frogdb
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0.1.5 • Public • Published

🐸 Lightweight, adaptable JSON database

FrogDB is a lightweight, file-based JSON database system designed for local development and small-scale applications. It allows for quick setup and easy data manipulation with the flexibility of JSON.

Features

  • Dynamic Schemas: Define your data structure on the fly with flexible schemas.
  • CRUD Operations: Full support for create, read, update, and delete operations.
  • Local Storage: All data is stored locally in JSON files, making it easy to inspect and manage.
  • Type Checking: Ensures data integrity with basic type checking for string, number, and boolean fields.
  • Fast: It can handle up to 32,000 thousand of write operations per second.
  • Type-safe: Written in TypeScript, FrogDB provides type safety and intellisense support. (also generates types for your schemas)

Installation

bun add frogdb

frogdb is only supported within the bun rumetime

Quick Start

  1. Define Your Schemas: Create schemas for your data models. Each schema should have a name and an array of fields.
import { Schema, FrogFieldType } from "frogdb";

const UserSchema = await Schema({
  name: "User",
  fields: [
    { name: "username", type: FrogFieldType.String, required: true },
    { name: "age", type: FrogFieldType.Number, required: false },
    { name: "isActive", type: FrogFieldType.Boolean, required: true }
  ],
};
  1. Initialize FrogDB: Set up FrogDB with your schemas.
import FrogDB from "frogdb";
import { UserSchema } from "./schemas/User";
import { PostSchema } from "./schemas/Post";

// This will create a new folder called `db` in your project root, with a "types" folder containing the generated types.
FrogDB().generate([UserSchema, PostSchema]);
  1. Perform Operations: Use the provided async functions to interact with your database.
async function createUser() {
  const newUser = await UserSchema.insert({
    username: "froggy123",
    age: 25,
    isActive: true,
  });

  console.log(newUser);
}

Schema Definition

Each schema requires a name and an array of fields. Fields must specify a name, type, and an optional required flag.

API Reference

  • insert(document: any): Inserts a new document into the database. Returns the inserted document with a unique id.
  • find(query: any): Finds documents matching the query. Returns an array of documents.
  • findOne(query: any): Finds the first document matching the query. Returns a single document.
  • deleteOne(id: string): Deletes the document with the specified id. Returns the deleted document.
  • deleteAll(query: any): Deletes all documents matching the query. Returns an array of deleted documents.
  • update(id: string, document: any): Updates the document with the specified id. Returns the updated document.

Type Safety

Simply import the generated types from the types folder to get type safety and intellisense support.

import { UserSchema } from "./schemas/User";
import { User } from "./db/types/User";

async function createUser() {
  const newUser: User = await UserSchema.insert({
    username: "froggy123",
    age: 25,
    isActive: true,
  });

 // or

  const newUser = await UserSchema.findOne<User>({
    username: "frog" // expected string
  });

  user.age = "25"; // error
}

Contributing

Contributions are welcome! Whether it's adding new features, fixing bugs, or improving documentation, your help is appreciated.

License

FrogDB is open source and released under the MIT License.

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npm i frogdb

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