Categoria: Programação

PHP Test Coverage Using Bitbucket and Codacy

Autor do post Por rafael
Data de publicação fevereiro 21, 2020
Nenhum comentário em PHP Test Coverage Using Bitbucket and Codacy

Wikipedia:

In computer science, code coverage is a measure used to describe the degree to which the source code of a program is tested by a particular test suite. A program with high code coverage has been more thoroughly tested and has a lower chance of containing software bugs than a program with low code coverage.

Testing is an unavoidable process for building a trustful software. Unfortunately, in PHP world we have a massive number of legacy software still running today that are very valuable but born in an age where testing was skipped for various reasons.

As today we are refactoring those untested systems into tested ones or we are creating new projects already focusing on having tests, we can go one step further and measure the code coverage, leveraging bug protection and code quality.

You can use these steps for a legacy project, a new project, a well-covered project, a poorly covered project; no matter the state of your project.

We are considering a PHP project using Bitbucket Pipelines as our CI and Codacy for monitoring our test coverage reports but the main concepts could be easily used when using other tools.

Table of contents:

Dependencies installation
PHPUnit configuration
Set up Codacy project API token
Pipelines configuration

1. Dependencies installation

Use composer to install dependencies:

composer require --dev phpunit/php-code-coverage codacy/coverage

Installation results would be similar to:

Using version ^1.4 for codacy/coverage
./composer.json has been updated
Loading composer repositories with package information
Updating dependencies (including require-dev)
Package operations: 3 installs, 0 updates, 0 removals
  - Installing symfony/process (v5.0.4): Downloading (100%)
  - Installing gitonomy/gitlib (v1.2.0): Downloading (100%)
  - Installing codacy/coverage (1.4.3): Downloading (100%)
Writing lock file
Generating autoload files
ocramius/package-versions:  Generating version class...
ocramius/package-versions: ...done generating version class

2. PHPUnit configuration

We need to configure at least whitelist and logging sections. They are required to code coverage.

Whitelist is the section that determines which files will be considered as your available code and how existent tests cover this code.

As I want that all my code loaded and analyzes by PHPUnit, I will set processUncoveredFilesFromWhitelist. Considering that all my code is under ./src folder:

<phpunit>
    <!-- ... -->
    <filter>
        <!-- ... -->
        <whitelist processUncoveredFilesFromWhitelist="true">
            <directory suffix=".php">./src</directory>
        </whitelist>
    </filter>
</phpunit>

Logging is where we configure logging of the test execution. Clover configuration is enough for now:

<phpunit>
    <!-- ... -->
    <logging>
      <log type="coverage-clover" target="/tmp/coverage.xml"/>
    </logging>
</phpunit>

You should now run your tests locally to ensure that you can fix everything that will be analyzed by PHPUnit. All errors have to be fixed. One example that might appear:

Fatal error: Interface 'InterfaceClass' not found in /var/www/src/Example/Application/ClassService.php on line 5

Oops.

<?php

namespace Example;

class ClassService implements InterfaceClass {
    /* */
}

I have a class extending from another but I missed the import for the parent class.

<?php

namespace Example;

use Example\Domain\InterfaceClass;

class ClassService implements InterfaceClass {
    /* */
}

And now I am good. After fixing all errors that might appear (and discovering some dead classes...), we test results and report generation message:

OK (10 tests, 17 assertions)

Generating code coverage report in Clover XML format ... done [5.71 seconds]

This has already configured code coverage. We will use Codacy as a tool to keep track of code coverage status, representing them in a beautiful dashboard and some other tools such as a check for new pull requests.

3. Set up Codacy project API token

For sending coverage results to Codacy, we need the project API token. This is located at Settings > Integrations tab.

If there is already a code, you can use it. Otherwise, generate one. A project token would look like something as:

a9564ebc3289b7a14551baf8ad5ec60a // not real

We will use this as an environment variable at Bitbucket. At your project in Bitbucket, go to Configurations > Pipelines > Repository Variables. In my case, I used:

Name: CODACY_PROJECT_TOKEN
Value: a9564ebc3289b7a14551baf8ad5ec60a

I want the value securely encrypted. Then I mark "Secure".

Right now we have Codacy token and the value enabled to use as an environment variable at our pipeline.

4. Pipelines configuration

For Pipelines now you should provide API token as an environment variable:

variables:
  - CODACY_PROJECT_TOKEN: $CODACY_PROJECT_TOKEN

Enable xdebug:

  - pecl install xdebug-2.9.2 && docker-php-ext-enable xdebug

And execute codacycoverage to send saved report to Codacy:

  - src/vendor/bin/codacycoverage clover /tmp/coverage.xml

Considering one of my legacy projects that I am adding code coverage, this could be my unit test step:

using alpine
source code (whitelisted) at site/src
logfile generated at /tmp/unit-clover.xml
g++ gcc make git php7-dev are required to install and enable xdebug

    - step: &step-unit-tests
        name: unit tests
        image: php:7.2-alpine
        variables:
          - CODACY_PROJECT_TOKEN: $CODACY_PROJECT_TOKEN
        caches:
          - composer
        script:
          - apk add --no-cache g++ gcc make git php7-dev
          - pecl install xdebug-2.9.2 && docker-php-ext-enable xdebug
          - site/src/vendor/bin/phpunit -c tests/Unit/phpunit.xml
          - site/src/vendor/bin/codacycoverage clover /tmp/unit-clover.xml

After being successfully executed by pipelines, you may see the results at your Codacy dashboard.

Now code with love.
And coverage.

Useful links:

Tags coverage, php, qa, testing

Programação

Environment Variables in Angular

Autor do post Por rafael
Data de publicação janeiro 23, 2020
Nenhum comentário em Environment Variables in Angular

Need to use different values depending on the environment you’re in? If you’re building an app that needs to use API host URLs depending on the environment, you may do it easily in Angular using the environmen.ts file.

We are considering Angular 8+ apps for this article.

Angular CLI projects already use a production environment variable to enable production mode when in the production environment at main.ts:

if (environment.production) {
  enableProdMode();
}

And you'll also notice that by default in the src/environment folder you have an environment file for development and one for production. Let's use this feature to allow us to use different API host URL depending if we're in development or production mode:

environment.ts:

export const environment = {
  production: false,
  apiHost: https://api.local.com
}

environment.prod.ts:

export const environment = {
  production: true,
  apiHost: https://api.production-url.com
};

And in our app.component.ts all we have to do in order to access the variable is the following:

import { Component } from '@angular/core';
import { environment } from '../environments/environment';

@Component({ ... })
export class AppComponent {
  apiHost: string = environment.apiHost;
}

Now in development mode the apiHost variable resolves to https://api.local.com and in production resolves to https://api.production-url.com. You may run ng build --prod and check.

Detecting Development Mode

Angular also provides us with an utility function called isDevMode that makes it easy to check if the app in running in dev mode:

import { Component, OnInit, isDevMode } from '@angular/core';

@Component({ ... })
export class AppComponent implements OnInit {
  ngOnInit() {
    if (isDevMode()) {
      console.log('Development!');
    } else {
      console.log('Cool. Production!');
    }
  }
}

Adding a Staging Environment

To add a new environment in Angular projects a new entry to configuration property should be added at angular.json file. Let's add a staging environment for example. Note that production property already exists.

"configurations": {
  "production": {
    "optimization": true,
    "outputHashing": "all",
    "sourceMap": false,
    "extractCss": true,
    "namedChunks": false,
    "aot": true,
    "extractLicenses": true,
    "vendorChunk": false,
    "buildOptimizer": true,
    "fileReplacements": [
      {
        "replace": "src/environments/environment.ts",
        "with": "src/environments/environment.prod.ts"
      }
    ]
  },
  "staging": {
    "optimization": true,
    "outputHashing": "all",
    "sourceMap": false,
    "extractCss": true,
    "namedChunks": false,
    "aot": true,
    "extractLicenses": true,
    "vendorChunk": false,
    "buildOptimizer": true,
    "fileReplacements": [
      {
        "replace": "src/environments/environment.ts",
        "with": "src/environments/environment.stating.ts"
      }
    ]
  }

And now we can add a staging environment file and suddenly be and build the project with ng build --configuration=staging on our CI (or deploy process) to deploy on staging environment:

environment.staging.ts

export const environment = {
  production: false,
  apiHost: https://staging.host.com
};

Tags angular, development, typescript

PHP

High-performance Fibonacci numbers generator in PHP

Autor do post Por rafael
Data de publicação janeiro 31, 2019
1 comentário em High-performance Fibonacci numbers generator in PHP

Based on the article High-performance Fibonacci numbers generator in Go I wrote my version using PHP. Despite the differences between PHP and Go architectures reflected in response times, we can face a huge performance difference when using an optimized function. We may notice that we can have the same results, but the quality of the written code can change lots of things.

Recursive approach

function fibonacci(int $n):int {
  if ($n <= 1) {
    return $n;
  }

  return fibonacci($n-1) + fibonacci($n-2);
}

Benchmark and test

function test_fibonacci() {
  $data = [
    [0,0], [1,1], [2,1], [3,2], [4,3], [5,5], [6,8], [10,55], [42,267914296]
  ];

  foreach($data as $test) {
    $result = fibonacci($test[0]);
    if ($result !== $test[1]) {
      throw new \UnexpectedValueException("Error Processing Request. N: {$test[0]}, got: {$result}, expected: {$test[1]}", 1);
    }
  }

  echo "Tests - Success.".PHP_EOL;
}

/**
  * From https://gist.github.com/blongden/2352583
  */
function benchmark($x)
{
    $start = $t = microtime(true);
    $total = $c = $loop = 0;
    while (true) {
        $x();
        $c++;
        $now = microtime(true);
        if ($now - $t > 1) {
            $loop++;
            $total += $c;
            list($t, $c) = array(microtime(true), 0);
        }
        if ($now - $start > 2) {
            return round($total / $loop);
        }
    }
}

Benchmark 10 run: 163,754/sec or 0.0061067210571955ms/op
Benchmark 20 run: 1,351/sec or 0.74019245003701ms/op

As we can see, calculations of 20 Fibonacci numbers takes 123 times longer than 10 Fibonacci numbers. Not well performed at all! The explanation can be found in the linked article.

Sequential approach

function fibonacci_tuned(int $n):float {
  if ($n <= 1) {
    return $n;
  }

  $n2 = 0;
  $n1 = 1;

  for ($i = 2; $i < $n; $i++) {
    $n2_ = $n2;
    $n2 = $n1;
    $n1 = ($n1 + $n2_);
  }

  return $n2 + $n1;
}

function test_fibonacci_tuned() {
  $data = [
    [0,0], [1,1], [2,1], [3,2], [4,3], [5,5], [6,8], [10,55], [42,267914296]
  ];

  foreach($data as $test) {
    $result = fibonacci_tuned($test[0]);
    $float_test_value = (float) $test[1];
    if ($result !== $float_test_value) {
      throw new \UnexpectedValueException("Error Processing Request. N: {$test[0]}, got: {$result}, expected: {$float_test_value}", 1);
    }
  }

  echo "Tests - Success.".PHP_EOL;
}

Results:

Benchmark 10 tuned run: 3,345,999/sec or 0.00029886440492062ms/op
Benchmark 20 tuned run: 2,069,100/sec or 0.00048330191870862ms/op

As a much better scenario, calculate 20 numbers takes almost 2 times longer than 10 numbers. Makes sense. And performs well!

Considering the two approaches, the recursive approach runs 10 Fibonacci numbers operations 20 times longer than sequential one and 1,824 times longer for 20 Fibonacci numbers.

Fibonacci implementation in PHP can be found at https://github.com/rafaelbernard/php-fibonacci.

PHP