topic_spider/find_source/t_channel.py

import copy

import pandas as pd

from common.databases import mongo_table
from common.tools import get_current_date
from crawler.download import Downloader, RenderDownloader
from crawler.services.channel import bfs

shujuziyuan = mongo_table('shujuziyuan', 'channel')


def is_duplicate(seed, href):
    if href != seed:
        return False
    return True


def read_local_data(file):
    data_lst = []
    browsing_history = {}
    df = pd.read_excel(io=file, sheet_name=0)
    for site, *item in df.values:
        # print(site, item)
        href = item.pop(2)
        # print(site, href, *item)

        if site not in browsing_history:
            browsing_history.setdefault(site, {})

        channel = item[1]
        if channel not in browsing_history[site]:
            channel_nums = len(browsing_history[site])
            if channel_nums == 0:
                browsing_history[site][channel] = 1
            else:
                channel_nums += 1
                browsing_history[site][channel] = channel_nums
        nums = browsing_history[site][channel]
        # print(f"{site}_{channel}", nums)
        data = (site, href, *item, nums)
        if data not in data_lst:
            data_lst.append(data)
    return data_lst


def excavate_data(tasks):
    static = Downloader()
    render = RenderDownloader()
    download_tools = [static, render]
    for site, href, *other in tasks:
        print("开始 >>> ", site, href, *other)

        # 尝试多种页面请求处理方式
        insert_lst = []
        item = {
            'site': site,  # 网站名称
            'seed': href,  # 种子地址
            'seed_spidercode': other[0],  # 种子爬虫代码
            'seed_channel': other[1],  # 种子栏目名称
            'seed_spiderstatus': other[2],  # 种子爬虫状态
            'nums': other[-1],  # 栏目的序号
            'remark': '',
        }
        for dl in download_tools:
            resp = dl.get(href, timeout=3)
            results = bfs(resp, href)
            for key, items in results.items():
                print(f"搜索 >>> {key} && {len(items)}")
                for val in items:
                    channel, url = val
                    copy_data = copy.deepcopy(item)
                    copy_data.update({
                        'channel': channel,  # 栏目地址
                        'href': url,  # 网站名称
                        'is_duplicate': is_duplicate(href, url),  # 种子与新栏目地址是否相同
                    })
                    insert_lst.append(copy_data)
            if len(results) > 0:
                break

        if len(insert_lst) > 0:
            shujuziyuan.insert_many(insert_lst)
        else:
            shujuziyuan.insert_one(item)
        print('结束 >>>\n')


def to_excel():
    date = get_current_date(fmt="%Y%m%d")
    file = f'{date}_栏目挖掘.xlsx'
    writer = pd.ExcelWriter(file)
    # q = {'channel': {'$exists': 1}, 'is_duplicate': False}
    q = {'channel': {'$exists': 1}, 'nums': 1}
    projection = {
        'site': 1,
        'seed_spidercode': 1,
        'seed': 1,
        'seed_channel': 1,
        'href': 1,
        'channel': 1,
        'seed_spiderstatus': 1,
        'remark': 1,
        '_id': 0
    }
    cursor = shujuziyuan.find(q, projection=projection)
    df = pd.DataFrame(list(cursor))
    df.columns = [
        '网站名称',
        '种子栏目地址',
        '种子爬虫代码',
        '种子栏目名称',
        '种子爬虫状态',
        '栏目名称',
        '栏目地址',
        '备注'
    ]
    df.to_excel(writer, encoding='utf-8', sheet_name='栏目挖掘(有结果)', index=False)

    q = {'channel': {'$exists': 0}}
    projection = {
        'site': 1,
        'seed_spidercode': 1,
        'seed': 1,
        'seed_channel': 1,
        'seed_spiderstatus': 1,
        'remark': 1,
        '_id': 0
    }
    cursor = shujuziyuan.find(q, projection=projection)
    df = pd.DataFrame(list(cursor))
    df.columns = [
        '网站名称',
        '种子栏目地址',
        '种子爬虫代码',
        '种子栏目名称',
        '种子爬虫状态',
    ]
    df.to_excel(writer, encoding='utf-8', sheet_name='栏目挖掘(无结果)', index=False)
    writer.save()
    print(f"{file} 录入完成")


if __name__ == '__main__':
    # crawl_tasks = read_local_data('seed.xlsx')
    # excavate_data(crawl_tasks)
    to_excel()