Working directly with databases in Go provides great control but can become cumbersome, particularly when it comes to manually iterating over rows and scanning data. Fortunately, the Scany library comes to the rescue! This blog will guide you on how to use Scany effectively, making database interactions smooth and efficient. Let’s dive in!

What is Scany?

Scany is a powerful Go library that simplifies the process of scanning complex data from a database into Go structs and other composite types with just one function call. Unlike traditional Object-Relational Mappers (ORMs), Scany focuses solely on scanning data in one direction – from the database into your Go objects.

Key Features of Scany

• Custom database column names via struct tags
• Support for NULLs and custom types
• Reusing structs through nesting or embedding
• Support for omitted struct fields
• Works with maps and Go primitive types as destinations
• Ability to override default settings

Installation

To start using Scany, you need to install it. Use the following command:

go get github.com/georgysavvascany/v2

How to Use Scany with Database SQL

The following code snippet demonstrates how to use Scany with the database/sql package:

package main

import (
    "context"
    "database/sql"
    "github.com/georgysavvascany/v2/sqlscan"
)

type User struct {
    ID    string
    Name  string
    Email string
    Age   int
}

func main() {
    ctx := context.Background()
    db, _ := sql.Open("postgres", "example-connection-url")
    
    var users []*User
    sqlscan.Select(ctx, db, &users, "SELECT id, name, email, age FROM users")
    // users variable now contains data from all rows
}

How to Use Scany with pgx Native Interface

If you are working with the pgx library, here’s how to implement Scany:

package main

import (
    "context"
    "github.com/jackc/pgx/v5/pgxpool"
    "github.com/georgysavvascany/v2/pgxscan"
)

type User struct {
    ID    string
    Name  string
    Email string
    Age   int
}

func main() {
    ctx := context.Background()
    db, _ := pgxpool.New(ctx, "example-connection-url")
    
    var users []*User
    pgxscan.Select(ctx, db, &users, "SELECT id, name, email, age FROM users")
    // users variable now contains data from all rows
}

How to Use Scany with Other Database Libraries

For other database libraries, use the dbscan package to work with an abstract database. This provides flexibility for integrating with various database libraries.

Scany vs. SQLX: A Quick Comparison

While both Scany and SQLX serve similar purposes, here are some key differences:

• Scany is compatible with multiple database drivers, whereas SQLX is limited to database/sql.
• Scany has a simpler API, making it easier for new users to adopt.

Troubleshooting

Here are a few tips if you’re running into issues using Scany:

• Ensure your database connection string is correctly formatted.
• Double-check that your struct fields match the database columns.
• If you experience issues or need further assistance, feel free to check out the project’s Wiki for detailed documentation.
• For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

With Scany, you can greatly simplify your interactions with databases in Go, allowing you to focus more on building features rather than getting lost in tedious data handling.