我使用2个蜘蛛从网页获取数据，我使用Crawler Process()同时运行它们。
蜘蛛的代码：
class GDSpider(Spider):
name = "GenDis"
allowed_domains = ["gold.jgi.doe.gov"]
base_url ="https://gold.jgi.doe.gov/projects"
stmp = []
term = "man"
for i in range(1, 1000):
url = "https://gold.jgi.doe.gov/projects?page="+ str(i) +"&Project.Project+Name="+ term+ "&count=25"
stmp.append(url)
start_urls = stmp
def parse(self, response):
sel = Selector(response)
sites = sel.xpath('//tr[@class="odd"]|//tr[@class="even"]')
for site in sites:
item = GenDis()
item['Id'] = site.xpath('td/a/text()').extract()
item['Link'] = site.xpath('td/a/@href').extract()
item['Name'] = map(unicode.strip, site.xpath('td[2]/text()').extract())
item['Status'] = map(unicode.strip, site.xpath('td[3]/text()').extract())
item['Add_Date'] = map(unicode.strip, site.xpath('td[4]/text()').extract())
yield item
class EPGD_spider(Spider):
name = "EPGD"
allowed_domains = ["epgd.biosino.org"]
term = "man"
start_urls = ["http://epgd.biosino.org/EPGD/search/textsearch.jsp?textquery="+term+"&submit=Feeling+Lucky"]
MONGODB_DB = name + "_" + term
MONGODB_COLLECTION = name + "_" + term
def parse(self, response):
sel = Selector(response)
sites = sel.xpath('//tr[@class="odd"]|//tr[@class="even"]')
url_list = []
base_url = "http://epgd.biosino.org/EPGD"
for site in sites:
item = EPGD()
item['genID'] = map(unicode.strip, site.xpath('td[1]/a/text()').extract())
item['genID_url'] = base_url+map(unicode.strip, site.xpath('td[1]/a/@href').extract())[0][2:]
item['taxID'] = map(unicode.strip, site.xpath('td[2]/a/text()').extract())
item['taxID_url'] = map(unicode.strip, site.xpath('td[2]/a/@href').extract())
item['familyID'] = map(unicode.strip, site.xpath('td[3]/a/text()').extract())
item['familyID_url'] = base_url+map(unicode.strip, site.xpath('td[3]/a/@href').extract())[0][2:]
item['chromosome'] = map(unicode.strip, site.xpath('td[4]/text()').extract())
item['symbol'] = map(unicode.strip, site.xpath('td[5]/text()').extract())
item['description'] = map(unicode.strip, site.xpath('td[6]/text()').extract())
yield item
sel_tmp = Selector(response)
link = sel_tmp.xpath('//span[@id="quickPage"]')
for site in link:
url_list.append(site.xpath('a/@href').extract())
for i in range(len(url_list[0])):
if cmp(url_list[0][i], "#") == 0:
if i+1 < len(url_list[0]):
print url_list[0][i+1]
actual_url = "http://epgd.biosino.org/EPGD/search/"+ url_list[0][i+1]
yield Request(actual_url, callback=self.parse)
break
else:
print "The index is out of range!"
process = CrawlerProcess()
process.crawl(EPGD_spider)
process.crawl(GDSpider)
process.start() # the script will block here until all crawling jobs are finished
我想将数据保存到MongoDB数据库。这是我的管道代码：
class EPGD_pipeline(object):
def __init__(self):
connection = pymongo.MongoClient(
settings['MONGODB_SERVER'],
settings['MONGODB_PORT']
)
db = connection[settings['MONGODB_DB']]
self.collection = db[settings['MONGODB_COLLECTION']]
def process_item(self, item, spider):
valid = True
for data in item:
if not data:
valid = False
raise DropItem("Missing {0}!".format(data))
if valid:
self.collection.insert(dict(item))
log.msg("Item wrote to MongoDB database {}, collection {}, at host {}, port {}".format(
settings['MONGODB_DB'],
settings['MONGODB_COLLECTION'],
settings['MONGODB_SERVER'],
settings['MONGODB_PORT']))
return item
当我一次使用一只蜘蛛时，它可以正常工作。但是当我同时运行它们时，似乎管道不再起作用了。既没有设置数据库也没有设置集合。
我已多次看到Scrapy文档的CrawlerProcess()部分，但它没有提到管道事物。那么有人能告诉我我的代码有什么问题吗？
答案 0 :(得分：2)
这应解决问题：
from scrapy.utils.project import get_project_settings
process = CrawlerProcess(get_project_settings())
process.crawl(EPGD_spider)
process.crawl(GDSpider)
process.start()
您还可能需要重构您的蜘蛛代码以打开每个蜘蛛的连接（此示例使用下面的“额外提示2”）：
# In your pipeline
class EPGD_pipeline(object):
def __init__(self):
self.collections = {
spider_name: self.setup_db_connection(dj_mongo_database_url.parse(url))
for spider_name, url in settings['MONGODB_PIPELINE_SETTINGS'].iterItems()
)
}
def process_item(self, item, spider):
collection = self.collections[spider.name]
...
# In settings.py
MONGODB_PIPELINE_SETTINGS = {
"GenDis": "mongodb://myhost:29297/test_db/collection",
"EPGD": "mongodb://myhost:29297/test_db/collection2",
}
奖金提示1：使用txmongo代替pymongo，否则您的表现可能会非常糟糕（另请参阅here）。
奖金提示2：所有这些设置都难以管理。考虑使用类似django-mongo-database-url的内容将它们“打包”在一个网址中，并使它们更易于管理（如果collection was also in the URL会更干净。）
奖金提示3：你可能会做太多的写/交易。如果用例允许，请将结果保存到.jl个文件，并使用mongoimport在抓取完成时批量导入。以下是更详细的说明。
假设一个名为tutorial的项目和名为example的蜘蛛创建了100个项目，您可以在tutorial/extensions.py中创建一个扩展名：
import logging
import subprocess
from scrapy import signals
from scrapy.exceptions import NotConfigured
logger = logging.getLogger(__name__)
class MyBulkExtension(object):
@classmethod
def from_crawler(cls, crawler):
return cls(crawler)
def __init__(self, crawler):
settings = crawler.settings
self._feed_uri = settings.get('FEED_URI', None)
if self._feed_uri is None:
raise NotConfigured('Missing FEED_URI')
self._db = settings.get('BULK_MONGO_DB', None)
if self._db is None:
raise NotConfigured('Missing BULK_MONGO_DB')
self._collection = settings.get('BULK_MONGO_COLLECTION', None)
if self._collection is None:
raise NotConfigured('Missing BULK_MONGO_COLLECTION')
crawler.signals.connect(self._closed, signal=signals.spider_closed)
def _closed(self, spider, reason, signal, sender):
logger.info("writting file %s to db %s, colleciton %s" %
(self._feed_uri, self._db, self._collection))
command = ("mongoimport --db %s --collection %s --drop --file %s" %
(self._db, self._collection, self._feed_uri))
p = subprocess.Popen(command.split())
p.communicate()
logger.info('Import done')
在tutorial/settings.py上，激活扩展程序并设置两个设置：
EXTENSIONS = {
'tutorial.extensions.MyBulkExtension': 500
}
BULK_MONGO_DB = "test"
BULK_MONGO_COLLECTION = "foobar"
然后您可以像这样运行抓取：
$ scrapy crawl -L INFO example -o foobar.jl
...
[tutorial.extensions] INFO: writting file foobar.jl to db test, colleciton foobar
connected to: 127.0.0.1
dropping: test.foobar
check 9 100
imported 100 objects
[tutorial.extensions] INFO: Import done
...