#coding=utf-8
'''
Created on 2017年11月14日

@author: bailiangjun
'''
def change_dict_p2m(item,p2m,ms=[],ems=[]):
    """
    @attention: 把指定信息的关键字换成对应的模型字段m
    @param item: 默认为 {p:值}
    @note: 
    {p:值} ==> {m:值}
    如果传入指定序列ps,则只取序列中的值
    如果传入指定序列eps,则取除eps以外的值
    """
    if not item:
        return {}
    
    if not ms:
        ms = set(p2m.itervalues())
    temp = {p:m for p,m in p2m.iteritems() if (m in ms) and (m not in ems)}
    return {m:item.get(p,"") for p,m in temp.iteritems()}

def change_dict_m2p(item,p2m,ms=[],ems=[]):
    """
    @attention: 把指定信息的关键字换成对应的api协议字段
    @param item: 默认为 {m:值}
    @note: 
    {m:值} ==> {p:值}
    如果传入指定序列ps,则只取序列中的值
    如果传入指定序列eps,则取除eps以外的值
    """
    if not item:
        return {}
    
    if not ms:
        ms = set(p2m.itervalues())
    
    temp = {p:m for p,m in p2m.iteritems() if (m in ms) and (m not in ems)}
    return {p:item.get(m,"") for p,m in temp.iteritems()}


def change_list_p2m(item,p2m,ms=[],ems=[]):
    """
    @attention: 把指定信息的关键字换成对应的模型字段m,针对列表
    @param item: 默认为 {p:值}
    @note: 
    {p:值} ==> {m:值}
    如果传入指定序列ps,则只取序列中的值
    如果传入指定序列eps,则取除eps以外的值
    """
    if not item:
        return []
    
    if not ms:
        ms = set(p2m.itervalues())
    
    temp = {p:m for p,m in p2m.iteritems() if (m in ms) and (m not in ems)}

    return map(lambda x:{m:x.get(p,"") for p,m in temp.iteritems()}, item)


def change_list_m2p(item,p2m,ms=[],ems=[]):
    """
    @attention: 把指定信息的关键字换成对应的api协议字段,针对列表
    @param item: 默认为 {m:值}
    @note: 
    {m:值} ==> {p:值}
    如果传入指定序列ps,则只取序列中的值
    如果传入指定序列eps,则取除eps以外的值
    """
    if not item:
        return []
    
    if not ms:
        ms = set(p2m.itervalues())
    
    temp = {p:m for p,m in p2m.iteritems() if (m in ms) and (m not in ems)}
    return map(lambda x:{p:x.get(m,"") for p,m in temp.iteritems()}, item)


def change_node_m2p(item, p2m, ms=[], ems=[]):
    """
    @attention: 把指定信息的关键字换成对应的api协议字段,针对列表
    @param item: 默认为 {m:值}
    @note:
    {m:值} ==> {p:值}
    如果传入指定序列ps,则只取序列中的值
    如果传入指定序列eps,则取除eps以外的值
    """
    if not item:
        return []

    if not ms:
        ms = set(p2m.itervalues())

    temp = {p: m for p, m in p2m.iteritems() if (m in ms) and (m not in ems)}
    return map(lambda x: {p: x.get(m, "") for p, m in temp.iteritems()}, item)


def transfer_top_info(info, lkey, tkey):
    """
    @attention: 转换top数据给前端
    @note:
            由 二维数组[[标签,值],[]]---> [{label:标签,"times":值}]
    """
    return [{"name": item[lkey], "value": item[tkey]} for item in info]


def transfer_list_info(info, params):
    """
    @attention: 转换趋势数据给前端
    """
    if not info:
        return {"axis_x": [], "axis_y": {}}

    if isinstance(params, list):
        params = {item: [item] for item in params}

    print params

    pkeys = params.keys()
    if len(pkeys) == 1:
        key = pkeys[0]
        inkeys = params[key]
        inkeys = inkeys if inkeys else [key]
        v = info[key]
        axis_x = [item["dt"] for item in v]
        axis_y = {}
        for ik in inkeys:
            axis_y[ik] = [item[ik] for item in v]
    else:
        axis_y = {}
        for key in pkeys:
            inkeys = params[key]
            inkeys = inkeys if inkeys else [key]
            v = info[key]
            axis_x = [item["dt"] for item in v]
            for ik in inkeys:
                axis_y[ik] = [item[ik] for item in v]

    return {"axis_x": axis_x, "axis_y": axis_y}


def classify_access_statistic_info(info):
    """
    @attention: 区分access统计数据项
    """
    total_values = []
    list_values = []
    top_values = {}
    if info.has_key("total_hit_flow"):
        total_values.append("hit_flow")

    if info.has_key("total_hit_num"):
        total_values.append("hit_total")

    if info.has_key("total_req_flow"):
        total_values.append("req_flow")

    if info.has_key("total_req_num"):
        total_values.append("req_total")

    if info.has_key("tendency_pv"):
        list_values.append("pageview")

    if info.has_key("tendency_quote"):
        list_values.append("search")

    if info.has_key("tendency_req_flow"):
        list_values.append("req_flow")
        list_values.append("hit_flow")

    if info.has_key("tendency_req_num"):
        list_values.append("req_total")
        list_values.append("hit_total")

    if info.has_key("tendency_ip"):
        list_values.append("ip_num")

    if info.get("top_location"):
        top_values["location"] = int(info["top_location"])
    if info.get("top_location_flow"):
        top_values["location"] = int(info["top_location_flow"])

    return total_values, list_values, top_values


def classify_waf_statistic_info(info):
    """
    @attention: 区分waf统计数据项
    """
    total_values = []
    list_values = []
    top_values = {}
    if info.has_key("level"):
        total_values.append("level")

    if info.has_key("total_cc") or info.has_key("total_web"):
        total_values.append("att_num")

    if info.has_key("total_ip"):
        total_values.append("ip_num")

    if info.has_key("tendency_attack"):
        list_values.append("att_num")

    if info.get("top_ip"):
        top_values["src_ip"] = int(info["top_ip"])

    if info.get("top_location"):
        top_values["location"] = int(info["top_location"])

    if info.get("top_type"):
        top_values["rule"] = int(info["top_type"])

    if info.get("top_site"):
        top_values["domain"] = int(info["top_site"])

    return total_values, list_values, top_values


def dict_unicode2str(**params):
    item = {}
    for k in params:
        item[str(k)] = str(params[k])
    return str(item)