drf 一次错误排查

前言

在使用最新版本的 DRF 框架时,注册路由阶段报了一个错

“django.core.exceptions.ImproperlyConfigured: The included URLconf ‘bingo.urls’ does not appear to have any patterns in it. If you see valid patterns in the file then the issue is probably caused by a circular import.”

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2019和2020

前言

2019年总体来说还是有所收获的,除了技术上成长了许多,还开发了自己的博客;另外还参与了 Pycon China2019 成都 的志愿者活动,有机会和各位大佬近距离接触

志愿者和讲师合影,阿里老哥、日本小姐姐以及 Flask 项目大神维护者的讲解让小生受益匪浅。

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Elasticsearch组合查询

准备数据

POST lagou/testjob/_bulk
{"index":{"_id":1}}
{"salary":10, "title": "Python"}
{"index":{"_id":2}}
{"salary":20, "title": "Scrapy"}
{"index":{"_id":3}}
{"salary":30, "title": "Django"}
{"index":{"_id":4}}
{"salary":40, "title": "Elasticsearch"}

组合查询

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Elasticsearch基本查询

准备数据

# 添加映射  
PUT lagou
{
  "mappings": {
    "job":{
      "properties": {
        "title":{
          "store": true,
          "type": "text",
          "analyzer": "ik_max_word"
        },
        "company_name":{
          "store": true,
          "type": "keyword"
        },
        "desc":{
          "type": "text"
        },
        "comments":{
          "type": "integer"
        },
        "add_time":{
          "type": "date",
          "format": "yyyy-MM-dd"
        }
      }
    }
  }
}

POST lagou/job/
{
    "title":"python django 开发工程师",
    "company_name":"美团科技有限公司",
    "desc":"对django的概念熟悉,熟悉python基础知识",
    "comments":20,
    "add_time":"2019-5-30"
}

POST lagou/job/
{
    "title":"python scrapy redis分布式爬虫基本",
    "company_name":"百度科技有限公司",
    "desc":"scrapy的概念熟悉,熟悉redis基础知识",
    "comments":5,
    "add_time":"2019-5-1"
}

POST lagou/job/
{
    "title":"elasticsearch打造搜索引擎",
    "company_name":"阿里巴巴科技有限公司",
    "desc":"熟悉数据结构算法,熟悉python基础开发",
    "comments":60,
    "add_time":"2019-4-15"
}

POST lagou/job/
{
    "title":"python打造推荐引擎系统",
    "company_name":"阿里巴巴科技有限公司",
    "desc":"熟悉推荐引擎的原理以及算法,掌握C语言",
    "comments":60,
    "add_time":"2019-1-22"
}

查询

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Elasticsearch操作

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# es的文档,索引的 CRUD 操作

# 索引初始化操作

# 指定分片和副本的数量

# shards一旦设置不能修改(副本数量)



# 设置索引

PUT lagou

{

"settings": {

"index":{

"number_of_shards": 5,

"number_of_replicas": 2

}

}

}



GET lagou/_settings

GET _all/_settings

GET .kibana,lagou/_settings

GET lagou/job/1/_source



# 修改settings

PUT lagou/_settings

{

"number_of_shards": 2

}



# 保存文档

PUT lagou/job/2

{

"title": "python分布式爬虫开发",

"salary_min": 15000,

"city": "北京",

"company": {

"name": "百度",

"company_addr": "北京市软件园"

},

"publish_data": "2019-5-30",

"comments": 15

}



POST lagou/job/1

{

"title": "python django 开发工程师",

"salary_min": 3000,

"city": "天猫",

"company": {

"name": "美团科技",

"company_addr": "北京市软件园A区"

},

"publish_data": "2019-5-30",

"comments": 2

}





GET lagou/job/2?_source=city,company.name



# 修改文章

PUT lagou/job/2

{

"title": "python分布式爬虫开发",

"salary_min": 15000,

"city": "北京",

"company": {

"name": "百度",

"company_addr": "北京市软件园"

},

"publish_data": "2019-5-30",

"comments": 23

}



# 修改文章2

POST lagou/job/2/_update

{

"doc":{

"comments": 21

}

}





DELETE lagou/job/1

DELETE lagou



# 批量获取

GET _mget

{

"docs":[

{

"_index":"lagou",

"_type": "job2",

"_id": 2

},

{

"_index":"lagou",

"_type": "job",

"_id": 1

}

]

}



# index一样

GET lagou/_mget

{

"docs":[

{

"_type": "job2",

"_id": 2

},

{

"_type": "job",

"_id": 1

}

]

}





# index,type一样



GET lagou/job2/_mget

{

"docs":[

{

"_id": 2

},

{

"_id": 1

}

]

}



GET lagou/job2/_mget

{

"ids": [1,2]

}





bulk批量操作

bulk操作不能分行,json必需一行写完

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Elasticsearch配置

安装

  1. Java环境
  2. Git 下载 elasticsearch-rtf 压缩包,解压 进入bin 运行 elasticsearch.bat
  3. Git clone elasticsearch-head 进入,npm install,npm run start
  4. 配置elasticsearch.yml
http.cors.enabled: true
http.cors.allow-origin: "*"
http.cors.allow-methods: OPTIONS, HEAD, GET, PUT, DELETE
http.cors.allow-headers: "X-Requested_With, Content-Type, Content_Length, X-User"
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Docker 指令2

  • RUN 执行命令并创建新的Image layer
  • CMD 设置容器启动后默认执行的命令和参数
  • ENTRYPOINT 设置容器启动时执行的命令
  • shell 格式
RUN apt-get install -y vim 
CMD echo "hello docker"
ENTRYPOINT echo "hello docker"
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Docker 指令

  1. docker images 显示所有镜像

  2. docker build -t image_name . (点就是从当前路径查找Dockerfile)

  3. docker container ls 列举当前运行的容器

  4. docker run -it image_name 交互式运行image

  5. docker rm/docker container rm container_id 删除container

  6. docker rmi/docker image rm image_id 删除image

  7. docker container -aq 列出所有container_id (-q代表只列出id)

  8. docker rm $(docker container -aq) ($,删除所有列表中的元素)

  9. docker rm $(docker container ls -f “status=exited” -q) 删除退出的容器

  10. docker commit container_name new_container_name

    docker commit frozty_jeew caesar123/centos-vim

  11. Dockerfile 用来build一个一模一样的image

Dokerfile

  • FROM strach # 制作base image
  • FROM centos # 使用base image
  • FROM ubuntu:14.04
  • LABEL maintainer = “775650117@qq.com“ (METADATA:注释)
  • LABEL version = “1.0”
  • RUN yum update && yun install -y vim
    python-dev
  • 每次运行RUN都会生成新的image,所以尽量合并成一行
  • WORKDIR /root # 设定工作目录
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