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Production-grade todo app REST API in functional scala
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README.md

fpscala2

Production-grade todo app REST API in functional scala

This is an effort to create high quality application using FP approach with cats. As this is a learning project, custom code is preferred over existing FP libraries.

Features so far

  • functional modular system
  • layered architecture (dao - service - controller - route)
  • configuration from multiple sources (including --help command line parameter)
  • pure data access layer based on JDBC
  • pure JDBC transaction management
  • separate thread pool for JDBC code
  • quality JSON handling and validation (with readable messages, including reason, line and column)
  • input validation (using Validated)
  • quality error handling (error classification, REST error messages)
  • pure logging
  • data access layer tests using embedded postgres
  • acceptance tests using embedded postgres
  • packaging and dockerization. Try it now: docker run --rm scf37/fpscala2 --help

Architecture

Layers

Typical multi layer architecture consisting of:

  • data access layer (DAO)
  • service layer (busines logic, intended to be called from within application)
  • controller layer (includes transaction boundary, intended to be exposed to external clients via REST API)
  • route layer (converts incoming HTTP request to controller call)
  • server layer (HTTP server)

Effects

Effect is an abstraction of some computation. Every effect can be created from computation definition, usually function (lifted) and at some time later can be run, extracting computation result (evaluated)

Application uses three types of effects:

  • Generic effect F[_].
    • This is generic F used for asynchonous code with lazy evaluation, e.g. cats IO or monix Task
  • Abstract database effect DbEffect[_] concrete database effect SqlEffect[F[_], ?]
    • It wraps function java.sql.Connection => T. Usual synchronous database code takes this form. Instance of java.sql.Connection is needed to evaluate this effect.
  • application initialization effect I[_]
    • it wraps component initialization code. It is lazy so components will only be created on demand and caches its result to produce singletons

Modules

Modules system used can be seen as extension of well-known cake pattern keeping its strengths of ability to override any instance or to get any instance from assembled application.

In addition, it supports composition, precise explicit dependency management and lazy evaluation.

TODOs

  • Immutable in-memory dao using StateT
  • request context (including requestId for logging) using Kleisli[F, Context, ?] instead of F
  • application statistics: query and transaction execution timings. Finagle also provides request timing stats, make it more explicit somehow?
  • delayed logging - delay logging evaluation till end of request processing to decide log level based on response (e.g. enable debug logging for failed requests only)
  • find better way to manage Application effects (3 seems to be a bit high)
  • add scalacheck?
  • add scalafmt?
  • consider moving to http4s?
  • use Resource for I[_]? Not sure I should care about proper shutdown - well-written application should behave well in case of forced termination.
  • Add request flow control: timeouts, parallel request count limit
  • cancellation on timeout? Does it make sense on JDBC? Will it improve behavior of overloaded app?
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