CrawlersTools 1.4.69

Tools for Crawlers

CrawlersTools

CrawlersTools is a comprehensive tools for crawlers base on Python3.

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Install CrawlersTools using pip:

pip install CrawlersTools

CrawlersTools requires Python 3.7+.

Modules Introduction

Extraction of Policy HTML

With this module,you can extract policy html automatically.

Extraction of List HTML

Usage example:

from CrawlersTools import ListExtractor

list_extract = ListExtractor()
extract_result = list_extract.extract(html)
print(extract_result)

Outputs:

[{
    'title': '关于对迎泽区2023年乡村振兴项目储备库的公示',
    'url': '/p222/ncjbmxxgk/20221111/30003142.html'
}, {
    'title': '迎泽区2022年第四批实际种粮农民一次性补贴发放明细公示',
    'url': '/p222/ncjbmxxgk/20221027/1249082.html'
}, {
    'title': '迎泽区2022年第三批实际种粮农民一次性补贴发放明细公示',
    'url': '/p222/ncjbmxxgk/20221027/1249081.html'
}, {
    'title': '迎泽区2022年第二批实际种粮农民一次性补贴发放明细公示',
    'url': '/p222/ncjbmxxgk/20221027/1249078.html'
}, {
    'title': '迎泽区2022年第一批实际种粮农民一次性补贴发放明细公示',
    'url': '/p222/ncjbmxxgk/20221027/1249077.html'
}, ***]

Extraction of Detail HTML

Usage example:

from CrawlersTools import PolicyExtractor

detail_extract = PolicyExtractor()
detail_result = detail_extract.extract(html)
print(detail_result)

Outputs:

{
  'title': '玉溪市2018年工业经济运行工作指导意见', 
  'publish_time': '2018-03-15', 
  'content': '2017年，在作为全市工业主要支柱产业的烟草制品业增加值增速持续负增长，虽然全市非烟产业平稳高速增长，但占比小、支撑作用不明显，全市工业稳增长面临严峻困难和挑战的形势下，市委、市政府早谋划、早部署，及时出台稳增长促转型系列政策措施，工业经济运行缓中趋稳，稳中有升，结构调整和转型升级取得积极进展。全年全部工业完成增加值\n662.5\n亿元，增长\n7.1%\n，拉动\nGDP\n增长\n3.6\n个百分点，对经济增长的贡献率为\n38.1%\n，其中：规模以上工业完成增加值\n623.7\n亿元，增长\n7.2%\n。\n2018\n年是贯彻党的十九大精神的开局之年，是改革开放\n40\n周年，也是决胜全面建成小康社会、实施\n“\n十三五\n”\n规划承上启下的关键一年。当前，我国经济正处在转变发展方式、优化经济结构、转换增长动力的攻关期。十九大报告作出这样的判断：我国经济已由高速增长阶段转向高质量发展阶段。\n“\n十三五\n”\n行至一半，\n2018\n年成为承上启下的关键一年，全市工业经济运行调节要全面贯彻党的十九大精神，以习近平新时代中国特色社会主义思想为指导，牢固树立\n“\n四个意识\n”\n和\n“\n四个自信\n”\n，坚持稳中求进工作总基调，坚持新发展理念，紧扣我国社会主要矛盾变化，着眼建设现代化经济体系，立足制造强国、网络强国建设全局，以供给侧结构性改革为主线，以提高制造业供给体系质量为主攻方向，深入实施\n“\n中国制造\n2025”\n，强化创新驱动、改革推动、融合带动，推动质量变革、效率变革、动力变革，加快培育壮大新动能、改造提升传统动能，实现工业及信息化业持续健康发展。\n一、2018年工业经济运行形势研判\n（一）有利条件\n当前，玉溪工业发展正处于工业化中期的前半阶段，资本、技术等要素边际贡献率较高，工业发展空间仍然较大，支撑工业平稳较快增长的有利条件和因素不断增多。\n一是宏观经济运行企稳。\n全球经济\n“\n低增长、低通胀、低利率\n”\n态势将会有所回暖，传统产业负增长的情况会有所改变。同时，随着滇中城市经济圈和\n“\n五大基础设施网络\n”\n等一系列项目实施，国家、省、市出台的稳增长、供给侧结构性改革等系列政策效应逐步释放，经济增长的内生动力不断增强，国内经济稳中向好，全市经济稳中有进，为工业稳增长调结构提供了良好的宏观环境。\n二是面临良好发展机遇和政策环境。\n玉溪地处滇中区域，位于泛亚铁路中线和东线的交汇点，是昆曼高速的重要节点，有助于在更高、更广的平台上深化对内和对外两个开放，辐射带动滇中城市经济圈发展，开创面向南亚、东南亚开放合作的新局面。且玉溪处于多个重大国家战略的交汇点，\n“\n一带一路\n”“\n长江经济带\n”\n创造新战略空间，有望加快面向南亚东南亚辐射中心建设和沿边地区开发开放，同时在基建、能源、金融、贸易合作等方面将获得更为广阔的发展空间。市委市政府高位推进\n“\n五网\n”\n建设，加快培育七大重点产业，实施工业经济攻坚战，将助力补齐工业经济发展短板，打造工业增长新引擎。\n三是工业企业生产经营环境有所改善。\n全市大宗工业品价格稳步回升，工业通缩局面得到缓解。工业企业经营环境逐步改善，将在一定程度上改善企业市场预期，增强库存回补动力和投资意愿。创新驱动发展战略深入实施，大众创业、万众创新成为经济提质增效的新引擎。\n“\n互联网\n+”\n加快跨界融合，将极大提升实体经济的创新力和生产力，企业生产经营环境不断得到创新及改善。\n（二）不利条件\n在内外需求偏弱，周期性和结构性矛盾叠加的背景下，\n2018\n年玉溪工业经济平稳健康运行仍然面临诸多制约因素，主要表现为：\n一是结构性矛盾制约。\n全市工业结构中，\n2017\n年烟草制品业占比达\n62.68%\n，从\n2017\n年运行趋势看，烟草行业仍将面临三个不变，即国家控烟的力度不会改变、对烟草行业的政策调控不会改变、烟草行业运行环境难有较大改变，烟草行业保增长的压力仍较为突出。传统行业中，钢铁行业虽呈现恢复性增长，但受工业增加值率和价格指数影响，对全市工业增长拉动较小。新兴产业中，装备制造、生物医药和电子信息制造产业虽然增速较快，但在全市规上工业增加值中的占比仅分别为\n4.2%\n、\n1.5%\n、\n0.5%\n，占比小，拉动增长较弱，全市工业经济结构性矛盾依然突出。\n二是要素成本制约。\n近年来，资金、用工、土地等要素刚性成本和环保、物流等隐性成本不断上升，给企业生产经营造成较大压力。企业成本上升明显，工业企业融资难、融资贵矛盾仍未有效缓解，金融资本一定程度上\n“\n脱实向虚\n”\n。企业难贷款和银行贷款难\n“\n两难矛盾\n”\n以及慎贷、限贷、抽贷现象仍然不同程度存在。\n三是新增增量制约。\n由于工业企业生产经营困难、效益下滑影响，导致对未来市场的预期和信心不足。民营企业由于缺乏担保，实际资金支付率和到付率偏低，加之投资回报率下降、用地成本高、落地困难等多种因素影响，民间投资意愿下降，新增投资大幅下滑。\n四是新投产项目匮乏。\n全市新建成投产且能纳入规上统计的项目较少，尤其是缺乏大项目形成新的增量。招商优质项目不多，带动性不强，投资额度大的项目不多，跨越发展缺少大项目支撑，工业经济缺乏增量支撑。\n综上所述，\n2018\n年全市工业经济处于新旧动能转换，并将加速向纵深推进期，工业经济将在合理区间稳定运行，工业发展质量将稳步提升。但仍需要密切关注影响工业经济平衡充分发展的一些突出问题：供给体系质量与消费升级需求不匹配、新技术对传统产业的渗透融合不深入、工业领域民间投资意愿不强烈等，经济继续下行的压力和风险较大，延续低速低效运行趋势的可能性较大，完成全年工业经济发展目标任务十分艰巨，全市工信系统的广大干部职工务必高度重视，振奋精神，迎难而上，恪尽职守，竭尽全力，全面完成市委市政府下达各县区的工业经济发展目标。\n二、2018年工业经济运行总体思路和主要指标\n（一）总体思路\n全面贯彻落实十九大、中央经济工作会议、省委十届四次全会、市委五届五次全会，以及\n2018\n年全省工业和信息化工作会议精神，牢固树立\n“\n创新、协调、绿色、开放、共享\n”\n的发展新理念，坚持稳中求进工作总基调，适应新常态，谋划新思路，把稳增长作为首要任务，坚持全局视野、问题导向、创新意识、聚焦目标任务的运行调节原则，强化重点监测、准确定位、分类指导、精准施策，实现将短期需求管理与中长期供给管理相结合、从侧重需求侧向供需两侧并重逐步转变，实施重点行业挖潜、重大项目驱动、产融合作推进、达规企业培育\n“\n四大工程\n”\n，增强工业持续增长动力，促进工业经济平稳增长。\n（二）主要目标\n2018\n年非烟规上工业增加值增长\n21%\n。\n三、主要措施\n（一）压实各县区、工业园区主体责任。\n督促各县区、工业园区要扛起责任使命，压紧压实工业经济发展主体责任，扎实推进工业经济发展工作，着力营造良好的发展环境。实现责任全厘清，层层建立主体责任清单，主要领导带头，以上率下，重视工业、研究工业、推动工业发展。\n（二）提前谋划，实现高开稳走。\n提前谋划部署，科学有序部署，减少工业经济大幅波动，促进全年工业经济平稳发展。抓好节后企业复产复工，确保实现一季度工业经济\n“\n开门红\n”\n。及早部署和安排\n2018\n年工业投资重点项目，促进项目早启动、早投产、早落地，支撑全市工业经济平稳发展。\n（三）抓好成本费用调查工作。\n市工信委和市统计局联合组织对全市\n94\n户成本费用调查工业企业开展业务培训。各级工信、统计部门要深入填报企业开展业务指导，进一步提高全市规模以上工业企业成本费用调查数据质量，客观真实反映工业各行业增加值率情况。\n（四）抓好在库企业生产经营监测工作。\n一是\n组建\n10\n个帮扶督导组，对\n9\n个县区和高新区全覆盖，每月一调研一督导，继续抓好扩销促产、电力市场化交易等措施落实，强化稳增长政策落到实处，激励在库工业企业做好生产经营工作。\n二是\n加强分析预测，认真研究提出工业经济平稳发展的支撑点，以更加有力的措施确保工业经济增长态势。\n三是\n抓好重点企业稳增长工作。对全市工业经济贡献较大，占比较高的重点企业，实行面对面帮、点对点扶，保障重点企业生产经营中的各种生产要素，确保企业满负荷生产，支撑全市工业经济稳定增长。\n（五）抓好负增长企业扭负为正工作。\n以企业帮扶为手段，进一步优化发展环境。创新帮扶工作机制，切实帮助企业解决具体问题，重点排查帮扶企业存在的突出矛盾和问题，采取\n“\n一企一策\n”\n的办法，分类指导，重点帮扶，加大惠企政策落实力度，努力实现负增长企业达产增效。\n（六）创新工业企业纳规培育工作机制。\n依托全市工业企业纳规工作联席会议制度，比对筛选全市符合纳规条件工业企业，做好政策宣传，企业帮扶工作，推动全市工业企业纳规工作。'
}

Font Decryption

Font encryption is one of the common scenarios for crawlers.With this module,you can only provide font file and encrypted strings to get decrypted strings.

FreeTypeFont isn`t compatible with bytes, so you must change the source code in advance.

def load_from_bytes(f):
    if isinstance(f, bytes):    # 直接传入bytes
        self.font_bytes = f
    else:
        self.font_bytes = f.read()
    self.font = core.getfont(
        "", size, index, encoding, self.font_bytes, layout_engine
    )

if isinstance(font, bytes): # 直接传入bytes
    load_from_bytes(font)
elif isPath(font):
    ***

Usage example:

from CrawlersTools.js_crawler import FontDecrypt

str_base64_ = 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 '
font = FontDecrypt(str_base64=str_base64_)
font.decrypt('𤵼𥙌腐进𤵝防护𥪵𤹩腐蚀𧒄𥉥𥪵𥌙测试𢺔𦰤𤵢𤵩𥤣𥎧𤹩𥤣𥎧')

Outputs:

2022-01-20 17:01:47.932 | SUCCESS  | __main__:decrypt:89 - Out Decrypted Strings：中国腐进与防护学会腐蚀电化学及测试方法专业委员会委员

Database Pipelines

With this module,insert data into database is more conveniently.

MySQL Pipeline

There is no need to care the order of items when insert data.

Usage example:

from CrawlersTools import MysqlPipeline

mysql_client = MysqlPipeline(host='127.0.0.1', username='root', password='', db='project', drop_column=["id"])
item = {"name": "MuggleK", "age": "18"}
mysql_client.insert_one(item, table_name='test_table')

Outputs:

2022-11-25 11:25:18.291 | SUCCESS  | pipelines.mysql_pipeline:insert:160 - Success: Insert {"name": "MuggleK", "age": "18"} -> test_table

Http Request Base on Httpx

Usage example:

from CrawlersTools import base_requests

response = base_requests('https://example.org')
print(response)

Outputs:

<Response [200 OK]>

Dynamic Thread

This concurrent mode will create a child thread for every task below max threads and when children thread less than max threads,the main thread will create child thread for new task.

Usage example:

from CrawlersTools import AutoThread

a_thread = AutoThread(thread_num=20, fun, arg_list)
a_thread.main_thread()

Reference

Paper

• 面向不规则列表的网页数据抽取技术的研究
• 基于文本及符号密度的网页正文提取方法
• 基于块密度加权标签路径特征的Web新闻在线抽取
• 基于DOM树和视觉特征的网页信息自动抽取
• 基于行块分布函数的通用网页正文抽取算法

Project

• GeneralNewsExtractor
• GerapyAutoExtractor
• artical-spider
• html-extractor
• vthread

Contribute

If you want to contribute with CrawlersTools check out the GitHub.