Question

这是原始问题的简化版本。

我有一个名为Person的课程：

public class Person {
  public string Name { get; set; }
  public int Age { get; set; }
  public int Weight { get; set; }
  public DateTime FavouriteDay { get; set; }
}

......让我们说一个例子：

var bob = new Person {
  Name = "Bob",
  Age = 30,
  Weight = 213,
  FavouriteDay = '1/1/2000'
}

我想在我最喜欢的文本编辑器中将以下内容写成 string ....

(Person.Age > 3 AND Person.Weight > 50) OR Person.Age < 3

我想取这个字符串和我的对象实例并评估为TRUE或FALSE - 即评估一个Func＆lt; Person，bool＆gt;在对象实例上。

以下是我目前的想法：

在ANTLR中实现基本语法以支持基本比较和逻辑运算符。我想在这里复制Visual Basic优先级和一些功能集：http://msdn.microsoft.com/en-us/library/fw84t893(VS.80).aspx
让ANTLR从提供的字符串中创建合适的AST。
走AST并使用Predicate Builder框架动态创建Func＆lt; Person，bool＆gt;
根据需要针对Person实例评估谓词

我的问题是我是否完全覆盖了这个？任何替代方案？

编辑：选择解决方案

我决定使用Dynamic Linq Library，特别是LINQSamples中提供的Dynamic Query类。

以下代码：

using System;
using System.Linq.Expressions;
using System.Linq.Dynamic;

namespace ExpressionParser
{
  class Program
  {
    public class Person
    {
      public string Name { get; set; }
      public int Age { get; set; }
      public int Weight { get; set; }
      public DateTime FavouriteDay { get; set; }
    }

    static void Main()
    {
      const string exp = @"(Person.Age > 3 AND Person.Weight > 50) OR Person.Age < 3";
      var p = Expression.Parameter(typeof(Person), "Person");
      var e = System.Linq.Dynamic.DynamicExpression.ParseLambda(new[] { p }, null, exp);
      var bob = new Person
      {
        Name = "Bob",
        Age = 30,
        Weight = 213,
        FavouriteDay = new DateTime(2000,1,1)
      };

      var result = e.Compile().DynamicInvoke(bob);
      Console.WriteLine(result);
      Console.ReadKey();
    }
  }
}

结果的类型为System.Boolean，在此实例中为TRUE。

非常感谢Marc Gravell。

包括System.Linq.Dynamic nuget包，文档here

Answer 1

dynamic linq library会帮助吗？特别是，我正在考虑Where条款。如有必要，将它放在列表/数组中只是为了调用它上面的.Where(string)！即。

var people = new List<Person> { person };
int match = people.Where(filter).Any();

如果没有，编写一个解析器（在引擎盖下使用Expression）并没有太大的负担 - 我在圣诞节前的火车通勤中写了一个类似的（虽然我不认为我有源头）。 ..

Answer 2

另一个这样的库是Flee

我对Dynamic Linq Library和Flee进行了快速比较，而对于表达式"(Name == \"Johan\" AND Salary > 500) OR (Name != \"Johan\" AND Salary > 300)"而言，Flee的速度提高了10倍

这是如何使用Flee编写代码的。

static void Main(string[] args)
{
  var context = new ExpressionContext();
  const string exp = @"(Person.Age > 3 AND Person.Weight > 50) OR Person.Age < 3";
  context.Variables.DefineVariable("Person", typeof(Person));
  var e = context.CompileDynamic(exp);

  var bob = new Person
  {
    Name = "Bob",
    Age = 30,
    Weight = 213,
    FavouriteDay = new DateTime(2000, 1, 1)
  };

  context.Variables["Person"] = bob;
  var result = e.Evaluate();
  Console.WriteLine(result);
  Console.ReadKey();
}

Answer 3

void Main()
{
    var testdata = new List<Ownr> {
        //new Ownr{Name = "abc", Qty = 20}, // uncomment this to see it getting filtered out
        new Ownr{Name = "abc", Qty = 2},
        new Ownr{Name = "abcd", Qty = 11},
        new Ownr{Name = "xyz", Qty = 40},
        new Ownr{Name = "ok", Qty = 5},
    };

    Expression<Func<Ownr, bool>> func = Extentions.strToFunc<Ownr>("Qty", "<=", "10");
    func = Extentions.strToFunc<Ownr>("Name", "==", "abc", func);

    var result = testdata.Where(func.ExpressionToFunc()).ToList();

    result.Dump();
}

public class Ownr
{
    public string Name { get; set; }
    public int Qty { get; set; }
}

public static class Extentions
{
    public static Expression<Func<T, bool>> strToFunc<T>(string propName, string opr, string value, Expression<Func<T, bool>> expr = null)
    {
        Expression<Func<T, bool>> func = null;
        try
        {
            var type = typeof(T);
            var prop = type.GetProperty(propName);
            ParameterExpression tpe = Expression.Parameter(typeof(T));
            Expression left = Expression.Property(tpe, prop);
            Expression right = Expression.Convert(ToExprConstant(prop, value), prop.PropertyType);
            Expression<Func<T, bool>> innerExpr = Expression.Lambda<Func<T, bool>>(ApplyFilter(opr, left, right), tpe);
            if (expr != null)
                innerExpr = innerExpr.And(expr);
            func = innerExpr;
        }
        catch (Exception ex)
        {
            ex.Dump();
        }

        return func;
    }
    private static Expression ToExprConstant(PropertyInfo prop, string value)
    {
        object val = null;

        try
        {
            switch (prop.Name)
            {
                case "System.Guid":
                    val = Guid.NewGuid();
                    break;
                default:
                    {
                        val = Convert.ChangeType(value, prop.PropertyType);
                        break;
                    }
            }
        }
        catch (Exception ex)
        {
            ex.Dump();
        }

        return Expression.Constant(val);
    }
    private static BinaryExpression ApplyFilter(string opr, Expression left, Expression right)
    {
        BinaryExpression InnerLambda = null;
        switch (opr)
        {
            case "==":
            case "=":
                InnerLambda = Expression.Equal(left, right);
                break;
            case "<":
                InnerLambda = Expression.LessThan(left, right);
                break;
            case ">":
                InnerLambda = Expression.GreaterThan(left, right);
                break;
            case ">=":
                InnerLambda = Expression.GreaterThanOrEqual(left, right);
                break;
            case "<=":
                InnerLambda = Expression.LessThanOrEqual(left, right);
                break;
            case "!=":
                InnerLambda = Expression.NotEqual(left, right);
                break;
            case "&&":
                InnerLambda = Expression.And(left, right);
                break;
            case "||":
                InnerLambda = Expression.Or(left, right);
                break;
        }
        return InnerLambda;
    }

    public static Expression<Func<T, TResult>> And<T, TResult>(this Expression<Func<T, TResult>> expr1, Expression<Func<T, TResult>> expr2)
    {
        var invokedExpr = Expression.Invoke(expr2, expr1.Parameters.Cast<Expression>());
        return Expression.Lambda<Func<T, TResult>>(Expression.AndAlso(expr1.Body, invokedExpr), expr1.Parameters);
    }

    public static Func<T, TResult> ExpressionToFunc<T, TResult>(this Expression<Func<T, TResult>> expr)
    {
        var res = expr.Compile();
        return res;
    }
}

LinqPad有Dump()方法

Answer 4

您可以查看DLR。它允许您评估和执行.NET 2.0应用程序内的脚本。以下是IronRuby的示例：

using System;
using IronRuby;
using IronRuby.Runtime;
using Microsoft.Scripting.Hosting;

class App
{
    static void Main()
    {
        var setup = new ScriptRuntimeSetup();
        setup.LanguageSetups.Add(
            new LanguageSetup(
                typeof(RubyContext).AssemblyQualifiedName,
                "IronRuby",
                new[] { "IronRuby" },
                new[] { ".rb" }
            )
        );
        var runtime = new ScriptRuntime(setup);
        var engine = runtime.GetEngine("IronRuby");
        var ec = Ruby.GetExecutionContext(runtime);
        ec.DefineGlobalVariable("bob", new Person
        {
            Name = "Bob",
            Age = 30,
            Weight = 213,
            FavouriteDay = "1/1/2000"
        });
        var eval = engine.Execute<bool>(
            "return ($bob.Age > 3 && $bob.Weight > 50) || $bob.Age < 3"
        );
        Console.WriteLine(eval);

    }
}

public class Person
{
    public string Name { get; set; }
    public int Age { get; set; }
    public int Weight { get; set; }
    public string FavouriteDay { get; set; }
}

当然，这种技术基于运行时评估，并且在编译时无法验证代码。

Answer 5

以下是基于Scala DSL的解析器组合器的示例，用于解析和评估算术表达式。

import scala.util.parsing.combinator._
/** 
* @author Nicolae Caralicea
* @version 1.0, 04/01/2013
*/
class Arithm extends JavaTokenParsers {
  def expr: Parser[List[String]] = term ~ rep(addTerm | minusTerm) ^^
    { case termValue ~ repValue => termValue ::: repValue.flatten }

  def addTerm: Parser[List[String]] = "+" ~ term ^^
    { case "+" ~ termValue => termValue ::: List("+") }

  def minusTerm: Parser[List[String]] = "-" ~ term ^^
    { case "-" ~ termValue => termValue ::: List("-") }

  def term: Parser[List[String]] = factor ~ rep(multiplyFactor | divideFactor) ^^
    {
      case factorValue1 ~ repfactor => factorValue1 ::: repfactor.flatten
    }

  def multiplyFactor: Parser[List[String]] = "*" ~ factor ^^
    { case "*" ~ factorValue => factorValue ::: List("*") }

  def divideFactor: Parser[List[String]] = "/" ~ factor ^^
    { case "/" ~ factorValue => factorValue ::: List("/") }

  def factor: Parser[List[String]] = floatingPointConstant | parantExpr

  def floatingPointConstant: Parser[List[String]] = floatingPointNumber ^^
    {
      case value => List[String](value)
    }

  def parantExpr: Parser[List[String]] = "(" ~ expr ~ ")" ^^
    {
      case "(" ~ exprValue ~ ")" => exprValue
    }

  def evaluateExpr(expression: String): Double = {
    val parseRes = parseAll(expr, expression)
    if (parseRes.successful) evaluatePostfix(parseRes.get)
    else throw new RuntimeException(parseRes.toString())
  }
  private def evaluatePostfix(postfixExpressionList: List[String]): Double = {
    import scala.collection.immutable.Stack

    def multiply(a: Double, b: Double) = a * b
    def divide(a: Double, b: Double) = a / b
    def add(a: Double, b: Double) = a + b
    def subtract(a: Double, b: Double) = a - b

    def executeOpOnStack(stack: Stack[Any], operation: (Double, Double) => Double): (Stack[Any], Double) = {
      val el1 = stack.top
      val updatedStack1 = stack.pop
      val el2 = updatedStack1.top
      val updatedStack2 = updatedStack1.pop
      val value = operation(el2.toString.toDouble, el1.toString.toDouble)
      (updatedStack2.push(operation(el2.toString.toDouble, el1.toString.toDouble)), value)
    }
    val initial: (Stack[Any], Double) = (Stack(), null.asInstanceOf[Double])
    val res = postfixExpressionList.foldLeft(initial)((computed, item) =>
      item match {
        case "*" => executeOpOnStack(computed._1, multiply)
        case "/" => executeOpOnStack(computed._1, divide)
        case "+" => executeOpOnStack(computed._1, add)
        case "-" => executeOpOnStack(computed._1, subtract)
        case other => (computed._1.push(other), computed._2)
      })
    res._2
  }
}

object TestArithmDSL {
  def main(args: Array[String]): Unit = {
    val arithm = new Arithm
    val actual = arithm.evaluateExpr("(12 + 4 * 6) * ((2 + 3 * ( 4 + 2 ) ) * ( 5 + 12 ))")
    val expected: Double = (12 + 4 * 6) * ((2 + 3 * ( 4 + 2 ) ) * ( 5 + 12 ))
    assert(actual == expected)
  }
}

提供的算术表达式的等效表达式树或解析树将是Parser [List [String]]类型。

更多详情请访问以下链接：

http://nicolaecaralicea.blogspot.ca/2013/04/scala-dsl-for-parsing-and-evaluating-of.html

Answer 6

除了动态Linq库（构建强类型表达式并需要强类型变量）之外，我建议使用更好的替代方法：linq解析器NReco Commons Library的一部分（开源）。它对齐所有类型并在运行时执行所有调用，其行为类似于动态语言：

var lambdaParser = new NReco.LambdaParser();
var varContext = new Dictionary<string,object>();
varContext["one"] = 1M;
varContext["two"] = "2";

Console.WriteLine( lambdaParser.Eval("two>one && 0<one ? (1+8)/3+1*two : 0", varContext) ); // --> 5

Answer 7

尽管这是相对较旧的文章-这是表达式构建器的代码：AnyService - ExpressionTreeBuilder 这些是单元测试：AnyService - ExpressionTreeBuilder Unit Tests

如何将String转换为其等效的LINQ表达式树？

编辑：选择解决方案

7 个答案: