How to use 如何使用¶
tinyCrawl 支持2种运行方法
函数式：定义爬虫的方法 task()，实例化
BaseCrawl(iter_url, iter_num_range, thread_num)后，调用其run方法，以task对象作为参数执行继承式：继承
BaseCrawl(iter_url, iter_num_range, thread_num)，重写crawl()和sink()方法，其中crawl()类似于上一方法中的爬虫方法task()，定义爬取单页的爬虫代码，sink()是将结果输出的方法，最后执行main()方法执行总程序
函数式¶
from tinyCrawl import BaseCrawl, RowContainer
from urllib.request import urlopen
from lxml import etree
# 定义xpath
song_name_xpath = '//div[@class="song-name"]/a/text()'
singer_xpath = '//div[@class="singers"]/a[1]/text()'
album_xpath = '//div[@class="album"]/a[1]/text()'
def task(url):
"""
定义爬取单页的爬虫代码
"""
# 定义数据存放的容器，容器名字就是最后爬取结果存放字典的self.out的key
song_name_list = RowContainer("song name")
singer_list = RowContainer("singer")
album_list = RowContainer("album")
page = urlopen(url).read().decode("utf-8", 'ignore')
parse = etree.HTML(page)
for _song_name, _singer, _album in zip(parse.xpath(song_name_xpath),
parse.xpath(singer_xpath),
parse.xpath(album_xpath)):
# 将数据append进指定容器中
song_name_list.append(str(_song_name))
singer_list.append(str(_singer))
album_list.append(str(_album))
if __name__ == '__main__':
# 第一个参数是链接地址，需通过 %s 定义页数等迭代的参数
# 第二个参数是迭代的范围，
# 第三个参数是启用的线程数，大于1就是多线程，等于1就是单线程
bc = BaseCrawl("http://example.com/?page=%s", range(1, 5), 3)
# 输入task的对象，开始执行程序
bc.run(task)
# 执行完毕后，通过out属性，获取结果
print(bc.out)
继承式¶
from tinyCrawl import BaseCrawl, RowContainer
from urllib.request import urlopen
from lxml import etree
import pandas as pd
# 需继承BaseCrawl类，覆写crawl和sink方法
class Scratch(BaseCrawl):
def __init__(self, iter_url, iter_num_range, thread_num):
super().__init__(iter_url, iter_num_range, thread_num)
# 覆写crawl方法
def crawl(self, url):
# 定义数据存放的容器，容器名字就是最后爬取结果存放字典的self.out的key
song_name_list = RowContainer("song name")
singer_list = RowContainer("singer")
album_list = RowContainer("album")
page = urlopen(url).read().decode("utf-8", 'ignore')
parse = etree.HTML(page)
for _song_name, _singer, _album in zip(parse.xpath(song_name_xpath),
parse.xpath(singer_xpath),
parse.xpath(album_xpath)):
# 将数据append进指定容器中
song_name_list.append(str(_song_name))
singer_list.append(str(_singer))
album_list.append(str(_album))
# 覆写sink方法，将爬取的结果输出
def sink(self):
# self.out是字典结构的结果，可以直接输入pandas存为dataframe
recent_music = pd.DataFrame(self.out)
recent_music.to_csv("D:/tmptest.csv", index=0)
if __name__ == '__main__':
mc = Scratch("http://example.com/?page=%s", range(1, 5), 3)
# 调用main函数执行程序
mc.main()
output:
2021-01-10 16:18:36,944 - base.py - __init__ - [line:30] - INFO: Checkpoint path: D:\breakpoint_page.txt
2021-01-10 16:18:38,539 - base.py - __source - [line:119] - INFO: Now is running on multithread mode, total thread num is `3`
2021-01-10 16:18:38,539 - base.py - __source - [line:126] - INFO: Total iteration num: 4
2021-01-10 16:18:38,541 - base.py - _multi_thread_wrap - [line:59] - INFO: ThreadPoolExecutor-1_0 now is processing: http://example.com/?page=1
2021-01-10 16:18:38,541 - base.py - _multi_thread_wrap - [line:59] - INFO: ThreadPoolExecutor-1_1 now is processing: http://example.com/?page=2
2021-01-10 16:18:38,542 - base.py - _multi_thread_wrap - [line:59] - INFO: ThreadPoolExecutor-1_2 now is processing: http://example.com/?page=3
2021-01-10 16:18:41,544 - base.py - __task_done - [line:115] - INFO: ThreadPoolExecutor-1_1 task finished; (Time took: 3.0009s)
2021-01-10 16:18:41,544 - base.py - __task_done - [line:115] - INFO: ThreadPoolExecutor-1_0 task finished; (Time took: 3.0019s)
2021-01-10 16:18:41,544 - base.py - __task_done - [line:115] - INFO: ThreadPoolExecutor-1_2 task finished; (Time took: 3.0009s)
2021-01-10 16:18:41,545 - base.py - _multi_thread_wrap - [line:59] - INFO: ThreadPoolExecutor-1_1 now is processing: http://example.com/?page=4
2021-01-10 16:18:44,551 - base.py - __task_done - [line:115] - INFO: ThreadPoolExecutor-1_1 task finished; (Time took: 3.0022s)
2021-01-10 16:18:44,551 - base.py - __source - [line:151] - INFO: All done. (Time took: 6.0102s)