Teach you step by step how to use Flask to build an ES search engine (Practical)

Start using Flask Build ES search.

1

#Configuration file

#Config.py

#coding:utf-8
import os
DB_USERNAME = 'root'
DB_PASSWORD = None # 如果没有密码的话
DB_HOST = '127.0.0.1'
DB_PORT = '3306'
DB_NAME = 'flask_es'

class Config:
    SECRET_KEY ="随机字符" # 随机 SECRET_KEY
    SQLALCHEMY_COMMIT_ON_TEARDOWN = True # 自动提交
    SQLALCHEMY_TRACK_MODIFICATIONS = True # 自动sql
    DEBUG = True # debug模式
    SQLALCHEMY_DATABASE_URI = 'mysql+pymysql://%s:%s@%s:%s/%s' % (DB_USERNAME, DB_PASSWORD,DB_HOST, DB_PORT, DB_NAME) #数据库URL

    MAIL_SERVER = 'smtp.qq.com'
    MAIL_POST = 465
    MAIL_USERNAME = '3417947630@qq.com'
    MAIL_PASSWORD = '邮箱授权码'
    FLASK_MAIL_SUBJECT_PREFIX='M_KEPLER'
    FLASK_MAIL_SENDER=MAIL_USERNAME # 默认发送人
    # MAIL_USE_SSL = True
    MAIL_USE_TLS = False
    MAIL_DEBUG = False
    ENABLE_THREADS=True

This is a relatively simple

Flask Config

file. Of course, the database connection is not necessary for the current project. I just use Mysql for auxiliary purposes. Partners do not need to configure the connection database, ES is enough. Then the email notification will depend on personal needs...

##2

#Log

Logger.py

The log module is an essential part of engineering applications. It is very necessary to output log files according to different production environments. . To use a Jianghu saying: "If there is no log file, you will die without knowing how to die..."

# coding=utf-8
import os
import logging
import logging.config as log_conf
import datetime
import coloredlogs

coloredlogs.DEFAULT_FIELD_STYLES = {'asctime': {'color': 'green'}, 'hostname': {'color': 'magenta'}, 'levelname': {'color': 'magenta', 'bold': False}, 'name': {'color': 'green'}}

log_dir = os.path.dirname(os.path.dirname(__file__)) + '/logs'
if not os.path.exists(log_dir):
    os.mkdir(log_dir)
today = datetime.datetime.now().strftime("%Y-%m-%d")

log_path = os.path.join(log_dir, today + ".log")

log_config = {
    'version': 1.0,

    # 格式输出
    'formatters': {
        'colored_console': {
                        'format': "%(asctime)s - %(name)s - %(levelname)s - %(message)s",
                        'datefmt': '%H:%M:%S'
        },
        'detail': {
            'format': '%(asctime)s - %(name)s - %(levelname)s - %(message)s',
            'datefmt': "%Y-%m-%d %H:%M:%S"  #时间格式
        },
    },

    'handlers': {
        'console': {
            'class': 'logging.StreamHandler', 
            'level': 'DEBUG',
            'formatter': 'colored_console'
        },
        'file': {
            'class': 'logging.handlers.RotatingFileHandler',  
            'maxBytes': 1024 * 1024 * 1024,  
            'backupCount': 1, 
            'filename': log_path, 
            'level': 'INFO',  
            'formatter': 'detail',  # 
            'encoding': 'utf-8',  # utf8 编码  防止出现编码错误
        },
    },

    'loggers': {
        'logger': {
            'handlers': ['console'],  
            'level': 'DEBUG', 
        },

    }
}

log_conf.dictConfig(log_config)
log_v = logging.getLogger('log')

coloredlogs.install(level='DEBUG', logger=log_v)


# # Some examples.
# logger.debug("this is a debugging message")
# logger.info("this is an informational message")
# logger.warning("this is a warning message")
# logger.error("this is an error message")
# logger.critical("this is a critical message")

Here is a copy of what I commonly use. The log configuration file can be used as a commonly used log format. It can be called directly and output to the terminal or

.log

file according to different levels. You can take it away without any thanks.

3

路由

对于 Flask 项目而言， 蓝图和路由会让整个项目更具观赏性(当然指的是代码的阅读)。

这里我采用两个分支来作为数据支撑，一个是 Math 入口，另一个是 Baike 入口，数据的来源是基于上一篇的百度百科爬虫所得，根据 深度优先 的爬取方式抓取后放入 ES 中。

# coding:utf8
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from app.config.config import Config
from flask_mail import Mail
from flask_wtf.csrf import CSRFProtect

app = Flask(__name__,template_folder='templates',static_folder='static')
app.config.from_object(Config)

db = SQLAlchemy(app)
db.init_app(app)

csrf = CSRFProtect(app)
mail = Mail(app)
# 不要在生成db之前导入注册蓝图。
from app.home.baike import baike as baike_blueprint
from app.home.math import math as math_blueprint
from app.home.home import home as home_blueprint

app.register_blueprint(home_blueprint)
app.register_blueprint(math_blueprint,url_prefix="/math")
app.register_blueprint(baike_blueprint,url_prefix="/baike")

# -*- coding:utf-8 -*-
from flask import Blueprint
baike = Blueprint("baike", __name__)

from app.home.baike import views

# -*- coding:utf-8 -*-
from flask import Blueprint
math = Blueprint("math", __name__)

from app.home.math import views

声明路由并在 __init__ 文件中初始化

下面来看看路由的实现(以Baike为例)

# -*- coding:utf-8 -*-
import os
from flask_paginate import Pagination, get_page_parameter
from app.Logger.logger import log_v
from app.elasticsearchClass import elasticSearch

from app.home.forms import SearchForm

from app.home.baike import baike
from flask import request, jsonify, render_template, redirect

baike_es = elasticSearch(index_type="baike_data",index_name="baike")

@baike.route("/")
def index():
    searchForm = SearchForm()
    return render_template('baike/index.html', searchForm=searchForm)

@baike.route("/search", methods=['GET', 'POST'])
def baikeSearch():
    search_key = request.args.get("b", default=None)
    if search_key:
        searchForm = SearchForm()
        log_v.error("[+] Search Keyword: " + search_key)
        match_data = baike_es.search(search_key,count=30)

        # 翻页
        PER_PAGE = 10
        page = request.args.get(get_page_parameter(), type=int, default=1)
        start = (page - 1) * PER_PAGE
        end = start + PER_PAGE
        total = 30
        print("最大数据总量:", total)
        pagination = Pagination(page=page, start=start, end=end, total=total)
        context = {
            'match_data': match_data["hits"]["hits"][start:end],
            'pagination': pagination,
            'uid_link': "/baike/"
        }
        return render_template('data.html', q=search_key, searchForm=searchForm, **context)
    return redirect('home.index')


@baike.route(&#39;/<uid>&#39;)
def baikeSd(uid):
    base_path = os.path.abspath(&#39;app/templates/s_d/&#39;)
    old_file = os.listdir(base_path)[0]
    old_path = os.path.join(base_path, old_file)
    file_path = os.path.abspath(&#39;app/templates/s_d/{}.html&#39;.format(uid))
    if not os.path.exists(file_path):
        log_v.debug("[-] File does not exist, renaming !!!")
        os.rename(old_path, file_path)
    match_data = baike_es.id_get_doc(uid=uid)
    return render_template(&#39;s_d/{}.html&#39;.format(uid), match_data=match_data)

可以看到我们成功的将 elasticSearch 类初始化并且进行了数据搜索。

我们使用了 Flask 的分页插件进行分页并进行了单页数量的限制，根据 Uid 来跳转到详情页中。

细心的小伙伴会发现我这里用了个小技巧

@baike.route(&#39;/<uid>&#39;)
def baikeSd(uid):
    base_path = os.path.abspath(&#39;app/templates/s_d/&#39;)
    old_file = os.listdir(base_path)[0]
    old_path = os.path.join(base_path, old_file)
    file_path = os.path.abspath(&#39;app/templates/s_d/{}.html&#39;.format(uid))
    if not os.path.exists(file_path):
        log_v.debug("[-] File does not exist, renaming !!!")
        os.rename(old_path, file_path)
    match_data = baike_es.id_get_doc(uid=uid)
    return render_template(&#39;s_d/{}.html&#39;.format(uid), match_data=match_data)

以此来保证存放详情页面的模板中始终只保留一个 html 文件。

4

项目启动

一如既往的采用 flask_script 作为项目的启动方案，确实方便。

# coding:utf8
from app import app
from flask_script import Manager, Server

manage = Manager(app)

# 启动命令
manage.add_command("runserver", Server(use_debugger=True))


if __name__ == "__main__":
    manage.run()

黑窗口键入

python manage.py runserver

就可以启动项目，默认端口 5000，访问 http://127.0.0.1:5000

使用gunicorn启动

pip install gunicorn

#encoding:utf-8
import multiprocessing

from gevent import monkey
monkey.patch_all()

# 并行工作进程数
workers = multiprocessing.cpu_count() * 2 + 1

debug = True

reload = True # 自动重新加载

loglevel = 'debug'

# 指定每个工作者的线程数
threads = 2

# 转发为监听端口8000
bind = '0.0.0.0:5001'

# 设置守护进程,将进程交给supervisor管理
daemon = 'false'

# 工作模式协程
worker_class = 'gevent'

# 设置最大并发量
worker_connections = 2000

# 设置进程文件目录
pidfile = 'log/gunicorn.pid'
logfile = 'log/debug.log'

# 设置访问日志和错误信息日志路径
accesslog = 'log/gunicorn_acess.log'
errorlog = 'log/gunicorn_error.log'

利用配置文件来启动 gunicorn 服务器

gunicorn -c gconfig.py manage:app

项目截图

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