Python Rule Engines: Automate and Enforce with Python

Python rule engines are powerful tools that can be used to automate business processes, make decisions, and enforce business logic. Learn more about how Python rule engines can help your business.

Alankrit Gupta

11
 min read
Python Rule Engines: Automate and Enforce with Python
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11
 min read
Table of Contents

Rule engines are a type of software that can be used to automate business processes, make decisions, and enforce business logic. They are typically written in declarative language, which means that they describe the conditions that must be met in order for an action to be taken. Rule engines are used in a wide variety of industries, including financial services, healthcare, and manufacturing.

In this blog post, we will provide an overview of Python rule engines. We will discuss what they are, how they work, and some of the benefits of using them. We will also provide a list of some of the most popular Python rule engines.

By the end of this blog post, you will have a good understanding of Python rule engines and how they can be used to automate business processes, make decisions, and enforce business logic.

Things You Must Know About Python Rule Engines

Python rule engines offers solutions for businesses seeking to automate decision-making processes and manage rule-based systems effectively. However, it's essential to understand both their advantages and limitations to make informed choices. Here, we'll explore key aspects of Python rule engines and shed light on how Nected addresses these issues even more effectively.

1. Rule Representation in Python: Python rule engines provide an intuitive and structured way to represent business rules, fostering collaboration between developers and domain experts. Representing rules in code can be complex and require technical expertise, potentially limiting accessibility. Nected simplifies rule representation with a user-friendly interface, eliminating the need for coding and enabling rule creation through simple steps.

2. Rule Execution and Inference Mechanisms: Python rule engines offer robust mechanisms for rule evaluation, efficiently matching data against rules to trigger actions. As rule sets grow larger, traditional Python rule engines may face scalability issues, impacting performance. Nected's language-agnostic approach ensures flexibility and scalability, making it ideal for managing complex rule sets and extensive data volumes without compromising efficiency.

3. Integration with Python Ecosystem: Python rule engines seamlessly integrate with the Python ecosystem, allowing businesses to tap into a vast library of Python tools and frameworks. Relying heavily on Python can make rule engines less flexible when dealing with non-Python-based systems. Nected's language-agnostic design transcends these limitations, enabling rule management and execution without requiring extensive Python expertise. This makes it a versatile choice for businesses with diverse technology stacks.

4. Complexity and Technical Expertise: Python rule engines empower rule-based automation but often demand a certain level of technical knowledge and coding skills. This complexity may hinder the adoption of Python rule engines for non-technical users and smaller businesses.

Nected levels the playing field by offering a no-code/low-code approach. It simplifies rule engine usage, making it accessible to a broader audience and minimizing the need for in-depth technical expertise.

In essence, while Python rule engines bring undeniable benefits to the table, Nected takes the concept further by providing a more user-friendly, scalable, and versatile alternative. It addresses the challenges associated with code-heavy solutions, making rule-based decision management accessible to all.

This workflow demonstrates how Python rule engines can automate decision-making and manage rule-based systems effectively. However, Nected's unique approach makes it an even more powerful and versatile solution for a wide range of applications.

Read Also: Spring Boot Rule Engine: Powering Business Logic with Ease

Advantages of Using Nected as a Python Rule Engine:

Nected distinguishes itself from other rule engines through various features:

  1. Seamless Data & API Integration: Nected seamlessly integrates data across different systems via database connectors, enabling smooth data access and processing. further you can integrate Nected in your Python application via HTTP protocol seamlessly.
  2. Cloud-based: Nected is a cloud-based rule engine, which means that it can be accessed from anywhere with an internet connection. This makes it easy to use Nected for businesses with distributed teams or that need to access their rule engine from multiple locations.
  3. Limitless Customizability: With Nected's custom code capabilities, users can code in Javascript to write any complex conditions and outputs to meet any specific requirements beyond built-in features.
  4. Syncing Rule Outcomes: Nected allows users to sync rule outcomes back into their systems through database and API connectors, ensuring seamless data flow.
  5. Support for Different Rule Types: Nected supports various rule types, including decision tables, simple rules, and rulesets, catering to diverse business needs.
  6. Language agnostic: Nected is language agnostic, which means that it can be used with any programming language. This makes it easy to use Nected with other languages or frameworks including Python.

By leveraging these advantages, Nected empowers businesses to overcome limitations commonly encountered in Python rule engines, providing a powerful and customizable rule-based automation platform.

To import and utilize rules from Nected in your Python projects, follow this video guide:

Below is the Python code snippet that we’ve used in this tutorial to create the Loan Rule:

import requests
import json

# Define the API endpoint for the Loan rule
rule_endpoint = "https://nected-59.nected.io/nected/rule/{RULE_API}"

# Define your API key obtained from Nected
api_key = "YOUR_API_KEY" # If authentication is enabled

# Define the payload for the API request
payload = {
    "environment": "staging",
    "isTest": False,
    "params": {
        "Credit_Score": 750,  # Set the credit score parameter
        "Loan_Amount": 100000  # Set the loan amount parameter
    }
}

# Define headers with the API key
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {api_key}" #If auth is enabled
}

# Make a POST request to execute the rule
response = requests.post(rule_endpoint, headers=headers, data=json.dumps(payload))

if response.status_code == 200:
    # Parse the JSON response
    response_data = response.json()

    # Extract the relevant output data from the response
    output_data = response_data["data"]["output"][0]

    # Check if the rule is satisfied
    if output_data["defaultOutputData"]:
        print("Loan is approved")
    else:
        print("Loan is not approved")
else:
    print("Failed to execute the rule")

By following these steps and utilizing Nected's API, you can seamlessly integrate your Nected rules into your Python applications, enabling you to make data-driven decisions effortlessly.

Read Also: Camunda Rule Engine: Streamlining Workflow Automation

Comparing with other Popular Python Rule Engines

Here is a comparison of the top Python rule engines:

Parameters PyKE Nected PyCLIPS PyKnow PyDrools
Coding Knowledge Needed Basic Python and machine learning concepts needed Most cases No coding knowledge is required to use Nected  Basic Python and CLIPS rule-based expert system. Basic Python, ontologies, and reasoning Basic Python and Drools business rules management system
Use Cases Powerful and versatile. Can be used to build a wide variety of applications, including customer relationship management (CRM), enterprise resource planning (ERP), and business process management (BPM) applications. Very powerful and versatile. Can be used to build a wide variety of applications, including customer relationship management (CRM), enterprise resource planning (ERP), and business process management (BPM) applications. Less powerful and versatile than Nected and PyKE. Can be used to build simpler rule-based applications. Less powerful and versatile than others. Can be used to build simpler rule-based applications. Less powerful and versatile than Nected and PyKE. Can be used to build simpler rule-based applications.
Supported Rule Formats Decision tables, simple rules, and rulesets. Decision tables, simple rules, and rulesets. Decision tables and simple rules. Decision tables, simple rules, and rulesets. Decision tables and simple rules.
Scalability Scalable. Can be used to develop and deploy applications of all sizes. Highly scalable. Can be used to develop and deploy applications of all sizes. Less scalable than Nected or PyKE. Can be used to develop and deploy small to medium-sized applications. Less scalable than Nected, PyKE, or PyDrools. Can be used to develop and deploy small to medium-sized applications. Less scalable than Nected, PyKE, PyCLIPS, or PyKnow. Can be used to develop and deploy small applications.
Application Size Can handle mostly medium to large applications. Can handle high-volume applications. Can handle small to medium-sized applications. Can handle small to medium-sized applications. Can handle small applications.
Features Decision tables, simple rules, rulesets, and custom code. Built-in low-code application platform, visual drag-and-drop interface, pre-built components, reusable templates, integration with existing IT systems, support for mobile devices, and a variety of security features. Decision tables, simple rules, and rulesets. Decision tables, simple rules, and rulesets. Decision tables and simple rules.
Documentation easy-to-read for programmers only Detailed and easy-to-read Detailed but easy-to-read for programmers Detailed and easy-to-read Detailed but easy-to-read for programmers only
Community Support quality Good. Active community. Excellent. Active and supportive community. Fair. Less active community than Nected or PyKE. Fair. Less active community than Nected, PyKE, or PyDrools. Fair. Less active community than Nected, PyKE, PyCLIPS, or PyKnow.

The best rule engine for you will depend on your specific needs. If you need a rule engine that is easy to use and understand, then PyKE, PyCLIPS, or PyKnow may be a good choice. If you need a rule engine that is powerful and scalable, then PyDrools may be a good choice. And if you need a rule engine that is lightweight and does not require a lot of system resources, then PyRules may be a good choice.

However, if you are looking for a rule engine that is all of the above, then Nected is the best choice for you. Nected is a low-code, no-code rule engine that is compatible with Python applications. It is easy to use and understand, and it is powerful yet lightweight. Nected supports all rule formats, and it is scalable, efficient, and feature-rich.

Try Nected for free today and experience a more user-friendly approach to building and managing rules.

Conclusion:

Python rule engines are a powerful tool that can be used to automate business processes, make decisions, and enforce business logic. They offer a number of benefits, including automation, decision-making, business logic enforcement, scalability, and flexibility. However, they also have some limitations, including complexity, performance, scalability, and integration.

There are a number of popular Python rule engines available, including PyKE, PyCLIPS, PyKnow, PyDrools, and PyRules. Each of these engines has its own strengths and weaknesses, so you need to choose one that meets your specific needs.

Python Rule Engines FAQs:

Q1. What is the Python alternative to drools?

There are a number of Python alternatives to Drools. Some of the most popular alternatives include:

  1. PyKE: PyKE is a powerful rule engine that supports a variety of rule formats.
  2. PyCLIPS: PyCLIPS is a lightweight rule engine that is easy to use and understand.
  3. PyKnow: PyKnow is a powerful rule engine that supports a variety of rule formats.
  4. PyRules: PyRules is a lightweight rule engine that is easy to use and understand.
  5. Nected: Nected is lightweight cloud-based rule engine that is easy to setup, easy to use and supports variety of rule formats including option to custom code giving unlimited flexibility

Q2. What is a rule in Python?

In Python, a rule refers to a logical condition represented as an "if-then" statement, used for decision-making and automation. Rules dictate specific actions or outcomes when certain conditions are met, empowering efficient and structured code execution.

Q3. What is a rule-based engine?

A rule-based engine is a software application that executes a set of rules. Rules are typically written in declarative language, which means that they describe the conditions that must be met in order for an action to be taken. Rule-based engines are used to automate business processes, make decisions, and enforce business logic.

Q4. What is the rule engine in AI?

In AI, a rule engine is a critical component that applies predefined rules to process data and generate decisions or actions. Rule engines are often incorporated into AI systems to facilitate logic-based decision-making in complex scenarios.

Q5. What are the benefits of a rules engine?

The benefits of rule engines include:

  1. Automation: Rule engines can automate business processes, freeing up employees to focus on more strategic tasks.
  2. Decision-making: Rule engines can help businesses make better decisions by providing a structured way to evaluate data and identify patterns.
  3. Business logic enforcement: Rule engines can help businesses enforce business logic by ensuring that rules are consistently applied.
  4. Scalability: Rule engines can be scaled to meet the needs of growing businesses.
  5. Flexibility: Rule engines can be customized to meet the specific needs of businesses.

Q6. What is the rule engine pattern in Python?

The rule engine pattern in Python is a design pattern that allows you to create and execute rule-based systems in Python. Rule-based systems are a type of computer program that makes decisions based on a set of rules. These rules can be simple or complex, and they can be used to solve a wide variety of problems, such as routing customer support tickets, detecting fraud, or recommending products to users.

To use the rule engine pattern in Python, you first need to choose a rule engine library. There are many different rule engine libraries available, so it's important to choose one that is right for your needs. Once you've chosen a rule engine library, you need to define your rules. This can be done using the rule engine library's API.

Once you've defined your rules, you can execute them using the rule engine library's API. This will cause the rule engine to evaluate your rules and make decisions based on them.

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