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Introduction to Entity Framework Core
Introduction to Entity Framework Core

In this post I am going to look into Entity Framework Core, present the new features, the similarities and differences from EF6. ? hope that the people who will read this post are familiar with what EF is. In a nutshell EF is the official data access technology platform from Microsoft. It is a  mature platform since it is almost 9 years old. It is a new way of accessing and storing data, a set of .NET APIs for accessing data from any data store. Going into more details Entity Framework fits into a category of data access technologies called Object Relational Mappers or ORMs. ORMs reduce the friction between how data is structured in a relational database and how you define your classes. Without an ORM, we typically have to write a lot of code to transform database results into instances of the classes. An ORM allows us to express our queries using our classes, and then the ORM builds and executes the relevant SQL for us, as well as materializing objects from the data that came back from the database. ?y using an ORM we can really eliminate redundant data interaction tasks and we can really enhance developer productivity. Instead of writing the relevant SQL to target whatever relational database you’re working with, Entity Framework uses the LINQ syntax that’s part of the .NET framework. LINQ to Entities allows developers to use strongly-typed query language regardless of which database they’re targeting. When we use EF Core in your application, firstly you need to create your domain classes. These are pure .Net classes or objects and have nothing to do with EF Core.Then you use Entity Framework Core APIs to define a data model based on those domain classes. You also use Entity Framework APIs to write and execute LINQ to Entities Queries against those classes. When you need to save data back to the database you use SaveChanges methods. EF Core keeps track of the state of objects that it’s aware of, it’ll determine the SQL it needs to save data back to the database. Entity Framework will transform your LINQ to Entities Queries into SQL, execute that SQL, and then create objects from query results. As you many know, Entity Framework development was moved to CodePlex and became open source.  Entity Framework 6 has since then been moved to GitHub. The URL is github.com/aspnet/EntityFramework. You can download and experiment with the latest version, you can clone the repository, add your own fixes/features, and then submit those as pull requests to become part of Entity Framework Core. All pull requests that are submitted from the community are examined from the ADO.Net team before becoming part of EF Core. Another thing I wanted to mention is that different people call EF with different names. Let me be clear on that so that there is no confusion. EF Core was released in late June of 2016 and it was called Entity Framework 7, but in January 2016, its name was changed to Entity Framework Core. At the same time ASP.NET 5 was changed to ASP.NET Core. EF Core is not simply an update from EF6, it’s a different kind of Entity Framework, it is a complete rewrite. For developers who have invested time and effort on EF6 and have projects on EF6 should not worry as it will be actively supported. Entity Framework Core can run  on .NET Core. NET Core  can run on the CoreCLR and CoreCLR can run natively, not only in Windows, but also on Mac and Linux. EF Core can also run inside the full .NET Framework that is any version that is 4.5.1 or newer. Entity Framework Core is a brand new set of APIs and it doesn’t have all of the features that you might be used to with Entity Framework so it’s important to understand that before starting a  new project with Entity Framework Core. If you want to target cross platform or UWP apps then you have no other way but to use Entity Framework Core. For .NET apps that you want to run on Windows, you can still use Entity Framework 6. If you are building an ASP.NET Core applications that will run on Windows you can still use Entity Framework 6, so bear that in mind as well. There are Entity Framework features that will never be part of the Entity Framework Core, for example in EF Core there is no support for a designer-based model, there’s no EDMX and it isn’t supported by the Entity Framework Designer. Having said that in EF Core you can can still define a data model with classes and a DbContext. The DbContext API is still there and so is DbSets. You can also create and migrate to the database as your model changes, and you can still query with LINQ to Entities. Entity Framework continues to track changes to entities in memory. There are some new features in  EF Core that there were no available in earlier versions. In EF Core we have the ability to do batch inserts, updates, and deletes. We can specify unique foreign keys in entities and LINQ queries have become smarter and more efficient. In EF Core there is an In Memory provider that makes it really easy to build automated tests using Entity Framework without hitting the database. EF Core makes it really easy to use with inversion of control patterns and dependency injection. EF Core has the ability to populate backing fields not just properties. EF Core supports mapping to IEnumerables. Hope you have a better understanding of EF Core now. Hope it helps!!!  


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Trying out MongoDB with EF Core using Testcontainers
Trying out MongoDB with EF Core using Testcontaine ...

Helping developers use both relational and non-relational databases effectively was one of the original tenets of EF Core. To this end, there has been an EF Core database provider for Azure Cosmos DB document databases for many years now. Recently, the EF Core team has been collaborating with engineers from MongoDB to bring support for MongoDB to EF Core. The initial result of this collaboration is the first preview release of the MongoDB provider for EF Core. In this post, we will try out the MongoDB provider for EF Core by using it to Map a C# object model to documents in a MongoDB database Use EF to save some documents to the database Write LINQ queries to retrieve documents from the database Make changes to a document and use EF’s change tracking to update the document The code shown in this post can be found on GitHub. Testcontainers It’s very easy to get a MongoDB database in the cloud that you can use to try things out. However, Testcontainers is another way to test code with different database systems which is particularly suited to Running automated tests against the database Creating standalone reproductions when reporting issues Trying out new things with minimal setup Testcontainers are distributed as NuGet packages that take care of running a container containing a configured ready-to-use database system. The containers use Docker or a Docker-alternative to run, so this may need to be installed on your machine if you don’t already have it. See Welcome to Testcontainers for .NET! for more details. Other than starting Docker, you don’t need to do anything else except import the NuGet package. The C# project We’ll use a simple console application to try out MongoDB with EF Core. This project needs two package references MongoDB.EntityFrameworkCore to install the EF Core provider. This package also transitives installs the common EF Core packages and the MongoDB.Driver package which is used by the EF Provider to access the MongoDB database. Testcontainers.MongoDb to install the pre-defined Testcontainer for MongoDB. The full csproj file looks like this <Project Sdk="Microsoft.NET.Sdk"> <PropertyGroup> <OutputType>Exe</OutputType> <TargetFramework>net7.0</TargetFramework> <ImplicitUsings>enable</ImplicitUsings> <Nullable>enable</Nullable> <RootNamespace /> </PropertyGroup> <ItemGroup> <PackageReference Include="Testcontainers.MongoDB" Version="3.5.0" /> <PackageReference Include="MongoDB.EntityFrameworkCore" Version="7.0.0-preview.1" /> </ItemGroup> </Project> Remember, the full project is available to download from GitHUb. The object model We’ll map a simple object model of customers and their addresses public class Customer { public Guid Id { get; set; } public required string Name { get; set; } public required Species Species { get; set; } public required ContactInfo ContactInfo { get; set; } } public class ContactInfo { public required Address ShippingAddress { get; set; } public Address? BillingAddress { get; set; } public required PhoneNumbers Phones { get; set; } } public class PhoneNumbers { public PhoneNumber? HomePhone { get; set; } public PhoneNumber? WorkPhone { get; set; } public PhoneNumber? MobilePhone { get; set; } } public class PhoneNumber { public required int CountryCode { get; set; } public required string Number { get; set; } } public class Address { public required string Line1 { get; set; } public string? Line2 { get; set; } public string? Line3 { get; set; } public required string City { get; set; } public required string Country { get; set; } public required string PostalCode { get; set; } } public enum Species { Human, Dog, Cat } Since MongoDB works with documents, we’re going to map this model to a top level Customer document, with the addresses and phone numbers embedded in this document. We’ll see how to do this in the next section. Creating the EF model EF works by building a model of the mapped CLR types, such as those for Customer, etc. in the previous section. This model defines the relationships between types in the model, as well as how each type maps to the database. Luckily there is not much to do here, since EF uses a set of model building conventions that generate a model based on input from both the model types and the database provider. This means that for relational databases, each type gets mapped to a different table by convention. For document databases like Azure CosmosDB and now MongoDB, only the top-level type (Customer in our example) is mapped to its own document. Other types referenced from the top-level types are, by-convention, included in the main document. This means that the only thing EF needs to know to build a model is the top-level type, and that the MongoDB provider should be used. We do this by defining a type that extends from DbContext. For example public class CustomersContext DbContext { private readonly MongoClient _client; public CustomersContext(MongoClient client) { _client = client; } protected override void OnConfiguring(DbContextOptionsBuilder optionsBuilder) => optionsBuilder.UseMongoDB(_client, "efsample"); public DbSet<Customer> Customers => Set<Customer>(); } In this DbContext class UseMongoDB is called, passing in the client driver and the database name. This tells EF Core to use the MongoDB provider when building the model and accessing the database. A DbSet<Customer> property that defines the top-level type for which documents should be modeled. We’ll see later how to create the MongoClient instance and use the DbContext. When we do, examining the model DebugView shows this Model EntityType ContactInfo Owned Properties CustomerId (no field, Guid) Shadow Required PK FK AfterSaveThrow Navigations BillingAddress (Address) ToDependent ContactInfo.BillingAddress#Address (Address) Phones (PhoneNumbers) ToDependent PhoneNumbers ShippingAddress (Address) ToDependent ContactInfo.ShippingAddress#Address (Address) Keys CustomerId PK Foreign keys ContactInfo {'CustomerId'} -> Customer {'Id'} Unique Ownership ToDependent ContactInfo Cascade EntityType ContactInfo.BillingAddress#Address (Address) CLR Type Address Owned Properties ContactInfoCustomerId (no field, Guid) Shadow Required PK FK AfterSaveThrow City (string) Required Country (string) Required Line1 (string) Required Line2 (string) Line3 (string) PostalCode (string) Required Keys ContactInfoCustomerId PK Foreign keys ContactInfo.BillingAddress#Address (Address) {'ContactInfoCustomerId'} -> ContactInfo {'CustomerId'} Unique Ownership ToDependent BillingAddress Cascade EntityType ContactInfo.ShippingAddress#Address (Address) CLR Type Address Owned Properties ContactInfoCustomerId (no field, Guid) Shadow Required PK FK AfterSaveThrow City (string) Required Country (string) Required Line1 (string) Required Line2 (string) Line3 (string) PostalCode (string) Required Keys ContactInfoCustomerId PK Foreign keys ContactInfo.ShippingAddress#Address (Address) {'ContactInfoCustomerId'} -> ContactInfo {'CustomerId'} Unique Ownership ToDependent ShippingAddress Cascade EntityType Customer Properties Id (Guid) Required PK AfterSaveThrow ValueGenerated.OnAdd Name (string) Required Species (Species) Required Navigations ContactInfo (ContactInfo) ToDependent ContactInfo Keys Id PK EntityType PhoneNumbers Owned Properties ContactInfoCustomerId (no field, Guid) Shadow Required PK FK AfterSaveThrow Navigations HomePhone (PhoneNumber) ToDependent PhoneNumbers.HomePhone#PhoneNumber (PhoneNumber) MobilePhone (PhoneNumber) ToDependent PhoneNumbers.MobilePhone#PhoneNumber (PhoneNumber) WorkPhone (PhoneNumber) ToDependent PhoneNumbers.WorkPhone#PhoneNumber (PhoneNumber) Keys ContactInfoCustomerId PK Foreign keys PhoneNumbers {'ContactInfoCustomerId'} -> ContactInfo {'CustomerId'} Unique Ownership ToDependent Phones Cascade EntityType PhoneNumbers.HomePhone#PhoneNumber (PhoneNumber) CLR Type PhoneNumber Owned Properties PhoneNumbersContactInfoCustomerId (no field, Guid) Shadow Required PK FK AfterSaveThrow CountryCode (int) Required Number (string) Required Keys PhoneNumbersContactInfoCustomerId PK Foreign keys PhoneNumbers.HomePhone#PhoneNumber (PhoneNumber) {'PhoneNumbersContactInfoCustomerId'} -> PhoneNumbers {'ContactInfoCustomerId'} Unique Ownership ToDependent HomePhone Cascade EntityType PhoneNumbers.MobilePhone#PhoneNumber (PhoneNumber) CLR Type PhoneNumber Owned Properties PhoneNumbersContactInfoCustomerId (no field, Guid) Shadow Required PK FK AfterSaveThrow CountryCode (int) Required Number (string) Required Keys PhoneNumbersContactInfoCustomerId PK Foreign keys PhoneNumbers.MobilePhone#PhoneNumber (PhoneNumber) {'PhoneNumbersContactInfoCustomerId'} -> PhoneNumbers {'ContactInfoCustomerId'} Unique Ownership ToDependent MobilePhone Cascade EntityType PhoneNumbers.WorkPhone#PhoneNumber (PhoneNumber) CLR Type PhoneNumber Owned Properties PhoneNumbersContactInfoCustomerId (no field, Guid) Shadow Required PK FK AfterSaveThrow CountryCode (int) Required Number (string) Required Keys PhoneNumbersContactInfoCustomerId PK Foreign keys PhoneNumbers.WorkPhone#PhoneNumber (PhoneNumber) {'PhoneNumbersContactInfoCustomerId'} -> PhoneNumbers {'ContactInfoCustomerId'} Unique Ownership ToDependent WorkPhone Cascade Looking at this model, it can be seen that EF created owned entity types for the ContactInfo, Address, PhoneNumber and PhoneNumbers types, even though only the Customer type was referenced directly from the DbContext. These other types were discovered and configured by the model-building conventions. Create the MongoDB test container We now have a model and a DbContext. Next we need an actual MongoDB database, and this is where Testcontainers come in. There are Testcontainers available for many different types of database, and they all work in a very similar way. That is, a container is created using the appropriate DbBuilder, and then that container is started. For example await using var mongoContainer = new MongoDbBuilder() .WithImage("mongo6.0") .Build(); await mongoContainer.StartAsync(); And that’s it! We now have a configured, clean MongoDB instance running locally with which we can do what we wish, before just throwing it away. Save data to MongoDB Let’s use EF Core to write some data to the MongoDB database. To do this, we’ll need to create a DbContext instance, and for this we need a MongoClient instance from the underlying MongoDB driver. Often, in a real app, the MongoClient instance and the DbContext instance will be obtained using dependency injection. For the sake of simplicity, we’ll just new them up here var mongoClient = new MongoClient(mongoContainer.GetConnectionString()); await using (var context = new CustomersContext(mongoClient)) { // ... } Notice that the Testcontainer instance provides the connection string we need to connect to our MongoDB test database. To save a new Customer document, we’ll use Add to start tracking the document, and then call SaveChangesAsync to insert it into the database. await using (var context = new CustomersContext(mongoClient)) { var customer = new Customer { Name = "Willow", Species = Species.Dog, ContactInfo = new() { ShippingAddress = new() { Line1 = "Barking Gate", Line2 = "Chalk Road", City = "Walpole St Peter", Country = "UK", PostalCode = "PE14 7QQ" }, BillingAddress = new() { Line1 = "15a Main St", City = "Ailsworth", Country = "UK", PostalCode = "PE5 7AF" }, Phones = new() { HomePhone = new() { CountryCode = 44, Number = "7877 555 555" }, MobilePhone = new() { CountryCode = 1, Number = "(555) 2345-678" }, WorkPhone = new() { CountryCode = 1, Number = "(555) 2345-678" } } } }; context.Add(customer); await context.SaveChangesAsync(); } If we look at the JSON (actually, BSON, which is a more efficient binary representation for JSON documents) document created in the database, we can see it contains nested documents for all the contact information. This is different from what EF Core would do for a relational database, where each type would have been mapped to its own top-level table. { "_id" "CSUUID(\"9a97fd67-515f-4586-a024-cf82336fc64f\")", "Name" "Willow", "Species" 1, "ContactInfo" { "BillingAddress" { "City" "Ailsworth", "Country" "UK", "Line1" "15a Main St", "Line2" null, "Line3" null, "PostalCode" "PE5 7AF" }, "Phones" { "HomePhone" { "CountryCode" 44, "Number" "7877 555 555" }, "MobilePhone" { "CountryCode" 1, "Number" "(555) 2345-678" }, "WorkPhone" { "CountryCode" 1, "Number" "(555) 2345-678" } }, "ShippingAddress" { "City" "Walpole St Peter", "Country" "UK", "Line1" "Barking Gate", "Line2" "Chalk Road", "Line3" null, "PostalCode" "PE14 7QQ" } } } Using LINQ queries EF Core supports LINQ for querying data. For example, to query a single customer using (var context = new CustomersContext(mongoClient)) { var customer = await context.Customers.SingleAsync(c => c.Name == "Willow"); var address = customer.ContactInfo.ShippingAddress; var mobile = customer.ContactInfo.Phones.MobilePhone; Console.WriteLine($"{customer.Id} {customer.Name}"); Console.WriteLine($" Shipping to {address.City}, {address.Country} (+{mobile.CountryCode} {mobile.Number})"); } Running this code results in the following output 336d4936-d048-469e-84c8-d5ebc17754ff Willow Shipping to Walpole St Peter, UK (+1 (555) 2345-678) Notice that the query pulled back the entire document, not just the Customer object, so we are able to access and print out the customer’s contact info without going back to the database. Other LINQ operators can be used to perform filtering, etc. For example, to bring back all customers where the Species is Dog var customers = await context.Customers .Where(e => e.Species == Species.Dog) .ToListAsync(); Updating a document By default, EF tracks the object graphs returned from queries. Then, when SaveChanges or SaveChangesAsync is called, EF detects any changes that have been made to the document and sends an update to MongoDB to update that document. For example using (var context = new CustomersContext(mongoClient)) { var baxter = (await context.Customers.FindAsync(baxterId))!; baxter.ContactInfo.ShippingAddress = new() { Line1 = "Via Giovanni Miani", City = "Rome", Country = "IT", PostalCode = "00154" }; await context.SaveChangesAsync(); } In this case, we’re using FindAsync to query a customer by primary key–a LINQ query would work just as well. After that, we change the shipping address to Rome, and call SaveChangesAsync. EF detects that only the shipping address for a single document has been changed, and so sends a partial update to patch the updated address into the document stored in the MongoDB database. Going forward So far, the MongoDB provider for EF Core is only in its first preview. Full CRUD (creating, reading, updating, and deleting documents) is supported by this preview, but there are some limitations. See the readme on GitHub for more information, and for places to ask questions and file bugs. Learn more To learn more about EF Core and MongoDB See the EF Core documentation to learn more about using EF Core to access all kinds of databases. See the MongoDB documentation to learn more about using MongoDB from any platform. Watch Introducing the MongoDB provider for EF Core on the .NET Data Community Standup. Watch the upcoming Announcing MongoDB Provider for Entity Framework Core on the MongoDB livestream. Summary We used Testcontainers to try out the first preview release of the MongoDB provider for EF Core. Testcontainers allowed us to test MongoDB with very minimal setup, and we were able to create, query, and update documents in the MongoDB database using EF Core. The post Trying out MongoDB with EF Core using Testcontainers appeared first on .NET Blog.


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