折腾：
【未解决】用Python实现解析excel计算业绩统计并打包成可执行文件
期间，此处接着去更新计算逻辑：
要去计算整个团队的业绩
对于这种推荐关系：
a推荐b，c，d
b推荐e，f
e推荐g，h
则
- bcdefgh各自的业绩，加起来就是a团队的业绩。
- a团队业绩=b团队+C+d=（b+e团队+f）+c+d=b+e+（g+h）+f+c+d
- e，f，g，h加起来就是b团队的业绩
- g，h的业绩加起来就是e团队的业绩
然后就在考虑：
是否要用Tree树状结构去辅助计算团队业绩
还是直接手动计算，调用循环处理
想了想，为了以后计算逻辑更清晰，还是用树吧
所以问题转换为：
【已解决】Python中如何实现Tree树结构且带辅助数据以便于后续计算
构建好树tree后，很容易就计算好了团队业绩：
由此，后续再去更新和计算 团队业绩teamSaleMoney，就很简单了：
for eachNode in gRootNode.descendants:
eachNode.teamSaleMoney = calcTeamSaleMoney(eachNode)
print("Updated team sale money: eachNode=%s" % eachNode)
for eachNode in gRootNode.descendants:
teamSaleMoneyDict[eachNode.name] = eachNode.teamSaleMoney然后调试，加了团队业绩后的效果：
# for debug updatedTeamSaleMoneyFilename = "RelationAll_%s_updatedTeamSaleMoney.json" % gCurDateStr dbgPrintTreeToJson(gRootNode, outputFilename=updatedTeamSaleMoneyFilename)
值是：
{
"children": [
{
"children": [
{
"name": "wyj121212121",
"personalSaleMoney": 431485.96540387,
"teamSaleMoney": 0
},
{
"name": "wyf333222111",
"personalSaleMoney": 23265.72892793,
"teamSaleMoney": 0
},
{
"name": "tzf123451234",
"personalSaleMoney": 93156.16512627,
"teamSaleMoney": 0
},
{
"name": "jch123123123",
"personalSaleMoney": 45692.213125,
"teamSaleMoney": 0
},
{
"name": "ha1234512345",
"personalSaleMoney": 45613.9907069,
"teamSaleMoney": 0
}
],
"name": "aaaaaaaa5522",
"personalSaleMoney": 0,
"teamSaleMoney": 639214.06328997
},
。。。
{
"children": [
{
"name": "neo12345cccc",
"personalSaleMoney": 4916.84429293,
"teamSaleMoney": 0
}
],
"name": "zz12345ccccc",
"personalSaleMoney": 1230090.8656935801,
"teamSaleMoney": 4916.84429293
}
],
"name": "fakeroot0000",
"personalSaleMoney": 0,
"teamSaleMoney": 0
}
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