Metadata-Version: 2.1
Name: business-rule-engine
Version: 0.1.1
Summary: Python DSL for setting up business intelligence rules
Home-page: https://github.com/manfred-kaiser/business-rule-engine
Author: Manfred Kaiser
Author-email: manfred.kaiser@logfile.at
License: UNKNOWN
Project-URL: Source, https://github.com/manfred-kaiser/business-rule-engine
Project-URL: Tracker, https://github.com/manfred-kaiser/business-rule-engine/issues
Keywords: business rules engine
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >= 3.6
Description-Content-Type: text/markdown
Requires-Dist: formulas

business-rule-engine
====================

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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.

```python
params = {
    'products_in_stock': 10
}
```

### 2. Define custom functions

```python
def order_more(items_to_order):
    print("you ordered {} new items".format(items_to_order))
    return items_to_order
```

### 3. Write the rules


```python
rules = """
rule "order new items"
when
    products_in_stock < 20
then
    order_more(50)
end
"""
```

### 3. Create the parser and parse the rule

```python
from business_rule_engine import RuleParser

parser = RuleParser()
parser.register_function(order_more)
parser.parsestr(rules)
parser.execute(params)
```

## Supported functions

Business rule engine uses Excel like functions (thanks to [formulas](https://github.com/vinci1it2000/formulas). So it is possible to use most of them in rules.


## Multiple conditions and multiple actions

You can make multiple checks on the same params, and call multiple actions as needed:

```python
rules = """
rule "order new items"
when
    AND(products_in_stock < 20,
    products_in_stock >= 5)
then
    order_more(50)
end

rule "order new items urgent"
when
    products_in_stock < 5,
then
    AND(order_more(10, true),
    order_more(50))
end
"""
```

## Custom functions

You can also write your own functions to validate conditions and use other libraries functions as actions:

```python
from business_rule_engine import RuleParser

def is_even(num):
   if (num % 2) == 0:
      return True
   return False

params = {
    'number': 10
}

rules = """
rule "check even number"
when
    is_even(number) = True
then
    print("is even")
end
"""

parser = RuleParser()
parser.register_function(is_even)
parser.register_function(print)
parser.parsestr(rules)
parser.execute(params)

```

## Handle missing rule parameters

If some argruments are missing, the rule engine will raise a ValueError.

There are some use cases, when you have to work with incomplete data. In such cases, you can define
default arguments.

You enable default rule arguments with the parameter `set_defaule_arg`. The default argument will have the Value `None`. To provide another value you can use `default_arg`.

```python
params = {}

rules = """
rule "order new items"
when
    products_in_stock < 20
then
    order_more(50)
end
"""

parser = RuleParser()
parser.register_function(order_more)
parser.parsestr(rules)
parser.execute(params, set_default_arg=True, default_arg=0)
```

## Error Handling

Most of the errors are caused by missing parameters, you can handle the errors and interpret the results handling ValueError:

```python
from business_rule_engine import RuleParser

# proposital typo
params = {
    'produtcs_in_stock': 30
}

rules = """
rule "order new items"
when
    products_in_stock < 20
then
    order_more(50)
end
"""

parser = RuleParser()
parser.register_function(order_more)
parser.parsestr(rules)
try:
    ret = parser.execute(params)
    if ret is False:
        print("No conditions matched")
except ValueError as e:
    print(e)
```

## Debug

To debug the rules processing, use the logging lib.

You can insert in your Python script to log to stdout:
```
import logging
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
```


