原文链接:https://www.cnblogs.com/podolski/p/14380360.html
当编写应用程序时,经常性需要花费大量的时间与精力处理业务逻辑,往往业务逻辑的变化需要重构或者增加大量代码,对开发测试人员很不友好。
之前在这篇文章说过,可以使用脚本引擎来将我们需要经常变化的代码进行动态编译执行,自由度非常大,不过对应的需要资源也多。如果只是针对非常具体业务逻辑的变化,可以尝试使用RulesEngine对程序进行操作。
下文使用了官方示例且部分内容翻译自说明文档
RulesEngine是微软推出的规则引擎,规则引擎在很多企业开发中有所应用,是处理经常变动需求的一种优雅的方法。个人任务,规则引擎适用于以下的一些场景:
RulesEngine的规则使用JSON进行存储,通过lambda表达式方式表述规则(Rules)。
安装很方便,直接使用nuget进行安装:
install-pacakge RulesEngine
需要有Rules,有WorkflowName,然后还有一些属性。
[
{
"WorkflowName": "Discount",
"Rules": [
{
"RuleName": "GiveDiscount10",
"SuccessEvent": "10",
"ErrorMessage": "One or more adjust rules failed.",
"ErrorType": "Error",
"RuleExpressionType": "LambdaExpression",
"Expression": "input1.country == \"india\" AND input1.loyalityFactor <= 2 AND input1.totalPurchasesToDate >= 5000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
}
]
}
]
除了标准的
RuleExpressionType
,还可以通过定义Rules嵌套多个条件,下面是Or逻辑。
{
"RuleName": "GiveDiscount30NestedOrExample",
"SuccessEvent": "30",
"ErrorMessage": "One or more adjust rules failed.",
"ErrorType": "Error",
"Operator": "OrElse",
"Rules":[
{
"RuleName": "IsLoyalAndHasGoodSpend",
"ErrorMessage": "One or more adjust rules failed.",
"ErrorType": "Error",
"RuleExpressionType": "LambdaExpression",
"Expression": "input1.loyalityFactor > 3 AND input1.totalPurchasesToDate >= 50000 AND input1.totalPurchasesToDate <= 100000"
},
{
"RuleName": "OrHasHighNumberOfTotalOrders",
"ErrorMessage": "One or more adjust rules failed.",
"ErrorType": "Error",
"RuleExpressionType": "LambdaExpression",
"Expression": "input2.totalOrders > 15"
}
]
}
可以从官方的代码库中下载示例,定义了上述规则,就可以直接开始用了。示例描述了这么一个应用场景:
根据不同的客户属性,提供不同的折扣。由于销售的情况变化较快,提供折扣的规则也需要经常变动。因此比较适用于规则引擎。
public void Run()
{
Console.WriteLine($"Running {nameof(BasicDemo)}....");
//创建输入
var basicInfo = "{\"name\": \"hello\",\"email\": \"abcy@xyz.com\",\"creditHistory\": \"good\",\"country\": \"canada\",\"loyalityFactor\": 3,\"totalPurchasesToDate\": 10000}";
var orderInfo = "{\"totalOrders\": 5,\"recurringItems\": 2}";
var telemetryInfo = "{\"noOfVisitsPerMonth\": 10,\"percentageOfBuyingToVisit\": 15}";
var converter = new ExpandoObjectConverter();
dynamic input1 = JsonConvert.DeserializeObject<ExpandoObject>(basicInfo, converter);
dynamic input2 = JsonConvert.DeserializeObject<ExpandoObject>(orderInfo, converter);
dynamic input3 = JsonConvert.DeserializeObject<ExpandoObject>(telemetryInfo, converter);
var inputs = new dynamic[]
{
input1,
input2,
input3
};
//加载规则
var files = Directory.GetFiles(Directory.GetCurrentDirectory(), "Discount.json", SearchOption.AllDirectories);
if (files == null || files.Length == 0)
throw new Exception("Rules not found.");
var fileData = File.ReadAllText(files[0]);
var workflowRules = JsonConvert.DeserializeObject<List<WorkflowRules>>(fileData);
//初始化规则引擎
var bre = new RulesEngine.RulesEngine(workflowRules.ToArray(), null);
string discountOffered = "No discount offered.";
//执行规则
List<RuleResultTree> resultList = bre.ExecuteAllRulesAsync("Discount", inputs).Result;
//处理结果
resultList.OnSuccess((eventName) => {
discountOffered = $"Discount offered is {eventName} % over MRP.";
});
resultList.OnFail(() => {
discountOffered = "The user is not eligible for any discount.";
});
Console.WriteLine(discountOffered);
}
输入一般来说是IEnumerable<dynamic>
或者是匿名类型,上面实例展示的是由json反序列化形成的dynamic类型,对于程序生成的数据,使用匿名类型更加方便。
var nestedInput = new {
SimpleProp = "simpleProp",
NestedProp = new {
SimpleProp = "nestedSimpleProp",
ListProp = new List<ListItem>
{
new ListItem
{
Id = 1,
Value = "first"
},
new ListItem
{
Id = 2,
Value = "second"
}
}
}
};
和脚本引擎一样,默认规则引擎只能访问System的命名空间。如果需要使用到稍微复杂一些的类型,可以自己定义类型或者函数。比如定义一个这样的函数:
public static class Utils
{
public static bool CheckContains(string check, string valList)
{
if (String.IsNullOrEmpty(check) || String.IsNullOrEmpty(valList))
return false;
var list = valList.Split(',').ToList();
return list.Contains(check);
}
}
需要使用的时候,先将类传递给RulesEngine:
var reSettingsWithCustomTypes = new ReSettings { CustomTypes = new Type[] { typeof(Utils) } };
var engine = new RulesEngine.RulesEngine(workflowRules.ToArray(), null, reSettingsWithCustomTypes);
然后就可以直接在表达式中使用了。
"Expression": "Utils.CheckContains(input1.country, \"india,usa,canada,France\") == true"
默认情况下,规则的输入使用的是类似input1 input2这样的形式,如果想直观一点,可以使用RuleParameter
来进行封装具体的参数类型。
RuleParameter ruleParameter = new RuleParameter("NIP", nestedInput);
var resultList = bre.ExecuteAllRulesAsync(workflow.WorkflowName, ruleParameter).Result;
如果表达式比较复杂的情况下,可以使用本地变量来进行分段处理,这对调试来说会比较方便。
本地变量的关键字为localParams,可以将中间的内容简单理解成var name = expression
{
"name": "allow_access_if_all_mandatory_trainings_are_done_or_access_isSecure",
"errorMessage": "Please complete all your training(s) to get access to this content or access it from a secure domain/location.",
"errorType": "Error",
"localParams": [
{
"name": "completedSecurityTrainings",
"expression": "MasterSecurityComplainceTrainings.Where(Status.Equals(\"Completed\", StringComparison.InvariantCultureIgnoreCase))"
},
{
"name": "completedProjectTrainings",
"expression": "MasterProjectComplainceTrainings.Where(Status.Equals(\"Completed\", StringComparison.InvariantCultureIgnoreCase))"
},
{
"name": "isRequestAccessSecured",
"expression": "UserRequestDetails.Location.Country == \"India\" ? ((UserRequestDetails.Location.City == \"Bangalore\" && UserRequestDetails.Domain=\"xxxx\")? true : false):false"
}
],
"expression": "(completedSecurityTrainings.Any() && completedProjectTrainings.Any()) || isRequestAccessSecured "
}
使用规则引擎,可以将经常变动的业务逻辑独立摘出来,为我们编写动态、可拓展的程序提供了很大的便利。RulesEngine这个东西提供的API也比较简洁,上手非常简单。
作者:波多尔斯基
出处:https://www.cnblogs.com/podolski/p/14380360.html
版权:本作品采用「署名-非商业性使用-相同方式共享 4.0 国际」许可协议进行许可。
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