.write(sheet_iterator, 25, amScraping.commission)
|
|
|
1369 |
sheet.write(sheet_iterator, 26, amScraping.competitorCommission)
|
|
|
1370 |
sheet.write(sheet_iterator, 27, amScraping.returnProvision)
|
|
|
1371 |
sheet.write(sheet_iterator, 28, round(amScraping.ourSellingPrice - amScraping.lowestPossibleSp))
|
|
|
1372 |
sheet.write(sheet_iterator, 29, item.risky)
|
|
|
1373 |
sheet.write(sheet_iterator, 30, amScraping.proposedSp)
|
| 12468 |
kshitij.so |
1374 |
sheet.write(sheet_iterator, 31, amScraping.avgSale)
|
|
|
1375 |
sheet.write(sheet_iterator, 32, getOosString(saleMap.get(sku)))
|
| 12444 |
kshitij.so |
1376 |
if amScraping.decision is None:
|
| 12468 |
kshitij.so |
1377 |
sheet.write(sheet_iterator, 33, 'Auto Pricing Inactive')
|
| 12444 |
kshitij.so |
1378 |
sheet_iterator+=1
|
|
|
1379 |
continue
|
| 12468 |
kshitij.so |
1380 |
sheet.write(sheet_iterator, 33, Decision._VALUES_TO_NAMES.get(amScraping.decision))
|
|
|
1381 |
sheet.write(sheet_iterator, 34, amScraping.reason)
|
| 12444 |
kshitij.so |
1382 |
if Decision._VALUES_TO_NAMES.get(amScraping.decision) == "AUTO_DECREMENT_SUCCESS":
|
| 12468 |
kshitij.so |
1383 |
sheet.write(sheet_iterator, 35, math.ceil(amScraping.proposedSellingPrice))
|
| 12444 |
kshitij.so |
1384 |
if Decision._VALUES_TO_NAMES.get(amScraping.decision) == "AUTO_INCREMENT_SUCCESS":
|
| 12468 |
kshitij.so |
1385 |
sheet.write(sheet_iterator, 35, math.ceil(amScraping.ourSellingPrice+max(10,.01*amScraping.ourSellingPrice)))
|
| 12396 |
kshitij.so |
1386 |
sheet_iterator+=1
|
|
|
1387 |
|
|
|
1388 |
sheet = wbk.add_sheet('Cheapest')
|
|
|
1389 |
xstr = lambda s: s or ""
|
|
|
1390 |
heading_xf = xlwt.easyxf('font: bold on; align: wrap off, vert centre, horiz center')
|
|
|
1391 |
|
|
|
1392 |
excel_integer_format = '0'
|
|
|
1393 |
integer_style = xlwt.XFStyle()
|
|
|
1394 |
integer_style.num_format_str = excel_integer_format
|
|
|
1395 |
|
|
|
1396 |
sheet.write(0, 0, "Item Id", heading_xf)
|
|
|
1397 |
sheet.write(0, 1, "Amazon Sku", heading_xf)
|
|
|
1398 |
sheet.write(0, 2, "Asin", heading_xf)
|
|
|
1399 |
sheet.write(0, 3, "Location", heading_xf)
|
|
|
1400 |
sheet.write(0, 4, "Brand", heading_xf)
|
|
|
1401 |
sheet.write(0, 5, "Product Name", heading_xf)
|
|
|
1402 |
sheet.write(0, 6, "Weight", heading_xf)
|
|
|
1403 |
sheet.write(0, 7, "Courier Cost", heading_xf)
|
|
|
1404 |
sheet.write(0, 8, "Our SP", heading_xf)
|
| 12432 |
kshitij.so |
1405 |
sheet.write(0, 9, "Promo Price", heading_xf)
|
|
|
1406 |
sheet.write(0, 10, "Is Promotion", heading_xf)
|
|
|
1407 |
sheet.write(0, 11, "Lowest Possible SP", heading_xf)
|
| 12396 |
kshitij.so |
1408 |
sheet.write(0, 12, "Rank", heading_xf)
|
|
|
1409 |
sheet.write(0, 13, "Our Inventory", heading_xf)
|
| 12432 |
kshitij.so |
1410 |
sheet.write(0, 14, "Lowest Seller SP", heading_xf)
|
|
|
1411 |
sheet.write(0, 15, "Lowest Seller Rating", heading_xf)
|
|
|
1412 |
sheet.write(0, 16, "Lowest Seller Shipping Time", heading_xf)
|
| 12396 |
kshitij.so |
1413 |
sheet.write(0, 17, "Second Lowest Seller SP", heading_xf)
|
| 12432 |
kshitij.so |
1414 |
sheet.write(0, 18, "Second Lowest Seller Rating", heading_xf)
|
|
|
1415 |
sheet.write(0, 19, "Second Lowest Seller Shipping Time", heading_xf)
|
|
|
1416 |
sheet.write(0, 20, "Third Lowest Seller SP", heading_xf)
|
|
|
1417 |
sheet.write(0, 21, "Third Lowest Seller Rating", heading_xf)
|
|
|
1418 |
sheet.write(0, 22, "Third Lowest Seller Shipping Time", heading_xf)
|
| 12447 |
kshitij.so |
1419 |
sheet.write(0, 23, "Other Cost", heading_xf)
|
|
|
1420 |
sheet.write(0, 24, "WANLC", heading_xf)
|
|
|
1421 |
sheet.write(0, 25, "Commission", heading_xf)
|
|
|
1422 |
sheet.write(0, 26, "Competitor Commission", heading_xf)
|
|
|
1423 |
sheet.write(0, 27, "Return Provision", heading_xf)
|
|
|
1424 |
sheet.write(0, 28, "Margin", heading_xf)
|
|
|
1425 |
sheet.write(0, 29, "Risky", heading_xf)
|
|
|
1426 |
sheet.write(0, 30, "Proposed Sp", heading_xf)
|
| 12468 |
kshitij.so |
1427 |
sheet.write(0, 31, "Avg Sale", heading_xf)
|
|
|
1428 |
sheet.write(0, 32, "Sales History", heading_xf)
|
|
|
1429 |
sheet.write(0, 33, "Decision", heading_xf)
|
|
|
1430 |
sheet.write(0, 34, "Reason", heading_xf)
|
|
|
1431 |
sheet.write(0, 35, "Updated Price", heading_xf)
|
| 12396 |
kshitij.so |
1432 |
|
|
|
1433 |
sheet_iterator = 1
|
|
|
1434 |
cheapestItems = session.query(AmazonScrapingHistory,Item).join((Item,AmazonScrapingHistory.item_id==Item.id)).filter(AmazonScrapingHistory.competitiveCategory==CompetitionCategory.BUY_BOX).all()
|
|
|
1435 |
for cheapestItem in cheapestItems:
|
|
|
1436 |
amScraping = cheapestItem[0]
|
|
|
1437 |
item = cheapestItem[1]
|
|
|
1438 |
sheet.write(sheet_iterator, 0, amScraping.item_id)
|
|
|
1439 |
if amScraping.warehouseLocation == 1:
|
|
|
1440 |
sku = 'FBA'+str(amScraping.item_id)
|
|
|
1441 |
loc = 'MUMBAI'
|
|
|
1442 |
else:
|
|
|
1443 |
sku = 'FBB'+str(amScraping.item_id)
|
|
|
1444 |
loc = 'BANGLORE'
|
|
|
1445 |
sheet.write(sheet_iterator, 1, sku)
|
|
|
1446 |
sheet.write(sheet_iterator, 2, (amazonAsinPrice.get(sku).asin))
|
|
|
1447 |
sheet.write(sheet_iterator, 3, loc)
|
|
|
1448 |
sheet.write(sheet_iterator, 4, item.brand)
|
|
|
1449 |
sheet.write(sheet_iterator, 5, xstr(item.brand)+" "+xstr(item.model_name)+" "+xstr(item.model_number)+" "+xstr(item.color))
|
|
|
1450 |
sheet.write(sheet_iterator, 6, item.weight)
|
|
|
1451 |
sheet.write(sheet_iterator, 7, amScraping.courierCost)
|
|
|
1452 |
sheet.write(sheet_iterator, 8, amScraping.ourSellingPrice)
|
| 12432 |
kshitij.so |
1453 |
sheet.write(sheet_iterator, 9, amScraping.promoPrice)
|
|
|
1454 |
if amScraping.isPromotion:
|
|
|
1455 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1456 |
else:
|
|
|
1457 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1458 |
sheet.write(sheet_iterator, 11, amScraping.lowestPossibleSp)
|
| 12396 |
kshitij.so |
1459 |
if amScraping.ourRank > 3:
|
|
|
1460 |
sheet.write(sheet_iterator, 12, 'Greater than 3')
|
|
|
1461 |
else:
|
|
|
1462 |
sheet.write(sheet_iterator, 12, amScraping.ourRank)
|
|
|
1463 |
sheet.write(sheet_iterator, 13, amScraping.ourInventory)
|
| 12432 |
kshitij.so |
1464 |
sheet.write(sheet_iterator, 14, amScraping.lowestSellerSp)
|
|
|
1465 |
sheet.write(sheet_iterator, 15, amScraping.lowestSellerRating)
|
|
|
1466 |
sheet.write(sheet_iterator, 16, amScraping.lowestSellerShippingTime)
|
| 12396 |
kshitij.so |
1467 |
sheet.write(sheet_iterator, 17, amScraping.secondLowestSellerSp)
|
| 12432 |
kshitij.so |
1468 |
sheet.write(sheet_iterator, 18, amScraping.secondLowestSellerRating)
|
|
|
1469 |
sheet.write(sheet_iterator, 19, amScraping.secondLowestSellerShippingTime)
|
|
|
1470 |
sheet.write(sheet_iterator, 20, amScraping.thirdLowestSellerSp)
|
|
|
1471 |
sheet.write(sheet_iterator, 21, amScraping.thirdLowestSellerRating)
|
|
|
1472 |
sheet.write(sheet_iterator, 22, amScraping.thirdLowestSellerShippingTime)
|
| 12447 |
kshitij.so |
1473 |
sheet.write(sheet_iterator, 23, amScraping.otherCost)
|
|
|
1474 |
sheet.write(sheet_iterator, 24, amScraping.wanlc)
|
|
|
1475 |
sheet.write(sheet_iterator, 25, amScraping.commission)
|
|
|
1476 |
sheet.write(sheet_iterator, 26, amScraping.competitorCommission)
|
|
|
1477 |
sheet.write(sheet_iterator, 27, amScraping.returnProvision)
|
|
|
1478 |
sheet.write(sheet_iterator, 28, round(amScraping.ourSellingPrice - amScraping.lowestPossibleSp))
|
|
|
1479 |
sheet.write(sheet_iterator, 29, item.risky)
|
|
|
1480 |
sheet.write(sheet_iterator, 30, amScraping.proposedSp)
|
| 12468 |
kshitij.so |
1481 |
sheet.write(sheet_iterator, 31, amScraping.avgSale)
|
|
|
1482 |
sheet.write(sheet_iterator, 32, getOosString(saleMap.get(sku)))
|
| 12444 |
kshitij.so |
1483 |
if amScraping.decision is None:
|
| 12468 |
kshitij.so |
1484 |
sheet.write(sheet_iterator, 33, 'Auto Pricing Inactive')
|
| 12444 |
kshitij.so |
1485 |
sheet_iterator+=1
|
|
|
1486 |
continue
|
| 12468 |
kshitij.so |
1487 |
sheet.write(sheet_iterator, 33, Decision._VALUES_TO_NAMES.get(amScraping.decision))
|
|
|
1488 |
sheet.write(sheet_iterator, 34, amScraping.reason)
|
| 12444 |
kshitij.so |
1489 |
if Decision._VALUES_TO_NAMES.get(amScraping.decision) == "AUTO_DECREMENT_SUCCESS":
|
| 12468 |
kshitij.so |
1490 |
sheet.write(sheet_iterator, 35, math.ceil(amScraping.proposedSellingPrice))
|
| 12444 |
kshitij.so |
1491 |
if Decision._VALUES_TO_NAMES.get(amScraping.decision) == "AUTO_INCREMENT_SUCCESS":
|
| 12468 |
kshitij.so |
1492 |
sheet.write(sheet_iterator, 35, math.ceil(amScraping.ourSellingPrice+max(10,.01*amScraping.ourSellingPrice)))
|
| 12396 |
kshitij.so |
1493 |
sheet_iterator+=1
|
|
|
1494 |
|
|
|
1495 |
sheet = wbk.add_sheet('Negative Margin')
|
|
|
1496 |
xstr = lambda s: s or ""
|
|
|
1497 |
heading_xf = xlwt.easyxf('font: bold on; align: wrap off, vert centre, horiz center')
|
|
|
1498 |
|
|
|
1499 |
excel_integer_format = '0'
|
|
|
1500 |
integer_style = xlwt.XFStyle()
|
|
|
1501 |
integer_style.num_format_str = excel_integer_format
|
|
|
1502 |
|
|
|
1503 |
sheet.write(0, 0, "Item Id", heading_xf)
|
|
|
1504 |
sheet.write(0, 1, "Amazon Sku", heading_xf)
|
|
|
1505 |
sheet.write(0, 2, "Asin", heading_xf)
|
|
|
1506 |
sheet.write(0, 3, "Location", heading_xf)
|
|
|
1507 |
sheet.write(0, 4, "Brand", heading_xf)
|
|
|
1508 |
sheet.write(0, 5, "Product Name", heading_xf)
|
|
|
1509 |
sheet.write(0, 6, "Weight", heading_xf)
|
|
|
1510 |
sheet.write(0, 7, "Courier Cost", heading_xf)
|
|
|
1511 |
sheet.write(0, 8, "Our SP", heading_xf)
|
| 12432 |
kshitij.so |
1512 |
sheet.write(0, 9, "Promo Price", heading_xf)
|
|
|
1513 |
sheet.write(0, 10, "Is Promotion", heading_xf)
|
|
|
1514 |
sheet.write(0, 11, "Lowest Possible SP", heading_xf)
|
| 12396 |
kshitij.so |
1515 |
sheet.write(0, 12, "Rank", heading_xf)
|
|
|
1516 |
sheet.write(0, 13, "Our Inventory", heading_xf)
|
| 12432 |
kshitij.so |
1517 |
sheet.write(0, 14, "Lowest Seller SP", heading_xf)
|
|
|
1518 |
sheet.write(0, 15, "Lowest Seller Rating", heading_xf)
|
|
|
1519 |
sheet.write(0, 16, "Lowest Seller Shipping Time", heading_xf)
|
| 12396 |
kshitij.so |
1520 |
sheet.write(0, 17, "Second Lowest Seller SP", heading_xf)
|
| 12432 |
kshitij.so |
1521 |
sheet.write(0, 18, "Second Lowest Seller Rating", heading_xf)
|
|
|
1522 |
sheet.write(0, 19, "Second Lowest Seller Shipping Time", heading_xf)
|
|
|
1523 |
sheet.write(0, 20, "Third Lowest Seller SP", heading_xf)
|
|
|
1524 |
sheet.write(0, 21, "Third Lowest Seller Rating", heading_xf)
|
|
|
1525 |
sheet.write(0, 22, "Third Lowest Seller Shipping Time", heading_xf)
|
| 12447 |
kshitij.so |
1526 |
sheet.write(0, 23, "Other Cost", heading_xf)
|
|
|
1527 |
sheet.write(0, 24, "WANLC", heading_xf)
|
|
|
1528 |
sheet.write(0, 25, "Commission", heading_xf)
|
|
|
1529 |
sheet.write(0, 26, "Competitor Commission", heading_xf)
|
|
|
1530 |
sheet.write(0, 27, "Return Provision", heading_xf)
|
|
|
1531 |
sheet.write(0, 28, "Margin", heading_xf)
|
|
|
1532 |
sheet.write(0, 29, "Avg Sale", heading_xf)
|
|
|
1533 |
sheet.write(0, 30, "Sales History", heading_xf)
|
| 12396 |
kshitij.so |
1534 |
|
|
|
1535 |
sheet_iterator = 1
|
|
|
1536 |
amongCheapestItems = session.query(AmazonScrapingHistory,Item).join((Item,AmazonScrapingHistory.item_id==Item.id)).filter(AmazonScrapingHistory.competitiveCategory==CompetitionCategory.AMONG_CHEAPEST_CAN_COMPETE).all()
|
|
|
1537 |
for amongCheapestItem in amongCheapestItems:
|
|
|
1538 |
amScraping = amongCheapestItem[0]
|
|
|
1539 |
item = amongCheapestItem[1]
|
|
|
1540 |
sheet.write(sheet_iterator, 0, amScraping.item_id)
|
|
|
1541 |
if amScraping.warehouseLocation == 1:
|
|
|
1542 |
sku = 'FBA'+str(amScraping.item_id)
|
|
|
1543 |
loc = 'MUMBAI'
|
|
|
1544 |
else:
|
|
|
1545 |
sku = 'FBB'+str(amScraping.item_id)
|
|
|
1546 |
loc = 'BANGLORE'
|
|
|
1547 |
sheet.write(sheet_iterator, 1, sku)
|
|
|
1548 |
sheet.write(sheet_iterator, 2, (amazonAsinPrice.get(sku).asin))
|
|
|
1549 |
sheet.write(sheet_iterator, 3, loc)
|
|
|
1550 |
sheet.write(sheet_iterator, 4, item.brand)
|
|
|
1551 |
sheet.write(sheet_iterator, 5, xstr(item.brand)+" "+xstr(item.model_name)+" "+xstr(item.model_number)+" "+xstr(item.color))
|
|
|
1552 |
sheet.write(sheet_iterator, 6, item.weight)
|
|
|
1553 |
sheet.write(sheet_iterator, 7, amScraping.courierCost)
|
|
|
1554 |
sheet.write(sheet_iterator, 8, amScraping.ourSellingPrice)
|
| 12432 |
kshitij.so |
1555 |
sheet.write(sheet_iterator, 9, amScraping.promoPrice)
|
|
|
1556 |
if amScraping.isPromotion:
|
|
|
1557 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1558 |
else:
|
|
|
1559 |
sheet.write(sheet_iterator, 10, "Yes")
|
|
|
1560 |
sheet.write(sheet_iterator, 11, amScraping.lowestPossibleSp)
|
| 12396 |
kshitij.so |
1561 |
if amScraping.ourRank > 3:
|
|
|
1562 |
sheet.write(sheet_iterator, 12, 'Greater than 3')
|
|
|
1563 |
else:
|
|
|
1564 |
sheet.write(sheet_iterator, 12, amScraping.ourRank)
|
|
|
1565 |
sheet.write(sheet_iterator, 13, amScraping.ourInventory)
|
| 12432 |
kshitij.so |
1566 |
sheet.write(sheet_iterator, 14, amScraping.lowestSellerSp)
|
|
|
1567 |
sheet.write(sheet_iterator, 15, amScraping.lowestSellerRating)
|
|
|
1568 |
sheet.write(sheet_iterator, 16, amScraping.lowestSellerShippingTime)
|
| 12396 |
kshitij.so |
1569 |
sheet.write(sheet_iterator, 17, amScraping.secondLowestSellerSp)
|
| 12432 |
kshitij.so |
1570 |
sheet.write(sheet_iterator, 18, amScraping.secondLowestSellerRating)
|
|
|
1571 |
sheet.write(sheet_iterator, 19, amScraping.secondLowestSellerShippingTime)
|
|
|
1572 |
sheet.write(sheet_iterator, 20, amScraping.thirdLowestSellerSp)
|
|
|
1573 |
sheet.write(sheet_iterator, 21, amScraping.thirdLowestSellerRating)
|
|
|
1574 |
sheet.write(sheet_iterator, 22, amScraping.thirdLowestSellerShippingTime)
|
| 12447 |
kshitij.so |
1575 |
sheet.write(sheet_iterator, 23, amScraping.otherCost)
|
|
|
1576 |
sheet.write(sheet_iterator, 24, amScraping.wanlc)
|
|
|
1577 |
sheet.write(sheet_iterator, 25, amScraping.commission)
|
|
|
1578 |
sheet.write(sheet_iterator, 26, amScraping.competitorCommission)
|
|
|
1579 |
sheet.write(sheet_iterator, 27, amScraping.returnProvision)
|
| 12468 |
kshitij.so |
1580 |
sheet.write(sheet_iterator, 28, round(amScraping.ourSellingPrice - amScraping.lowestPossibleSp))
|
| 12447 |
kshitij.so |
1581 |
sheet.write(sheet_iterator, 29, amScraping.avgSale)
|
|
|
1582 |
sheet.write(sheet_iterator, 30, getOosString(saleMap.get(sku)))
|
| 12396 |
kshitij.so |
1583 |
sheet_iterator+=1
|
|
|
1584 |
|
|
|
1585 |
sheet = wbk.add_sheet('Exception List')
|
|
|
1586 |
xstr = lambda s: s or ""
|
|
|
1587 |
heading_xf = xlwt.easyxf('font: bold on; align: wrap off, vert centre, horiz center')
|
|
|
1588 |
|
|
|
1589 |
excel_integer_format = '0'
|
|
|
1590 |
integer_style = xlwt.XFStyle()
|
|
|
1591 |
integer_style.num_format_str = excel_integer_format
|
|
|
1592 |
|
|
|
1593 |
sheet.write(0, 0, "Item Id", heading_xf)
|
|
|
1594 |
sheet.write(0, 1, "Amazon Sku", heading_xf)
|
|
|
1595 |
sheet.write(0, 2, "Asin", heading_xf)
|
|
|
1596 |
sheet.write(0, 3, "Location", heading_xf)
|
|
|
1597 |
sheet.write(0, 4, "Brand", heading_xf)
|
|
|
1598 |
sheet.write(0, 5, "Product Name", heading_xf)
|
|
|
1599 |
sheet.write(0, 6, "Reason", heading_xf)
|
|
|
1600 |
|
|
|
1601 |
sheet_iterator = 1
|
|
|
1602 |
amongCheapestItems = session.query(AmazonScrapingHistory,Item).join((Item,AmazonScrapingHistory.item_id==Item.id)).filter(AmazonScrapingHistory.competitiveCategory==CompetitionCategory.AMONG_CHEAPEST_CAN_COMPETE).all()
|
|
|
1603 |
for amongCheapestItem in amongCheapestItems:
|
|
|
1604 |
amScraping = amongCheapestItem[0]
|
|
|
1605 |
item = amongCheapestItem[1]
|
|
|
1606 |
sheet.write(sheet_iterator, 0, amScraping.item_id)
|
|
|
1607 |
if amScraping.warehouseLocation == 1:
|
|
|
1608 |
sku = 'FBA'+str(amScraping.item_id)
|
|
|
1609 |
loc = 'MUMBAI'
|
|
|
1610 |
else:
|
|
|
1611 |
sku = 'FBB'+str(amScraping.item_id)
|
|
|
1612 |
loc = 'BANGLORE'
|
|
|
1613 |
sheet.write(sheet_iterator, 1, sku)
|
|
|
1614 |
sheet.write(sheet_iterator, 2, (amazonAsinPrice.get(sku).asin))
|
|
|
1615 |
sheet.write(sheet_iterator, 3, loc)
|
|
|
1616 |
sheet.write(sheet_iterator, 4, item.brand)
|
|
|
1617 |
sheet.write(sheet_iterator, 5, xstr(item.brand)+" "+xstr(item.model_name)+" "+xstr(item.model_number)+" "+xstr(item.color))
|
|
|
1618 |
sheet.write(sheet_iterator, 6, amScraping.reason)
|
|
|
1619 |
sheet_iterator+=1
|
|
|
1620 |
|
| 12444 |
kshitij.so |
1621 |
|
|
|
1622 |
if (runType=='FULL'):
|
|
|
1623 |
sheet = wbk.add_sheet('Auto Favorites')
|
|
|
1624 |
|
|
|
1625 |
heading_xf = xlwt.easyxf('font: bold on; align: wrap off, vert centre, horiz center')
|
|
|
1626 |
|
|
|
1627 |
excel_integer_format = '0'
|
|
|
1628 |
integer_style = xlwt.XFStyle()
|
|
|
1629 |
integer_style.num_format_str = excel_integer_format
|
|
|
1630 |
xstr = lambda s: s or ""
|
|
|
1631 |
|
|
|
1632 |
sheet.write(0, 0, "Item ID", heading_xf)
|
|
|
1633 |
sheet.write(0, 1, "Brand", heading_xf)
|
|
|
1634 |
sheet.write(0, 2, "Product Name", heading_xf)
|
|
|
1635 |
sheet.write(0, 3, "Auto Favourite", heading_xf)
|
|
|
1636 |
sheet.write(0, 4, "Reason", heading_xf)
|
|
|
1637 |
|
|
|
1638 |
sheet_iterator=1
|
|
|
1639 |
for autoFav in nowAutoFav:
|
|
|
1640 |
itemId = autoFav[0]
|
|
|
1641 |
reason = autoFav[1]
|
|
|
1642 |
it = Item.query.filter_by(id=itemId).one()
|
|
|
1643 |
sheet.write(sheet_iterator, 0, itemId)
|
|
|
1644 |
sheet.write(sheet_iterator, 1, it.brand)
|
|
|
1645 |
sheet.write(sheet_iterator, 2, xstr(it.brand)+" "+xstr(it.model_name)+" "+xstr(it.model_number)+" "+xstr(it.color))
|
|
|
1646 |
sheet.write(sheet_iterator, 3, "True")
|
|
|
1647 |
sheet.write(sheet_iterator, 4, reason)
|
|
|
1648 |
sheet_iterator+=1
|
|
|
1649 |
for prevFav in previousAutoFav:
|
|
|
1650 |
it = Item.query.filter_by(id=prevFav).one()
|
|
|
1651 |
sheet.write(sheet_iterator, 0, prevFav)
|
|
|
1652 |
sheet.write(sheet_iterator, 1, it.brand)
|
|
|
1653 |
sheet.write(sheet_iterator, 2, xstr(it.brand)+" "+xstr(it.model_name)+" "+xstr(it.model_number)+" "+xstr(it.color))
|
|
|
1654 |
sheet.write(sheet_iterator, 3, "False")
|
|
|
1655 |
sheet_iterator+=1
|
|
|
1656 |
|
| 12396 |
kshitij.so |
1657 |
filename = "/tmp/amazon-scraping.xls"
|
|
|
1658 |
wbk.save(filename)
|
|
|
1659 |
|
| 12363 |
kshitij.so |
1660 |
def main():
|
|
|
1661 |
parser = optparse.OptionParser()
|
|
|
1662 |
parser.add_option("-t", "--type", dest="runType",
|
|
|
1663 |
default="FULL", type="string",
|
|
|
1664 |
help="Run type FULL or FAVOURITE")
|
|
|
1665 |
(options, args) = parser.parse_args()
|
|
|
1666 |
if options.runType not in ('FULL','FAVOURITE'):
|
|
|
1667 |
print "Run type argument illegal."
|
|
|
1668 |
sys.exit(1)
|
|
|
1669 |
time.sleep(5)
|
|
|
1670 |
timestamp = datetime.now()
|
|
|
1671 |
fetchFbaSale()
|
|
|
1672 |
itemInfo = populateStuff(timestamp,options.runType)
|
|
|
1673 |
itemsToPopulate = 0
|
| 12430 |
kshitij.so |
1674 |
toSync = 0
|
|
|
1675 |
lenItems = len(itemInfo)
|
|
|
1676 |
while(toSync < lenItems):
|
|
|
1677 |
oldSync = toSync
|
|
|
1678 |
if lenItems >= 20:
|
|
|
1679 |
toSync = 20
|
|
|
1680 |
else:
|
|
|
1681 |
toSync = lenItems - oldSync
|
|
|
1682 |
getPriceAndAsin(itemInfo[oldSync:toSync+oldSync])
|
|
|
1683 |
toSync = oldSync + toSync
|
|
|
1684 |
|
| 12363 |
kshitij.so |
1685 |
while (len(itemInfo)>0):
|
| 12430 |
kshitij.so |
1686 |
if len(itemInfo) >= 20:
|
|
|
1687 |
itemsToPopulate = 20
|
| 12363 |
kshitij.so |
1688 |
else:
|
|
|
1689 |
itemsToPopulate = len(itemInfo)
|
| 12456 |
kshitij.so |
1690 |
print "items to popluate"
|
| 12370 |
kshitij.so |
1691 |
print itemsToPopulate
|
| 12363 |
kshitij.so |
1692 |
exceptionList, negativeMargin, cheapest, amongCheapestAndCanCompete, canCompete, almostCompete, cantCompete = decideCategory(itemInfo[0:itemsToPopulate])
|
|
|
1693 |
itemInfo[0:itemsToPopulate] = []
|
|
|
1694 |
commitExceptionList(exceptionList,timestamp,options.runType)
|
|
|
1695 |
commitNegativeMargin(negativeMargin,timestamp,options.runType)
|
|
|
1696 |
commitCheapest(cheapest,timestamp,options.runType)
|
|
|
1697 |
commitAmongCheapestAndCanCompete(amongCheapestAndCanCompete,timestamp,options.runType)
|
|
|
1698 |
commitCanCompete(canCompete,timestamp,options.runType)
|
|
|
1699 |
commitAlmostCompete(almostCompete,timestamp,options.runType)
|
|
|
1700 |
commitCantCompete(cantCompete, timestamp,options.runType)
|
| 12396 |
kshitij.so |
1701 |
exceptionList[:], negativeMargin[:], cheapest[:], amongCheapestAndCanCompete[:], canCompete[:], almostCompete[:], cantCompete[:] =[],[],[],[],[],[],[]
|
|
|
1702 |
autoDecreaseItems = fetchItemsForAutoDecrease(timestamp)
|
|
|
1703 |
autoIncreaseItems = fetchItemsForAutoIncrease(timestamp)
|
|
|
1704 |
previousAutoFav, nowAutoFav = markAutoFavourites(timestamp)
|
| 12444 |
kshitij.so |
1705 |
writeReport(timestamp,autoDecreaseItems,autoIncreaseItems,previousAutoFav,nowAutoFav,options.runType)
|
| 12363 |
kshitij.so |
1706 |
if __name__=='__main__':
|
|
|
1707 |
main()
|