[开源].NET数据库访问框架Chloe.ORM

时间:2021-09-02 18:58:18

扯淡

13年毕业之际,进入第一家公司实习,接触了 EntityFramework,当时就觉得这东西太牛了,访问数据库都可以做得这么轻松、优雅!毕竟那时还年轻,没见过世面。工作之前为了拿个实习机会混个工作证明,匆匆忙忙学了两个月的 C#,就这样,稀里糊涂的做了程序员,从此走上了一条不归路。那会也只知道 SqlHelper,DataTable。ORM?太高大上,没听说过。虽然在第一家公司只呆了两个月,但让我认识了 EntityFramework,从此也走上了 ORM 的不归路...纯纯的实体,增改删超级简单,查询如行云流水,真心没理由抗拒!以至于后来进入第二家公司做开发极其不适应,因为他们没用 EF,也不用类 linq 的 ORM,他们有自己数据库访问框架。那套东西实体设计复杂,支持的功能少,查询条件还依赖字符串,开发容错率太低,DB操作入口接口设计也很重,里面方法不下60个,看心凉,用心累!那时,好怀念 EF~在新公司工作的时间内,来回都是增改页面,做增删查改,修复BUG,多少有点枯燥乏味,渐渐感觉编码能力提升太慢。同时鉴于用公司的 ORM 也不是很顺手,于是,萌生了自己写 ORM 的念头,再然后...Chloe.ORM 面世了~

导航

Chloe.ORM

Chloe 查询接口设计借(zhao)鉴(ban) linq,但不支持 linq。开发之前,我给我的 ORM 查询条件接口定义一定要支持lambda表达式(潮流、趋势,在这不讨论表达式树的性能)。开发之初,也有自己设计过查询接口,想了一套又一套,始终没 linq 设计的接口方便,后来,不想了,直接抄 linq,不解释!前人如此伟大设计,不用真对不起他们,我要站在他们的肩膀上!

先看下 IDbContext 接口:

public interface IDbContext : IDisposable
{
IDbSession CurrentSession { get; } IQuery<T> Query<T>() where T : new();
IEnumerable<T> SqlQuery<T>(string sql, params DbParam[] parameters) where T : new(); T Insert<T>(T entity);
object Insert<T>(Expression<Func<T>> body); int Update<T>(T entity);
int Update<T>(Expression<Func<T, T>> body, Expression<Func<T, bool>> condition); int Delete<T>(T entity);
int Delete<T>(Expression<Func<T, bool>> condition); void TrackEntity(object entity);
}

Chloe 操作入口是 IDbContext。IDbContext 仅有两个 Query、两个 Insert、两个 Update 、两个 Delete 和一个 TrackEntity 方法,以及一个 CurrentSession 的属性,设计很简单,但绝对能满足81%的需求(多一点满足,多一分热爱)!
这篇文章,主要介绍 Query 接口使用。

事前准备

实体:

public enum Gender
{
Man = 1,
Woman
} [TableAttribute("Users")]
public class User
{
[Column(IsPrimaryKey = true)]
[AutoIncrementAttribute]
public int Id { get; set; }
public string Name { get; set; }
public Gender? Gender { get; set; }
public int? Age { get; set; }
public int? CityId { get; set; }
public DateTime? OpTime { get; set; }
} public class City
{
[Column(IsPrimaryKey = true)]
public int Id { get; set; }
public string Name { get; set; }
public int ProvinceId { get; set; }
} public class Province
{
[Column(IsPrimaryKey = true)]
public int Id { get; set; }
public string Name { get; set; }
}

首先,创建一个 DbContext:

IDbContext context = new MsSqlContext(DbHelper.ConnectionString);

再创建一个 IQuery<T>:

IQuery<User> q = context.Query<User>();

基本查询

IQuery<User> q = context.Query<User>();
q.Where(a => a.Id > 0).FirstOrDefault();
q.Where(a => a.Id > 0).ToList();
q.Where(a => a.Id > 0).OrderBy(a => a.Age).ToList();
q.Where(a => a.Id > 0).Take(999).OrderBy(a => a.Age).ToList(); //分页。避免生成的 sql 语句太长占篇幅,只选取 Id 和 Name 两个字段
q.Where(a => a.Id > 0).OrderBy(a => a.Age).ThenByDesc(a => a.Id).Select(a => new { a.Id, a.Name }).Skip(1).Take(999).ToList();
/*
* SELECT TOP (999) [T].[Id] AS [Id],[T].[Name] AS [Name] FROM (SELECT [Users].[Id] AS [Id],[Users].[Name] AS [Name],ROW_NUMBER() OVER(ORDER BY [Users].[Age] ASC,[Users].[Id] DESC) AS [ROW_NUMBER_0] FROM [Users] AS [Users] WHERE [Users].[Id] > 0) AS [T] WHERE [T].[ROW_NUMBER_0] > 1
*/ //如果需要多个条件的话
q.Where(a => a.Id > 0).Where(a => a.Name.Contains("lu")).ToList();
/*
* SELECT [Users].[Id] AS [Id],[Users].[Name] AS [Name],[Users].[Gender] AS [Gender],[Users].[Age] AS [Age],[Users].[CityId] AS [CityId],[Users].[OpTime] AS [OpTime] FROM [Users] AS [Users] WHERE ([Users].[Id] > 0 AND [Users].[Name] LIKE '%' + N'lu' + '%')
*/ //选取指定字段
q.Select(a => new { a.Id, a.Name, a.Age }).ToList();
//或者
q.Select(a => new User() { Id = a.Id, Name = a.Name, Age = a.Age }).ToList();
/*
* SELECT [Users].[Id] AS [Id],[Users].[Name] AS [Name],[Users].[Age] AS [Age] FROM [Users] AS [Users]
*/

连接查询

建立连接:

MsSqlContext context = new MsSqlContext(DbHelper.ConnectionString);
IQuery<User> users = context.Query<User>();
IQuery<City> cities = context.Query<City>();
IQuery<Province> provinces = context.Query<Province>(); IJoiningQuery<User, City> user_city = users.InnerJoin(cities, (user, city) => user.CityId == city.Id);
IJoiningQuery<User, City, Province> user_city_province = user_city.InnerJoin(provinces, (user, city, province) => city.ProvinceId == province.Id);

只获取 UserId,CityName,ProvinceName:

user_city_province.Select((user, city, province) => new { UserId = user.Id, CityName = city.Name, ProvinceName = province.Name }).Where(a => a.UserId == 1).ToList();
/*
* SELECT [Users].[Id] AS [UserId],[City].[Name] AS [CityName],[Province].[Name] AS [ProvinceName] FROM [Users] AS [Users] INNER JOIN [City] AS [City] ON [Users].[CityId] = [City].[Id] INNER JOIN [Province] AS [Province] ON [City].[ProvinceId] = [Province].[Id] WHERE [Users].[Id] = 1
*/

调用 Select 方法返回一个包含所有信息的 IQuery<T> 对象:

var view = user_city_province.Select((user, city, province) => new { User = user, City = city, Province = province });

查出一个用户及其隶属的城市和省份:

view.Where(a => a.User.Id == 1).ToList();
/*
* SELECT [Users].[Id] AS [Id],[Users].[Name] AS [Name],[Users].[Gender] AS [Gender],[Users].[Age] AS [Age],[Users].[CityId] AS [CityId],[Users].[OpTime] AS [OpTime],[City].[Id] AS [Id0],[City].[Name] AS [Name0],[City].[ProvinceId] AS [ProvinceId],[Province].[Id] AS [Id1],[Province].[Name] AS [Name1] FROM [Users] AS [Users] INNER JOIN [City] AS [City] ON [Users].[CityId] = [City].[Id] INNER JOIN [Province] AS [Province] ON [City].[ProvinceId] = [Province].[Id] WHERE [Users].[Id] = 1
*/

这时候也可以选取指定的字段:

view.Where(a => a.User.Id == 1).Select(a => new { UserId = a.User.Id, CityName = a.City.Name, ProvinceName = a.Province.Name }).ToList();
/*
* SELECT [Users].[Id] AS [UserId],[City].[Name] AS [CityName],[Province].[Name] AS [ProvinceName] FROM [Users] AS [Users] INNER JOIN [City] AS [City] ON [Users].[CityId] = [City].[Id] INNER JOIN [Province] AS [Province] ON [City].[ProvinceId] = [Province].[Id] WHERE [Users].[Id] = 1
*/

Chloe 也支持 Left Join、Right Join、Full Join 连接,用法和 Inner Join 一样,就不一一介绍了。

聚合函数

IQuery<User> q = context.Query<User>();

q.Select(a => DbFunctions.Count()).First();
/*
* SELECT TOP (1) COUNT(1) AS [C] FROM [Users] AS [Users]
*/ q.Select(a => new { Count = DbFunctions.Count(), LongCount = DbFunctions.LongCount(), Sum = DbFunctions.Sum(a.Age), Max = DbFunctions.Max(a.Age), Min = DbFunctions.Min(a.Age), Average = DbFunctions.Average(a.Age) }).First();
/*
* SELECT TOP (1) COUNT(1) AS [Count],COUNT_BIG(1) AS [LongCount],SUM([Users].[Age]) AS [Sum],MAX([Users].[Age]) AS [Max],MIN([Users].[Age]) AS [Min],CAST(AVG([Users].[Age]) AS FLOAT) AS [Average] FROM [Users] AS [Users]
*/ var count = q.Count();
/*
* SELECT COUNT(1) AS [C] FROM [Users] AS [Users]
*/ var longCount = q.LongCount();
/*
* SELECT COUNT_BIG(1) AS [C] FROM [Users] AS [Users]
*/ var sum = q.Sum(a => a.Age);
/*
* SELECT SUM([Users].[Age]) AS [C] FROM [Users] AS [Users]
*/ var max = q.Max(a => a.Age);
/*
* SELECT MAX([Users].[Age]) AS [C] FROM [Users] AS [Users]
*/ var min = q.Min(a => a.Age);
/*
* SELECT MIN([Users].[Age]) AS [C] FROM [Users] AS [Users]
*/ var avg = q.Average(a => a.Age);
/*
* SELECT CAST(AVG([Users].[Age]) AS FLOAT) AS [C] FROM [Users] AS [Users]
*/

分组查询

IQuery<User> q = context.Query<User>();

IGroupingQuery<User> g = q.Where(a => a.Id > 0).GroupBy(a => a.Age);
g = g.Having(a => a.Age > 1 && DbFunctions.Count() > 0); g.Select(a => new { a.Age, Count = DbFunctions.Count(), Sum = DbFunctions.Sum(a.Age), Max = DbFunctions.Max(a.Age), Min = DbFunctions.Min(a.Age), Avg = DbFunctions.Average(a.Age) }).ToList();
/*
* SELECT [Users].[Age] AS [Age],COUNT(1) AS [Count],SUM([Users].[Age]) AS [Sum],MAX([Users].[Age]) AS [Max],MIN([Users].[Age]) AS [Min],CAST(AVG([Users].[Age]) AS FLOAT) AS [Avg] FROM [Users] AS [Users] WHERE [Users].[Id] > 0 GROUP BY [Users].[Age] HAVING ([Users].[Age] > 1 AND COUNT(1) > 0)
*/

SqlQuery

上面是纯面向对象的方式查询。连接查询、聚合查询、分组查询如此轻松,有没有觉得很方便?当然,始终和 linq 那种接近 sql 的 from v in q where v > 3 select v 写法没法比!同时,ORM始终是个工具,它并不是万能的,对于一些复杂的语句,还是得需要手写,因此,DbContext 也提供原生 sql 查询接口:

context.SqlQuery<User>("select Id,Name,Age from Users where Name=@name", DbParam.Create("@name", "lu")).ToList();
context.SqlQuery<int>("select Id from Users").ToList();

经测试,非 Debug 情况下,且都经过预热后,相同的查询在速度、性能上与 Dapper 相当,甚至比 Dapper 还快那么一丢丢。

使用进阶

IQuery<T> 接口支持连接查询、聚合查询、分组查询,这几个接口配合使用可以减少很多我们开发中的烦恼。比如:

去视图

做数据库开发,多表关联的数据结构肯定不少,难免会有多表连接查询,很多时候,为了方便查询,一般我们都会建立视图。在我看来视图很烦,真的烦。

int 烦 = 0;

1.建视图的时候,字段多的话,烦++,如果出现字段重名的情况,必须起别名,烦++。

2.视图建立起来了以后,查询是方便了,但后面维护就不那么友好了,比如某个表字段名改了、增加一个字段、删除一个字段等情况,得修改相应的视图(1个或多个),烦++;同时又要去修改相映射的实体,烦++。总之,Console.Write("烦烦烦: " + 烦.ToString()); 对于我这种懒程序员,这简直就是种煎熬!如果一套 ORM 支持连接查询,在一定程度上可以减少在数据库上建视图数量,无形中省出好多时间。

为了让 Chloe 支持连接查询,费了我不少劲。连接查询的好处可以看上面连接查询部分。

勉强应付一些复杂查询

比如,本文中的 User 表、City 表,他们的关系是一个 User 隶属一个 City,一个 City 有多个用户。假设,现在有需求要查出 City 的信息,同时也要把该 City 下用户最小的年龄输出,如果用原生 sql 写的话大概是:

select City.*,T.MinAge from City left join (select CityId,Min(Users.Age) as MinAge from Users group by Users.CityId) as T on City.Id=T.CityId

虽然也不是很复杂。来看看 Chloe 如何实现:

IQuery<User> users = context.Query<User>();
IQuery<City> cities = context.Query<City>();
var gq = users.GroupBy(a => a.CityId).Select(a => new { a.CityId, MinAge = DbFunctions.Min(a.Age) }); cities.LeftJoin(gq, (city, g) => city.Id == g.CityId).Select((city, g) => new { City = city, MinAge = g.MinAge }).ToList();
/*
* SELECT [T].[MinAge] AS [MinAge],[City].[Id] AS [Id],[City].[Name] AS [Name],[City].[ProvinceId] AS [ProvinceId] FROM [City] AS [City] LEFT JOIN (SELECT [Users].[CityId] AS [CityId],MIN([Users].[Age]) AS [MinAge] FROM [Users] AS [Users] GROUP BY [Users].[CityId]) AS [T] ON [City].[Id] = [T].[CityId]
*/

完全可以用面向对象的方式就可以实现,怎么样?很实用吧,免去拼 sql,让更多的时间去做业务开发!

更多的用法还有待挖掘。

支持的lambda

Chloe 查询条件依赖 lambda 表达式,从对 lambda 表达式树零认知到完成对其解析这块,花了我好多精力,费了好多神,掉了不少头发。现在对谓语支持很丰富,可以说爱怎么写就怎么写~

IQuery<User> q = context.Query<User>();

List<int> ids = new List<int>();
ids.Add(1);
ids.Add(2);
ids.Add(2); string name = "lu";
string nullString = null;
bool b = false;
bool b1 = true; q.Where(a => true).ToList();
q.Where(a => a.Id == 1).ToList();
q.Where(a => a.Id == 1 || a.Id > 1).ToList();
q.Where(a => a.Id == 1 && a.Name == name && a.Name == nullString && a.Id == FeatureTest.ID).ToList();
q.Where(a => ids.Contains(a.Id)).ToList();
q.Where(a => !b == (a.Id > 0)).ToList();
q.Where(a => a.Id > 0).Where(a => a.Id == 1).ToList();
q.Where(a => !(a.Id > 10)).ToList();
q.Where(a => !(a.Name == name)).ToList();
q.Where(a => a.Name != name).ToList();
q.Where(a => a.Name == name).ToList();
q.Where(a => (a.Name == name) == (a.Id > 0)).ToList();
q.Where(a => a.Name == (a.Name ?? name)).ToList();
q.Where(a => (a.Age == null ? 0 : 1) == 1).ToList(); //运算操作符
q.Select(a => new
{
Add = 1 + 2,
Subtract = 2 - 1,
Multiply = 2 * 11,
Divide = 4 / 2,
And = true & false,
IntAnd = 1 & 2,
Or = true | false,
IntOr = 3 | 1,
}).ToList();

常用的函数

  IQuery<User> q = context.Query<User>();

  var space = new char[] { ' ' };

  DateTime startTime = DateTime.Now;
DateTime endTime = DateTime.Now.AddDays(1);
q.Select(a => new
{
Id = a.Id, String_Length = (int?)a.Name.Length,//LEN([Users].[Name])
Substring = a.Name.Substring(0),//SUBSTRING([Users].[Name],0 + 1,LEN([Users].[Name]))
Substring1 = a.Name.Substring(1),//SUBSTRING([Users].[Name],1 + 1,LEN([Users].[Name]))
Substring1_2 = a.Name.Substring(1, 2),//SUBSTRING([Users].[Name],1 + 1,2)
ToLower = a.Name.ToLower(),//LOWER([Users].[Name])
ToUpper = a.Name.ToUpper(),//UPPER([Users].[Name])
IsNullOrEmpty = string.IsNullOrEmpty(a.Name),//太长,不贴了
Contains = (bool?)a.Name.Contains("s"),//太长,略
Trim = a.Name.Trim(),//RTRIM(LTRIM([Users].[Name]))
TrimStart = a.Name.TrimStart(space),//LTRIM([Users].[Name])
TrimEnd = a.Name.TrimEnd(space),//RTRIM([Users].[Name])
StartsWith = (bool?)a.Name.StartsWith("s"),//太长,略
EndsWith = (bool?)a.Name.EndsWith("s"),//太长,略 SubtractTotalDays = endTime.Subtract(startTime).TotalDays,//CAST(DATEDIFF(DAY,@P_0,@P_1)
SubtractTotalHours = endTime.Subtract(startTime).TotalHours,//CAST(DATEDIFF(HOUR,@P_0,@P_1)
SubtractTotalMinutes = endTime.Subtract(startTime).TotalMinutes,//CAST(DATEDIFF(MINUTE,@P_0,@P_1)
SubtractTotalSeconds = endTime.Subtract(startTime).TotalSeconds,//CAST(DATEDIFF(SECOND,@P_0,@P_1)
SubtractTotalMilliseconds = endTime.Subtract(startTime).TotalMilliseconds,//CAST(DATEDIFF(MILLISECOND,@P_0,@P_1) Now = DateTime.Now,//GETDATE()
UtcNow = DateTime.UtcNow,//GETUTCDATE()
Today = DateTime.Today,//CAST(GETDATE() AS DATE)
Date = DateTime.Now.Date,//CAST(GETDATE() AS DATE)
Year = DateTime.Now.Year,//DATEPART(YEAR,GETDATE())
Month = DateTime.Now.Month,//DATEPART(MONTH,GETDATE())
Day = DateTime.Now.Day,//DATEPART(DAY,GETDATE())
Hour = DateTime.Now.Hour,//DATEPART(HOUR,GETDATE())
Minute = DateTime.Now.Minute,//DATEPART(MINUTE,GETDATE())
Second = DateTime.Now.Second,//DATEPART(SECOND,GETDATE())
Millisecond = DateTime.Now.Millisecond,//DATEPART(MILLISECOND,GETDATE())
DayOfWeek = DateTime.Now.DayOfWeek,//(DATEPART(WEEKDAY,GETDATE()) - 1) Int_Parse = int.Parse(""),//CAST(N'1' AS INT)
Int16_Parse = Int16.Parse(""),//CAST(N'11' AS SMALLINT)
Long_Parse = long.Parse(""),//CAST(N'2' AS BIGINT)
Double_Parse = double.Parse(""),//CAST(N'3' AS FLOAT)
Float_Parse = float.Parse(""),//CAST(N'4' AS REAL)
Decimal_Parse = decimal.Parse(""),//CAST(N'5' AS DECIMAL)
Guid_Parse = Guid.Parse("D544BC4C-739E-4CD3-A3D3-7BF803FCE179"),//CAST(N'xxx' AS UNIQUEIDENTIFIER) AS [Guid_Parse] Bool_Parse = bool.Parse(""),//CASE WHEN CAST(N'1' AS BIT) = CAST(1 AS BIT) THEN CAST(1 AS BIT) WHEN NOT (CAST(N'1' AS BIT) = CAST(1 AS BIT)) THEN CAST(0 AS BIT) ELSE NULL END AS [Bool_Parse]
DateTime_Parse = DateTime.Parse("1992-1-16"),//CAST(N'1992-1-16' AS DATETIME) AS [DateTime_Parse] B = a.Age == null ? false : a.Age > 1,
}).ToList();

Chloe 的查询,基本就这些用法。因为查询接口直接借鉴 linq,所以,看起来就好像在介绍 linq 一样,抱歉- -。也正因为这点,之前我把项目中的 EF 替换成 Chloe 的时候,因为我个人不怎么用 linq 的 from in select 那种语法,所以,替换的时候几乎不用改什么代码,就可以成功编译运行。EF 对实体间的关系处理得非常好,如一对多,一对一导航,Chloe 倒没那么强大。就目前的 Chloe 的 Query 接口,基本可以满足大部分查询需求了。

现在市面上各种ORM,层出不穷,有人可能会问 LZ 为什么还要重复造*?

  1. 这确实是一个ORM齐放的年代,各色各样,千奇百怪的都有。但让人满意的框架(EF除外,EF在我心中是神一样的存在)少之又少。做得不错的,也总有些方面不足,恰恰却因为一些小小的不足让我止步,如实体复杂,不支持 lambda,支持lambda的但支持的写法又不多,连接查询不是很友好、便捷等等,都怪我太挑剔,抱歉。
  2. 文章开头也说过,增删查改,烦了。想用业余时间做点有意思的东西,提升自己编码能力的同时也可以学到更多知识。因为写了这个框架,我对面对对象的理解更加深刻了,如果不尝试的话,我估计我在程序员职业生涯内连个抽象类、接口都不会设计,更别说会什么设计模式,面对对象编程原则了。之所以选择做 ORM,因为 ORM 很贴切我们日常开发,只要涉及数据库,就可以用到!
  3. 如果上面两点还不足以让您明白我为什么要造*,那最后我要告诉您的是:我是一枚任性的程序员,我就是要造*!

[开源].NET数据库访问框架Chloe.ORM

结语

Chloe.ORM 完全开源,遵循 Apache2.0 协议,托管于GitHub,供大伙学习参考,如果能参与开发与完善 Chloe 那再好不过了,项目地址:https://github.com/shuxinqin/Chloe。感兴趣或觉得不错的望赏个star,不胜感激!

若能顺手点个赞,更加感谢!