Recently, I encountered a small obstacle while sending data from a Vue.js interface to the backend. It seemed like everything was fine, but then you realize the data didn’t arrive. At those moments, the question “Where did I go wrong?” comes to mind. I filled out a form on the Vue.js side, clicked the ‘Send’ button, but unfortunately, that data didn’t reach the backend. After some trials, I realized the issue was a simple configuration mistake. Nonetheless, such setbacks don’t discourage us; instead, they make us more cautious.
This situation made me think a bit. The importance of communication between frontend and backend, right? Imagine two systems that don’t understand each other. No matter how well they give commands, if one side doesn’t understand, the outcome is disappointment. In our work, the same applies. The data sent from Vue.js must be properly received and processed by the C# side with Dapper. If there’s a disconnect in this chain, all efforts can go to waste. That’s why establishing these links reliably is crucial, both during development and in live environments.
This article will step-by-step explain how to send data received from Vue.js to a PostgreSQL database using a C# REST API and Dapper. Sharing my real experiences and practical tips, I hope it sheds light for those facing similar issues.
First, let’s assume we have created a backend REST API project. I usually work with C# and .NET Core for such projects. I prefer PostgreSQL as the database because it’s flexible and powerful. Our API will have a controller to handle incoming user data from Vue.js and a service layer to process this data.
Dapper is a high-performance, simple ORM (Object-Relational Mapper) developed for .NET. It simplifies converting SQL query results directly into C# objects, speeding up the process. Especially when working with large data sets or performance-critical situations, Dapper can be a lifesaver. Think of it as using an optimized, ready-made tool instead of writing everything from scratch.
Data Sending Process: From Vue.js to C# API
Suppose we have a form on the Vue.js side with fields like username and email. After users fill in this information and click the ‘Save’ button, Vue.js should use a library like “axios” to send this data via an HTTP POST request to our C# API. The content of this request is usually in JSON format.
On the API side, we need an endpoint to handle this request. Typically, this will be a method defined inside a controller. For example, when a POST request comes to a URL like `/api/users`, this method will be triggered. It will take the incoming JSON data and convert it into a C# object, for example, `UserModel`. It’s like translating a language; converting JSON data from the frontend into a C# object that the backend understands.
A critical point here is that the data structure sent from the frontend should match the model in the backend. If the field names in Vue.js don’t exactly match the property names of the C# model, Dapper or the .NET Core model binding won’t be able to correctly match the data. This can lead to the initial hiccup I experienced. Rendering, types, all should be consistent.
Let’s say we’ve received the data as a `UserModel` object. The next step is to save this data to PostgreSQL. Here, Dapper plays a role. After establishing the database connection, we prepare our INSERT statement. Dapper’s `ExecuteAsync` method is perfect for this job. This method runs the query and returns the number of affected rows. Of course, to prevent SQL injection and similar security issues, using parameterized queries is essential—think of giving a key with a lock.
Now, regarding the mistake I fixed in my code. Initially, I tried passing the JSON from Vue.js directly as a dictionary to Dapper. But that didn’t allow the parameters to be correctly mapped to the database. Then I realized I needed to bind the incoming data to the C# model first, and then pass this model object as a parameter in the Dapper query. This simple change was key to solving the problem.
Here is how my initial incorrect approach looked:
// WRONG: Processed incoming data as a dynamic dictionary public async Task<IActionResult> PostUserIncorrect(dynamic userData) { var userDict = (IDictionary<string, object>)userData; var sql = "INSERT INTO Users (Name, Email) VALUES (@Name, @Email)"; // Parameter mapping doesn't work properly await _dbConnection.ExecuteAsync(sql, userDict); return Ok(); }In this code, I tried to process the data as a dictionary directly from `dynamic`, but Dapper’s parameter mapping didn’t work correctly because of this. The parameters `@Name` and `@Email` didn’t match the dictionary keys properly, causing issues.
So, I changed it to the correct method:
// CORRECT: Bind incoming data to model and use it with Dapper public class UserModel { public string Name { get; set; } public string Email { get; set; } }public async Task<IActionResult> PostUserCorrect([FromBody] UserModel user) { var sql = "INSERT INTO Users (Name, Email) VALUES (@Name, @Email)"; // Dapper automatically matches properties with query parameters await _dbConnection.ExecuteAsync(sql, user); return Ok("User successfully saved."); }
As you can see, with the `[FromBody]` attribute, we directly bind the incoming JSON data to the `UserModel`. When calling `ExecuteAsync` from Dapper, the properties of the `UserModel` object (`Name` and `Email`) automatically match with the SQL parameters `@Name` and `@Email`. This not only produces cleaner code but also enhances security. This simple adjustment resolved my initial problem.
Also, when debugging this data transfer process, the ‘Network’ tab in your browser developer tools is very helpful. You can see the request content and the response details. It’s like playing detective—tracking exactly what was sent, received, and processed.
Ensuring the `Users` table in PostgreSQL is built correctly is also important. The `Name` and `Email` columns should have appropriate data types (such as `VARCHAR` or `TEXT`). If the database schema is mismatched, errors will occur again. Do not overlook these infrastructural checks.
In conclusion, sending data from Vue.js to a C# REST API with Dapper and PostgreSQL becomes quite straightforward and efficient when models are properly designed and parameterized queries are used. The robustness of these links is fundamental to reliable applications. Think of it as building a solid foundation—resilient even to earthquakes. I hope this practical example helps in your projects.