Python DSL for setting up business intelligence rules that can be configured without code
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.
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.
from business_rules2.variables import ( BaseVariables, numeric_rule_variable, string_rule_variable, select_rule_variable ) class Products(): def __init__(self): self.stock_state = 0 self.related_products = 2 self.current_inventory = 3 self.expire_in_days = 2 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): return self.product.expire_in_days @string_rule_variable() def current_month(self): return datetime.datetime.now().strftime("%B")
2. Define your set of actions
These are the actions that are available to be taken when a condition is triggered.
from business_rules2.fields import FIELD_NUMERIC from business_rules2.actions import ( BaseActions, rule_action ) class ProductActions(BaseActions): def __init__(self, product): self.product = product @rule_action() def change_stock_state(self, stock_state): self.product.stock_state = stock_state @rule_action() def order_more(self, number_to_order): self.product.stock_state += number_to_order
3. Build the rules
= equal to
* int * str
> greater than
< less than
>= greater than or equal to
>= less than or equal to
* startswith * endswid * in * not in * all in * one in * exactly one in * containedby * not containedby * matches * is * True * False * notblank
rule "expired foods" when expiration_days < 5 AND current_inventory > 20 then put_on_sale(sale_percentage=0.25, value=25) end rule "christmas time" when current_inventory < 5 OR (current_month = 'December' AND current_inventory < 30) then order_more(number_to_order=40) end
4. Run your rules
from business_rules2 import run_all from business_rules2.parser import RuleParser rules = """ rule "expired foods" when expiration_days < 5 AND current_inventory > 20 then put_on_sale(sale_percentage=0.25, value=25) end rule "christmas time" when current_inventory < 5 OR (current_month = 'December' AND current_inventory < 30) then order_more(number_to_order=40) end """ product = Products() parser = RuleParser() rules_translated = parser.parsestr(rules) run_all( rule_list=rules_translated, defined_variables=ProductVariables(product), defined_actions=ProductActions(product), stop_on_first_trigger=True )
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.
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.
boolean - a True or False value.
select - a set of values, where the threshold will be a single item.
select_multiple - a set of values, where the threshold will be a set of items.
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Hashes for business_rules2-1.1.4-py3-none-any.whl