# -*- coding: utf-8 -*-
"""
Created on 2023-04-05
---------
@summary:  爬虫监控数据汇总
---------
@author: dzr
"""
import hashlib
from datetime import datetime, time, timedelta

from bson.int64 import Int64
from bson.son import SON
from pymongo import MongoClient

from log import logger
from operator import itemgetter

# mongo
# MONGO_HOST = "172.17.4.87"
# MONGO_PORT = 27080

MONGO_HOST = "127.0.0.1"
MONGO_PORT = 27001
client = MongoClient(MONGO_HOST, MONGO_PORT)

MONGO_DB1 = "py_spider"
MONGO_DB2 = "editor"

mongodb1 = client[MONGO_DB1]
mongodb2 = client[MONGO_DB2]

# 爬虫数据表
data_bak = mongodb1["data_bak"]

# 心跳表
spider_heartbeat = mongodb1["spider_heartbeat"]

# py_spiders列表
py_spiders_crawl_list = mongodb1["crawl_data"]

# 列表页汇总表
spider_monitor = mongodb1["spider_monitor"]

# luaconfig表
spider_lua_config = mongodb2["luaconfig"]

# 特殊网站
special_sites = ["云南省政府采购网", "湖南省政府采购电子卖场"]


def get_md5(*args, **kwargs):
    """
    @summary: 获取唯一的32位md5
    ---------
    @param args: 参与联合去重的值数组
    @param kwargs: 参与联合去重的值字典
    ---------
    @result: 7c8684bcbdfcea6697650aa53d7b1405
    """
    conditions = ["site", "channel", "spidercode"]
    data_lst = list(filter(lambda x: x is not None, args))
    for k, v in kwargs.items():
        if k in conditions and (v and v not in data_lst):
            data_lst.append(v)

    if not data_lst or len(data_lst) != 3:
        # raise AttributeError(f"缺少{conditions}属性")
        logger.error(f"[Monitor]缺少{conditions}属性,内容:{data_lst}")
        return None

    data_lst = sorted(data_lst)
    content = "_".join(data_lst)
    return hashlib.md5(str(content).encode()).hexdigest()


def get_runtime(datestr=None):
    if datestr is None:
        today = datetime.now().date()
        yesterday = today + timedelta(days=-1)
        datestr = yesterday.strftime("%Y-%m-%d")
    return datestr


def save(documents, collection):
    """保存数据"""

    is_list = isinstance(documents, list)
    documents = documents if is_list else [documents]

    count = 0
    data_lst = []
    for items in documents:
        items.pop("_id", None)
        items.pop("business_type", None)
        items["comeintime"] = Int64(datetime.now().timestamp())
        data_lst.append(items)
        count += 1
        if len(data_lst) % 100 == 0:
            collection.insert_many(data_lst)
            data_lst.clear()
            logger.info(f"[Monitor]{collection.name}-批量上传{count}条数据--已保存")

    # 提交剩余数据
    collection.insert_many(data_lst)
    logger.info(f"[Monitor]{collection.name}-批量上传{count}条数据--已保存")


def get_crawler_basic_information():
    """爬虫基础信息"""
    crawler_lst = []
    q = {"platform": "python", "state": 11}
    projection = {
        "_id": 0, "site": 1, "channel": 1,
        "modifyuser": 1, "modifyuserid": 1, "code": 1, "event": 1
    }
    cursor = spider_lua_config.find(q, projection=projection)
    try:
        for doc in cursor:
            crawler_lst.append({
                "site": doc["site"],
                "channel": doc["channel"],
                "spidercode": doc["code"],
                "modifyid": doc["modifyuserid"],
                "modifyuser": doc["modifyuser"],
                "event": doc["event"]
            })
    finally:
        client.close()
        logger.info(f"[Monitor]爬虫采集监控--共计{len(crawler_lst)}个爬虫")
        yield from crawler_lst


def aggregate_query(collection, pipeline, is_print_error=False):
    """
    聚合查询

    @param collection: MongoDB集合
    @param pipeline: 聚合查询条件
    @param is_print_error: 是否在console打印错误日志
    @return: 聚合结果
    """
    results = []
    cursor = collection.aggregate(pipeline, allowDiskUse=True)
    try:
        for doc in cursor:
            results.append(doc)
    except Exception as e:
        if is_print_error:
            logger.exception(e)
    finally:
        client.close()
        yield from results


def aggregate_query_crawl_count(runtime):
    """
    feapder爬虫列表和详情采集聚合查询结果统计

    @param runtime: 运行时间
    @return:
    """
    aggregate_items = {}
    pipeline = [
        {"$match": {"runtime": runtime}},
        {
            "$group": {
                "_id": "$spider_id",
                "rel_count": {"$sum": "$rel_count"},  # 入库量
                "count": {"$sum": "$count"},  # 下载量
                "spider_item": {
                    "$addToSet": {
                        "site": "$site",
                        "channel": "$channel",
                        "spidercode": "$spidercode",
                        "business_type": "$business_type"
                    }
                }
            }
        },
        {"$sort": SON([("rel_count", -1)])}
    ]
    results = aggregate_query(spider_heartbeat, pipeline)
    for doc in results:
        spider_item = doc["spider_item"]
        label_dict = {}
        for items in spider_item:
            site = items["site"]
            channel = items["channel"]
            spidercode = items["spidercode"]
            business_type = items["business_type"]

            if len(spider_item) > 1 and site not in special_sites:
                logger.warning(f"[Monitor]{spidercode} -> {site}--存在风险, {len(spider_item)}")

            is_list = str(business_type).endswith("List")

            hash_key = get_md5(**items)  # 防止多站点对应1个spidercode,数据相互重叠
            if not hash_key:
                # logger.error(f"[Monitor]{site}-{channel}-{spidercode}--监控异常")
                logger.error(f"[Monitor]{doc['_id']}--爬虫异常")
                continue

            if not aggregate_items.get(hash_key):
                data = {
                    "spider_id": doc["_id"],
                    "site": site,
                    "channel": items["channel"],
                    "spidercode": spidercode,
                    "business_type": business_type,
                    "runtime": runtime,
                    "spidercode_at_site_num": 0  # 爬虫代码与站点对应的关系数量
                }
                if is_list:
                    data["list_count"] = doc["count"]
                    data["list_rel_count"] = doc["rel_count"]
                    data["list_runtimes"] = 1
                    data["detail_count"] = 0
                    data["detail_rel_count"] = 0
                    data["detail_runtimes"] = 0
                else:
                    data["detail_count"] = doc["count"]
                    data["detail_rel_count"] = doc["rel_count"]
                    data["detail_runtimes"] = 1
                    data["list_count"] = 0
                    data["list_rel_count"] = 0
                    data["list_runtimes"] = 0

                aggregate_items.setdefault(hash_key, data)
            else:
                data = aggregate_items.get(hash_key)
                if is_list:
                    data["list_count"] += doc["count"]
                    data["list_rel_count"] += doc["rel_count"]
                    data["list_runtimes"] += 1
                else:
                    data["detail_count"] += doc["count"]
                    data["detail_rel_count"] += doc["rel_count"]
                    data["detail_runtimes"] += 1

                aggregate_items.update({hash_key: data})

            # 监控爬虫任务，当 spidercode_at_site_num > 1
            # 表明创建的爬虫任务存在问题，问题反馈数据寻源人员
            if site not in special_sites:
                label = f"{business_type}_{spidercode}"
                if label not in label_dict:
                    aggregate_items[hash_key]["spidercode_at_site_num"] = 1
                    conditions = {"keys": [hash_key], "websites": [site]}
                    label_dict.setdefault(label, conditions)
                else:
                    # 相同spidercode但site不同的爬虫进行计数+1
                    websites = label_dict[label]["websites"]
                    if site not in websites:
                        keys = label_dict[label]["keys"]
                        for key in keys:
                            aggregate_items[key]["spidercode_at_site_num"] += 1
                        # 记录身份id - hash_key
                        keys.append(hash_key)
                        # 记录站点
                        websites.append(site)
                        aggregate_items[hash_key]["spidercode_at_site_num"] = len(websites)

    return aggregate_items


def aggregate_query_crawl_list(runtime):
    """feapder列表爬虫采集聚合查询结果统计"""
    aggregate_items = {}
    pipeline = [
        {"$match": {"runtime": runtime, "business_type": {"$regex": "List"}}},
        {
            "$group": {
                "_id": "$spider_id",
                "spider_item": {
                    "$addToSet": {
                        "site": "$site",
                        "channel": "$channel",
                        "spidercode": "$spidercode",
                        "count": {"$ifNull": ["$count", 0]},
                        "rel_count": {"$ifNull": ["$rel_count", 0]},
                    }
                }
            }
        }
    ]
    results = aggregate_query(spider_heartbeat, pipeline)
    for doc in results:
        spider_item = doc["spider_item"]
        for item in spider_item:
            hask_key = get_md5(**item)
            if not aggregate_items.get(hask_key):
                if all([
                    item["count"] > 0,
                    item["rel_count"] > 0,
                    item["count"] == item["rel_count"]
                ]):
                    aggregate_items.setdefault(hask_key, {"list_allintimes": 1})
            else:
                aggregate_items.get(hask_key)["list_allintimes"] += 1
    return aggregate_items


def aggregate_query_crawlab_info(runtime):
    """feapder爬虫采集聚合查询crawlab平台运行信息统计"""
    aggregate_items = {}
    pipeline = [
        {
            "$project": {
                "_id": 0,
                "spider_id": 1,
                "spidercode": 1,
                "runtime": 1,
                "node_ip": 1,
                "crawlab_taskid": 1,
                "create_at": 1,
            }
        },
        {"$match": {"runtime": runtime}},
        {
            "$group": {
                "_id": "$spider_id",
                "crawlab_item": {
                    "$addToSet": {
                        "spidercode": "$spidercode",
                        "create_at": "$create_at",
                        "node_ip": "$node_ip",
                        "crawlab_taskid": "$crawlab_taskid"
                    },
                }
            }
        }
    ]
    results = aggregate_query(spider_heartbeat, pipeline)
    for doc in results:
        crawlab_item = sorted(doc["crawlab_item"], key=itemgetter("create_at"), reverse=True)
        items: dict = crawlab_item[0]
        spidercode = items.pop("spidercode")
        if not aggregate_items.get(spidercode):
            aggregate_items.setdefault(spidercode, items)
    return aggregate_items


_runtime = get_runtime()
aggregate_results = aggregate_query_crawl_count(_runtime)
aggregate_list_results = aggregate_query_crawl_list(_runtime)
aggregate_query_crawlab_results = aggregate_query_crawlab_info(_runtime)


def get_node_and_taskid(spidercode, default=None):
    """获取最新爬虫工作节点和任务id"""
    if aggregate_query_crawlab_results.get(spidercode):
        default = aggregate_query_crawlab_results[spidercode]
    return default


def get_list_isgetdata(hash_key, default=0):
    """列表页是否采集数据"""
    if aggregate_results.get(hash_key):
        default = aggregate_results[hash_key]["list_count"]
    return True if default > 0 else False


def get_list_allintimes(hash_key, default=0):
    """日采集列表数量与入库数量相等的次数（扣除标题去重数量 + 增量（全量）去重数量）"""
    if aggregate_list_results.get(hash_key):
        default = aggregate_list_results[hash_key]["list_allintimes"]
    return default


def get_list_runtimes(hash_key, default=0):
    """列表采集运行频次"""
    if aggregate_results.get(hash_key):
        default = aggregate_results[hash_key]["list_runtimes"]
    return default


def get_detail_downloadnum(hash_key, default=0):
    """详情页下载量"""
    if aggregate_results.get(hash_key):
        default = aggregate_results[hash_key]["detail_count"]
    return default


def get_detail_downloadsuccessnum(hash_key, default=0):
    """详情页下载成功量"""
    if aggregate_results.get(hash_key):
        default = aggregate_results[hash_key]["detail_rel_count"]
    return default


def get_detail_downloadfailnum(**kwargs):
    """详情页下载失败量"""
    count = -1
    if kwargs["detail_downloadnum"] >= 0 and kwargs["detail_downloadnum"] >= 0:
        count = kwargs["detail_downloadnum"] - kwargs["detail_downloadsuccessnum"]
    return count


def main():
    summary_queue = []
    crawlers = get_crawler_basic_information()
    for crawler in crawlers:
        site = crawler["site"]
        channel = crawler["channel"]
        spidercode = crawler["spidercode"]

        join_data = {**crawler}  # 添加爬虫基础数据
        hash_key = get_md5(site, channel, spidercode)
        if aggregate_results.get(hash_key):
            # crawlab平台
            crawlab = get_node_and_taskid(spidercode)
            if crawlab:
                join_data["py_taskid"] = crawlab["crawlab_taskid"]
                join_data["py_nodename"] = crawlab["node_ip"]

            # 聚合查询心跳统计结果
            result = aggregate_results[hash_key]
            join_data["spider_id"] = result["spider_id"]
            join_data["business_type"] = result["business_type"]
            join_data["spidercode_at_site_num"] = result["spidercode_at_site_num"]
            join_data["list_count"] = result["list_count"]
            join_data["list_rel_count"] = result["list_rel_count"]
            join_data["detail_count"] = result["detail_count"]
            join_data["detail_rel_count"] = result["detail_rel_count"]

        # 列表采集汇总数据
        join_data["list_isgetdata"] = get_list_isgetdata(hash_key)
        join_data["list_allintimes"] = get_list_allintimes(hash_key)
        join_data["list_runtimes"] = get_list_runtimes(hash_key)
        # 详情采集汇总数据
        join_data["detail_downloadnum"] = get_detail_downloadnum(hash_key)
        join_data["detail_downloadsuccessnum"] = get_detail_downloadsuccessnum(hash_key)
        join_data["detail_downloadfailnum"] = get_detail_downloadfailnum(**join_data)
        summary_queue.append(join_data)
        logger.info(f"[Monitor]{crawler['site']}-{crawler['channel']}-{spidercode}--完成统计")
    # 上传数据库
    save(summary_queue, spider_monitor)


if __name__ == '__main__':
    main()