@jsiqle/core

@jsiqle/core

JavaScript In-memory Query Language with Events.

Installation

npm install @jsiqle/core

Usage

You would typically use this library much like a traditional ORM, but without the data bindings to interface with a database. In such a scenario, data would be provided by loading data from a filesystem-based data storage such as JSON files.

// Suppose data for yur schema is appropriately stored in data.json
import data from './data.json';
import jsiqle from '@jsiqle/core';

const Ledger = jsiqle.create({
  name: 'Ledger',
  models: [
    {
      name: 'Person',
      key: { name: 'id', type: 'auto' },
      fields: [
        {
          name: 'username',
          type: 'string',
          validators: {
            unique: true,
            minLength: 5,
            regex: /\w/g
          }
        },
        {
          name: 'role',
          type: 'enum',
          values: ['user', 'admin'],
          defaultValue: 'user'
        },
        { name: 'firstName', type: 'string' }
        { name: 'lastName', type: 'string' },
      ],
      methods: {
        fullName: rec => `${rec.firstName} ${rec.lastName}`
      }
    },
    {
      name: 'Transaction',
      key: { name: 'id', type: 'auto' },
      fields: [
        { name: 'time', type: 'date' }
        { name: 'amount', type: 'number' }
      ]
    }
  ]
});

Ledger.createRelationship({
  from: { model: 'Transaction', name: 'payer' },
  to: { model: 'Person', name: 'outgoingTransactions' },
  type: 'manyToOne'
});

Ledger.createRelationship({
  from: { model: 'Transaction', name: 'payee' },
  to: { model: 'Person', name: 'incomingTransactions' },
  type: 'manyToOne'
});

const Person = Ledger.getModel('Person');
const Transaction = Ledger.getModel('Transaction');

// Load some data from storage
data.people.forEach(
  personData => Person.createRecord(personData)
);
data.transactions.forEach(
  transactionData => Transaction.createRecord(transactionData)
);

// Get the name of the first person that has at least one outgoing transaction
Person.records.where(p => p.outgoingTransactions.length).first.fullName;

Note: Data bindings for a standardized JSON-based data storage may be coming soon, either as part of this package or a complementary one.

API Reference

Schema definition

A schema instance can be created using jsiqle.create():

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({ name: 'MySchema' });

Schema definition requires an object argument with the following attributes:

• name: The name of the schema. By convention, schema names and variables should be title-cased (i.e. MySchema instead of mySchema).
• models: (Optional) An array of models that are part of the schema. More information about model definitions can be found in the next section.
• config: (Optional) A configuration object that supports the following attributes:
  • experimentalAPIMessages: One of 'warn', 'error' or 'off'. Depending on this flag, experimental API messages can either be logged as warnings, throw an error or be turned off entirely.

Model definitions

Models can be defined either as part of the schema definition or individually using Schema.prototype.createModel():

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({
  name: 'MySchema',
  models: [{ name: 'MyModel' }]
});

const AnotherModel = MySchema.createModel({ name: 'AnotherModel' });

Both of these model definition options require an object argument with the following attributes:

• name: The name of the model. By convention, model names and variables should be title-cased (i.e. MyModel instead of myModel). Model names must be globally unique.
• fields: (Optional) An array of fields that make up the model. More information about field definitions can be found in the next section.
• key: (Optional) Parameter to create a key field, not part of the fields themselves. Can either be a string with the name of the key or an object with a name (string) and a type (either 'string' or 'auto') representing a string or auto-incrementing integer key. By default, a model's key is a string field named 'id'.
• methods: (Optional) An object containing key-value pairs for getter methods to be defined on the model. All methods expect a single argument representing a record of the given model. More information about method definitions can be found in one of the following sections.
• scopes: (Optional) An object containing key-value pairs for getter methods to be defined on the record set of the model. All scopes expect a single argument representing the record set or a subset of records from the current model. More information about scope definitions can be found in one of the following sections.
• validators: (Optional) An object containing key-value pairs for validation methods that return a boolean value depending on the validation's result. All validators expect two arguments, the current record and the record set of the current model. More information about validators and field validators can be found in one of the following sections.

You can retrieve an already defined model by calling Schema.prototype.getModel() with the model name:

const MyModel = MySchema.getModel('MyModel');

Finally, models can be removed from a schema by calling Schema.prototype.removeModel() with the model name:

MySchema.removeModel('MyModel');

Field definitions

Fields can be defined as part of a model definition or added individually to a model by calling Model.prototype.addField():

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({
  name: 'MySchema',
  models: [
    {
      name: 'MyModel',
      fields: [
        { name: 'firstName', type: 'string' },
        { name: 'age', type: 'numberRequired', defaultValue: 18 },
        {
          name: 'username',
          type: 'stringRequired',
          defaultValue: '',
          validators: {
            unique: true,
            minLength: 5
          }
        }
      ]
    }
  ]
});

const MyModel = MySchema.getModel('MyModel');

MyModel.addField(
  {
    name: 'role',
    type: 'enumRequired',
    values: ['user', 'admin'],
    defaultValue: 'user'
  },
  record => record.username === 'admin' ? 'admin' : 'user'
);

Both of these field definition options require an object argument with the following attributes:

• name: The name of the field. By convention, field names should be camel-cased (i.e. myField). Field names must be unique for each model.
• type: The type of the field. Read below for more information on types and validation.
• required: (Optional) Boolean value that determines if a field can be empty (null or undefined). If specified, defaultValue also needs to be specified.
• defaultValue: (Optional) A value that will be used as the default for records with an empty value in this field if the field is required. The defaultValue must be a valid value for the given type.
• validators: (Optional) An object that defines what validations the field needs to pass. More information can be found below.

Fields added via Model.prototype.addField() can specify a retrofill function as a second argument. This function takes one argument, the existing record, and is used to determine the value of the new field added to the record.

Fields can be updated by calling Model.prototype.updateField() with the field name and a new field definition. The new field definition's name must match the existing one:

MyModel.updateField('firstName', {
  name: 'firstName',
  type: 'stringRequired'
});

Finally, fields can be removed by calling Model.prototype.removeField() with the field name:

MyModel.removeField('firstName');

Field types

There are a few standard field types corresponding to primitives and certain common field type values:

boolean string number date positiveNumber
stringOrNumber numberOrString
booleanArray numberArray stringArray dateArray
object booleanObject numberObject
stringObject dateObject objectArray
enum

Each of these types can be specified as is or suffixed with Required (e.g. stringRequired) to specify the required flag of the field as well. Required field types have a preset default value corresponding to an "empty" value of the type.

For enum types, the values key must also be specified as an array of distinct values.

Apart from standard types, there's also an experimental API that allows types to be specified as a function that takes one argument and returns a boolean determining the validity of the argument. In most cases, a validator function would suffice and you're strongly recommended to use one, instead.

Field validation

Fields can have additional validations specified, by specifying a validators object which includes key-value pairs for each validator. Standard validators for common use-cases are as follows:

• unique: Takes one argument (true) and validates that each record has a unique value for this field. Works with any value type.
• minLength: Takes a numeric argument, min, and validates that no value can have a length smaller than the min specified. Works with strings, arrays and other enumerable types.
• maxLength: Takes a numeric argument, max, and validates that no value can have a length greater than the max specified. Works with strings, arrays and other enumerable types.
• length: Takes a 2-element array, [min, max], and acts as a combination of minLength and maxLength. Works with strings, arrays and other enumerable types.
• min: Takes a numeric argument, min, and validates that no value can be smaller than the min specified. Works with numeric values and dates.
• max: Takes a numeric argument, max, and validates that no value can be greater than the max specified. Works with numeric values and dates.
• range: Takes a 2-element array, [min, max], and acts as a combination of min and max. Works with numeric values and dates.
• integer: Takes one argument (true) and validates that a given numeric value is an integer. Works with numeric types.
• regex: Takes a regular expression argument, regex, and checks each value against it. Works with strings.
• uniqueValues: Takes one argument (true) and validates that an array has no duplicates. Works with array types.
• sortedAscending: Takes one argument (true) and validates that an array is sorted in ascending order. Works with array types.
• sortedDescending: Takes one argument (true) and validates that an array is sorted in descending order. Works with array types.

Apart from standard validators, custom ones can be specified using a new name as the key and a function as the value. The function takes two arguments, the field value of the current record and an array of field values in other records in the model.

Method definitions

Methods can be defined as part of a model definition or added individually to a model by calling Model.prototype.addMethod():

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({
  name: 'MySchema',
  models: [
    {
      name: 'MyModel',
      fields: [
        { name: 'firstName', type: 'string' },
        { name: 'lastName', type: 'string' },
      ],
      methods: {
        fullName: record => `${record.firstName} ${record.lastName}`
      }
    }
  ]
});

const MyModel = MySchema.getModel('MyModel');

MyModel.addMethod(
  'formalName',
  record => `${record.lastName} ${record.firstName}`
);

Methods defined as part of the model definition as specified as key-value pairs, whereas methods defined in Model.prototype.addMethod() are passed as two separate arguments, the name and the method body.

Methods expect one argument, the current record, and may return any type of value.

You can remove a method from a model using Model.prototype.removeMethod():

MyModel.removeMethod('formalName');

Scope definitions

Scopes can be defined as part of a model definition or added individually to a model by calling Model.prototype.addScope():

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({
  name: 'MySchema',
  models: [
    {
      name: 'MyModel',
      fields: [
        { name: 'firstName', type: 'string' },
        { name: 'lastName', type: 'string' },
      ],
      scopes: {
        smiths: record => record.lastName === 'Smith'
      }
    }
  ]
});

const MyModel = MySchema.getModel('MyModel');

MyModel.addSchema('does', record => record.lastName === 'Doe');

Scopes defined as part of the model definition as specified as key-value pairs, whereas scopes defined in Model.prototype.addscope() are passed as two separate arguments, the name and the scope body.

Scopes expect one argument, the current record, and must return a boolean indicating if the scope should include the record or not.

You can remove a scope from a model using Model.prototype.removeScope():

MyModel.removeMethod('does');

Validator definitions

Validators can be defined as part of a model definition or added individually to a model by calling Model.prototype.addValidator():

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({
  name: 'MySchema',
  models: [
    {
      name: 'MyModel',
      fields: [
        { name: 'startDate', type: 'date' },
        { name: 'endDate', type: 'date' },
      ],
      validators: {
        datesValid: record => record.startDate <= record.endDate
      }
    }
  ]
});

const MyModel = MySchema.getModel('MyModel');

MyModel.addValidator(
  'datesDifferent',
  record => record.startDate !== record.endDate
);

Validators defined as part of the model definition as specified as key-value pairs, whereas validators defined in Model.prototype.addValidator() are passed as two separate arguments, the name and the validator body.

Validators expect two arguments, the current record and an array of other records in the model. They return a boolean indicating if the current record is valid.

You can remove a validator from a model using Model.prototype.removeValidator():

MyModel.removeValidator('datesDifferent');

Validators should be used to perform multi-field validations. For single-field validations, validators specified on the field are preferred due to their increased performance.

Relationship definitions

Note: The relationships API is not currently stable and is considered experimental. While no major changes are expected in the future, it might not be fit for use in production just yet.

Relationships can be defined by calling Schema.prototype.createRelationship():

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({
  name: 'MySchema',
  models: [
    {
      name: 'Person',
      fields: [
        {
          name: 'username',
          type: 'string',
        },
      ],
    },
    {
      name: 'Transaction',
      fields: [
        { name: 'amount', type: 'number' }
      ]
    }
  ]
});

Ledger.createRelationship({
  from: { model: 'Transaction', name: 'payer' },
  to: { model: 'Person', name: 'outgoingTransactions' },
  type: 'manyToOne'
});

Ledger.createRelationship({
  from: { model: 'Transaction', name: 'payee' },
  to: { model: 'Person', name: 'incomingTransactions' },
  type: 'manyToOne'
});

A relationship definition is an object with the following keys:

• from: Either a string representing the name of a model or an object with a model key and a name key. In the latter case, the name key is the name that will be given to the field in the specified model.
• to: Either a string representing the name of a model or an object with a model key and a name key. In the latter case, the name key is the name that will be given to the field in the specified model.
• type: One of oneToOne, oneToMany, manyToOne, manyToMany depending on the type of relationship.

When a relationship is defined between to models, the model specified as from will receive a new field named accordingly. Similarly, the to model will receive a new method instead that performs the reverse operation. Only the field on the from model is writeable.

The names for the field and method are automatically generated if not specified, must be valid names and not already exist in the model. For singular relationships, the name of the other model is used, whereas for plural the name of the model followed by Set. For example, a manyToOne relationship between two models, Person and Transaction, would be named transactionSet on Person and person on Transaction.

Relationships between records of the same model are allowed. The only caveat is that symemtric (i.e. oneToOne and manyToMany) relationships in the same model need to be named on both sides.

Record manipulation

At the heart of datasets are records, which represent individual data points. Each record belongs to a model and must comply with the model's definition.

Creating records

Records can be created using the Model.prototype.createRecord() method:

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({
  name: 'MySchema',
  models: [
    {
      name: 'MyModel',
      fields: [
        { name: 'firstName', type: 'string' },
        { name: 'lastName', type: 'string' },
      ],
      methods: {
        fullName: record => `${record.firstName} ${record.lastName}`
      }
    }
  ]
});

const MyModel = MySchema.getModel('MyModel');
MyModel.createRecord({ id: 'jsmith', firstName: 'John', lastName: 'Smith' });
MyModel.createRecord({ id: 'jdoe', firstName: 'John', lastName: 'Doe' });

Each record definition consists of an object with the appropriate key-value pairs. Required fields without a value will be automatically set to the respective field's defaultValue. Key-value pairs that do not match a field definition will be stored in the record. This can be useful for fields that might be added in later operations (e.g. adding relationships to a populated model).

Updating records

Records can be updated in place (i.e. retrieving them from the record set and updating their attributes). They can also be updated by calling Model.prototype.updateRecord():

MyModel.records.first.firstName = 'Jim';
MyModel.updateRecord('jdoe', { firstName: 'Josh' });

When calling Model.prototype.updateRecord(), the given object will be merged into the existing record, allowing for partial record updating.

Removing records

Records can be removed using Model.prototype.removeRecord(). Note that record removal does not currently run any validations or perform any cascade operations to ensure relationship stability.

MyModel.removeRecord('jdoe');

Querying

Data from a model is stored in records that make up the model's record set. Records and record sets can be queried in various ways.

Querying individual models

To query the record set of an individual model, use the Model.prototype.records getter. This returns the record set along with all the tools neccessary to filter and transform results.

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({
  name: 'MySchema',
  models: [
    {
      name: 'MyModel',
      fields: [
        { name: 'firstName', type: 'string' },
        { name: 'lastName', type: 'string' },
      ],
      methods: {
        fullName: record => `${record.firstName} ${record.lastName}`
      }
    }
  ]
});

const MyModel = MySchema.getModel('MyModel');
MyModel.createRecord({ id: 'jsmith', firstName: 'John', lastName: 'Smith' });
MyModel.createRecord({ id: 'jdoe', firstName: 'John', lastName: 'Doe' });

const records = MyModel.records;

Record set operations

Record sets can be filtered, mapped and sorted much like regular arrays. Here's a list of operations:

• RecordSet.prototype.map(): Creates an object populated with the results of calling a provided mapping function on every element in the calling record set. This method takes a mapping callback function as an argument that expects three arguments (record, key, recordSet), similar to Array.prototype.map(). The result is an object with each key mapped to the result of the mapping function.
• RecordSet.prototype.flatMap(): Same as RecordSet.prototype.map() except that the resulting value is an array instead of an object.
• RecordSet.prototype.reduce(): Executes a user-supplied reducer callback function on each element of the record set, passing in the return value from the calculation on the preceding element. This method takes a reducer callback function as an argument that expects four arguments (accumulator, record, key, recordSet) and an initial value, similar to Array.prototype.reduce(). The final result of running the reducer across all elements of the record set is a single value.
• RecordSet.prototype.filter(): Creates a new record set with all elements that pass the test implemented by the provided filtering function. This method takes a filtering callback function as an argument that expects three arguments (record, key, recordSet), similar to Array.prototype.filter(). The result is a record set containing only the records that pass the test.
• RecordSet.prototype.flatFilter(): Same as RecordSet.prototype.filter() except that the resulting value is an array instead of a record set.
• RecordSet.prototype.find(): Retrieves the first record matching the condition implemented by the provided testing function. This method takes a testing callback function as an argument that expects three arguments (record, key, recordSet), similar to Array.prototype.find(). The result is a record or undefined if none match the condition.
• RecordSet.prototype.findKey(): Same as RecordSet.prototype.find() except that the resulting value is the record's key instead of the record itself.
• RecordSet.prototype.only(): Returns a new record set containing only objects that match the key/keys provided. Expects any number of keys as arguments.
• RecordSet.prototype.except(): Returns a new record set containing only objects that don't match the key/keys provided. Expects any number of keys as arguments.
• RecordSet.prototype.every(): Returns a boolean indicating if all the records in the record set pass the test implemented by the provided testing function. This method takes a testing callback function as an argument that expects three arguments (record, key, recordSet), similar to Array.prototype.every().
• RecordSet.prototype.some(): Returns a boolean indicating if any of the records in the record set pass the test implemented by the provided testing function. This method takes a testing callback function as an argument that expects three arguments (record, key, recordSet), similar to Array.prototype.some().
• RecordSet.prototype.where(): Creates a new record set with all elements that pass the test implemented by the provided filtering function. This method takes a filtering callback function as an argument that expects three arguments (record, key, recordSet), similar to Array.prototype.filter(). The result is a record set containing only the records that pass the test.
• RecordSet.prototype.whereNot(): Creates a new record set with all elements that fail the test implemented by the provided filtering function. This method takes a filtering callback function as an argument that expects three arguments (record, key, recordSet), similar to Array.prototype.filter(). The result is a record set containing only the records that fail the test.

Attribute selection

Specific attributes can be selected from records via the following methods:

• RecordSet.prototype.select(): Expects any number of field names in a record. Returns a record set with partial records containing only those fields.
• RecordSet.prototype.flatSelect(): Same as RecordSet.prototype.select() except that the resulting value is an array of objects instead of a record set of partial records.
• RecordSet.prototype.pluck(): Expects any number of field names in a record. Returns a record set with record fragments containing only those fields. Record fragments behave similar to arrays.
• RecordSet.prototype.flatPluck(): Same as RecordSet.prototype.pluck() except that the resulting value is an array of arrays instead of a record set of record fragments. If only one key is provided, an array of individual attributes will be returned instead.

Sorting and grouping

Record sets can be grouped or sorted via the following methods:

• RecordSet.prototype.groupBy(): Expects a field name and groups the records based on its value. Returns a record set containing record groups, which in turn behave like nested record sets themselves.
• RecordSet.prototype.sort(): Sorts the elements of the record set and returns a new sorted record set. Expects a comparator callback function as an argument that takes three arguments (firstValue, secondValue, firstKey, secondKey) and returns an appropriate value for sorting similar to Array.prototype.sort().

Iterating over records

Record sets are iterable, meaning you can use for loops to iterate over them, similar to a regular ES6 Map. Additionally, RecordSet.prototype.batchOperator() is available expecting a batchSize numeric argument and allowing for the records in a record set to be iterated in batches.

Accessing specific records

You can acces the first record of a record set using RecordSet.prototype.first. Similarly, you can acces the last record of a record set using RecordSet.prototype.last.

Additionally, you can get the first n elements of a record set using RecordSet.prototype.limit() with an appropriate numeric argument or skip over them and get all other records using RecordSet.prototype.offset() with an appropriate numeric argument. These methods can be combined to get specific records in a record set based on the order of insertion.

Querying scopes

Scopes defined on a model are defined as getters on its record set. Thus, they can be used by calling them on the record set:

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({
  name: 'MySchema',
  models: [
    {
      name: 'MyModel',
      fields: [
        { name: 'firstName', type: 'string' },
        { name: 'lastName', type: 'string' },
      ],
      scopes: {
        smiths: record => record.lastName === 'Smith'
      }
    }
  ]
});

const MyModel = MySchema.getModel('MyModel');
MyModel.createRecord({ id: 'jsmith', firstName: 'John', lastName: 'Smith' });
MyModel.createRecord({ id: 'jdoe', firstName: 'John', lastName: 'Doe' });

const smithsFamily = MyModel.records.smiths;

Querying relationships

Relationships can be queried from either side of the relationship using the field/method name added to the model. For more information refer to the section about relationship definitions and how they are represented in models.

Querying from the schema

The schema provides a quick way to access a model, record or even an attribute using the Schema.prototype.get() method. This method takes a .-separated path and returns the value at that particular location:

import jsiqle from '@jsiqle/core';
const MySchema = jsiqle.create({
  name: 'MySchema',
  models: [
    {
      name: 'MyModel',
      fields: [
        { name: 'firstName', type: 'string' },
        { name: 'lastName', type: 'string' },
      ],
    }
  ]
});

const MyModel = MySchema.getModel('MyModel');
MyModel.createRecord({ id: 'jsmith', firstName: 'John', lastName: 'Smith' });
MyModel.createRecord({ id: 'jdoe', firstName: 'John', lastName: 'Doe' });

const myModel = MySchema.get('MyModel');
const johnSmith = MySchema.get('MyModel.jsmith');
const johnSmithsName = MySchema.get('MyModel.jsmith.firstName');

Serializing data

Records and record sets can be serialized to regular objects, arrays or JSON. Calling JSON.stringify() will suffice in most cases, as all records and record sets have appropriate methods to handle serialization. Apart from that, Record.prototype.toObject() can be called for individual records to convert them into regular objects.

Additionally, record sets implement the following serialization methods:

• RecordSet.prototype.toArray(): Returns an array of records contained in the record set.
• RecordSet.prototype.toFlatArray(): Returns an array of objects representing the records contained in the record set.
• RecordSet.prototype.toObject(): Returns an object of records representing the key-value pairs of the records in the record set.
• RecordSet.prototype.toFlatObject(): Returns an object of objects representing the key-value pairs of the records in the record set.

Listening for events

Both the schema and its models are event emitters, allowing event listeners to be added to them as necessary.

MySchema.addEventListener('change', data => console.log(data));
MyModel.addEventListener('change', data => console.log(data));

Schema events

The schema object emits the following events:

beforeCreateModel modelCreated
beforeRemoveModel modelRemoved
beforeCreateRelationship relationshipCreated
beforeGet got
change

All emitted events contain an object argument with the related data in appropriate keys, as well as a schema key with the schema itself. Events prefixed with before contain the raw data passed to the related method call, whereas events emitted after a method finishes contain the result of the method. change events are emitted for all non-before events except got and have the same arguments, as well as a type argument that specifies the event type. change events are also emitted as wrappers of model change events with the model event type prefixed (e.g. modelMethodAdded instead of methodAdded).

Model events

Model objects emit the following events:

beforeAddField fieldAdded
beforeRetrofillField fieldRetrofilled
beforeUpdateField fieldUpdated
beforeAddMethod methodAdded
beforeRemoveMethod methodRemoved
beforeAddScope scopeAdded
beforeRemoveScope scopeRemoved
beforeAddValidator validatorAdded
beforeRemoveValidator validatorRemoved
beforeCreateRecord recordCreated
beforeRemoveRecord recordRemoved
beforeUpdateRecord recordUpdated
beforeAddRelationship relationshipAdded
change

All emitted events contain an object argument with the related data in appropriate keys, as well as a model key with the model itself. Events prefixed with before contain the raw data passed to the related method call, whereas events emitted after a method finishes contain the result of the method. change events are emitted for all non-before events except recordCreated, recordRemoved and recordUpdated and have the same arguments, as well as a type argument that specifies the event type.

Naming conventions

Certain naming conventions and rules are in place.

Generally, names can only include alphanumeric characters and underscores and are expected to be unique in their scope. There are a few exceptions to this rule that are not enforced (e.g. scope names), but it should be followed across as part of the convention.

Additionally, conventions dictate that model and schema names are title-cased, and that all other names are camel-cased. Variables should also match this convention.

Terminology

To clear up any confusion, here are the names of the definition types and the names of the corresponding data objects they create:

• A schema is a set of definitions that contain models, fields, relationships etc. The data contained within a schema is called a dataset.
• A model is a set of field, method, validator and scope definitions. The data contained within a model is called a record set and each individual item within it is called a record.
• A record is a set of values corresponding to different keys. Each of these values is called an attribute.

License

This project is licensed under the MIT license.