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LogParser v0.8.0 发布:一个用于定期增量式解析 Scrapy 爬虫日志的 Python 库,配合 ScrapydWeb 使用可实现爬虫进度可视化

GitHub 开源

my8100 / logparser

安装

  • 通过 pip:
pip install logparser
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  • 通过 git:
git clone https://github.com/my8100/logparser.git
cd logparser
python setup.py install
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使用方法

作为 service 运行

  1. 请先确保当前主机已经安装和启动 Scrapyd
  2. 通过命令 logparser 启动 LogParser
  3. 访问 http://127.0.0.1:6800/logs/stats.json (假设 Scrapyd 运行于端口 6800)
  4. 访问 http://127.0.0.1:6800/logs/projectname/spidername/jobid.json 以获取某个爬虫任务的日志分析详情

配合 ScrapydWeb 实现爬虫进度可视化

详见 my8100 / scrapydweb

visualization

在 Python 代码中使用

查看代码
In [1]: from logparser import parse

In [2]: log = """2018-10-23 18:28:34 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: demo)
   ...: 2018-10-23 18:29:41 [scrapy.statscollectors] INFO: Dumping Scrapy stats:
   ...: {'downloader/exception_count': 3,
   ...:  'downloader/exception_type_count/twisted.internet.error.TCPTimedOutError': 3,
   ...:  'downloader/request_bytes': 1336,
   ...:  'downloader/request_count': 7,
   ...:  'downloader/request_method_count/GET': 7,
   ...:  'downloader/response_bytes': 1669,
   ...:  'downloader/response_count': 4,
   ...:  'downloader/response_status_count/200': 2,
   ...:  'downloader/response_status_count/302': 1,
   ...:  'downloader/response_status_count/404': 1,
   ...:  'dupefilter/filtered': 1,
   ...:  'finish_reason': 'finished',
   ...:  'finish_time': datetime.datetime(2018, 10, 23, 10, 29, 41, 174719),
   ...:  'httperror/response_ignored_count': 1,
   ...:  'httperror/response_ignored_status_count/404': 1,
   ...:  'item_scraped_count': 2,
   ...:  'log_count/CRITICAL': 5,
   ...:  'log_count/DEBUG': 14,
   ...:  'log_count/ERROR': 5,
   ...:  'log_count/INFO': 75,
   ...:  'log_count/WARNING': 3,
   ...:  'offsite/domains': 1,
   ...:  'offsite/filtered': 1,
   ...:  'request_depth_max': 1,
   ...:  'response_received_count': 3,
   ...:  'retry/count': 2,
   ...:  'retry/max_reached': 1,
   ...:  'retry/reason_count/twisted.internet.error.TCPTimedOutError': 2,
   ...:  'scheduler/dequeued': 7,
   ...:  'scheduler/dequeued/memory': 7,
   ...:  'scheduler/enqueued': 7,
   ...:  'scheduler/enqueued/memory': 7,
   ...:  'start_time': datetime.datetime(2018, 10, 23, 10, 28, 35, 70938)}
   ...: 2018-10-23 18:29:42 [scrapy.core.engine] INFO: Spider closed (finished)"""

In [3]: d = parse(log, headlines=1, taillines=1)

In [4]: d
Out[4]:
OrderedDict([('head',
              '2018-10-23 18:28:34 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: demo)'),
             ('tail',
              '2018-10-23 18:29:42 [scrapy.core.engine] INFO: Spider closed (finished)'),
             ('first_log_time', '2018-10-23 18:28:34'),
             ('latest_log_time', '2018-10-23 18:29:42'),
             ('elapsed', '0:01:08'),
             ('first_log_timestamp', 1540290514),
             ('latest_log_timestamp', 1540290582),
             ('datas', []),
             ('pages', 3),
             ('items', 2),
             ('latest_matches',
              {'resuming_crawl': '',
               'latest_offsite': '',
               'latest_duplicate': '',
               'latest_crawl': '',
               'latest_scrape': '',
               'latest_item': '',
               'latest_stat': ''}),
             ('latest_crawl_timestamp', 0),
             ('latest_scrape_timestamp', 0),
             ('log_categories',
              {'critical_logs': {'count': 5, 'details': []},
               'error_logs': {'count': 5, 'details': []},
               'warning_logs': {'count': 3, 'details': []},
               'redirect_logs': {'count': 1, 'details': []},
               'retry_logs': {'count': 2, 'details': []},
               'ignore_logs': {'count': 1, 'details': []}}),
             ('shutdown_reason', 'N/A'),
             ('finish_reason', 'finished'),
             ('last_update_timestamp', 1547559048),
             ('last_update_time', '2019-01-15 21:30:48')])

In [5]: d['elapsed']
Out[5]: '0:01:08'

In [6]: d['pages']
Out[6]: 3

In [7]: d['items']
Out[7]: 2

In [8]: d['finish_reason']
Out[8]: 'finished'
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