如何将字符串转换为等效的 LINQ 表达式树?

这是原始问题的简化版本。

我有一个叫人的类:

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

举个例子:

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

我想写以下作为一个 绳子在我最喜欢的文本编辑器... 。

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

我想使用这个字符串和我的对象实例来计算 TRUE 或 FALSE-即在对象实例上计算 Func < Person,bool > 。

以下是我目前的想法:

  1. 在 ANTLR 中实现基本语法,以支持基本的比较和逻辑运算符。我正在考虑复制 VisualBasic 优先级和这里的一些特性集: http://msdn.microsoft.com/en-us/library/fw84t893(VS.80).aspx
  2. 让 ANTLR 从提供的字符串创建一个合适的 AST。
  3. 遍历 AST 并使用 谓词生成器框架动态创建 Func < Person,bool >
  4. 根据需要计算针对 Person 实例的谓词

我的问题是,我是不是把它烤过头了? 还有别的选择吗?


编辑: 选择的解决方案

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

密码如下:

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();
}
}
}

结果类型为 System.Boolean,并且在此实例中为 TRUE。

非常感谢 Marc Gravell。

包括 系统,林克,动态核心包,文件 给你

111149 次浏览

你可以看看 DLR。它允许您在内部计算和执行脚本。NET 2.0应用程序。下面是 铁红宝石的一个例子:

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,这种技术是基于运行时计算的,代码无法在编译时进行验证。

动态 linq 库动态 linq 库在这方面有帮助吗?特别是,我想作为一个 Where条款。如果有必要,将它放在一个列表/数组中,以便在其上调用 .Where(string)!也就是说。

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)并不是很费力——我在圣诞节前的火车上写了一个类似的解析器(尽管我不认为我有源代码)。

另一个这样的库是 逃吧

我对 动态 Linq 库逃吧做了一个快速比较,对于表达式 "(Name == \"Johan\" AND Salary > 500) OR (Name != \"Johan\" AND Salary > 300)",Flee 的速度快了10倍

这就是如何使用 Flee 编写代码的方法。

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();
}

下面是一个基于 Scala DSL 的用于解析和计算算术表达式的解析器组合子的例子。

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)
}
}

所提供的算术表达式的等效表达式树或解析树应该是 Parser [ List [ String ]]类型。

详情请浏览以下连结:

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

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 具有 Dump()方法

除了 Dynamic Linq Library (构建强类型表达式并需要强类型变量)之外,我还推荐更好的替代方案: 使用 NReco Commons 图书馆(开放源码)的一部分 Linq 解析器。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

虽然这是相对较老的后-这是表达式构建器的代码: < a href = “ https://github.com/aturn72/AnyService/blob/dev/pagination _ query/src/AnyService.Core/网址1”rel = “ nofollow noReferrer”> AnyService-ExpressionTreeBuilder 这些是单元测试: AnyService-ExpressionTreeBuilder 单元测试