最近要做一个国内外新冠疫情的热点信息的收集系统，所以，需要爬取推特上的一些数据，然后做数据分类及情绪分析。作为一名合格的程序员，我们要有「拿来主义精神」，借助别人的轮子来实现自己的项目，而不是从头搭建。
一、爬虫框架Scrapy
Scrapy 是用Python实现一个为爬取网站数据、提取结构性数据而编写的应用框架。专业的事情交给专业的框架来做，所以，本项目我们确定使用 Scrapy 框架来进行数据爬取。如果对 Scrapy 还不熟悉，可以看我之前写的这篇博文帮你快速上手，Python Scrapy爬虫框架学习 。
二、寻找开源项目
在开始一个项目之前，避免重复造轮子，所以通过关键词 「Scrapy」，「Twitter」在 GitHub上搜索是否有现成的开源项目。
通过搜索，我们发现有很多符合条件的开源项目，那么如何选择这些项目呢？有三个条件，第一是Star数，Star数多说明项目质量应该不错得到了大家的认可，第二是，更新时间，说明这个项目一直在维护，第三是，文档是否完整，通过文档我们可以快速使用这个开源项目。所以，通过以上三个条件，我们看了下排在第一个的开源项目很不错，star数颇高，最近更新时间在几个月前，而且文档很详细，因此我们就用这个项目做二次开发，项目GitHub地址：jonbakerfish/TweetScraper。
三、本地安装及调试
1、拉取项目
It requires Scrapy and PyMongo (Also install MongoDB if you want to save the data to database). Setting up:
$ git clone https://github.com/jonbakerfish/TweetScraper.git
$ cd TweetScraper/
$ pip install -r requirements.txt #add '--user' if you are not root
$ scrapy list
$ #If the output is 'TweetScraper', then you are ready to go.2、数据持久化
通过阅读文档，我们发现该项目有三种持久化数据的方式，第一种是保存在文件中，第二种是保存在Mongo中，第三种是保存在MySQL数据库中。因为我们抓取的数据需要做后期的分析，所以，需要将数据保存在MySQL中。
抓取到的数据默认是以Json格式保存在磁盘 ./Data/tweet/ 中的，所以，需要修改配置文件 TweetScraper/settings.py。
ITEM_PIPELINES = {
# 'TweetScraper.pipelines.SaveToFilePipeline':100,
#'TweetScraper.pipelines.SaveToMongoPipeline':100, # replace `SaveToFilePipeline` with this to use MongoDB
'TweetScraper.pipelines.SavetoMySQLPipeline':100, # replace `SaveToFilePipeline` with this to use MySQL
}
#settings for mysql
MYSQL_SERVER = "18.126.219.16"
MYSQL_DB = "scraper"
MYSQL_TABLE = "tweets" # the table will be created automatically
MYSQL_USER = "root" # MySQL user to use (should have INSERT access granted to the Database/Table
MYSQL_PWD = "admin123456" # MySQL user's password3、测试
进入到项目的根目录下，运行以下命令：
# 进入到项目目录
# cd /work/Code/scraper/TweetScraper
scrapy crawl TweetScraper -a query="Novel coronavirus,#COVID-19"注意，抓取Twitter的数据需要科学上网或者服务器部署在国外，我使用的是国外的服务器。
[root@cs TweetScraper]# scrapy crawl TweetScraper -a query="Novel coronavirus,#COVID-19"
2020-04-16 19:22:40 [scrapy.utils.log] INFO: Scrapy 2.0.1 started (bot: TweetScraper)
2020-04-16 19:22:40 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.1.0, parsel 1.5.2, w3lib 1.21.0, Twisted 20.3.0, Python 3.6.5 |Anaconda, Inc.| (default, Apr 29 2018, 16:14:56) - [GCC 7.2.0], pyOpenSSL 18.0.0 (OpenSSL 1.0.2o 27 Mar 2018), cryptography 2.2.2, Platform Linux-3.10.0-862.el7.x86_64-x86_64-with-centos-7.5.1804-Core
2020-04-16 19:22:40 [scrapy.crawler] INFO: Overridden settings:
{'BOT_NAME': 'TweetScraper',
'LOG_LEVEL': 'INFO',
'NEWSPIDER_MODULE': 'TweetScraper.spiders',
'SPIDER_MODULES': ['TweetScraper.spiders'],
'USER_AGENT': 'TweetScraper'}
2020-04-16 19:22:40 [scrapy.extensions.telnet] INFO: Telnet Password: 1fb55da389e595db
2020-04-16 19:22:40 [scrapy.middleware] INFO: Enabled extensions:
['scrapy.extensions.corestats.CoreStats',
'scrapy.extensions.telnet.TelnetConsole',
'scrapy.extensions.memusage.MemoryUsage',
'scrapy.extensions.logstats.LogStats']
2020-04-16 19:22:41 [scrapy.middleware] INFO: Enabled downloader middlewares:
['scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware',
'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware',
'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware',
'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware',
'scrapy.downloadermiddlewares.retry.RetryMiddleware',
'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware',
'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware',
'scrapy.downloadermiddlewares.redirect.RedirectMiddleware',
'scrapy.downloadermiddlewares.cookies.CookiesMiddleware',
'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware',
'scrapy.downloadermiddlewares.stats.DownloaderStats']
2020-04-16 19:22:41 [scrapy.middleware] INFO: Enabled spider middlewares:
['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware',
'scrapy.spidermiddlewares.offsite.OffsiteMiddleware',
'scrapy.spidermiddlewares.referer.RefererMiddleware',
'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware',
'scrapy.spidermiddlewares.depth.DepthMiddleware']
Mysql连接成功###################################### MySQLCursorBuffered: (Nothing executed yet)
2020-04-16 19:22:41 [TweetScraper.pipelines] INFO: Table 'tweets' already exists
2020-04-16 19:22:41 [scrapy.middleware] INFO: Enabled item pipelines:
['TweetScraper.pipelines.SavetoMySQLPipeline']
2020-04-16 19:22:41 [scrapy.core.engine] INFO: Spider opened
2020-04-16 19:22:41 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min)
2020-04-16 19:22:41 [scrapy.extensions.telnet] INFO: Telnet console listening on 127.0.0.1:6023
2020-04-16 19:23:45 [scrapy.extensions.logstats] INFO: Crawled 1 pages (at 1 pages/min), scraped 11 items (at 11 items/min)
2020-04-16 19:24:44 [scrapy.extensions.logstats] INFO: Crawled 2 pages (at 1 pages/min), scraped 22 items (at 11 items/min)
^C2020-04-16 19:26:27 [scrapy.crawler] INFO: Received SIGINT, shutting down gracefully. Send again to force
2020-04-16 19:26:27 [scrapy.core.engine] INFO: Closing spider (shutdown)
2020-04-16 19:26:43 [scrapy.extensions.logstats] INFO: Crawled 3 pages (at 1 pages/min), scraped 44 items (at 11 items/min)
我们可以看到，该项目运行OK，抓取到的数据也已经被保存在数据库了。
四、清洗数据
因为抓取到的Twitter上有表情等特殊符号，在插入数据库时会报错，所以，这里需要对抓取的内容信息进行清洗。
TweetScraper/utils.py 文件新增filter_emoji过滤方法
import re
def filter_emoji(desstr, restr=''):
"""
filter emoji
desstr: origin str
restr: replace str
"""
# filter emoji
try:
res = re.compile(u'[\U00010000-\U0010ffff]')
except re.error:
res = re.compile(u'[\uD800-\uDBFF][\uDC00-\uDFFF]')
return res.sub(restr, desstr)
在 TweetCrawler.py 文件中调用该方法：
from TweetScraper.utils import filter_emoji
def parse_tweet_item(self, items):
for item in items:
try:
tweet = Tweet()
tweet['usernameTweet'] = item.xpath('.//span[@class="username u-dir u-textTruncate"]/b/text()').extract()[0]
ID = item.xpath('.//@data-tweet-id').extract()
if not ID:
continue
tweet['ID'] = ID[0]
### get text content
tweet['text'] = ' '.join(
item.xpath('.//div[@class="js-tweet-text-container"]/p//text()').extract()).replace(' # ',
'#').replace(
' @ ', '@')
### clear data[20200416]
# tweet['text'] = re.sub(r"[\s+\.\!\/_,$%^*(+\"\')]+|[+——?【】？~@#￥%……&*]+|\\n+|\\r+|(\\xa0)+|(\\u3000)+|\\t", "", tweet['text']);
# 过滤掉表情符号【20200417】
tweet['text'] = filter_emoji(tweet['text'], '')
if tweet['text'] == '':
# If there is not text, we ignore the tweet
continue
### get meta data
tweet['url'] = item.xpath('.//@data-permalink-path').extract()[0]
nbr_retweet = item.css('span.ProfileTweet-action--retweet > span.ProfileTweet-actionCount').xpath(
'@data-tweet-stat-count').extract()
if nbr_retweet:
tweet['nbr_retweet'] = int(nbr_retweet[0])
else:
tweet['nbr_retweet'] = 0
nbr_favorite = item.css('span.ProfileTweet-action--favorite > span.ProfileTweet-actionCount').xpath(
'@data-tweet-stat-count').extract()
if nbr_favorite:
tweet['nbr_favorite'] = int(nbr_favorite[0])
else:
tweet['nbr_favorite'] = 0
nbr_reply = item.css('span.ProfileTweet-action--reply > span.ProfileTweet-actionCount').xpath(
'@data-tweet-stat-count').extract()
if nbr_reply:
tweet['nbr_reply'] = int(nbr_reply[0])
else:
tweet['nbr_reply'] = 0
tweet['datetime'] = datetime.fromtimestamp(int(
item.xpath('.//div[@class="stream-item-header"]/small[@class="time"]/a/span/@data-time').extract()[
0])).strftime('%Y-%m-%d %H:%M:%S')
### get photo
has_cards = item.xpath('.//@data-card-type').extract()
if has_cards and has_cards[0] == 'photo':
tweet['has_image'] = True
tweet['images'] = item.xpath('.//*/div/@data-image-url').extract()
elif has_cards:
logger.debug('Not handle "data-card-type":\n%s' % item.xpath('.').extract()[0])
### get animated_gif
has_cards = item.xpath('.//@data-card2-type').extract()
if has_cards:
if has_cards[0] == 'animated_gif':
tweet['has_video'] = True
tweet['videos'] = item.xpath('.//*/source/@video-src').extract()
elif has_cards[0] == 'player':
tweet['has_media'] = True
tweet['medias'] = item.xpath('.//*/div/@data-card-url').extract()
elif has_cards[0] == 'summary_large_image':
tweet['has_media'] = True
tweet['medias'] = item.xpath('.//*/div/@data-card-url').extract()
elif has_cards[0] == 'amplify':
tweet['has_media'] = True
tweet['medias'] = item.xpath('.//*/div/@data-card-url').extract()
elif has_cards[0] == 'summary':
tweet['has_media'] = True
tweet['medias'] = item.xpath('.//*/div/@data-card-url').extract()
elif has_cards[0] == '__entity_video':
pass # TODO
# tweet['has_media'] = True
# tweet['medias'] = item.xpath('.//*/div/@data-src').extract()
else: # there are many other types of card2 !!!!
logger.debug('Not handle "data-card2-type":\n%s' % item.xpath('.').extract()[0])
is_reply = item.xpath('.//div[@class="ReplyingToContextBelowAuthor"]').extract()
tweet['is_reply'] = is_reply != []
is_retweet = item.xpath('.//span[@class="js-retweet-text"]').extract()
tweet['is_retweet'] = is_retweet != []
tweet['user_id'] = item.xpath('.//@data-user-id').extract()[0]
yield tweet
if self.crawl_user:
### get user info
user = User()
user['ID'] = tweet['user_id']
user['name'] = item.xpath('.//@data-name').extract()[0]
user['screen_name'] = item.xpath('.//@data-screen-name').extract()[0]
user['avatar'] = \
item.xpath('.//div[@class="content"]/div[@class="stream-item-header"]/a/img/@src').extract()[0]
yield user
except:
logger.error("Error tweet:\n%s" % item.xpath('.').extract()[0])
# raise通过数据清洗，现在可以正常插入到表里了。
五、翻译成中文
我们可以看到，爬取的数据内容有多个国家的语言，如英文、日语、阿拉伯语、法语等，为了能够知道是什么意思，需要将这些文字翻译成中文，怎么翻译呢？其实很简单，GitHub上有一个开源的Python 谷歌翻译包ssut/py-googletrans ，该项目非常强大，可以自动识别语言并且翻译成我们指定的语言，我们只需安装即可使用。
1、安装
$ pip install googletrans2、使用
>>> from googletrans import Translator
>>> translator = Translator()
>>> translator.translate('안녕하세요.')
# <Translated src=ko dest=en text=Good evening. pronunciation=Good evening.>
>>> translator.translate('안녕하세요.', dest='ja')
# <Translated src=ko dest=ja text=こんにちは。 pronunciation=Kon'nichiwa.>
>>> translator.translate('veritas lux mea', src='la')
# <Translated src=la dest=en text=The truth is my light pronunciation=The truth is my light>from googletrans import Translator
destination = 'zh-CN' # 翻译为中文
t = '안녕하세요.'
res = Translator().translate(t, dest=destination).text
print(res)
你好3、引用到项目
在 TweetCrawler.py 文件中调用该方法，并且需要在数据库中新增加一个字段 text_cn。
# google translate[20200416]
# @see https://github.com/ssut/py-googletrans
from googletrans import Translator
def parse_tweet_item(self, items):
for item in items:
try:
tweet = Tweet()
tweet['usernameTweet'] = item.xpath('.//span[@class="username u-dir u-textTruncate"]/b/text()').extract()[0]
ID = item.xpath('.//@data-tweet-id').extract()
if not ID:
continue
tweet['ID'] = ID[0]
### get text content
tweet['text'] = ' '.join(
item.xpath('.//div[@class="js-tweet-text-container"]/p//text()').extract()).replace(' # ',
'#').replace(
' @ ', '@')
### clear data[20200416]
# tweet['text'] = re.sub(r"[\s+\.\!\/_,$%^*(+\"\')]+|[+——?【】？~@#￥%……&*]+|\\n+|\\r+|(\\xa0)+|(\\u3000)+|\\t", "", tweet['text']);
# 过滤掉表情符号【20200417】
tweet['text'] = filter_emoji(tweet['text'], '')
# 翻译成中文 Translate Chinese【20200417】
tweet['text_cn'] = Translator().translate(tweet['text'],'zh-CN').text;
if tweet['text'] == '':
# If there is not text, we ignore the tweet
continue
### get meta data
tweet['url'] = item.xpath('.//@data-permalink-path').extract()[0]
nbr_retweet = item.css('span.ProfileTweet-action--retweet > span.ProfileTweet-actionCount').xpath(
'@data-tweet-stat-count').extract()
if nbr_retweet:
tweet['nbr_retweet'] = int(nbr_retweet[0])
else:
tweet['nbr_retweet'] = 0
nbr_favorite = item.css('span.ProfileTweet-action--favorite > span.ProfileTweet-actionCount').xpath(
'@data-tweet-stat-count').extract()
if nbr_favorite:
tweet['nbr_favorite'] = int(nbr_favorite[0])
else:
tweet['nbr_favorite'] = 0
nbr_reply = item.css('span.ProfileTweet-action--reply > span.ProfileTweet-actionCount').xpath(
'@data-tweet-stat-count').extract()
if nbr_reply:
tweet['nbr_reply'] = int(nbr_reply[0])
else:
tweet['nbr_reply'] = 0
tweet['datetime'] = datetime.fromtimestamp(int(
item.xpath('.//div[@class="stream-item-header"]/small[@class="time"]/a/span/@data-time').extract()[
0])).strftime('%Y-%m-%d %H:%M:%S')
### get photo
has_cards = item.xpath('.//@data-card-type').extract()
if has_cards and has_cards[0] == 'photo':
tweet['has_image'] = True
tweet['images'] = item.xpath('.//*/div/@data-image-url').extract()
elif has_cards:
logger.debug('Not handle "data-card-type":\n%s' % item.xpath('.').extract()[0])
### get animated_gif
has_cards = item.xpath('.//@data-card2-type').extract()
if has_cards:
if has_cards[0] == 'animated_gif':
tweet['has_video'] = True
tweet['videos'] = item.xpath('.//*/source/@video-src').extract()
elif has_cards[0] == 'player':
tweet['has_media'] = True
tweet['medias'] = item.xpath('.//*/div/@data-card-url').extract()
elif has_cards[0] == 'summary_large_image':
tweet['has_media'] = True
tweet['medias'] = item.xpath('.//*/div/@data-card-url').extract()
elif has_cards[0] == 'amplify':
tweet['has_media'] = True
tweet['medias'] = item.xpath('.//*/div/@data-card-url').extract()
elif has_cards[0] == 'summary':
tweet['has_media'] = True
tweet['medias'] = item.xpath('.//*/div/@data-card-url').extract()
elif has_cards[0] == '__entity_video':
pass # TODO
# tweet['has_media'] = True
# tweet['medias'] = item.xpath('.//*/div/@data-src').extract()
else: # there are many other types of card2 !!!!
logger.debug('Not handle "data-card2-type":\n%s' % item.xpath('.').extract()[0])
is_reply = item.xpath('.//div[@class="ReplyingToContextBelowAuthor"]').extract()
tweet['is_reply'] = is_reply != []
is_retweet = item.xpath('.//span[@class="js-retweet-text"]').extract()
tweet['is_retweet'] = is_retweet != []
tweet['user_id'] = item.xpath('.//@data-user-id').extract()[0]
yield tweet
if self.crawl_user:
### get user info
user = User()
user['ID'] = tweet['user_id']
user['name'] = item.xpath('.//@data-name').extract()[0]
user['screen_name'] = item.xpath('.//@data-screen-name').extract()[0]
user['avatar'] = \
item.xpath('.//div[@class="content"]/div[@class="stream-item-header"]/a/img/@src').extract()[0]
yield user
except:
logger.error("Error tweet:\n%s" % item.xpath('.').extract()[0])
# raiseitems.py 中新增加字段
# -*- coding: utf-8 -*-
# Define here the models for your scraped items
from scrapy import Item, Field
class Tweet(Item):
ID = Field() # tweet id
url = Field() # tweet url
datetime = Field() # post time
text = Field() # text content
text_cn = Field() # text Chinese content (新增字段)
user_id = Field() # user id管道 piplines.py 文件中修改数据库持久化的方法，新增加text_cn字段
class SavetoMySQLPipeline(object):
''' pipeline that save data to mysql '''
def __init__(self):
# connect to mysql server
self.cnx = mysql.connector.connect(
user=SETTINGS["MYSQL_USER"],
password=SETTINGS["MYSQL_PWD"],
host=SETTINGS["MYSQL_SERVER"],
database=SETTINGS["MYSQL_DB"],
buffered=True)
self.cursor = self.cnx.cursor()
print('Mysql连接成功######################################', self.cursor)
self.table_name = SETTINGS["MYSQL_TABLE"]
create_table_query = "CREATE TABLE `" + self.table_name + "` (\
`ID` CHAR(20) NOT NULL,\
`url` VARCHAR(140) NOT NULL,\
`datetime` VARCHAR(22),\
`text` VARCHAR(280),\
`text_cn` VARCHAR(280),\
`user_id` CHAR(20) NOT NULL,\
`usernameTweet` VARCHAR(20) NOT NULL\
)"
try:
self.cursor.execute(create_table_query)
except mysql.connector.Error as err:
logger.info(err.msg)
else:
self.cnx.commit()
def find_one(self, trait, value):
select_query = "SELECT " + trait + " FROM " + self.table_name + " WHERE " + trait + " = " + value + ";"
try:
val = self.cursor.execute(select_query)
except mysql.connector.Error as err:
return False
if (val == None):
return False
else:
return True
def check_vals(self, item):
ID = item['ID']
url = item['url']
datetime = item['datetime']
text = item['text']
user_id = item['user_id']
username = item['usernameTweet']
if (ID is None):
return False
elif (user_id is None):
return False
elif (url is None):
return False
elif (text is None):
return False
elif (username is None):
return False
elif (datetime is None):
return False
else:
return True
def insert_one(self, item):
ret = self.check_vals(item)
if not ret:
return None
ID = item['ID']
user_id = item['user_id']
url = item['url']
text = item['text']
text_cn = item['text_cn']
username = item['usernameTweet']
datetime = item['datetime']
insert_query = 'INSERT INTO ' + self.table_name + ' (ID, url, datetime, text, text_cn, user_id, usernameTweet )'
insert_query += ' VALUES ( %s, %s, %s, %s, %s, %s, %s)'
insert_query += ' ON DUPLICATE KEY UPDATE'
insert_query += ' url = %s, datetime = %s, text= %s, text_cn= %s, user_id = %s, usernameTweet = %s'
try:
self.cursor.execute(insert_query, (
ID,
url,
datetime,
text,
text_cn,
user_id,
username,
url,
datetime,
text,
text_cn,
user_id,
username
))
# insert and updadte parameter,so repeat
except mysql.connector.Error as err:
logger.info(err.msg)
else:
self.cnx.commit()
def process_item(self, item, spider):
if isinstance(item, Tweet):
self.insert_one(dict(item)) # Item is inserted or updated.
logger.debug("Add tweet:%s" %item['url'])
4、再次运行
然后再次运行该命令：
scrapy crawl TweetScraper -a query="Novel coronavirus,#COVID-19"
可以看到数据库中已经将外文翻译成中文了^_^。
python
twitter
**粗体** _斜体_ [链接](http://example.com) `代码` - 列表 > 引用。你还可以使用@来通知其他用户。