import uvicorn
from fastapi import FastAPI
from pydantic import BaseModel
from hashlib import md5


from logger import LoggerHandler
logger = LoggerHandler(name="kgupdate")
logger.set_file_handler(filename="kgupdate.log")


app = FastAPI()

global cookie, base_url, pushed


cookie = "JSESSIONID=40225388-b817-471b-8fc0-7afb72389712"
base_url = 'http://180.76.188.39:8284/'

pushed = []

eduback_dict = {
	26:'博士后', 
	24:'博士', 
	22:'MBA/EMBA', 
	20:'硕士', 
	18:'本科', 
	16:'大专', 
	14:'中专/中技', 
	12: '高中', 
	10:'初中及以下'
}

def post_json(json_obj, token="1654940290763"):
	""" 
	将json数据提交到push接口
	:param json_obj: 
	:return: 
	""" 
	global pushed
	# 是否已推送
	if json_obj['@id'] in pushed:
		return

	# 推送
	url = base_url + "data/api/access/push"

	headers = {
		"token": token,
		"Cookie": cookie
	}

	try:
		response = requests.post(url, json=json_obj, headers=headers)
		result = response.text
		logger.info(result)
	except:
		logger.error(e)
		return "ERROR: {} 数据推送 KG 失败!".format(json)
	else:
		pushed.append(json_obj['@id'])
		return



@app.post("/API/TEST")
async def trans_push(xdpost: dict):
	xdpost = xdpost['data']
	high_edu = {"schoolName": None, "major": None, "degree": None}
	org_list = []
	job_list = []
	for job in xdpost["hisJob"]:
		org_list.append(job['companyName'])
		job_list.append(job['companyName'] + job['industry'] + job['jobName'] + job['jobDesc'])
		post_json({
			"@id": md5(job['companyName'].encode(encoding="UTF-8")).hexdigest(),
			"id": md5(job['companyName'].encode(encoding="UTF-8")).hexdigest(),
			"@type": "相关机构",
			"@contentType": "struct",
			"@markdel": "0",
			"name": [{"@value": job['companyName']}]
		})
		post_json({
			"@id": md5(job['id'].encode(encoding="UTF-8")).hexdigest(),
			"id": job['id'],
			"@type": "工作经历demo",
			"name": job['companyName'] + job['industry'] + job['jobName'] + job['jobDesc'],
			"@markdel": "0",
			"@contentType": "struct",
			"时间": [{"@value": job['startTime']+job['endTime']}],
			"公司": [{"@value": job['companyName']}],
			"行业": [{"@value": job['industry']}],
			"职位": [{"@value": job['jobName']}],
			"工作内容": [{"@value": job['jobDesc']}]
		})
	edu_list = []
	for edu in xdpost["hisEdu"]:
		if (not high_edu.get("schoolName")) or (high_edu['degree'] < edu['degree']):
			high_edu['schoolName'] = edu['schoolName']
			high_edu['major'] = edu['major']
			high_edu['degree'] = edu['degree']
		org_list.append(edu['schoolName'])
		edu_list.append(edu['startTime'] + edu['schoolName'] + edu['major'] + eduback_dict[edu['degree']])
		post_json({
			"@id": md5(edu['schoolName'].encode(encoding="UTF-8")).hexdigest(),
			"id": md5(edu['schoolName'].encode(encoding="UTF-8")).hexdigest(),
			"@type": "相关机构",
			"@contentType": "struct",
			"@markdel": "0",
			"name": [{"@value": edu['schoolName']}]
		})
		post_json({
			"@id": md5(edu['id'].encode(encoding="UTF-8")).hexdigest(),
			"id": edu['id'],
			"@type": "教育经历demo",
			"name": edu['startTime'] + edu['schoolName'] + edu['major'] + eduback_dict[edu['degree']],
			"@markdel": "0",
			"@contentType": "struct",
			"时间": [{"@value": edu['startTime']+edu['endTime']}],
			"学校": [{"@value": edu['schoolName']}],
			"专业": [{"@value": edu['major']}],
			"学历": [{"@value": edu['degree']}]
		})
	pro_list = []
	for pro in xdpost["hisProject"]:
		pro_list.append(pro['companyName'] + pro['projectName'] + pro['projectOffice'] + pro['projectDuty'])
		post_json({
			"@id": md5(pro['id'].encode(encoding="UTF-8")).hexdigest(),
			"id": pro['id'],
			"@type": "项目经历demo",
			"name": pro['companyName'] + pro['projectName'] + pro['projectOffice'] + pro['projectDuty'],
			"@markdel": "0",
			"@contentType": "struct",
			"时间": [{"@value": pro['startTime']+pro['endTime']}],
			"公司": [{"@value": pro['companyName']}],
			"项目": [{"@value": pro['projectName']}],
			"职位": [{"@value": pro['projectDuty']}],
			"成果": [{"@value": pro['projectOffice']}]
		})
	tra_list = []
	json_obj = {
		"@id": md5(xdpost['tId'].encode(encoding='UTF-8')).hexdigest(),
		"id": xdpost['tId'],
		"@type": "人才特征demo",
		"name": xdpost['name'],
		"@markdel": '0',
		"@contentType": "struct",
		"姓名": [{"@value": xdpost['name']}],
		"年龄": [{"@value": xdpost['age']}],
		"性别": [{"@value": '男' if xdpost['gender'] == "0" else '女'}],
		"出生年月": [{"@value": xdpost['birthTime']}],
		"手机号码": [{"@value": xdpost['mobile']}],
		"电子邮箱": [{"@value": xdpost['email']}],
		"政治面貌": [{"@value": xdpost['politics']}],
		"参加工作时间": [{"@value": xdpost['workBeginTime']}],
		"当前职位": [{"@value": xdpost['currentJob']}],
		"意向职位": [{"@value": xdpost['intentJob']}],
		"当前年薪": [{"@value": xdpost['currentSalaryYearly']}],
		"当前所在城市": [{"@value": None}],
		"意向城市": [{"@value": None}],
		"意向年薪": [{"@value": xdpost['intentSalaryYearlyMax']}],

		"相关机构": org_list,
		"教育经历": edu_list,
		"工作经历": job_list,
		"项目经历": pro_list,
		"培训和海外经历": tra_list,
		"当前最高学历": [{"@value": eduback_dict[high_edu['degree']]}],
		"最高学历学校": [{"@value": high_edu['schoolName']}],
		"当前最高学历专业": [{"@value": high_edu['major']}],
		"语言能力": [{"@value": val['lanName']} for val in xdpost['language']],
		"技术职称": [{"@value": None}],
		"研究领域": [{"@value": val['researchName']} for val in xdpost['researchList']],
		"研究领域分类": [{"@value": val['researchName']} for val in xdpost['researchList']],

		"婚姻状况": [{"@value": None}],
		"特长爱好": [{"@value": None}],
		"人才标签": [{"@value": None}],
		"人才特点": [{"@value": None}],
		"当前行业": [{"@value": None}],
		"专业证书": [{"@value": None}],
		"入选人才": [{"@value": None}],
		"知识产权": [{"@value": None}],
		"获得荣誉及证明": [{"@value": None}],
		"备注信息": [{"@value": None}],
		"对报名岗位认识及工作设想": [{"@value": None}],
		"自我评价及主要工作业绩": [{"@value": None}],
		"当前公司": [{"@value": None}],
		"毕业院校分类": [{"@value": None}],
		"工作年限": [{"@value": None}],
		"专业方向大类": [{"@value": None}],
		"报名岗位": [{"@value": None}],
	}
	return {"errno": 0, "msg": "Success"}

if __name__ == '__main__':
	uvicorn.run(app=app, host="0.0.0.0", port=8400)