business-rules

As a software system grows in complexity and usage, it can become burdensome if
every change to the logic/behavior of the system also requires you to write and
deploy new code. The goal of this business rules engine is to provide a simple
interface allowing anyone to capture new rules and logic defining the behavior
of a system, and a way to then process those rules on the backend.

You might, for example, find this is a useful way for analysts to define
marketing logic around when certain customers or items are eligible for a
discount or to automate emails after users enter a certain state or go through
a particular sequence of events.

Usage

1. Define Your set of variables

Variables represent values in your system, usually the value of some particular object. You create rules by setting threshold conditions such that when a variable is computed that triggers the condition some action is taken.

You define all the available variables for a certain kind of object in your code, and then later dynamically set the conditions and thresholds for those.

For example:

class
 
ProductVariables
(
BaseVariables
):

    
def
 
__init__
(
self
,
 
product
):
        
self
.
product
 
=
 
product

    
@numeric_rule_variable
    
def
 
current_inventory
(
self
):
        
return
 
self
.
product
.
current_inventory

    
@numeric_rule_variable
(
label
=
'Days until expiration'
)
    
def
 
expiration_days
(
self
)
        
last_order
 
=
 
self
.
product
.
orders
[
-
1
]
        
return
 
(
last_order
.
expiration_date
 
-
 
datetime
.
date
.
today
())
.
days

    
@string_rule_variable
()
    
def
 
current_month
(
self
):
        
return
 
datetime
.
datetime
.
now
()
.
strftime
(
"%B"
)

    
@select_rule_variable
(
options
=
Products
.
top_holiday_items
())
    
def
 
goes_well_with
(
self
):
        
return
 
products
.
related_products

2. Define your set of actions

These are the actions that are available to be taken when a condition is triggered.

For example:

class
 
ProductActions
(
BaseActions
):

    
def
 
__init__
(
self
,
 
product
):
        
self
.
product
 
=
 
product

    
@rule_action
(
params
=
{
"sale_percentage"
:
 
FIELD_NUMERIC
})
    
def
 
put_on_sale
(
self
,
 
sale_percentage
):
        
self
.
product
.
price
 
=
 
(
1.0
 
-
 
sale_percentage
)
 
*
 
self
.
product
.
price
        
self
.
product
.
save
()

    
@rule_action
(
params
=
{
"number_to_order"
:
 
FIELD_NUMERIC
})
    
def
 
order_more
(
self
,
 
number_to_order
):
        
ProductOrder
.
objects
.
create
(
product_id
=
self
.
product
.
id
,
                                    
quantity
=
number_to_order
)

If you need a select field for an action parameter, another -more verbose- syntax is available:

class
 
ProductActions
(
BaseActions
):

    
def
 
__init__
(
self
,
 
product
):
        
self
.
product
 
=
 
product

    
@rule_action
(
params
=
[{
'fieldType'
:
 
FIELD_SELECT
,
                          
'name'
:
 
'stock_state'
,
                          
'label'
:
 
'Stock state'
,
                          
'options'
:
 
[
                            
{
'label'
:
 
'Available'
,
 
'name'
:
 
'available'
},
                            
{
'label'
:
 
'Last items'
,
 
'name'
:
 
'last_items'
},
                            
{
'label'
:
 
'Out of stock'
,
 
'name'
:
 
'out_of_stock'
}
                        
]}])
    
def
 
change_stock_state
(
self
,
 
stock_state
):
        
self
.
product
.
stock_state
 
=
 
stock_state
        
self
.
product
.
save
()

3. Build the rules

A rule is just a JSON object that gets interpreted by the business-rules engine.

Note that the JSON is expected to be auto-generated by a UI, which makes it simple for anyone to set and tweak business rules without knowing anything about the code. The javascript library used for generating these on the web can be found here.

An example of the resulting python lists/dicts is:

rules
 
=
 
[
# expiration_days < 5 AND current_inventory > 20
{
 
"conditions"
:
 
{
 
"all"
:
 
[
      
{
 
"name"
:
 
"expiration_days"
,
        
"operator"
:
 
"less_than"
,
        
"value"
:
 
5
,
      
},
      
{
 
"name"
:
 
"current_inventory"
,
        
"operator"
:
 
"greater_than"
,
        
"value"
:
 
20
,
      
},
  
]},
  
"actions"
:
 
[
      
{
 
"name"
:
 
"put_on_sale"
,
        
"params"
:
 
{
"sale_percentage"
:
 
0.25
},
      
},
  
],
},

# current_inventory < 5 OR (current_month = "December" AND current_inventory < 20)
{
 
"conditions"
:
 
{
 
"any"
:
 
[
      
{
 
"name"
:
 
"current_inventory"
,
        
"operator"
:
 
"less_than"
,
        
"value"
:
 
5
,
      
},
    
]},
      
{
 
"all"
:
 
[
        
{
  
"name"
:
 
"current_month"
,
          
"operator"
:
 
"equal_to"
,
          
"value"
:
 
"December"
,
        
},
        
{
 
"name"
:
 
"current_inventory"
,
          
"operator"
:
 
"less_than"
,
          
"value"
:
 
20
,
        
}
      
]},
  
},
  
"actions"
:
 
[
    
{
 
"name"
:
 
"order_more"
,
      
"params"
:{
"number_to_order"
:
 
40
},
    
},
  
],
}]

Export the available variables, operators and actions

To e.g. send to your client so it knows how to build rules

from
 
business_rules
 
import
 
export_rule_data
export_rule_data
(
ProductVariables
,
 
ProductActions
)

that returns

{
"variables"
:
 
[
    
{
 
"name"
:
 
"expiration_days"
,
      
"label"
:
 
"Days until expiration"
,
      
"field_type"
:
 
"numeric"
,
      
"options"
:
 
[]},
    
{
 
"name"
:
 
"current_month"
,
      
"label"
:
 
"Current Month"
,
      
"field_type"
:
 
"string"
,
      
"options"
:
 
[]},
    
{
 
"name"
:
 
"goes_well_with"
,
      
"label"
:
 
"Goes Well With"
,
      
"field_type"
:
 
"select"
,
      
"options"
:
 
[
"Eggnog"
,
 
"Cookies"
,
 
"Beef Jerkey"
]}
                
],
  
"actions"
:
 
[
    
{
 
"name"
:
 
"put_on_sale"
,
      
"label"
:
 
"Put On Sale"
,
      
"params"
:
 
{
"sale_percentage"
:
 
"numeric"
}},
    
{
 
"name"
:
 
"order_more"
,
      
"label"
:
 
"Order More"
,
      
"params"
:
 
{
"number_to_order"
:
 
"numeric"
}}
  
],
  
"variable_type_operators"
:
 
{
    
"numeric"
:
 
[
 
{
"name"
:
 
"equal_to"
,
                  
"label"
:
 
"Equal To"
,
                  
"input_type"
:
 
"numeric"
},
                 
{
"name"
:
 
"less_than"
,
                  
"label"
:
 
"Less Than"
,
                  
"input_type"
:
 
"numeric"
},
                 
{
"name"
:
 
"greater_than"
,
                  
"label"
:
 
"Greater Than"
,
                  
"input_type"
:
 
"numeric"
}],
    
"string"
:
 
[
 
{
 
"name"
:
 
"equal_to"
,
                  
"label"
:
 
"Equal To"
,
                  
"input_type"
:
 
"text"
},
                
{
 
"name"
:
 
"non_empty"
,
                  
"label"
:
 
"Non Empty"
,
                  
"input_type"
:
 
"none"
}]
  
}
}

Run your rules

from
 
business_rules
 
import
 
run_all

rules
 
=
 
_some_function_to_receive_from_client
()

for
 
product
 
in
 
Products
.
objects
.
all
():
    
run_all
(
rule_list
=
rules
,
            
defined_variables
=
ProductVariables
(
product
),
            
defined_actions
=
ProductActions
(
product
),
            
stop_on_first_trigger
=
True
           
)

API

Variable Types and Decorators:

The type represents the type of the value that will be returned for the variable and is necessary since there are different available comparison operators for different types, and the front-end that’s generating the rules needs to know which operators are available.

All decorators can optionally take a label:

• label – A human-readable label to show on the frontend. By default we just split the variable name on underscores and capitalize the words.

The available types and decorators are:

numeric – an integer, float, or python Decimal.

@numeric_rule_variable operators:

• equal_to
• greater_than
• less_than
• greater_than_or_equal_to
• less_than_or_equal_to

Note: to compare floating point equality we just check that the difference is less than some small epsilon

string – a python bytestring or unicode string.

@string_rule_variable operators:

• equal_to
• starts_with
• ends_with
• contains
• matches_regex
• non_empty

boolean – a True or False value.

@boolean_rule_variable operators:

• is_true
• is_false

select – a set of values, where the threshold will be a single item.

@select_rule_variable operators:

• contains
• does_not_contain

select_multiple – a set of values, where the threshold will be a set of items.

@select_multiple_rule_variable operators:

• contains_all
• is_contained_by
• shares_at_least_one_element_with
• shares_exactly_one_element_with
• shares_no_elements_with

Returning data to your client

Contributing

Open up a pull request, making sure to add tests for any new functionality. To set up the dev environment (assuming you’re using virtualenvwrapper):

$ python -m virtualenv venv
$ 
source
 ./venv/bin/activate
$ pip install -r dev-requirements.txt -e .
$ pytest

Alternatively, you can also use Tox:

$ pip install 
"tox<4"
$ tox -p auto --skip-missing-interpreters

History

1.1.1

Release date: 2022-3-18

• Fix package description and long description

1.1.0

Release date: 2022-3-18

• Add support for Python 3.5-3.7

1.0.1

Release date: 2016-3-16

• Fixes a packaging bug preventing 1.0.0 from being installed on some platforms.

1.0.0

Release date: 2016-3-16

• Removes caching layer on rule decorator