Automated Code Review Tool

Abstract

Automated Code Review Tool is a Python project that performs 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-tool.
2. Open the folder in your code editor or IDE.
3. Create a file named automated_code_review_tool.py.
4. Copy the code below into your file.

Write the Code

"""
Automated Code Review Tool

Features:
- Static analysis
- Style checks
- 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 Tool")
        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_tool.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_tool.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 12–15)

import sys
import os
import re
from collections import defaultdict

2. StaticAnalyzer — the class (lines 17–28)

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 30–42)

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 44–58)

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 60–77)

class CLI:
    @staticmethod
    def run():
        print("Automated Code Review Tool")
        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 a line-based linter that reports long lines, TODO markers and trailing whitespace.

Press Run to see what your code prints.

Conclusion

Automated Code Review Tool 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.