Alopex

Alopex is an easy to use data store. It can be used for persistent data in a sqlite file or just blazing fast in memory. It automatically synchronizes schema when you have have new fields or a new table. It has only TWO dependencies. Critical packages working with data like alopex shouldn't have much requirements. Alopex is future proof!

Features:

• insert
• update
• upsert
• delete
• count
• find
• findOne
• automatic index creation
• manual index creation
• persistent storage
• memory storage
• easy filtering while fetching data like in Django ORM
• fetching specific fields by providing an array with column names

This libary is the NodeJS version of my favorite python module: https://dataset.readthedocs.io/en/latest/

Try it out on: https://npm.runkit.com/alopex

Installation

npm install -g npm@latest
npm install alopex --save

Connect

Giving up a database name to connect is optional. Default database if none given is ':memory:'

const alopex = require('alopex')
const dataSet = await alopex()

Insert

This code will create a new table called myNewTable and will add the required fields automatically.

dataSet.myNewTable.insert({'name': 'John', 'surname': 'Snow'}).then(pk=>{
    console.info('Inserted record has primary key', pk)
})

Select

Select all columns by using null

dataSet.myNewTable.find({'name': 'John'}, null).then(records=>{
    console.info('Found records', records)
})

Select specific columns by column of field names

dataSet.myNewTable.find({'name': 'John'}, ['surname']).then(records=>{
    console.info('Found records', records)
})

Order by ascending

dataSet.myNewTable.find({'_orderBy': 'id'}).then(records=>{
    console.info('Found records', records)
})

Order by descending

Descending sorting is done by adding - in front of the column name.

dataSet.myNewTable.find({'_orderBy': '-id'}).then(records=>{
    console.info('Found records', records)
})

Limit

dataSet.myNewTable.find({'_limit': 100}).then(records=>{
    console.info('Found 100 records', records)
})

Offset

Using _offset without _limit is ignored.

dataSet.myNewTable.find({'_limit': 100, '_offset': 100}).then(records=>{
    console.info('Found 100 records starting from offset 100', records)
})

Update

Update using array of column names

dataSet.myNewTable.update({'name': 'John', 'id': 5}, ['id']).then(updateCount=>{
    console.info('Updated records', updateCount)
})

Update using object

dataSet.myNewTable.update({'name': 'John'}, {'surname__like': '%Snow%'}).then(updateCount=>{
    console.info('Updated records', updateCount)
})

Delete

dataSet.myNewTable.delete({'name': 'John'}).then(changeCount=>{
    console.info('Total deleted', changeCount)
})

Count

dataSet.myNewTable.count({'name': 'John'}).then(total=>{
    console.info('Total records matcing criteria', total)
})

Supported filters

Filters used below can be used by update, upsert, delete and count.

• __eq
• __lt
• __lte
• __gt
• __gte
• __isnull
• __like (Case instenstive. This is default sqlite behavior)

Example usage:

dataSet.myTable.find({'name__like': '%test%', 'age__isnull': false, 'id__gte': 5, '_orderBy': '-id', '_limit': 5, '_offset': 10})

Indexes

Automatic create

Find record method creates indexes automatically. For example:

dataSet.find({'z': 1, 'y__eq': 2})

will create index idx_y_z. It only applies to fields filtered with = operator.

Manual create

Promise returns false if index already exist.

dataSet.myNewTable.createIndex(['age', 'length']).then(isIndexCreated=>{
    console.info('Created new index is ', isIndexCreated)
})