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README
GPL-3.0

家电之选


项目说明

家电之选项目源于《拜客商城系统》,原项目采用DRF(djangorestframework)框架开发,而本项目完全使用Django原生框架开发,后端逻辑与原项目逻辑完全不一样,充分利用Python面向对象编程,逻辑清晰,语法简洁。前端采用Vue2框架,减少对DOM元素的操作。后端采用Django-MTV设计模式,符合传统网站开发规范,适合中等偏下级别的程序员学习和开发。

访问地址:http://jiadian.rainbow.hi.cn

项目完成时间:2023年7月15日

功能迭代期:2023年7月16日——2023年9月3日

项目收获

这个项目和天天生鲜项目很像,都属于电商型项目。但是该项目在基本实现了天天生鲜项目已有的功能外,还增加许多新的功能,例如:使用Vue作为前端框架、支付宝沙箱支付、分布式文件系统等。

  1. 第一次独立完成整个后端逻辑,以及部分前端内容(前端发送请求以及Django模板部分)。
  2. 第一次独立设计整个数据库表结构。由于是第一次设计表结构,所以导致了一个表与表之间形成了循环关联的问题。
  3. 分布式文件系统的安装、配置以及使用。
  4. 调用支付宝接口的基本逻辑。
  5. 项目部署的基本流程。
  6. 域名注册及网站ICP备案。

虽然这个项目仍然还是作为一个用于学习的项目,但是项目基本上所有的后端逻辑都经过了自己的思考,在这个项目中学到的东西是最多的,因此这让我的的后端开发能力有了一次从量到质的飞跃。

项目开发环境

Python3.11,Django4.1,Mysql8.0

项目环境配置

  1. 进入requirements.txt文件对应的目录下面,将该项目所依赖的包安装好。

    pip install -r requirements.txt  # requirements.txt生成命令:pip freeze > requirements.txt
  2. 创建相应的数据库并在settings文件里面配置对应的数据库信息。

    DATABASES = {
        "default": {
            "ENGINE": "django.db.backends.mysql",
            "NAME": '',  # 你的数据库的名称
            "USER": '',  # 你的数据库的账号
            "PASSWORD": '',  # 你的数据库的密码
            "PORT": '3306',
            "HOST": 'localhost',
            'OPTIONS': {
                'isolation_level': 'read committed',  # 设置Mysql事务隔离级别为'read committed'
                "init_command": "SET foreign_key_checks = 0;",  # 迁移数据库时取消外键检查
            }
        }
    }
  3. 配置好发送邮箱信息。

    EMAIL_BACKEND = 'django.core.mail.backends.smtp.EmailBackend'
    EMAIL_HOST = 'smtp.163.com'  # 你所用的邮箱的smtp地址,这里是网易邮箱的
    EMAIL_PORT = 25  # 你所用邮箱的端口号,这里是网易邮箱的
    EMAIL_HOST_USER = ''  # 你的邮箱账号
    EMAIL_HOST_PASSWORD = ''  # 你的邮箱授权码
    EMAIL_FROM = ''  # 发件者信息,没有就填邮箱账号
  4. 在manage.py所对应的目录下执行迁移命令。

    在执行迁移命令之前,由于数据库表结构设计的缺陷,导致了一张表与另一张表的字段形成了循环关联,这两张表是:/apps/goods/models.py中的GoodsComment模型和/apps/order/models.py中的GoodsOrder模型。

    解决办法是:将GoodsComment中的goods_order字段先注释,然后正常迁移一遍数据表。迁移完毕后取消注释,然后再迁移一遍就可以了。

    python manage.py makemigrations
    python manage.py migrate
  5. 迁移完毕后执行项目目录下的几个sql文件,向数据库中插入对应的商品数据。

  6. 创建超级管理员,按照提示完成即可。

    python manage.py createsuperuser
  7. 执行完上述操作以后就可以启动项目了。

    python manage.py runserver

项目模块划分

  • 用户模块

    • 注册页面
    • 登录页面
    • 用户中心页面
    • 用户余额页面
    • 用户地址页面
    • 历史订单页面
    • 订单详情页面
    • 用户更改头像功能
    • 充值功能(非正式功能)
  • 商品模块

    • 商品首页
    • 商品详情页
    • 商品列表页
    • 商品搜索功能
  • 购物车模块

    • 购物车页面(购物车商品数量、删、改)
    • 加入购物车功能
  • 订单模块

    • 订单页面
    • 支付页面
    • 支付成功页面
    • 订单评价页面

项目部分功能展示

注册页面

登录页面

用户个人中心页面

用户余额页面

用户收货地址页面

用户历史订单页面

订单评价页面

订单详情页面

购物车页面

订单页面

商品列表页面

商品详情页面

首页一

首页二

首页三

支付页面

支付成功页面

数据库模型设计

  • 用户模型

​ 用户模型只包括两个模型类,一个是MyUser,一个是Address,前者继承并拓展了Django自带的 用户模型类,用于储存用户信息,后者用于储存用户的收货地址。

  • 商品模型

  1. GoodsType(商品类型表):记录所有商品的类型。

  2. GoodsImage(商品图片表):记录每个商品动态的图片。

  3. GoodsSPU(商品SPU表):商品SPU。

  4. GoodsSKU(商品SKU表):商品SKU。

  5. GoodsDynamics(商品动态表):商品动态表存储的是商品的价格、库存、销量、大小、颜色等,关联于商品SKU表。

  6. GoodsComment(商品评论表):主要存储用户对该商品的评价以及满意程度、关联于商品订单表、商品SKU表、 用户表。

  7. RotationCharts(首页轮播图表):哪张图片需要轮播,哪张图片不需要轮播。

  • 订单模型

​ 订单模型主要分为:(OrderInfo)订单信息表和(GoodsOrder)商品订单表。

​ 订单信息表:主要存储订单的编号(订单ID)和交易的编号,以及该订单的商品总数和总金额,关联的用户和用户地址 等。

​ 商品订单表:主要存储某商品的交易总数、交易总价等。

缓存后端的使用

在数据库模型类的说明中,没有提到购物车的模型类,这是因为购物车是一个频繁访问数据库的操作,而对于传统的Mysql数据库来说,频繁的访问数据库无疑会对数据库造成巨大的压力。因此本项目采用缓存后端来存储购物车信息。

在项目总目录中的settings文件里面的配置如下:

CACHES = {
    'default': {
        'BACKEND': 'django_redis.cache.RedisCache',
        'LOCATION': 'redis://127.0.0.1:6379/9',  # 使用redis服务器中的第9个数据库
        'OPTIONS': {
            'CLIENT_CLASS': 'django_redis.client.DefaultClient'
        }
    }
}
# 为了确保能够正常使用Redis作为Django的缓存后端,请仔细确认在本地已经开启了Redis的服务。

redis是一个非关系小型数据库,很擅长频繁的读取数据,换句话说,redis不怎么适合数据持久化,它更适合用于一个网站的缓存后端,即把需要频繁访问的数据存入redis中,以此来应对高并发场景,例如商品秒杀、标题热搜等。

在本项目的购物车业务中,主要用django-redis来操作redis。存储的数据结构选择的是哈希存储,即每个用户id对应一条数据。例如:{'用户id': {'商品id': '商品数量'}}。

涉及到的方法有:hget(获取用户购物车中某个商品的数量)、hset(增添或覆盖某个商品的数量)、hlen(用户购物车商品总条数)、hgetall(返回所有商品的id、数量)、hdel(清除该购物车的数据)。

拓展知识:虽然本项目中没有涉及,但是在一个电商平台中,用户的历史浏览记录也是必不可少的,对于历史浏览记录来说,同样也是一个频繁访问数据库的操作,因此历史浏览记录也应该使用redis来存储,但是对于数据结构的选择,这里应该使用列表来存储,即双向链表,例如:{'用户id': [浏览记录1, 浏览记录2...]}。但是历史浏览记录通常会优先显示近期浏览的商品,因此正确的数据结构应该是:{'用户id': [浏览记录2, 浏览记录1...]}。

订单并发场景

对于一些节假日来说,特别是双11、618等这些促销活动很频繁的节日,商家无疑会对某些或者某一类商品进行降价秒杀,那么无疑会有大量的用户集中购买某个商品,这样就会出现订单并发的场景。

对于订单并发场景,只需要对订单加上相应的锁就可以了,也就是说,在出现订单并发的场景中,我们只需要将某一个商品加上一把锁,当某个用户拿到这把锁的时候,才能对该商品进行操作,否则所有没有拿到锁的用户都需要排队等待前面一位用户下单完毕后,才有机会操作该商品。例如:有两个用户正在购买同一个商品,但是用户1先提交了订单的页面,也就是说用户1先拿到这把锁,若该商品只剩一件,那么这一件商品就归为用户1,那么此时商品的库存就变成了0件,在排队的用户2也就无法购买该商品了(悲观锁)。对于订单锁,这里可以分为两种:乐观锁和悲观锁。

悲观锁

当有多个用户操作一条数据的时候,可以用一把锁将该条数据锁住,也就是说,只有拿到了这把锁的用户,才能对这这条数据进行操作,否则所有用户都需要等到前面一位用户操作完该数据的时候才能对该数据进行操作。在Mysql中,提供了一种简单的锁,也可以达到这种目的,用sql语句来说,悲观锁就为以下:

select * from table where id=id for update;

当使用Django来操作数据库的时候,就是以下语句:

模型类名.objects.select_for_update().get(id=id)

乐观锁

乐观锁并不是实际意义上的锁,只是它的步骤相当于一把锁。

现在有一个场景:现在有用户1和用户2在同时操作同一个商品,但是商品的库存只有一件。现在,我们让两个用户同时操作该商品,也就是说,两个用户都可以操作这条数据。此时我们需要先记录该商品的库存,用户1和用户2拿到的库存都是1,接着程序继续往下执行,当代码执行到提交订单的那一行之前,我们加上一个判断,这个判断就是:再向数据库中查询一次该商品的库存,如果第二次查询到的库存与第一次拿到的库存一致,那么就说明没有其他用户跟我竞争该商品,我可以正常提交订单;如果第二次查询到的库存与第一次的库存不一致,那么就说明有其他用户在和我竞争该商品,那么就不能正常提交订单。当用户1比用户2先提交订单,那么商品库存减少为0,用户2在提交订单之前查询库存与第一次查询到的库存不一致,那么该订单下单失败。

对于第二种情况,也就是第二次查询到的商品库存与第一次的不一致,订单失败。对于这种情况,我们通常给用户四次机会来尝试下单,也就是说,当用户第一次下单失败的时候,会进入一个循环操作,循环有三次。当用户进入第一次循环的时候,如果判断的库存还是不一样,那么进入第二次循环,直至三次循环机会全部用完,用户还是没有得到正确的数据,那么才判定该用户下单失败。倘若三次循环中有一次得到的是正确的数据,那么该用户则下单成功。

我们也可以用sql语句来描述判断库存的情况:

select * from table set stock=new_stock where id=id stock=origin_stock

翻译成Django语句就是:

模型类名.objects.filter(id=id, stock=origin_stock).update(stock=new_stock, sales=new_sales)

这样会返回受影响的行数,也就是说,不是返回1就是返回0。如果受影响的行数为1,那么用户下单成功,反之则下单失败。

订单并发总结

  1. 不管是乐观锁还是悲观锁,都存在一个运气的成分在里面。
  2. 乐观锁适合低并发的场景(高并发会存在大量的循环操作,增加资源的损耗)。
  3. 悲观锁适合高并发的场景。
  4. 对于更高级别的并发场景,普通的悲观锁也不适合了,这时候需要用到分布式锁。

Mysql中事务的使用

在了解事务之前,我们先看一个简单的生活实例:在微信中,当我们向一个朋友转账的时候,我的钱刚被扣完,但是,我的手机断网了,而且朋友那边也没有收到相应的汇款,那么问题来了,钱包的钱到底会不会扣呢?答案是你的朋友没有收到钱是正常的,但是你钱包里的钱也会保持原原本本的数量,不会发生任何变化。那么没有扣钱这件事就是事务造成的。

事务的四大特性(ACID)

  1. 原子性(Atomicity):原子是不可再分割的最小粒子,也就是说,把一组操作看成是一个事务,那么这组操作的所有子操作要么全部成功,要么全部不成功。
  2. 一致性(Consistency):指的是对数据操作的规则,在事务的前后必须保持一致。
  3. 隔离性(Isolation):一个事务不会影响另一个事务的进行。
  4. 持久性(Durability):当一个事务提交之后,将不能撤销。

事务的执行流程

  1. 开启事务(start transaction)
  2. 执行相应的sql语句
  3. 若执行期间没有异常,那么则提交(commit);否则所有操作回滚(rollback)到之前。

若需要用到事务,那么必须保证在创建数据表的时候,需要选择Innodb引擎,事务才能正常使用,在Mysql中,事务的默认开启的。

在Django中需要正常使用Mysql的事务,需要在settings文件中做以下配置:

DATABASES = {
    "default": {
        "ENGINE": "django.db.backends.mysql",
        "NAME": 'home_appliances',
        "USER": 'root',
        "PASSWORD": '000000',
        "PORT": '3306',
        "HOST": 'localhost',
        'OPTIONS': {
            'isolation_level': 'read committed',  # 设置Mysql事务隔离级别为'read committed'
            "init_command": "SET foreign_key_checks = 0;",  # 迁移数据库时取消外键检查
        }
    }
}

在OPTIONS的选项中,需要设置Mysql的事务隔离级别为‘read committed’,不然有时候会导致一些数据的丢失(Django官方文档的原话)。

那么此时再回到订单的场景,假设用户在下单的时候发生了异常,比如断网或者代码异常等等,那么此时又为用户创建了相应的订单,这是不可取的。因此在用户下单的时候,我们应该启用事务来保证操作的完整性。

在Django中开启事务

Django为开发者提供了相应的模块来操作事务:

  1. 首先需要导入相应的模块。
from django.db import transaction
  1. 在需要开启事务的函数上面加上事务装饰器,以说明该函数需要开启事务
@transaction.atomic  # 绑定事务
def post(request):
    pass
  1. 在函数中可以设置一个事务保存点,用来记录事务回滚的位置
@transaction.atomic  # 绑定事务
def post(request):
    save_id = transaction.savepoint()
  1. 在可能发生异常的地方加上异常处理,若期间发生异常,那么期间所有涉及到的数据库操作将撤销并回到事务保存点(代码会继续往下执行)
@transaction.atomic  # 绑定事务
def post(request):
    save_id = transaction.savepoint()
    try:
        # 一系列数据库操作
    except Exception as exception:
        print("操作异常,回滚到事务保存点")
        transaction.savepoint_rollback(save_id)

通过以上操作,就可以在Django中使用事务了,这样就可以保证订单的完整性了。

余额充值系统

该项目的充值系统只是为了测试项目某些功能的可行性,如果想要用充值系统,那么需要修改settings文件下的RECHARGE_SYSTEM为True,否则会提示充值系统已关闭。

RECHARGE_SYSTEM = True

使用说明

  1. 首先需要注册并登录账号,进入用户个人中心界面,再点击充值按钮。

  1. 需要验证管理员身份即可完成充值。

说明:用户余额不能超过999999999.99,这样会充值失败,这是因为设计数据表时,账户余额不能超过这个数,想超过该数量的可以自己去数据库修改相应的字段即可。

支付宝功能开发

功能说明

由于没有正式的商家号,所以该功能使用的是支付宝的沙箱系统。也就是说,普通用户不能够完成支付,只有沙箱用户才能够完成支付。在这里提供一个已经注册好的沙箱用户(余额900多万,放心使用)。在项目目录下有一个名为:alipay_sandbox_user_info.txt的txt文件,打开即可看到沙箱用户名和密码(密码用于登录和支付)。

网站与支付宝的通信原理

网站在与支付宝接口通信时,需要传递一些参数。其中包括私钥和公钥(加密方式属于RSA2)。私钥:用于加密数据。公钥:用于解密数据。

例如:网站向支付宝接口发送了一个查询支付状态的请求,那么首先网站会用app私钥加密自己的数据,然后将数据发送给支付宝接口,那么支付宝接口就会用网站的app公钥解密这个数据;当支付宝收到请求后,会返回一个响应,这个响应会用支付宝密钥进行加密,然后将响应返回给网站;当网站接收到响应后,会用支付宝公钥对数据进行解密。

所以为了保证双方能够正常的通信,网页需要拥有app密钥和支付宝公钥;而支付宝需要拥有app公钥和支付宝密钥。

支付宝接口调用原理

当用户选择使用支付宝的方式进行支付时,前端会像后端发送一个ajax请求,那么后端在接收到请求后,会返回一个支付宝的支付url给前端,此时前端需要引导用户去支付页面进行支付的操作,那么剩下的事情就交给支付宝了,与网站没有什么关系了。

当用户完成支付后,支付宝会跳转到一个return_url(由后端进行配置)并且将支付结果告诉notify_url(由后端进行配置)。那么就由后端来进行相应的业务处理。

接口使用前的准备

在使用接口之前,需要前往支付宝官网申请好沙箱账号,点击前往

在申请好沙箱账号后,支付宝会提供一些关键信息:

  1. APPID:要保存,在申请支付接口的时候要用到。
  2. 商家信息:可以不保存,用于在支付时显示的商家信息。
  3. 买家信息:要保存,需要保存买家的账号和密码,用于沙箱支付。
  4. 接口密钥:要保存app密钥和支付宝公钥,用于接口调用。
  5. 支付宝网关地址:要保存,用于拼接支付页面的url。

对于app密钥和支付宝公钥,需要分别单独的保存到一个后缀名为“pem”的文件下面。

app密钥需要在文件的首行和末行写好以下标识:

-----BEGIN RSA PRIVATE KEY-----  首行
app密钥
-----END RSA PRIVATE KEY-----  末行

同样支付宝公钥也需要配置:

-----BEGIN RSA PUBLIC KEY-----  首行
支付宝公钥
-----END RSA PUBLIC KEY-----  末行

支付宝接口的使用

  1. 由于使用的是沙箱环境,所以需要先安装第三方模块,在项目环境下执行pip命令:
pip install python-alipay-sdk
  1. 接口初始化:
from alipay import Alipay
alipay = AliPay(
	appid=settings.ALIPAY_APP_ID,  # APPID,申请沙箱后会拥有
	app_private_key_string=app_private_key_string,  # app密钥
	alipay_public_key_string=alipay_public_key_string,  # 支付宝公钥
	debug=True  # 为True的时候调用沙箱接口,反之调用真实的支付接口
)
  1. 支付接口参数的生成,几个必选参数:
params = alipay.api_alipay_trade_page_pay(
	out_trade_no=trade_no,  # 交易编号
	total_amount=total_amount,  # 订单总价钱
	subject=subject,  # 订单标题
    # 用户支付后返回的页面URL,开发环境无法使用,生产环境才能生效。没有就写None
	return_url='http协议+域名+路径',  
	notify_url=None  # 支付结果通知的URL,没有就写None
)
  1. 支付接口的拼接:
url = 'https://openapi-sandbox.dl.alipaydev.com/gateway.do?' + params  # 支付宝网关接口 + 支付宝接口参数

那么到这里,url就是支付宝的支付页面地址了,用户只需访问这个网址,即可完成支付。

至于真正的代码怎么写(包括支付完成的后续),请参照项目源码。

源码位于:/apps/order/views.py下的AliPayView类。

解决调用api_alipay_trade_query接口时报ssl证书的错误

当调用该接口查询支付结果的时候报错:

<urlopen error [SSL: CERTIFICATE_ _VERIFY_ FAILED] certificate verify failed: unable to get local issuer certificate (_ ssl.c:997 )>

该报错是由于相关ssl证书没有的原因造成的,一般会在生产环境下报错。

我们需要在项目settings文件下编写以下代码:

import ssl

# 自定义 SSL 配置
custom_ssl_context = ssl.create_default_context()
custom_ssl_context.check_hostname = False
custom_ssl_context.verify_mode = ssl.CERT_NONE

# 将自定义 SSL 配置添加到 Django settings 中
SSL_CONFIG = custom_ssl_context

接着找到alipay的init.py文件,找到verified_sync_response这个函数。

def verified_sync_response(self, data, response_type):
	url = self._gateway + "?" + self.sign_data(data)
	raw_string = urlopen(url, timeout=self._config.timeout).read().decode()
	return self._verify_and_return_sync_response(raw_string, response_type)

我们需要修改一下这个函数的源码,改成以下:

def verified_sync_response(self, data, response_type):
    from django.conf import settings  # 导入配置文件
	url = self._gateway + "?" + self.sign_data(data)
	raw_string = urlopen(url, timeout=self._config.timeout, context=settings.SSL_CONFIG).read().decode()  # 新增一个context的字段
	return self._verify_and_return_sync_response(raw_string, response_type)

修改完后保存再重启项目即可解决该报错。

FastDFS分布式文件系统

注意:分布式文件系统只支持在生产环境中使用。

FastDFS简述

FastDFS 是一个开源的高性能分布式文件系统(DFS)。 它的主要功能包括:文件存储,文件同步和文件访问,以及高容量和负载平衡。主要解决了海量数据存储问题,特别适合以中小文件(建议范围:4KB < file_size <500MB)为载体的在线服务。

FastDFS 系统有三个角色:跟踪服务器(Tracker Server)、存储服务器(Storage Server)和客户端(Client)。

  • Tracker Server:跟踪服务器,主要做调度工作,起到均衡的作用;负责管理所有的 storage server和 group,每个 storage 在启动后会连接 Tracker,告知自己所属 group 等信息,并保持周期性心跳。
  • Storage Server:存储服务器,主要提供容量和备份服务;以 group 为单位,每个 group 内可以有多台 storage server,数据互为备份。
  • Client:客户端,上传下载数据的服务器,也就是我们自己的项目所部署在的服务器。

其为了支持大容量,存储节点(服务器)采用了分卷(或分组)的组织方式。存储系统由一个或多个卷组成,卷与卷之间的文件是相互独立的,所有卷的文件容量累加就是整个存储系统中的文件容量。一个卷可以由一台或多台存储服务器组成,一个卷下的存储服务器中的文件都是相同的,卷中的多台存储服务器起到了冗余备份和负载均衡的作用。

在卷中增加服务器时,同步已有的文件由系统自动完成,同步完成后,系统自动将新增服务器切换到线上提供服务。当存储空间不足或即将耗尽时,可以动态添加卷。只需要增加一台或多台服务器,并将它们配置为一个新的卷,这样就扩大了存储系统的容量。

对于电商网站而言,随着商品数目的增多,毫无疑问是需要上传海量的图片的,如果只凭借Django默认的文件存储系统,那么久而久之就会增加应用的负担,从而降低网站的访问速度和用户的满意程度。

安装FastDFS

  • 由于FastDFS暂时没有提供Windows版本,所以只能在Linux中安装。

  • 在安装之前需要开放两个端口:22122、23000。

  • 下载libfastcommon-master.zip文件

    1. 执行以下命令下载。
    wget https://github.com/happyfish100/libfastcommon/archive/V1.0.7.tar.gz
    # 如果下载速度慢,可以前往百度网盘进行下载:https://pan.baidu.com/s/1YshX1HAt5CWa_N9UgFV1vA?pwd=yyq9
  • 安装FastDFS需要先安装其依赖包

    1. 解压下载的文件。

    2. 进入解压后的目录。

    3. 执行以下命令进行编译:

    ./make.sh
    1. 执行以下命令安装依赖包:
    sudo ./make.sh install
  • 安装FastDFS

    1. 下载fastdfs-master。
    wget https://github.com/happyfish100/fastdfs/archive/V5.05.tar.gz
    # 如果下载速度慢,可以前往百度网盘进行下载:https://pan.baidu.com/s/1YshX1HAt5CWa_N9UgFV1vA?pwd=yyq9
    1. 解压下载的文件。

    2. 进入解压后的目录。

    3. 执行编译命令:

    ./make.sh
    1. 安装
    sudo ./make.sh install
  • 配置跟踪服务器tracker

    1. 复制一份配置文件:
    sudo cp /etc/fdfs/tracker.conf.sample /etc/fdfs/tracker.conf
    1. 创建目录/home/python/fastdfs/tracker,用于存放日志信息。
    mkdir /home/python/fastdfs/tracker
    1. 配置tracker信息:
    sudo vim /etc/fdfs/tracker.conf
    # 修改 base_path=/home/python/fastdfs/tracker
  • 配置储存服务器storage

    1. 复制一份配置文件:
    sudo cp /etc/fdfs/storage.conf.sample /etc/fdfs/storage.conf
    1. 创建目录/home/python/fastdfs/storage,用于存放日志信息。
    mkdir /home/python/fastdfs/storage
    1. 配置storage信息:
    sudo vim /etc/fdfs/storage.conf
    # 需要修改的信息如下:
    # base_path=/home/python/fastdfs/storage
    # store_path0=/home/python/fastdfs/storage
    # tracker_server=虚拟机的ip地址:22122(在终端输入ifconfig,eth0中的inet后面那个就是虚拟机内网ip)
  • 分别启动storage和tracker

    1. 输入以下命令启动:
    sudo service fdfs_trackerd start
    sudo service fdfs_storaged start
    1. 检查启动情况:
    ps aux | grep fdfs
    1. 可以看到已启动:

  • 尝试上传文件至分布式系统

    1. 复制一个客户端配置文件:
    sudo cp /etc/fdfs/client.conf.sample /etc/fdfs/client.conf
    1. 修改配置信息:
    sudo vim /etc/fdfs/client.conf
    # 需要修改的信息如下:
    # base_path=/home/python/fastdfs/tracker
    # tracker_server=虚拟机的ip地址:22122(在终端输入ifconfig,eth0中的inet后面那个就是虚拟机内网ip)
    1. 上传测试文件:
    fdfs_upload_file /etc/fdfs/client.conf test.png
    1. 若返回“group1/M00/00/00/CgAMDmTi7rSAHWfiAABH9ekAtBY137.png”类似的信息表明FastDFS配置成功!

FastDFS搭配Nginx

尽管FastDFS能够处理海量静态文件,但是一旦请求数目多起来,那么它的响应速度是会变慢的,所以这时候就需要处理静态文件的高手——Nginx来处理了。

  • 完成搭配之前需要确保安装好Nginx

  • 两者搭配使用需要安装一个依赖包

    1. 解压缩名为fastdfs-nginx-module-master的文件。
    2. 进入Nginx目录下,找到configure的文件,执行以下命令为Nginx添加依赖模块。
    ./configure --add-module=/www/server/fastdfs/fastdfs-nginx-module-master/src
    # 注意:除了添加上述模块以外,需用使用nginx -V命令查看已安装模块,并将这些已安装模块追加至上述命令。
    1. 分别执行以下命令编译并完成安装。
    make
    make install
    1. 查看是否安装完成。
    nginx -V

  • 修改配置信息

    1. 复制一份配置信息。
    sudo cp fastdfs-nginx-module-master_path/src/mod_fastdfs.conf  /etc/fdfs/mod_fastdfs.conf
    1. 修改配置信息。
    sudo vim /etc/fdfs/mod_fastdfs.conf
    # 需要修改的信息:
    # connect_timeout=10
    # tracker_server=虚拟机的ip地址:22122(在终端输入ifconfig,eth0中的inet后面那个就是虚拟机内网ip)
    # url_have_group_name=true  是否使用组名称
    # store_path0=/home/python/fastdfs/storage
    1. 复制fastdfs-master目录中的http.conf和mime.types。
    sudo cp fastdfs-master_path/http.conf  /etc/fdfs/http.conf
    sudo cp fastdfs-master_path/mime.types /etc/fdfs/mime.types
    # 这两个文件可能不在fastdfs-master的根目录中,可能在conf中。
  • 在Nginx中的配置信息添加以下配置

    # 在http的作用域中添加以下:
    server {
    	listen 8888;  # 这里是对外的端口,要与storage.conf中的http.server_port端口一致并在防火墙中打开。
    	server_name 114.132.47.115;
    	location ~ /group[0-9]/ {
    		ngx_fastdfs_module;
    	}
    }

    重启Nginx后通过输入:域名+上述配置的端口+文件id,就可以访问文件了。

Python与FastDFS交互

  1. 进入项目虚拟环境并安装对应的依赖:
pip install py3Fdfs
  1. 测试是否能正常交互。
from fdfs_client.client import get_tracker_conf, Fdfs_client

tracker_conf = get_tracker_conf('/etc/fdfs/client.conf')  # client.conf的具体位置
client = Fdfs_client(tracker_conf)  # 实例化对象
client.upload_by_filename('media/img/noyue.png')  # 上传文件
"""
返回值应该是这样的:
{'Group name': b'group1', 'Remote file_id': b'group1/M00/00/00/CgAMDmTjInCAPHyQAABH9ekAtBY301.png', 'Status': 'Upload successed.', 'Local file name': 'media/img/noyue.png', 'Uploaded size': '17.99KB', 'Storage IP': b'114.132.47.115'}
"""
  1. 若能够正常交互,就可以在Django中配置了。

在Django中配置FastDFS

由于Django用的是默认的文件存储类。也就是FileSystemStorage类,为了使用FastDFS,我们需要自定义文件系统类并继承 Storage类。

  1. 确保项目环境中有依赖包。
pip install py3Fdfs
  1. 在项目目录中创建一个py文件用于自定义文件存储类。
  2. 在该文件中写入以下内容:
from django.core.files.storage import Storage
from fdfs_client.client import Fdfs_client, get_tracker_conf
from django.conf import settings


# fastdfs文件存储类
class FastDFSStorage(Storage):
    def __init__(self, client_conf=None, base_url=None):
        """初始化"""
        self.client_conf = client_conf or settings.FDFS_CLIENT_CONF
        self.base_url = base_url or settings.FDFS_URL

    def _open(self, name, mode='rb'):
        """打开文件时使用"""
        pass

    def _save(self, name, content):
        """保存文件时使用"""
        tracker_conf = get_tracker_conf(self.client_conf)  # client.conf的具体位置
        client = Fdfs_client(tracker_conf)  # 创建一个client对象
    
        res = client.upload_by_buffer(content.read())  # 上传文件到fast dfs系统中
        
        if res.get('Status') != 'Upload successed.':
            # 上传失败
            raise Exception('上传文件到fast dfs失败')

        # 获取返回的文件ID
        filename = res.get('Remote file_id').decode()

        return filename

    def exists(self, name):
        """Django判断文件名是否可用"""
        return False

    def url(self, name):
        """
        返回访问文件的url路径。
        使用对象名.url的时候会调用该方法  image.url
        """
        return self.base_url + name
  1. 在项目settings文件下加入以下内容:
# 将Django默认的文件存储类改成自定义文件存储类
DEFAULT_FILE_STORAGE = 'utils.fds.fastdfs.FastDFSStorage'  # 自定义文件存储类的位置,变量名不能自定义

# 配置信息路径
FDFS_CLIENT_CONF = [BASE_DIR / 'utils/fds/client.conf']  # 配置信息的路径,变量名字可以自定义

# fastdfs的文件访问路径
FDFS_URL = 'http/https://域名:storage.conf中的http.server_port端口/'  # 变量名字可以自定义

此时已经配置好了自定义文件存储类,当我们通过后台添加文件的时候,就会调用这个类。

当我们点击保存的时候,Django就会调用自定义的文件存储类,并向FastDFS上传该文件,此时FastDFS就会返回一个字典信息,通过自定义文件存储类中的_save方法,获取该文件的ID并直接保存至数据库中。

生产环境下的Celery

在部署环境中,不能使用开发环境的命令来启动celery,要使用以下命令来启动celery。

先进入项目虚拟环境,输入下面命令启动celery。

celery multi start -A tasks worker

关闭celery

celery multi stop -A tasks worker
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