Code for the "Enterprise Information Systems Patterns" series of posts - didatic framework.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.


Enterprise Information Systems Patterns

This project aims at discussing and implementing in Python Design Patterns applyed to Enterprise Information Systems. The ideas here implemented are discussed in more detail in the blog Enterprise Information Systems Development, through a series of posts entitled "EIS Patterns". The current implementation, which uses the Decorator Design Pattern, is explained from Part IV of this series onwards. To better understand its evolution, it is suggested to read the Change Log <>.

Code is built on top of some concepts borrowed from ERP5 system, though implemented in a different way, given that this is a didactic framework. If you need a fully functional, scalable, and flexible EIS framework in Python, you should try ERP5 instead. The concepts here used are:

Concept 1: Resource
Is anything used for production. It can be material (components, money ...) or immaterial (machine time, human skill ...). Materials are referred as Work Items and immaterials as Operations in general. A Kit is a set of resources.
Concept 2: Node
Is a business entity that transforms resources. It can be a Person or a Machine. An Organization is a set of nodes.
Concept 3: Movement
Is a movement of any resource between two nodes. It is categorized as a Transformation or a Transportation. A Process is a set of movements.

Naturally, some supportive concepts will appear as the project evolves, such as Category, used to classify and configure the core concepts.

The core idea is to make the objects the closest to real-world entities, therefore, Processes controls Nodes, which are the active entities that perform Operations which transform or transport Resources. To extend the framework, different approaches are used in accordance to the type of entity - for a better understanding on how this is achieved, please refer to the blog.


Pre-setup (on Ubuntu):

$ apt-get install python-setuptools
$ easy_install pip

Install dependencies (if needed) and run all specs (depending on your environment, you'll need to call with sudo):

$ make

Run only unit specs:

$ make unit

Run only acceptance specs:

$ make acceptance