A node orm modeling tool that generates types and docs.
npm install orm-modelingorm-modeling is a robust Node.js ORM tool designed with TypeScript. It enables you to define your database schemas using JavaScript objects, with the added benefit of IDE autocompletion and type-checking for model definitions. Built on the Knex query builder, it offers compatibility with a variety of database engines.
  
Key Features:
- Define Knex schemas from models with TypeScript's autocompletion and type-checking capabilities.
- Generate Markdown documentation from models.
- Generate TypeScript interfaces for data entities from models.
- Future updates will add support for other Node.js ORM modules.
``bash`To install orm-modeling
npm install orm-modelingYou will also need to install Knex and your chosen database engine, for example MySQL
npm install knex mysql
What you need to do is to create a Knex instance and define your model. Then, pass these to the createKnexSchema function, which will return a Knex instance with the schema applied.
`TypeScript
import { createKnexSchema, Model } from 'orm-modeling';
import Knex, { Knex as KnexType } from 'knex';
// Create a Knex instance
const db: KnexType = Knex();
// Define your model
const model: Model = {
// ... model attributes go here
};
createKnexSchema({db, model}).then((db: KnexType) => {
// The function returns the Knex instance
});
`
- Models should be defined according to the TypeScript types provided. Thanks to TypeScript, your IDE will be able to provide useful prompts and indications as you define your models.
- Refer to this TypeScript example for a model definition.
In orm-modeling, a model is a representation of a database table and its associated attributes. Models are defined as JavaScript objects, taking advantage of TypeScript's autocompletion and type-checking capabilities to ensure correct model definitions.
Here's an example of how you can define a model for a 'files' table:
`ts
import {DataTypes, Model} from 'orm-modeling';
/**
* File model
*/
const model: Model = {
tableName: 'files',
autoId: true,
timestamps: {
makeDefaultNow: true
},
comment: 'File archives',
indexes: [],
columns: {
name: {
type: DataTypes.VARCHAR,
length: 500,
unique: true,
nullable: false,
comment: 'File name',
},
original_filename: {
type: DataTypes.VARCHAR,
length: 2000,
nullable: false,
comment: 'Original name'
},
mimetype: {
type: DataTypes.VARCHAR,
length: 256,
nullable: false,
comment: 'File type',
},
size: {
type: DataTypes.BIG_INTEGER,
nullable: false,
comment: 'File size',
},
data: {
type: DataTypes.LONG_BLOB,
comment: 'File data',
},
creator_id: {
type: DataTypes.INTEGER,
unsigned: true,
nullable: false,
comment: 'Creator id, admin user.'
},
// ... columns go here
}
};
export default model;
`
In this example, the Model object has several properties:
- tableName: The name of the table in the database.autoId
- : If set to true, an 'id' column of type 'integer' will be automatically added to the model.timestamps
- : If set to true, 'created_at' and 'updated_at' columns will be automatically added to the model. You can also pass an object with more specific configuration options.comment
- : A comment for the table.indexes
- : An array defining the indexes for the table.columns
- : An object defining the columns of the table. Each key in this object represents a column in the table, and the value is an object that defines the properties of the column.
The columns property is an object where each key-value pair represents a column in the table. The key is the column name, and the value is an object that defines the column properties.
Let's delve into the Column interface. Each property in the Column interface represents a configuration option for a column in a database table.
- type: This property defines the data type of the column. It can be one of the values from the DataTypes enum, or a string representing a valid data type. The DataTypes enum includes common data types such as 'string', 'integer', 'date', 'boolean', etc.
- autoIncrement: If set to true or 'bigIncrements', the column will automatically increment its value for each new row. This is typically used for primary key columns.
- length: This property specifies the maximum length of the column. It's applicable for string data types.
- unsigned: If set to true, the column will be set as an unsigned integer. This means it can only hold non-negative numbers. This property only applies to integer fields.
- nullable: If set to true, the column will allow null values. If not specified or set to false, the column will not accept null values.
- primaryKey: If set to true or a string, the column will be set as the primary key of the table. If the value is a string, it will be used as the name of the primary key constraint.
- unique: If set to true or a string, a unique constraint will be added to this column. If the value is a string, it will be used as the name of the unique constraint.
- comment: This property allows you to add a comment to the column.
- defaultValue: This property allows you to set a default value for the column.
- datetimeOptions: This property allows you to set options for 'datetime' and 'timestamp' column types. It should be an object of type DatetimeOptions, which can have properties like precision and useTz (for timezone).
- floatOptions: This property allows you to set options for 'float' and 'decimal' column types. It should be an object of type FloatOptions, which can have properties like precision and scale.
- enumType: This property allows you to set options for 'enum' or 'enu' column types. It should be an object of type EnumType, which includes enumValues (an array of possible values for the enum) and enumOptions (additional options for the enum).
- reference: This property allows you to add a foreign key reference to the column. It should be an object of type Reference, which includes properties like table (the referenced table), column (the referenced column), and foreignKeyName (the name of the foreign key constraint).
Each of these properties allows you to fine-tune the behavior and characteristics of your database columns, providing a high degree of flexibility in defining your data models.
By following this guide, you can define complex models that accurately represent your database tables. Remember, the power of orm-modeling lies in its ability to leverage TypeScript's features, providing you with autocompletion and type-checking capabilities as you define your models.
For a complete example, refer to this Knex schema creation example.
1. Import the toMarkdownTable function from the orm-modeling library.
`TypeScript`
import { toMarkdownTable } from 'orm-modeling';
2. Define your model object as per the Model interface.
`TypeScript`
const model: Model = {
// ... model definition goes here
};
3. Call the toMarkdownTable function with your model object. This will return a string containing a Markdown table.
`TypeScript`
const markdown: string = toMarkdownTable(model);
4. You can then write this string to a Markdown file, or use it however you like.
`TypeScript`
import { writeFileSync } from 'fs';
writeFileSync('model.md', markdown);
1. Import the toTypeScriptInterface function from the orm-modeling library.
`TypeScript`
import { toTypeScriptInterface } from 'orm-modeling';
2. Define your model object as per the Model interface.
`TypeScript`
const model: Model = {
// ... model definition goes here
};
3. Call the toTypeScriptInterface function with your model object. This will return a string containing a TypeScript interface.
`TypeScript`
const interfaceStr: string = toTypeScriptInterface(model);
4. You can then write this string to a TypeScript file, or use it however you like.
`TypeScript`
import { writeFileSync } from 'fs';
writeFileSync('model.ts', interfaceStr);
This will generate a TypeScript interface that describes the structure of a row in the table that your model represents. This can be very useful when you're writing TypeScript code that interacts with this table, as it allows your editor to provide autocompletion and type checking.
For TypeScript users, if you encounter issues with the type declarations of certain packages, you may need to enable skipLibCheck in your tsconfig.json:
`json``
{
"compilerOptions": {
"skipLibCheck": true
}
}