gobdb is a simple key-value database for Go binary objects encoded with encoding/gob.

• Open: Opens a file at the specified path and decodes its contents using the gob decoder.
• List: Returns the entire database as an array.
• Add: Appends a new value to the database and persist data to disk.

db, err := gobdb.Open[YourType]("path/to/yourfile.gob")
if err != nil {
    // handle error
}

data := db.List()
for _, item := range data {
    // process item
}

err := db.Add(yourData)
if err != nil {
    // handle error
}

This package is ideal for simple use-cases where you need to persist and retrieve Go binary objects without the overhead of a full-fledged database system. Here are a few scenarios where it can be handy:

• Caching: You can use gobdb to cache complex data structures that take time to generate or fetch from a slow source. This way, you can quickly retrieve the data from the disk whenever needed.

• Local Data Persistence: If you're building a Go application that needs to store data locally, you can use gobdb as a lightweight, file-based database.

• Data Serialization: The package can also be used for serializing and deserializing Go data structures for network communication or other purposes where you need to convert Go objects to a binary format and vice versa.

While gobdb provides a convenient way to work with gob encoded data, there are several features that could improve its utility:

• Delete Functionality: Currently, there's no way to delete data from the database. This feature is crucial for managing the data efficiently.

• Update Functionality: Another missing feature is the ability to update an existing value in the database.

• Search Functionality: The package currently lacks a way to search for a specific data object in the database. Implementing this would provide quicker access to data.

• Concurrency Safety: The package isn't currently safe for concurrent use. It would be beneficial to add some form of locking to ensure that concurrent reads and writes don't cause data corruption.

• Error Handling: The current error handling could be improved, for instance by providing more detailed error messages or different types of errors for different failure cases.

• Batch Operations: Adding support for batch operations could improve performance when working with large amounts of data.

Contributions are welcome to help implement these features and improve this package.