让我为您详细讲解“Python中Scrapy+adbapi提高数据库写入效率实现”的完整攻略。
1. Scrapy简介
Scrapy是一个开源的Python网络爬虫框架,它可以轻松地从网页中提取所需要的数据。Scrapy自带的Item Pipeline功能可以方便地将爬取到的数据存储到各种类型的数据库中。
2. adbapi介绍
adbapi是Twisted框架中一个用于连接数据库的API。使用adbapi可以较为方便地在异步的Twisted环境下连接和操作数据库。
3. Scrapy如何使用adbapi
Scrapy使用adbapi存储数据的步骤如下:
- 安装Twisted和adbapi。
pip install twisted
pip install psycopg2
这里以PostgreSQL数据库为例,如果您使用的是其他类型的数据库,需要相应地安装对应的驱动。
- 在Scrapy项目的settings.py配置文件中添加数据库配置信息。
DATABASE = {
'drivername': 'postgresql',
'host': 'localhost',
'port': '5432',
'username': 'postgres',
'password': 'password',
'database': 'scrapy_db'
}
- 在Scrapy项目中创建一个pipeline,在pipeline中使用adbapi连接数据库,并将数据存储到数据库中。
from scrapy.exceptions import DropItem
from scrapy import log
from twisted.enterprise import adbapi
import psycopg2
class PostgresPipeline(object):
def __init__(self, dbpool):
self.dbpool = dbpool
@classmethod
def from_settings(cls, settings):
dbargs = dict(
host=settings['PG_HOST'],
db=settings['PG_DBNAME'],
user=settings['PG_USER'],
password=settings['PG_PASSWORD']
)
dbpool = adbapi.ConnectionPool('psycopg2', **dbargs)
return cls(dbpool)
def process_item(self, item, spider):
# run db query in thread pool
query = self.dbpool.runInteraction(self.do_insert, item)
query.addErrback(self.handle_error)
return item
def handle_error(self, e):
log.err(e)
def do_insert(self, cursor, item):
# execute insert statement
insert_sql = """
INSERT INTO mytable (name,age,gender)
VALUES (%s, %s, %s)
"""
cursor.execute(insert_sql, (item['name'], item['age'], item['gender']))
在上面的代码中,我们使用PostgreSQL作为数据库,在pipeline的from_settings方法中使用adbapi创建一个连接池,然后在process_item方法中,通过runInteraction方法将数据插入到数据库中。
4. 示例说明
示例一
假设我们需要从一个论坛中爬取用户信息,存储到PostgreSQL数据库中。我们可以先定义一个Item:
# items.py
import scrapy
class UserItem(scrapy.Item):
name = scrapy.Field()
age = scrapy.Field()
gender = scrapy.Field()
然后定义一个Spider,在Spider中提取用户信息,并通过pipeline将数据存储到数据库中:
# spiders/users.py
import scrapy
from myproject.items import UserItem
class UsersSpider(scrapy.Spider):
name = "users"
allowed_domains = ["example.com"]
start_urls = [
"http://example.com/users/1",
"http://example.com/users/2",
"http://example.com/users/3",
]
def parse(self, response):
user = UserItem()
user['name'] = response.css('div.name::text').get()
user['age'] = response.css('div.age::text').get()
user['gender'] = response.css('div.gender::text').get()
yield user
最后,在pipeline中使用adbapi将数据存储到数据库中:
# pipelines.py
from scrapy.exceptions import DropItem
from scrapy import log
from twisted.enterprise import adbapi
import psycopg2
class PostgresPipeline(object):
def __init__(self, dbpool):
self.dbpool = dbpool
@classmethod
def from_settings(cls, settings):
dbargs = dict(
host=settings['PG_HOST'],
db=settings['PG_DBNAME'],
user=settings['PG_USER'],
password=settings['PG_PASSWORD']
)
dbpool = adbapi.ConnectionPool('psycopg2', **dbargs)
return cls(dbpool)
def process_item(self, item, spider):
# run db query in thread pool
query = self.dbpool.runInteraction(self.do_insert, item)
query.addErrback(self.handle_error)
return item
def handle_error(self, e):
log.err(e)
def do_insert(self, cursor, item):
# execute insert statement
insert_sql = """
INSERT INTO mytable (name,age,gender)
VALUES (%s, %s, %s)
"""
cursor.execute(insert_sql, (item['name'], item['age'], item['gender']))
示例二
假设我们需要从一个网站中爬取商品信息,并存储到MySQL数据库中。我们可以先定义一个Item:
# items.py
import scrapy
class ProductItem(scrapy.Item):
title = scrapy.Field()
price = scrapy.Field()
description = scrapy.Field()
然后定义一个Spider,在Spider中提取商品信息,并通过pipeline将数据存储到数据库中:
# spiders/products.py
import scrapy
from myproject.items import ProductItem
class ProductsSpider(scrapy.Spider):
name = "products"
allowed_domains = ["example.com"]
start_urls = [
"http://example.com/products/1",
"http://example.com/products/2",
"http://example.com/products/3",
]
def parse(self, response):
product = ProductItem()
product['title'] = response.css('h1.title::text').get()
product['price'] = response.css('span.price::text').get()
product['description'] = response.css('div.description::text').get()
yield product
最后,在pipeline中使用adbapi将数据存储到数据库中:
# pipelines.py
from scrapy.exceptions import DropItem
from scrapy import log
from twisted.enterprise import adbapi
import pymysql
class MySQLPipeline(object):
def __init__(self, dbpool):
self.dbpool = dbpool
@classmethod
def from_settings(cls, settings):
dbargs = dict(
host=settings['MYSQL_HOST'],
db=settings['MYSQL_DBNAME'],
user=settings['MYSQL_USER'],
password=settings['MYSQL_PASSWORD'],
charset='utf8mb4',
cursorclass=pymysql.cursors.DictCursor
)
dbpool = adbapi.ConnectionPool('pymysql', **dbargs)
return cls(dbpool)
def process_item(self, item, spider):
# run db query in thread pool
query = self.dbpool.runInteraction(self.do_insert, item)
query.addErrback(self.handle_error)
return item
def handle_error(self, e):
log.err(e)
def do_insert(self, cursor, item):
# execute insert statement
insert_sql = """
INSERT INTO mytable (title,price,description)
VALUES (%s, %s, %s)
"""
cursor.execute(insert_sql, (item['title'], item['price'], item['description']))
总结
通过以上的操作,我们成功地使用Scrapy和adbapi将数据存储到数据库中,实现了快速高效的数据库写入。Scrapy+adbapi的组合可以有效地提高数据的存储速度,减少数据库连接的开销,适用于需要高效处理大量数据存储的场景。
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