python 电商后台

Python 电商后台 Python 是一种热门的编程语言，它在电商领域中得到了广泛的利用。Python 可以用于构建网站、后台和机器学习算法等方面。在电商后台中，Python 常常用于处理定单数据、生成报告、管理存储和运营市场等多个方面。让我们来看看怎样使用 Python 构建一个强大的电商后台系统。 首先，我们需要安装所需的库。这里使用 Django 库作为网站框架，使用 Pandas 库来处理数据。请确保您已安装了这些库。以下是安装 Django 和 Pandas 的命令：

pip install django
pip install pandas

from django.db import models
class Product(models.Model):
name = models.CharField(max_length=200)
price = models.DecimalField(max_digits=10, decimal_places=2)
description = models.TextField(blank=True)
def __str__(self):
return self.name
class Order(models.Model):
product = models.ForeignKey(Product, on_delete=models.CASCADE)
quantity = models.IntegerField()
date = models.DateTimeField(auto_now_add=True)
customer_name = models.CharField(max_length=200)
customer_email = models.EmailField(max_length=200)
def __str__(self):
return f"{self.customer_name}'s order of {self.product} on {self.date}"

import pandas as pd
from myapp.models import Order
orders = Order.objects.all()
df = pd.DataFrame(list(orders.values()))
df['total_price'] = df['quantity'] * df['product__price']
# Top 10 products by revenue
top_products = df.groupby('product_id')['total_price'].sum().reset_index().nlargest(10, 'total_price')
top_products = top_products.merge(Product.objects.all().values('id', 'name'), on='id')
# Daily revenue
daily_revenue = df.groupby(pd.Grouper(key='date', freq='D'))['total_price'].sum()
# Export to Excel
with pd.ExcelWriter('report.xlsx') as writer:
top_products.to_excel(writer, sheet_name='Top Products', index=False)
daily_revenue.to_excel(writer, sheet_name='Daily Revenue')