Monolens - Declarative data transformations

Declarative data transformations expressed as simple .yaml or .json files. They are great to

• clean an Excel file
• transform a .json file
• transform data from a .csv file
• upgrade a .yaml configuration
• etc.

Monolens let's you tackle those tasks with small programs that are simple, declarative, robust, secure, reusable and sharable.

• Declarative & language agnostic

• Allows transforming scalars (e.g. string, dates), objects and arrays.

• Support for (simplified) jsonpath interpolation when defining objects

• Support for macros (monolens is an homoiconic language)

• Secure: not Turing Complete, no code injection, no RegExp DDoS

• Requires ruby >= 2.6

• Not reached 1.0 yet, still experimental

Please refer to the documentation/ folder for a longer introduction, documentation of the stdlib, and documented use-cases:

• Introduction
• Standard library
• Use cases
  • Kubernetes data templates
  • Migrating database seeds

gem install monolens

Then:

monolens --help
monolens lens.yaml input.json

# Gemfile
gem 'monolens', '< 1.0'

require 'monolens'
require 'json'

lens   = Monolens.load_file('lens.yml')
input  = JSON.parse(File.read('input.json'))
result = lens.call(input)

• Monolens is inspired by Project Cambria but is not as ambitious, and is not currently compatible with it.

• The name of some lenses mimic Tutorial D / relational algebra (Date & Darwen). See also Bmg

This library follows semantics versioning 2.0.

It has NOT reached 1.0 and is currently unstable.

Anyway, the public interface will cover at least the following:

• Monolens.lens factory method and its behavior

• The list of available lenses, their behavior and available options.

• Exception classes: Monolens::Error, Monolens::LensError

• bin/monolens, its args, options and general behavior

Everything else is condidered private and may change any time (i.e. even on patch releases).

Please use github issues and pull requests, and favor the latter if possible.

This software is distributed by Enspirit SRL under a MIT Licence. Please contact Bernard Lambeau (blambeau@gmail.com) with any question.