import 'dart:io';

import 'package:dart_code_metrics/lint_analyzer.dart';

Future<void> main() async {

// Get some folder you would like to analyze

const foldersToAnalyze = ['lib', 'test'];

// Root folder path is used to resolve relative file paths

const rootFolder = 'projectRoot';

// First of all config has to be created for a checker

const config = LintConfig(

excludePatterns: ['test/resources/**'],

excludeForMetricsPatterns: ['test/**'],

metrics: {

'maximum-nesting-level': '5',

'number-of-methods': '10',

},

excludeForRulesPatterns: ['test/**'],

rules: {

'double-literal-format': {},

'newline-before-return': {'severity': 'info'},

},

antiPatterns: {'long-method': {}},

);

const analyzer = LintAnalyzer();

final result =

await analyzer.runCliAnalysis(foldersToAnalyze, rootFolder, config);

// Now runner.results() contains some insights about analyzed code. Let's report it!

// For a simple example we would report results to terminal

// Now pass collected analysis reports from runner to reporter and that's it

await analyzer

.getReporter(name: 'console', output: stdout, reportFolder: '.')

?.report(result);

// There is also JsonReporter for making machine-readable reports

// HtmlReporter produces fancy html-documents with bells and whistles

// And CodeClimateReporter produces reports that are widely understood by various CI tools

// If none of these fits your case you can always access raw analysis info via results() method of runner and process it any way you see fit

}