Name: sails-mysql-transactions-waterline
Owner: Postman
Description: An adapter-based ORM for Node.js with support for mysql, mongo, postgres, redis, and more - with added ORM transactions support
Created: 2015-03-18 09:08:13.0
Updated: 2017-02-19 11:11:08.0
Pushed: 2017-02-19 11:11:05.0
Size: 2280
Language: JavaScript
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Waterline is a brand new kind of storage and retrieval engine.
It provides a uniform API for accessing stuff from different kinds of databases, protocols, and 3rd party APIs. That means you write the same code to get and store things like users, whether they live in Redis, mySQL, LDAP, MongoDB, or Postgres.
Waterline strives to inherit the best parts of ORMs like ActiveRecord, Hibernate, and Mongoose, but with a fresh perspective and emphasis on modularity, testability, and consistency across adapters.
For detailed documentation, go to Waterline Documentation repository.
Install from NPM.
m install waterline
Waterline was extracted from the Sails framework and is the default ORM used in Sails. For more information on using Waterline in your Sails App view the Sails Docs.
For examples of how to use with frameworks such as Express look in the Example folder.
Waterline = require('waterline');
efine your collection (aka model)
User = Waterline.Collection.extend({
tributes: {
firstName: {
type: 'string',
required: true
},
lastName: {
type: 'string',
required: true,
}
Waterline uses the concept of an Adapter to translate a predefined set of methods into a query that can be understood by your data store. Adapters allow you to use various datastores such as MySQL, PostgreSQL, MongoDB, Redis, etc. and have a clear API for working with your model data.
It also allows an adapter to define it's own methods that don't necessarily fit into the CRUD methods defined by default in Waterline. If an adapter defines a custom method, Waterline will simply pass the function arguments down to the adapter.
NOTE: When using custom adapter methods the features of Waterline are not used. You no longer get the Lifecycle Callbacks and Validations as you would when using a defined Waterline method.
You may also supply an array of adapters and Waterline will map out the methods so they are both mixed in. It works similar to Underscore's Extend method where the last item in the array will override any methods in adapters before it. This allows you to mixin both the traditional CRUD adapters such as MySQL with specialized adapters such as Twilio and have both types of methods available.
A Collection is the main object used in Waterline. It defines the layout/schema of your data along with any validations and instance methods you create.
To create a new collection you extend Waterline.Collection and add in any properties you need.
Available options are:
tableName Define a custom table name to store the modelsadapter the name of the adapter you would like to use for this collectionschema Set schema true/false to only allow fields defined in attributes to be saved. Only for schemaless adapters.attributes A hash of attributes to be defined for a modelautoCreatedAt and autoUpdatedAt Set false to prevent creating createdAt and updatedAt properties in your modelautoPK Set false to prevent creating id. By default id will be created as index with auto incrementThe following attribute types are currently available:
User = Waterline.Collection.extend({
Define a custom table name
bleName: 'user',
Set schema true/false for adapters that support schemaless
hema: true,
Define an adapter to use
apter: 'postgresql',
Define attributes for this collection
tributes: {
firstName: {
type: 'string',
// also accepts any validations
required: true
},
lastName: {
type: 'string',
required: true,
maxLength: 20
},
email: {
// Special types are allowed, they are used in validations and
// set as a string when passed to an adapter
type: 'email',
required: true
},
age: {
type: 'integer',
min: 18
},
// You can also define instance methods here
fullName: function() {
return this.firstName + ' ' + this.lastName
}
*
Lifecycle Callbacks
Run before and after various stages:
beforeValidate
afterValidate
beforeUpdate
afterUpdate
beforeCreate
afterCreate
beforeDestroy
afterDestroy
/
foreCreate: function(values, cb) {
// An example encrypt function defined somewhere
encrypt(values.password, function(err, password) {
if(err) return cb(err);
values.password = password;
cb();
});
Class Method
Something: function() {
// Do something here
Now that a collection is defined we can instantiate it and begin executing queries against it. All Collections take options and callback arguments.
Options will be made up of:
tableName, used if not defined in a Collection definitionadapters object that specifies each adapter, either custom definitions or from NPMpostgres = require('sails-postgresql');
User({ tableName: 'foobar', adapters: { postgresql: postgres }}, function(err, Model) {
We now have an instantiated collection to execute queries against
del.find()
here({ age: 21 })
imit(10)
xec(function(err, users) {
// Now we have an array of users
;
Each result that gets returned from a Waterline query will be an instance of Model. This will add in any instance methods defined in your collection along with some CRUD helper methods. View the Core Instance Methods to see how they are implemented.
Default CRUD instance methods:
If you would like to filter records and remove certain attributes you can override the toJSON method like so:
user = Waterline.Collection.extend({
tributes: {
name: 'string',
password: 'string',
// Override toJSON instance method
toJSON: function() {
var obj = this.toObject();
delete obj.password;
return obj;
}
hen on an instantiated user:
.find({ id: 1 }).exec(function(err, model) {
turn model.toJSON(); // Will return only the name
Queries can be run with either a callback interface or with a deferred object. For building complicated queries, the deferred object method is the best choice. For convenience, promises are supported by default.
Callback Method
.findOne({ id: 1 }, function(err, user) {
Do stuff here
Deferred Object Method
.find()
re({ id: { '>': 100 }})
re({ age: 21 })
it(100)
t('name')
c(function(err, users) {
Do stuff here
Promises
.findOne()
re({ id: 2 })
n(function(user){
var comments = Comment.find({userId: user.id}).then(function(comments){
return comments;
});
return [user.id, user.friendsList, comments];
pread(function(userId, friendsList, comments){
// Promises are awesome!
atch(function(err){
// An error occurred
Promises use the Bluebird library, so anything you do after the first then call (or spread, or catch), will be a complete Bluebird promise object. Remember, you must end the query somehow (by calling then or one of the other functions) in order to complete the database request.
Each of the following basic methods are available by default on a Collection instance:
In addition you also have the following helper methods:
Based on your Collection attributes you also have dynamic finders. So given a name attribute the following queries will be available:
In addition to the other find methods, there are a few helper methods to take care of pagination:
Skip takes an integer and can be used to skip records:
.find().skip(20);
Limit takes an integer and limits the amount of records returned:
.find().limit(10);
And put together they create the ability to paginate through records as you would pages. For example, if I wanted 'page 2' of a given record set, and I only want to see 10 records at a time, I know that I need to `skip(10)and ``limit(10)``` like so:
.find().skip(10).limit(10);
But, while we are thinking in terms of pagination, or pages, it might be easier to use the final helper - paginate:
.find().paginate({page: 2, limit: 10});
Paginate has several options:
It returns a deferred object so that you can continue to chain your helpers.
Sorting can be performed in the deferred object query method sort or by adding the sort key into the criteria object.
Simply specify an attribute name for natural (ascending) sort, or specify an asc or desc flag for ascending or descending orders respectively.
.find()
t('roleId asc')
t({ createdAt: 'desc' })
c(function(err, users) {
Do stuff here
Validations are handled by Anchor which is based off of Node Validate and supports most of the properties in node-validate. For a full list of validations see: Anchor Validations.
Validations are defined directly in you Collection attributes. In addition you may set the attribute type to any supported Anchor type and Waterline will build a validation and set the schema type as a string for that attribute.
Validation rules may be defined as simple values or functions (both sync and async) that return the value to test against.
User = Waterline.Collection.extend({
tributes: {
firstName: {
type: 'string',
required: true,
minLength: 5,
maxLength: 15
},
lastName: {
type: 'string',
required: true,
minLength: 5,
maxLength: 100
},
age: {
type: 'integer',
after: '12/12/2001'
},
website: {
type: 'string',
// Validation rule may be defined as a function. Here, an async function is mimicked.
contains: function(cb) {
setTimeout(function() {
cb('http://');
}, 1);
}
}
Event = Waterline.Collection.extend({
tributes: {
startDate: {
type: 'date',
// Validation rule functions allow you to validate values against other attributes
before: function() {
return this.endDate;
}
},
endDate: {
type: 'date',
after: function() {
return this.startDate;
}
}
You can define your own types and their validation with the types hash. It's possible to access and compare values to other attributes.
User = Waterline.Collection.extend({
pes: {
point: function(latlng){
return latlng.x && latlng.y
},
password: function(password) {
return password === this.passwordConfirmation;
});
tributes: {
firstName: {
type: 'string',
required: true,
minLength: 5,
maxLength: 15
},
location: {
// Note, that the base type (json) still has to be defined
type: 'json',
point: true
},
password: {
type: 'string',
password: true
},
passwordConfirmation: {
type: 'string'
}
You can add an index property to any attribute to create an index if your adapter supports it. This comes in handy when performing repeated queries against a key.
User = Waterline.Collection.extend({
tributes: {
serviceID: {
type: 'integer',
index: true
}
Currently Waterline doesn't support multi-column indexes in the attributes definition. If you would like to build any sort of special index you will still
need to build that manually. Also note that when adding a unique property to an attribute, an index will automatically be created for that attribute.
There is currently an issue with adding indexes to string fields. Because Waterline performs its queries in a case insensitive manner, we are unable to use the index on a string attribute. There are some workarounds being discussed but nothing is implemented so far. This will be updated in the near future to fully support indexes on strings.
Lifecycle callbacks are functions you can define to run at certain times in a query. They are useful for mutating data before creating or generating properties before they are validated.
Callbacks run on Create
Callbacks run on Update
Callbacks run on Destroy
All tests are written with mocha and should be run with npm:
npm test