719 lines
34 KiB
Python
719 lines
34 KiB
Python
import requests
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import random
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import json
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import time
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import ipaddress
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from builtins import list
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# Report纯接口测试正向用例方法，不验证数据统计准确性，单纯验证接口
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#生成随机ipv4或ipv6
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MAX_IPV4 = ipaddress.IPv4Address._ALL_ONES # 2 ** 32 - 1
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MAX_IPV6 = ipaddress.IPv6Address._ALL_ONES # 2 ** 128 - 1
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def random_ipv4():
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return ipaddress.IPv4Address._string_from_ip_int(
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random.randint(0, MAX_IPV4))
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def random_ipv6():
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return ipaddress.IPv6Address._string_from_ip_int(
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random.randint(0, MAX_IPV6))
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#随机生成邮箱地址
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def RandomEmail( emailType=None, rang=None):
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__emailtype = ["@qq.com", "@163.com", "@126.com", "@189.com"]
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# 如果没有指定邮箱类型，默认在 __emailtype中随机一个
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if emailType == None:
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__randomEmail = random.choice(__emailtype)
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else:
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__randomEmail = emailType
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# 如果没有指定邮箱长度，默认在4-10之间随机
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if rang == None:
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__rang = random.randint(4, 10)
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else:
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__rang = int(rang)
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__Number = "0123456789qbcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPWRSTUVWXYZ"
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__randomNumber = "".join(random.choice(__Number) for i in range(__rang))
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_email = __randomNumber + __randomEmail
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return _email
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#获取Schema
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def schema(schemauerl,token,logtype):
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url ="http://192.168.44.72:8080/v1/log/schema?logType="+logtype
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headers = {"Content-Type":"application/x-www-form-urlencoded","Authorization":token}
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response = requests.get(url=url,headers=headers)
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return response.json()
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#获取json串中groupColumnList的值
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def groupby(schemajson,logtype,testpoint,field):
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dimensions=schemajson["data"]["doc"]["schema_query"]["dimensions"]
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dimensions.append("common_recv_time");
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randomstr_1=[]
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if logtype == "security_event_log" or logtype == "connection_record_log" or logtype == "voip_record_log":
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dimensions.remove("common_start_time")
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dimensions.remove("common_end_time")
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if testpoint == "DataBindings":
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randomstr_1.append("common_recv_time")
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elif testpoint == "GroupBy":
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randomstr_1.append(field)
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else:
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randomstr_1=random.sample(dimensions, 4)
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#定义grp为返回值group的列表
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grp=[]
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for i in randomstr_1:
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a={"name":i}
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grp.append(a)
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re=[grp,randomstr_1]
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print("groupby",re)
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return re
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#获取json串中queryColumnList的值
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def DataBindings(schemajson,randomstr_1,testpoint,field):
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#生成queryColumnList列表
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metrics=schemajson["data"]["doc"]["schema_query"]["metrics"]
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metrics.append("common_log_id")
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#在列表里随机元素
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randomstr_2=[]
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if testpoint == "DataBindings":
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randomstr_2.append(field)
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else:
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randomstr_2=random.sample(metrics,6)
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#在聚合列表中去掉groupby中的重复的元素
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randomstr_3=array_diff(randomstr_2,randomstr_1)
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#将groupby中元素添加到串中
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qul=[]
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for i in randomstr_1:
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a={"name":i}
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qul.append(a)
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fields = schemajson["data"]["fields"]
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list_1=["sum","min","max","avg","count"]
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list_2=["count","count_distinct"]
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if testpoint == "DataBindings":
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for i in randomstr_3:
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for j in fields:
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if i == j["name"] :
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jtype=j["type"]
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label=i
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sun=1
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if jtype == "int" or jtype == "long" or jtype == "float" or jtype == "double":
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for Aggregate in list_1:
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randomstr_4={"name":i,"expression":Aggregate,"label":label}
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qul.append(randomstr_4)
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label=label+str(sun)
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sun+=1
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elif jtype == "randomstring" or jtype == "date" or jtype == "timestamp" or jtype == "string":
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for Aggregate in list_2:
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randomstr_4={"name":i,"expression":Aggregate,"label":label}
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qul.append(randomstr_4)
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label = label + str(sun)
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sun += 1
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else:
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for i in randomstr_3:
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for j in fields:
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if i == j["name"]:
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jtype = j["type"]
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if jtype == "int" or jtype == "long" or jtype == "float" or jtype == "double":
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radomlist = random.sample(list_1, 1)
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randomstr_4 = {"name": i, "expression": radomlist[0]}
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qul.append(randomstr_4)
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elif jtype == "randomstring" or jtype == "date" or jtype == "timestamp" or jtype == "string":
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randomlist = random.sample(list_2, 1)
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randomstr_4 = {"name": i, "expression": randomlist[0]}
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qul.append(randomstr_4)
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print("DataBindings",qul)
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return qul
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# #去除a列表中存在的b的元素
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def array_diff(a, b):
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#定义空列表
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c=[]
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#range(len(a))取的为列表a的索引，根据a的
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for i in range(len(a)):
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#取出索引对应的值
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t=a[i]
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#判断值是否存在在序列b中
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if t not in b:
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#如果序列不在b中，则写入序列c
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c.append(t)
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#返回序列c，c就是列表a去除列表b之后的元素
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return c
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def filterCondition(schemajson,testpoint,field):
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number = random.randint(0,100000)
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randomstr= random.choice('abcdefghijklmnopqrstuvwxyz')
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schemafilters=schemajson["data"]["doc"]["schema_query"]["filters"]
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list1=[]
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if testpoint=="Filter":
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list1.append(field)
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else:
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list1=random.sample(schemafilters, 4)
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#获取不同属性支持的部不同操作
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fields = schemajson["data"]["fields"]
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operator = schemajson["data"]["doc"]["schema_query"]["references"]["operator"]
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andConditions=[]
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for i in list1:
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#遍历fields列表
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for k in fields:
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#当filters列表值等于fields的name时
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if i == k["name"]:
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name = k["name"]
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doc = k["doc"]
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#获取无任何特殊说明列：
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if doc == None:
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type1 = k["type"]
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if type1 == "int" or type1 == "long":
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orConditions_list=[]
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Operator=["=","!=",">","<",">=","<="]
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if testpoint=="Filter":
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for op in Operator:
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value=[str(number)]
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Field={"name":name,"expression":op,"value":value,"type":type1}
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orConditions_list.append(Field)
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else:
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randomOperator= random.sample(Operator, 1)
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value=[str(number)]
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Field={"name":name,"expression":randomOperator[0],"value":value,"type":type1}
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orConditions_list.append(Field)
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orConditions={"orConditions":orConditions_list}
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andConditions.append(orConditions)
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elif type1 == "string":
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orConditions_list=[]
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Operator=["=","!=","Like","Not Like","notEmpty","empty"]
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if testpoint=="Filter":
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for op in Operator:
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value=[]
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if op == "=" or op == "!=":
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value.append(str(number))
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elif op == "Like" or op == "Not Like":
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value.append(randomstr)
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elif op=="notEmpty" or op == "empty":
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value=[]
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Field={"name":name,"expression":op,"value":value,"type":type1}
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orConditions_list.append(Field)
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else:
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randomOperator_1 = random.sample(Operator, 1)
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randomOperator = randomOperator_1[0]
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value = []
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if randomOperator == "=" or randomOperator == "!=":
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value.append(str(number))
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elif randomOperator == "Like" or randomOperator == "Not Like":
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value.append(randomstr)
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elif randomOperator == "notEmpty":
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value = []
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Field = {"name": name, "expression": randomOperator, "value": value, "type": type1}
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orConditions_list.append(Field)
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orConditions = {"orConditions": orConditions_list}
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andConditions.append(orConditions)
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else:
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if k["doc"]["constraints"]== None:
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type1 = k["type"]
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if type1 == "int" or type1 == "long":
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orConditions_list=[]
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Operator=["=","!=",">","<",">=","<="]
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if testpoint == "Filter":
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for op in Operator:
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value=[str(number)]
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Field={"name":name,"expression":op,"value":value,"type":type1}
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orConditions_list.append(Field)
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else:
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randomOperator= random.sample(Operator, 1)
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value=[str(number)]
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Field={"name":name,"expression":randomOperator[0],"value":value,"type":type1}
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orConditions_list.append(Field)
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orConditions={"orConditions":orConditions_list}
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andConditions.append(orConditions)
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elif type1 == "string":
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orConditions_list=[]
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Operator=["=","!=","Like","Not Like","notEmpty","empty"]
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if testpoint == "Filter":
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for op in Operator:
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randomOperator = op
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value = []
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if randomOperator == "=" or randomOperator == "!=":
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value.append(str(number))
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elif randomOperator == "Like" or randomOperator == "Not Like":
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value.append(randomstr)
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elif randomOperator == "notEmpty":
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value = []
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Field = {"name": name, "expression": randomOperator, "value": value, "type": type1}
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orConditions_list.append(Field)
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else:
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randomOperator_1= random.sample(Operator, 1)
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randomOperator=randomOperator_1[0]
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value=[]
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if randomOperator == "=" or randomOperator == "!=":
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value.append(str(number))
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elif randomOperator == "Like" or randomOperator == "Not Like":
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value.append(randomstr)
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elif randomOperator=="notEmpty":
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value=[]
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Field={"name":name,"expression":randomOperator,"value":value,"type":type1}
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orConditions_list.append(Field)
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orConditions={"orConditions":orConditions_list}
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andConditions.append(orConditions)
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else:
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if k["doc"]["constraints"]["operator_functions"]==None:
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conrandomstraints=k["doc"]["constraints"]
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type1 = k["type"]
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if type1 == "int" or type1 == "long":
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orConditions_list = []
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Operator=["=","!=",">","<",">=","<="]
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if testpoint == "Filter":
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for op in Operator:
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randomOperator = op
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if conrandomstraints["type"] == "timestamp":
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# 获取当前时间戳
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t = int(time.time())
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value = [str(t)]
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Field = {"name": name, "expression": randomOperator, "value": value,
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"type": type1}
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orConditions_list.append(Field)
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else:
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randomOperator_1= random.sample(Operator, 1)
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randomOperator=randomOperator_1[0]
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if conrandomstraints["type"] == "timestamp":
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#获取当前时间戳
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t = int(time.time())
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value=[str(t)]
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Field={"name":name,"expression":randomOperator,"value":value,"type":type1}
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orConditions_list.append(Field)
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orConditions={"orConditions":orConditions_list}
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andConditions.append(orConditions)
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elif type1 == "string":
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orConditions_list = []
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Operator=["=","!=","Like","Not Like","notEmpty","empty"]
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if testpoint == "Filter":
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if conrandomstraints["type"] == "ip":
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for op in Operator:
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# 获取ip
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ip = random_ipv4()
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value = []
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if op == "=" or op == "!=":
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value.append(ip)
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elif op == "Like" or op == "Not Like":
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value.append(ip)
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elif op == "notEmpty":
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value = []
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Field = {"name": name, "expression": op, "value": value,"type": type1}
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orConditions_list.append(Field)
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elif conrandomstraints["type"] == "email":
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for op in Operator:
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randomOperator = op
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Operator = ["=", "!=", "Like", "Not Like", "notEmpty","empty"]
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randomOperator_1 = random.sample(Operator, 1)
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randomOperator = randomOperator_1[0]
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# 获取ip
|
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emil = RandomEmail()
|
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value = []
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if randomOperator == "=" or randomOperator == "!=":
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value.append(emil)
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elif randomOperator == "Like" or randomOperator == "Not Like":
|
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value.append(emil)
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elif randomOperator == "notEmpty":
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||
value = []
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Field = {"name": name, "expression": randomOperator, "value": value,
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"type": type1}
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orConditions_list.append(Field)
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else:
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randomOperator_1= random.sample(Operator, 1)
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randomOperator=randomOperator_1[0]
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if conrandomstraints["type"] == "ip":
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#获取ip
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ip =random_ipv4()
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value=[]
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||
if randomOperator == "=" or randomOperator == "!=":
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value.append(ip)
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elif randomOperator == "Like" or randomOperator == "Not Like":
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value.append(ip)
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elif randomOperator=="notEmpty":
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value=[]
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Field={"name":name,"expression":randomOperator,"value":value,"type":type1}
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orConditions_list.append(Field)
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orConditions={"orConditions":orConditions_list}
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andConditions.append(orConditions)
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elif conrandomstraints["type"] == "email":
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Operator=["=","!=","Like","Not Like","notEmpty","empty"]
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randomOperator_1= random.sample(Operator, 1)
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randomOperator=randomOperator_1[0]
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#获取ip
|
||
emil =RandomEmail()
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||
value=[]
|
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if randomOperator == "=" or randomOperator == "!=":
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||
value.append(emil)
|
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elif randomOperator == "Like" or randomOperator == "Not Like":
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||
value.append(emil)
|
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elif randomOperator=="notEmpty":
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value=[]
|
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Field={"name":name,"expression":randomOperator,"value":value,"type":type1}
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orConditions_list.append(Field)
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orConditions={"orConditions":orConditions_list}
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andConditions.append(orConditions)
|
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else:
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type1 = k["type"]
|
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orConditions_list=[]
|
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operator1 = k["doc"]["constraints"]["operator_functions"]
|
||
operator2 = operator1.split(",")
|
||
if testpoint == "Filter":
|
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for op in operator2:
|
||
operatordata = k["doc"]["data"]
|
||
code = []
|
||
for i in operatordata:
|
||
code_1 = i["code"]
|
||
code.append(code_1)
|
||
for co in code:
|
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Field = {"name": name, "expression": op, "value": co, "type": type1}
|
||
orConditions_list.append(Field)
|
||
else:
|
||
operator3=random.sample(operator2,1)
|
||
operatordata=k["doc"]["data"]
|
||
code=[]
|
||
for i in operatordata:
|
||
code_1=i["code"]
|
||
code.append(code_1)
|
||
code2=random.sample(code, 1)
|
||
Field={"name":name,"expression":operator3[0],"value":code2,"type":type1}
|
||
orConditions_list.append(Field)
|
||
orConditions={"orConditions":orConditions_list}
|
||
andConditions.append(orConditions)
|
||
filterCondition={"andConditions":andConditions}
|
||
print("filterCondition",filterCondition)
|
||
return filterCondition
|
||
|
||
#获取having条件的串
|
||
def havingjson(schemajson,testpoint,field):
|
||
number = random.randint(0,100000)
|
||
schemametrics=schemajson["data"]["doc"]["schema_query"]["metrics"]
|
||
aggregation = schemajson["data"]["doc"]["schema_query"]["references"]["aggregation"]
|
||
schemametrics.append("common_log_id")
|
||
metricslist=[]
|
||
if testpoint == "Having":
|
||
metricslist.append(field)
|
||
else:
|
||
metricslist=random.sample(schemametrics, 4)
|
||
fields = schemajson["data"]["fields"]
|
||
operator=["=","!=",">","<",">=","<="]
|
||
Aggregate=["COUNT","AVG","SUM","MAX","MIN"]
|
||
andConditions_list=[]
|
||
#遍历的到的having条件列表
|
||
for i in metricslist:
|
||
for j in fields:
|
||
if i == j["name"]:
|
||
name = j["name"]
|
||
type1=j["type"]
|
||
for v in aggregation:
|
||
if type1 == v["type"]:
|
||
orConditions_list=[]
|
||
if v["type"] != "string":
|
||
functionslist=Aggregate
|
||
else:
|
||
functionsstr=v["functions"]
|
||
functionslist = functionsstr.split(",")
|
||
if field == "common_log_id":
|
||
functionslist=["COUNT"]
|
||
if testpoint == "Having":
|
||
for functions_1 in functionslist:
|
||
for operator_1 in operator:
|
||
havingdict = {"name": name, "function": str.lower(functions_1),
|
||
"expression": operator_1, "value": str(number)}
|
||
orConditions_list.append(havingdict)
|
||
orConditions = {"orConditions": orConditions_list}
|
||
andConditions_list.append(orConditions)
|
||
else:
|
||
functions_1=random.sample(functionslist, 1)
|
||
if functions_1=="COUNT_DISTINCT" and type1 != "string":
|
||
functions_1=random.sample(functionslist, 1)
|
||
operator_1=random.sample(operator, 1)
|
||
|
||
havingdict={"name":name,"function":str.lower(functions_1[0]),"expression":operator_1[0],"value":str(number)}
|
||
orConditions_list.append(havingdict)
|
||
orConditions={"orConditions":orConditions_list}
|
||
andConditions_list.append(orConditions)
|
||
havingCondition={"andConditions":andConditions_list}
|
||
print("having",havingCondition)
|
||
return havingCondition
|
||
|
||
#拼接字符串
|
||
def datasetjson(schemauerl,token,testname,logtype,testpoint,field):
|
||
schema_new=schema(schemauerl,token,logtype)
|
||
group_re=groupby(schema_new,logtype,testpoint,field)
|
||
groupColumnList=group_re[0]
|
||
group_randomstr=group_re[1]
|
||
queryColumnList=DataBindings(schema_new,group_randomstr,testpoint,field)
|
||
filterCondition_1=filterCondition(schema_new,testpoint,field)
|
||
havingjson_1=havingjson(schema_new,testpoint,field)
|
||
datasetdict = {
|
||
"list": {
|
||
"name":testname,
|
||
"logType": logtype,
|
||
"groupColumnList":groupColumnList,
|
||
"queryColumnList":queryColumnList,
|
||
"filterCondition":filterCondition_1,
|
||
"havingCondition":havingjson_1
|
||
}
|
||
}
|
||
print(datasetdict)
|
||
print("datasetjson",json.dumps(datasetdict))
|
||
return json.dumps(datasetdict)
|
||
|
||
#拼接char的json串
|
||
def charjson(schemaurl,token,queryColumnList,groupColumnList,datasetid,testname,logtype):
|
||
print("queryColumnList",queryColumnList)
|
||
schema_new=schema(schemaurl,token,logtype)
|
||
fields = schema_new["data"]["fields"]
|
||
# 获取条件的label
|
||
namelist=[]
|
||
for i in queryColumnList:
|
||
for j in fields:
|
||
if i["name"] == j["name"]:
|
||
j_label=j["label"]
|
||
namelist.append(j_label)
|
||
print("namelist",namelist)
|
||
#获取聚合条件的label
|
||
groupColumnlaberList=[]
|
||
for i in groupColumnList:
|
||
for j in fields:
|
||
if i["name"] == j["name"]:
|
||
j_label=j["label"]
|
||
groupColumnlaberList.append(j_label)
|
||
print("groupColumnlaberList",groupColumnlaberList)
|
||
#图表类型列表
|
||
chartType_1=["line","pie","bar","area","table"]
|
||
chartType_2=["pie","bar","table"]
|
||
chartType=[]
|
||
# #随机选择图表类型
|
||
s=1
|
||
for i in namelist:
|
||
if i == "Receive Time" or i == "Start Time" or i == "End Time":
|
||
s+=1
|
||
if s != 1:
|
||
chartType=random.sample(chartType_1, 1)
|
||
else:
|
||
chartType=random.sample(chartType_2, 1)
|
||
chardict={}
|
||
print("chartType",chartType)
|
||
if chartType[0] == "line" or chartType[0] == "area":
|
||
dataBinding=[]
|
||
#将时间条件赋值给dataBinding
|
||
for j in namelist:
|
||
if j == "Receive Time" or j == "Start Time" or j == "End Time":
|
||
dataBinding.append(j)
|
||
timelin={
|
||
"dataBinding": dataBinding[0],
|
||
"format": "Time"
|
||
}
|
||
print("timelin",timelin)
|
||
namelist.remove(dataBinding[0]) #从统计查询数据列对象内去掉时间条件
|
||
groupColumnlaberList.remove(dataBinding[0]) #从聚合条件内去掉时间的条件
|
||
for i in groupColumnlaberList: #从统计查询条件内去掉聚合条件内的值
|
||
namelist.remove(i)
|
||
print("namelistrome",namelist)
|
||
linlist=[]
|
||
for i in namelist:
|
||
lindict={
|
||
"dataBinding": i,
|
||
"type": "Line Up",
|
||
"format": "Default",
|
||
}
|
||
linlist.append(lindict)
|
||
listdict={
|
||
"name": testname,
|
||
"datasetId": datasetid,
|
||
"datasetName": "",
|
||
"chartType": chartType[0],
|
||
"dataTop": 0,
|
||
"orderBy": "",
|
||
"orderDesc": 0,
|
||
"drilldownTop": 0,
|
||
"timeline": timelin,
|
||
"line": linlist
|
||
}
|
||
chardict={"list": listdict}
|
||
elif chartType[0] == "pie" or chartType[0] == "bar":
|
||
xAxisdataBinding=random.sample(groupColumnlaberList, 1)
|
||
xAxisdict={
|
||
"dataBinding": xAxisdataBinding[0],
|
||
"dataTop": 5,
|
||
"dataType": ""
|
||
}
|
||
for i in groupColumnlaberList:
|
||
namelist.remove(i)
|
||
yAxisBinding=random.sample(namelist, 1)
|
||
yAxisdict={
|
||
"dataBinding": yAxisBinding[0],
|
||
"format": "Default",
|
||
}
|
||
yAxislist=[yAxisdict]
|
||
listdict={
|
||
"name": testname,
|
||
"datasetId": datasetid,
|
||
"datasetName": "",
|
||
"chartType": chartType[0],
|
||
"dataTop": 0,
|
||
"orderBy": "",
|
||
"orderDesc": "",
|
||
"xAxis": xAxisdict,
|
||
"yAxis": yAxislist
|
||
}
|
||
chardict={"list": listdict}
|
||
elif chartType[0] == "table":
|
||
columnslist=[]
|
||
for i in namelist:
|
||
dataBindings={
|
||
"dataType": "",
|
||
"dataBinding": i,
|
||
"format": "Default",
|
||
}
|
||
dataBindingslist=[]
|
||
dataBindingslist.append(dataBindings)
|
||
columnsdict={
|
||
"title": i,
|
||
"width": 0,
|
||
"dataBindings": dataBindingslist
|
||
}
|
||
columnslist.append(columnsdict)
|
||
|
||
listdict={
|
||
"name": testname,
|
||
"datasetId": datasetid,
|
||
"datasetName": "",
|
||
"chartType": "table",
|
||
"dataTop": 5,
|
||
"orderBy": "",
|
||
"orderDesc": "",
|
||
"drilldownTop": 5,
|
||
"tableType": "Regular",
|
||
"columns": columnslist
|
||
}
|
||
chardict={"list": listdict}
|
||
print("charjson",json.dumps(chardict))
|
||
return json.dumps(chardict)
|
||
|
||
def Reportsjson(chartId,testname):
|
||
charlist=[]
|
||
chardict={
|
||
"chartId": chartId,
|
||
"timeGranulartiy": 1,
|
||
"timeUnit": "",
|
||
# "disabled": true
|
||
}
|
||
charlist.append(chardict)
|
||
reportJobList=[]
|
||
reportJobdct_1={
|
||
"rangeType": "last",
|
||
"rangeInterval": 1,
|
||
"rangeUnit": "week",
|
||
"jobName": testname,
|
||
"scheduleId": "",
|
||
"chartList": charlist,
|
||
"isNotice": 0,
|
||
"noticeMethod": "",
|
||
"startTime": "",
|
||
"endTime": "",
|
||
"filterCondition": None,
|
||
"isDisplayTrafficTrend": 1
|
||
}
|
||
reportJobdct_2={"reportJobList": reportJobdct_1}
|
||
print("reportjson",json.dumps(reportJobdct_2))
|
||
return json.dumps(reportJobdct_2)
|
||
|
||
def ReportInterfaceTest(schemaurl,token,dataseturl,charurl,repporturl,datasetgeturl,chargeturl,testname,logtype,testpoint,field):
|
||
headers = {"Content-Type": "application/json","Authorization": token}
|
||
#dataset生成json串并发送请求
|
||
_datasetjson=datasetjson(schemaurl,token,testname,logtype,testpoint,field)
|
||
response1 = requests.post(url=dataseturl, data=_datasetjson, headers=headers)
|
||
print("返回数据1",response1)
|
||
code = response1.json()["code"]
|
||
print("datasetcode:",code)
|
||
assert code == 200
|
||
|
||
|
||
# 获取dataset的id
|
||
datasetget=requests.get(url=datasetgeturl,headers=headers)
|
||
dasetget=datasetget.json()
|
||
datesetid=dasetget["data"]["list"][0]["id"]
|
||
Deleteinterfaces(dataseturl,token,datesetid)
|
||
# _datasetjson=json.loads(_datasetjson)
|
||
# queryColumnList=_datasetjson["list"]["queryColumnList"]
|
||
# groupColumnList=_datasetjson["list"]["groupColumnList"]
|
||
#生成charlibrariesjson串
|
||
# charlibrariesjson=charjson(schemaurl, token,queryColumnList,groupColumnList,datesetid,testname,logtype)
|
||
# response2 = requests.post(url=charurl, data=charlibrariesjson, headers=headers)
|
||
# code = response2.json()["code"]
|
||
# assert code == 200
|
||
#
|
||
# #获取char libraries的id
|
||
# charget=requests.get(url=chargeturl,headers=headers)
|
||
# charget=charget.json()
|
||
# charid=charget["data"]["list"][0]["id"]
|
||
#
|
||
# #report生成json串并发送请求
|
||
# reportjson=Reportsjson(charid,testname)
|
||
# response3 = requests.post(url=repporturl, data=reportjson, headers=headers)
|
||
# code = response3.json()["code"]
|
||
# assert code == 200
|
||
#
|
||
|
||
# #循环调用ReportInterfaceTest方法
|
||
# def ReportTest(host,token,dataseturl,charurl,repporturl,logtypelist):
|
||
# for logtype in logtypelist:
|
||
# testname="Report"+logtype
|
||
# datasetgeturl=dataseturl+"?pageSize=20&pageNo=1&id=&name="+testname+"&logType=&opStartTime=&opEndTime=&opUser="
|
||
# chargeturl=charurl+"?pageSize=20&pageNo=1&id=&name="+testname+"&opUser="
|
||
# schemaurl="http://"+host+":8080/v1/log/schema?logType="+logtype
|
||
# ReportInterfaceTest(schemaurl,token,dataseturl,charurl,repporturl,datasetgeturl,chargeturl,testname,logtype)
|
||
|
||
|
||
def Deleteinterfaces(url,token,id):
|
||
headers = {"Content-Type": "application/json","Authorization": token}
|
||
datedict={"ids":[id]}
|
||
datajson=json.dumps(datedict)
|
||
response1 = requests.delete(url=url, data=datajson, headers=headers)
|
||
|
||
|
||
def ReportPositiveTest(host,port,token,dataseturl,charurl,repporturl,logtypelist):
|
||
testpoint=["GroupBy","DataBindings","Filter","Having"]
|
||
for logtype in logtypelist:
|
||
schemaurl="http://"+host+":"+port+"/v1/log/schema?logType="+logtype
|
||
schema_new=schema(schemaurl,token,logtype)
|
||
metrics = schema_new["data"]["doc"]["schema_query"]["metrics"]
|
||
schemafilters = schema_new["data"]["doc"]["schema_query"]["filters"]
|
||
dimensions = schema_new["data"]["doc"]["schema_query"]["dimensions"]
|
||
dimensions.append("common_recv_time");
|
||
metrics.append("common_log_id")
|
||
for j in testpoint:
|
||
if j == "GroupBy":
|
||
for filter in dimensions:
|
||
testname="Report"+logtype+j+filter
|
||
dataset_geturl=dataseturl+"?pageSize=20&pageNo=1&id=&name="+testname+"&logType=&opStartTime=&opEndTime=&opUser="
|
||
char_geturl=charurl+"?pageSize=20&pageNo=1&id=&name="+testname+"&opUser="
|
||
ReportInterfaceTest(schemaurl,token,dataseturl,charurl,repporturl,dataset_geturl,char_geturl,testname,logtype,j,filter)
|
||
if j == "DataBindings":
|
||
for filter in metrics:
|
||
testname="Report"+logtype+j+filter
|
||
dataset_geturl=dataseturl+"?pageSize=20&pageNo=1&id=&name="+testname+"&logType=&opStartTime=&opEndTime=&opUser="
|
||
char_geturl=charurl+"?pageSize=20&pageNo=1&id=&name="+testname+"&opUser="
|
||
ReportInterfaceTest(schemaurl,token,dataseturl,charurl,repporturl,dataset_geturl,char_geturl,testname,logtype,j,filter)
|
||
|
||
if j == "Filter" :
|
||
for filter in schemafilters:
|
||
testname="Report"+logtype+j+filter
|
||
dataset_geturl=dataseturl+"?pageSize=20&pageNo=1&id=&name="+testname+"&logType=&opStartTime=&opEndTime=&opUser="
|
||
char_geturl=charurl+"?pageSize=20&pageNo=1&id=&name="+testname+"&opUser="
|
||
ReportInterfaceTest(schemaurl,token,dataseturl,charurl,repporturl,dataset_geturl,char_geturl,testname,logtype,j,filter)
|
||
|
||
if j == "Having" :
|
||
for filter in metrics:
|
||
testname="Report"+logtype+j+filter
|
||
dataset_geturl=dataseturl+"?pageSize=20&pageNo=1&id=&name="+testname+"&logType=&opStartTime=&opEndTime=&opUser="
|
||
char_geturl=charurl+"?pageSize=20&pageNo=1&id=&name="+testname+"&opUser="
|
||
ReportInterfaceTest(schemaurl,token,dataseturl,charurl,repporturl,dataset_geturl,char_geturl,testname,logtype,j,filter)
|
||
|
||
|
||
|
||
|
||
|