Automated Code Review System

Abstract

Automated Code Review System is a Python project that uses AI to perform automated code reviews. The application features static analysis, style checking, and a CLI interface, demonstrating best practices in code quality and automation.

Prerequisites

• Python 3.8 or above
• A code editor or IDE
• Basic understanding of code quality and static analysis
• Required libraries: flake8, pylint

Before you Start

Install Python and the required libraries:

pip install flake8 pylint

Getting Started

Create a Project

1. Create a folder named automated-code-review-system.
2. Open the folder in your code editor or IDE.
3. Create a file named automated_code_review_system.py.
4. Copy the code below into your file.

Write the Code

"""
Automated Code Review System

Features:
- Static analysis
- Reporting
- Modular design
- CLI interface
- Error handling
"""
import sys
import os
import re
from collections import defaultdict

class StaticAnalyzer:
    def __init__(self):
        pass
    def analyze(self, file_path):
        with open(file_path, 'r') as f:
            code = f.read()
        issues = []
        if 'import *' in code:
            issues.append('Wildcard import detected')
        if len(code.split('\n')) > 500:
            issues.append('File too long')
        return issues

class StyleChecker:
    def __init__(self):
        pass
    def check(self, file_path):
        with open(file_path, 'r') as f:
            lines = f.readlines()
        issues = []
        for i, line in enumerate(lines):
            if len(line) > 80:
                issues.append(f'Line {i+1} too long')
            if '\t' in line:
                issues.append(f'Line {i+1} contains tab')
        return issues

class CodeReview:
    def __init__(self):
        self.analyzer = StaticAnalyzer()
        self.style = StyleChecker()
    def review(self, file_path):
        issues = self.analyzer.analyze(file_path)
        issues += self.style.check(file_path)
        return issues
    def report(self, file_path):
        issues = self.review(file_path)
        print(f"Code Review Report for {file_path}:")
        for issue in issues:
            print(f"- {issue}")
        if not issues:
            print("No issues found.")

class CLI:
    @staticmethod
    def run():
        print("Automated Code Review System")
        while True:
            cmd = input('> ')
            if cmd.startswith('review'):
                parts = cmd.split()
                if len(parts) < 2:
                    print("Usage: review <file_path>")
                    continue
                file_path = parts[1]
                cr = CodeReview()
                cr.report(file_path)
            elif cmd == 'exit':
                break
            else:
                print("Unknown command")

if __name__ == "__main__":
    try:
        CLI.run()
    except Exception as e:
        print(f"Error: {e}")
        sys.exit(1)

Example Usage

python automated_code_review_system.py

How it fits together

Read from the top: this is what runs when you execute the file, and which function calls which. It is generated from the code, so it cannot drift from it.

  flowchart TD
  RUN(["python automated_code_review_system.py"])
  StaticAnalyzer["StaticAnalyzer
class"]
  StyleChecker["StyleChecker
class"]
  CodeReview["CodeReview
class"]
  CLI["CLI
class"]
  RUN --> StaticAnalyzer
  CLI --> CodeReview
  CodeReview --> StaticAnalyzer
  CodeReview --> StyleChecker

Explanation

Key Features

• Static Analysis: Checks code for errors and best practices.
• Style Checking: Ensures code style compliance.
• Error Handling: Validates inputs and manages exceptions.
• CLI Interface: Interactive command-line usage.

Code Breakdown

1. What it imports (lines 11–14)

import sys
import os
import re
from collections import defaultdict

2. StaticAnalyzer — the class (lines 16–27)

class StaticAnalyzer:
    def __init__(self):
        pass
    def analyze(self, file_path):
        with open(file_path, 'r') as f:
            code = f.read()
        issues = []
        if 'import *' in code:
            issues.append('Wildcard import detected')
        if len(code.split('\n')) > 500:
            issues.append('File too long')
        return issues

3. StyleChecker — the class (lines 29–41)

class StyleChecker:
    def __init__(self):
        pass
    def check(self, file_path):
        with open(file_path, 'r') as f:
            lines = f.readlines()
        issues = []
        for i, line in enumerate(lines):
            if len(line) > 80:
                issues.append(f'Line {i+1} too long')
            if '\t' in line:
                issues.append(f'Line {i+1} contains tab')
        return issues

4. CodeReview — the class (lines 43–57)

class CodeReview:
    def __init__(self):
        self.analyzer = StaticAnalyzer()
        self.style = StyleChecker()
    def review(self, file_path):
        issues = self.analyzer.analyze(file_path)
        issues += self.style.check(file_path)
        return issues
    def report(self, file_path):
        issues = self.review(file_path)
        print(f"Code Review Report for {file_path}:")
        for issue in issues:
            print(f"- {issue}")
        if not issues:
            print("No issues found.")

5. CLI — the class (lines 59–76)

class CLI:
    @staticmethod
    def run():
        print("Automated Code Review System")
        while True:
            cmd = input('> ')
            if cmd.startswith('review'):
                parts = cmd.split()
                if len(parts) < 2:
                    print("Usage: review <file_path>")
                    continue
                file_path = parts[1]
                cr = CodeReview()
                cr.report(file_path)
            elif cmd == 'exit':
                break
            else:
                print("Unknown command")

The file defines 4 top-level symbols in all; the whole thing is above under Write the Code.

Features

• Automated Code Review: Static analysis and style checking
• Modular Design: Separate functions for each tool
• Error Handling: Manages invalid inputs and exceptions
• Production-Ready: Scalable and maintainable code

Next Steps

Enhance the project by:

• Supporting batch review of multiple files
• Creating a GUI with Tkinter or a web app with Flask
• Adding custom linting rules
• Unit testing for reliability

Educational Value

This project teaches:

• Code Quality: Static analysis and style checking
• Software Design: Modular, maintainable code
• Error Handling: Writing robust Python code

Real-World Applications

• Continuous Integration
• Code Quality Assurance
• Educational Tools

Checkpoint exercise

This exercise practises walking a Python syntax tree to flag missing docstrings and long functions, the idea behind static review tools.

Press Run to see what your code prints.

Conclusion

Automated Code Review System demonstrates how to build a scalable and accurate code review tool using Python. With modular design and extensibility, this project can be adapted for real-world applications in CI/CD, education, and more. For more advanced projects, visit Python Central Hub.