elliotjreed/ai

A library for interacting with ChatGPT and Claude AI

2.1.2 2025-03-03 12:26 UTC

Requires

• php: ^8.3
• ext-fileinfo: *
• ext-libxml: *
• ext-simplexml: *
• guzzlehttp/guzzle: ^7.0

Requires (Dev)

• friendsofphp/php-cs-fixer: *
• phpstan/phpstan: ^2.1
• phpstan/phpstan-phpunit: ^2.0
• phpunit/phpunit: ^12.0
• roave/security-advisories: dev-master
• squizlabs/php_codesniffer: *

MIT

• Elliot J. Reed

• ai
• openai
• ChatGpt
• llm
• claude
• anthropic

README

A library for interacting with Anthropic / Claude AI and OpenAI / ChatGPT.

PHP 8.3 and above is supported.

• Usage
  • Anthropic Claude AI
    • Text prompts
    • System (developer or role) prompt
    • Structured prompt
    • History
    • Images
  • OpenAI ChatGPT
    • Text prompts
    • System (developer or role) prompt
    • Structured prompt
    • History
    • Images
  • Error handling
• Testing
  • Simple mock
  • Advanced
• Development
  • Getting Started
    • Installing Composer
    • Installing
  • Running the Tests
    • Unit tests
      • Debugging
  • Code formatting
    • Running everything
    • Outdated dependencies
    • Validating Composer configuration
    • Running via GNU Make
    • Running the tests on a Continuous Integration platform (eg. Github Actions)
      • Github Actions

Usage

Install via Composer:

composer require elliotjreed/ai

There are two classes, one for Claude AI, and one for ChatGPT. Each extent the abstract Prompt class and are designed to be interoperable.

$claude = new ElliotJReed\AI\Claude\Prompt('API KEY', 'claude-3-5-haiku-latest');
$chatGPT = new ElliotJReed\AI\ChatGPT\Prompt('API KEY', 'gpt-4o-mini');

Each take the first argument in the constructor as your API key, and the second argument as the model you want to use.

You can optionally provide a Guzzle HTTP client:

$claude = new ElliotJReed\AI\Claude\Prompt('API KEY', 'claude-3-5-haiku-latest', new \GuzzleHttp\Client());
$chatGPT = new ElliotJReed\AI\ChatGPT\Prompt('API KEY', 'gpt-4o-mini', new \GuzzleHttp\Client());

This could be useful where you are using a framework such as Symfony, you could autowire the service and reference a configured Guzzle client.

Here's an example of a Symfony integration in the services.yaml file:

  guzzle.client.ai:
    class: GuzzleHttp\Client
    arguments:
      - {
        timeout: 10,
        headers: {
          'User-Agent': 'My Symfony Project'
        }
      }

  ElliotJReed\AI\Claude\Prompt:
    class: ElliotJReed\AI\Claude\Prompt
    arguments:
      $apiKey: '%env(string:CLAUDE_API_KEY)%'
      $model: 'claude-3-5-haiku-latest'
      $client: '@guzzle.client.ai'

  ElliotJReed\AI\ChatGPT\Prompt:
    class: ElliotJReed\AI\ChatGPT\Prompt
    arguments:
      $apiKey: '%env(string:CHATGPT_API_KEY)%'
      $model: 'gpt-4o-mini'
      $client: '@guzzle.client.ai'

The following two sections show examples for both Anthropic / Claude and OpenAI / ChatGPT - they take the same request and are functionally the same. The same examples are shown for both for simplicity.

Anthropic Claude AI

Text prompts

For text-based prompts you can either set a plain text prompt, or use the included StructuredPrompt to use a light prompting framework and format in an LLM-friendly way.

For a really simple request and response:

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\Claude\Prompt('API KEY', 'claude-3-5-haiku-latest');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setTextPrompt('Which programming language will outlive humanity?');

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL;

System (developer or role) prompt

You can also include a system prompt as either a string or a StructuredPrompt. This takes priority in terms of instructions over the user prompts. For example, you could let the LLM know what role it is taking on.

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\Claude\Prompt('API KEY', 'claude-3-5-haiku-latest');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert software development knowledge to help software developers of varying levels of experience')
    ->setTextPrompt('Which programming language will outlive humanity?');

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL;

Structured prompt

You can provide a StructuredPrompt too. A StructuredPrompt wraps context, instructions, user input, data, and examples in XML tags before sending the request to the AI API. This can help the LLMs understand a bit better, and can be particularly useful when dealing with potentially untrusted user input (eg. from a web form or chat bot implementation)/

Setting the temperature (between 0 and 1, basically how "creative" you want the AI to be), and the maximum tokens to use (recommended if the user input is from a indirect source, for example an online chatbot):

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\Claude\Prompt('API KEY', 'claude-3-5-haiku-latest');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are responding to customer queries from a web form.')
    ->setSystemPrompt((new ElliotJReed\AI\Entity\StructuredPrompt())
        ->setContext('The customer is querying via a form on a e-commerce website based in the United Kingdom.')
        ->setInstructions('Respond using the data from the FAQs in a friendly and accurate way using British English.')
        ->setData('FAQs. Q: Do you offer next day deliver. A: Yes we do, however we do not offer same day delivery.')
        ->setExamples(['Hello! Unfortunately we are not open on Bank Holidays.']))
    ->setTextPrompt((new ElliotJReed\AI\Entity\StructuredPrompt())
        ->setContext('The current date and time is: ' . (new DateTime())->format('Y-m-d H:i:s'))
        ->setUserInput('Can you deliver today at my address?'))
    ->setMaximumTokens(300);

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL;

History

If you want to keep a conversation going (like you would on ChatGPT or Claude's website or app), you can pass through the history from the previous response to a new request:

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\Claude\Prompt('API KEY', 'claude-3-5-haiku-latest');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are responding as a philosopher and ethicist who favours utilitarian methodology when answering ethical questions.')
    ->setTextPrompt('Should we all be vegan?')
    ->setTemperature(0.8)
    ->setMaximumTokens(600);

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens()  . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL;

$secondRequest = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are responding as a philosopher and ethicist who favours utilitarian methodology when answering ethical questions.')
    ->setTextPrompt('Elaborate on your response, providing 3 bullet points for arguing in favour of veganism, and 3 bullet points arguing against.')
    ->setTemperature(0.8)
    ->setMaximumTokens(600)
    ->setHistory($response->getHistory());

$secondResponse = $prompt->send($secondRequest);

echo 'Used input tokens: ' . $secondResponse->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $secondResponse->getUsage()->getOutputTokens()  . \PHP_EOL;
echo 'Response from AI: ' . $secondResponse->getContent() . \PHP_EOL;

Images

You can send image data, by either providing URL or a base64 encoded image file.

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\Claude\Prompt('API KEY', 'claude-3-5-haiku-latest');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert flower knowledge to identify individual flowers and foliage in bouquets of flowers when the user uploads one or more photographs.')
    ->setImages([
        'https://media.bunches.co.uk/products/586x586/ffreir-category.jpg',
        base64_encode(file_get_contents(__DIR__ . '/bouquet.webp'))
    ])
    ->setMaximumTokens(300);

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent()  . \PHP_EOL;

As with the text prompts you can also retain the history between requests.

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\Claude\Prompt('API KEY', 'claude-3-5-haiku-latest');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert flower knowledge to identify individual flowers and foliage in bouquets of flowers when the use uploads one or more photographs. Identify just the contents in bullet points.')
    ->setImages([
        'https://media.bunches.co.uk/products/586x586/ffreir-category.jpg',
        base64_encode(file_get_contents(__DIR__ . '/bouquet.webp'))
    ])
    ->setMaximumTokens(300);

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent()  . \PHP_EOL;

$secondRequest = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert flower knowledge to identify individual flowers and foliage in bouquets of flowers when the use uploads one or more photographs. Identify just the contents in bullet points.')
    ->setTextPrompt('List only the types of flower or foliage with no additional description.')
    ->setMaximumTokens(300)
    ->setHistory($response->getHistory());

$secondResponse = $prompt->send($secondRequest);

echo 'Used input tokens: ' . $secondResponse->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $secondResponse->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $secondResponse->getContent()  . \PHP_EOL;

OpenAI ChatGPT

Text prompts

For text-based prompts you can either set a plain text prompt, or use the included StructuredPrompt to use a light prompting framework and format in an LLM-friendly way.

For a really simple request and response:

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\ChatGPT\Prompt('API KEY', 'gpt-4o-mini');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setTextPrompt('Which programming language will outlive humanity?');

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL;

System (developer or role) prompt

You can also include a system prompt as either a string or a StructuredPrompt. This takes priority in terms of instructions over the user prompts. For example, you could let the LLM know what role it is taking on.

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\ChatGPT\Prompt('API KEY', 'gpt-4o-mini');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert software development knowledge to help software developers of varying levels of experience')
    ->setTextPrompt('Which programming language will outlive humanity?');

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL;

Structured prompt

You can provide a StructuredPrompt too. A StructuredPrompt wraps context, instructions, user input, data, and examples in XML tags before sending the request to the AI API. This can help the LLMs understand a bit better, and can be particularly useful when dealing with potentially untrusted user input (eg. from a web form or chat bot implementation)/

Setting the temperature (between 0 and 1, basically how "creative" you want the AI to be), and the maximum tokens to use (recommended if the user input is from a indirect source, for example an online chatbot):

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\ChatGPT\Prompt('API KEY', 'gpt-4o-mini');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are responding to customer queries from a web form.')
    ->setSystemPrompt((new ElliotJReed\AI\Entity\StructuredPrompt())
        ->setContext('The customer is querying via a form on a e-commerce website based in the United Kingdom.')
        ->setInstructions('Respond using the data from the FAQs in a friendly and accurate way using British English.')
        ->setData('FAQs. Q: Do you offer next day deliver. A: Yes we do, however we do not offer same day delivery.')
        ->setExamples(['Hello! Unfortunately we are not open on Bank Holidays.']))
    ->setTextPrompt((new ElliotJReed\AI\Entity\StructuredPrompt())
        ->setContext('The current date and time is: ' . (new DateTime())->format('Y-m-d H:i:s'))
        ->setUserInput('Can you deliver today at my address?'))
    ->setMaximumTokens(300);

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL;

History

If you want to keep a conversation going (like you would on ChatGPT or Claude's website or app), you can pass through the history from the previous response to a new request:

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\ChatGPT\Prompt('API KEY', 'gpt-4o-mini');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are responding as a philosopher and ethicist who favours utilitarian methodology when answering ethical questions.')
    ->setTextPrompt('Should we all be vegan?')
    ->setTemperature(0.8)
    ->setMaximumTokens(600);

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens()  . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL;

$secondRequest = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are responding as a philosopher and ethicist who favours utilitarian methodology when answering ethical questions.')
    ->setTextPrompt('Elaborate on your response, providing 3 bullet points for arguing in favour of veganism, and 3 bullet points arguing against.')
    ->setTemperature(0.8)
    ->setMaximumTokens(600)
    ->setHistory($response->getHistory());

$secondResponse = $prompt->send($secondRequest);

echo 'Used input tokens: ' . $secondResponse->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $secondResponse->getUsage()->getOutputTokens()  . \PHP_EOL;
echo 'Response from AI: ' . $secondResponse->getContent() . \PHP_EOL;

Images

You can send image data, by either providing URL or a base64 encoded image file.

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\Claude\Prompt('API KEY', 'claude-3-5-haiku-latest');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert flower knowledge to identify individual flowers and foliage in bouquets of flowers when the user uploads one or more photographs.')
    ->setImages([
        'https://media.bunches.co.uk/products/586x586/ffreir-category.jpg',
        base64_encode(file_get_contents(__DIR__ . '/bouquet.webp'))
    ])
    ->setMaximumTokens(300);

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent()  . \PHP_EOL;

As with the text prompts you can also retain the history between requests.

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\Claude\Prompt('API KEY', 'claude-3-5-haiku-latest');

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert flower knowledge to identify individual flowers and foliage in bouquets of flowers when the use uploads one or more photographs. Identify just the contents in bullet points.')
    ->setImages([
        'https://media.bunches.co.uk/products/586x586/ffreir-category.jpg',
        base64_encode(file_get_contents(__DIR__ . '/bouquet.webp'))
    ])
    ->setMaximumTokens(300);

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent()  . \PHP_EOL;

$secondRequest = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert flower knowledge to identify individual flowers and foliage in bouquets of flowers when the use uploads one or more photographs. Identify just the contents in bullet points.')
    ->setTextPrompt('List only the types of flower or foliage with no additional description.')
    ->setMaximumTokens(300)
    ->setHistory($response->getHistory());

$secondResponse = $prompt->send($secondRequest);

echo 'Used input tokens: ' . $secondResponse->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $secondResponse->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $secondResponse->getContent()  . \PHP_EOL;

Error handling

All exceptions extend the base AIException.

Testing

Simple mock

For convenience, there are two mock classes which can be used for simple unit tests, once for Claude (ElliotJReed\AI\Double\ClaudePromptMock) and one for ChatGPT(ElliotJReed\AI\Double\ChatGPTPromptMock).

One for each is provided as the underlying API requests differ, and the History between the two providers differ, even if the Request and usage is the same.

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\Double\ClaudePromptMock('API KEY', 'test-model');

$prompt->response = 'Mocked response here!'

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert software development knowledge to help software developers of varying levels of experience')
    ->setTextPrompt('Which programming language will outlive humanity?');

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL; // Output: 'Mocked response here!'

print_r($response->getHistory());

<?php

require_once __DIR__ . '/vendor/autoload.php';

$prompt = new ElliotJReed\AI\Double\ChatGPTPromptMock('API KEY', 'test-model');

$prompt->response = 'Mocked response here!'

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert software development knowledge to help software developers of varying levels of experience')
    ->setTextPrompt('Which programming language will outlive humanity?');

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL; // Output: 'Mocked response here!'

print_r($response->getHistory());

Advanced

For more complex requirements, you could use the Claude or ChatGPT Prompt classes directly and mock the raw response using Guzzle.

Refer to the Anthropic and OpenAI API documentation for raw response examples. Or view the source code of this library.

<?php

require_once __DIR__ . '/vendor/autoload.php';

$mock = new GuzzleHttp\Handler\MockHandler([new GuzzleHttp\Psr7\Response(200, [], '{
    "id": "msg_01Bblahblahnaughtygoose",
    "type": "message",
    "role": "assistant",
    "model": "claude-3-5-haiku-latest",
    "content": [
      {
        "type": "text",
        "text": "Mocked response here!"
      }
    ],
    "stop_reason": "end_turn",
    "stop_sequence": null,
    "usage": {
      "input_tokens": 100,
      "output_tokens": 20
    }
  }
')]);

$client = new GuzzleHttp\Client([
    'base_uri' => 'https://0.0.0.0',
    'handler' => GuzzleHttp\HandlerStack::create($mock)
]);

$prompt = new ElliotJReed\AI\Claude\Prompt('API KEY', 'test-model', $client);

$prompt->response = 'Mocked response here!'

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert software development knowledge to help software developers of varying levels of experience')
    ->setTextPrompt('Which programming language will outlive humanity?');

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL; // Output: 'Mocked response here!'

print_r($response->getHistory());

<?php

require_once __DIR__ . '/vendor/autoload.php';

$mock = new GuzzleHttp\Handler\MockHandler([new GuzzleHttp\Psr7\Response(200, [], '{
  "id": "chatcmpl-happymoosegoesboopboop",
  "object": "chat.completion",
  "created": 1723486738,
  "model": "gpt-4o-mini-2024-07-18",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "PHP will likely outlive humanity due to it being generally great and loved by all. It could easily last another 7 million years, powering what is left of the planet once all of humanity has migrated to Pluto for reasons of nostalgia.",
        "refusal": null
      },
      "logprobs": null,
      "finish_reason": "length"
    }
  ],
  "usage": {
    "prompt_tokens": 60,
    "completion_tokens": 29,
    "total_tokens": 89
  },
  "system_fingerprint": "fp_boopityboop"
}')]);

$client = new GuzzleHttp\Client([
    'base_uri' => 'https://0.0.0.0',
    'handler' => GuzzleHttp\HandlerStack::create($mock)
]);

$prompt = new ElliotJReed\AI\ChatGPT\Prompt('API KEY', 'test-model', $client);

$prompt->response = 'Mocked response here!'

$request = (new ElliotJReed\AI\Entity\Request())
    ->setSystemPrompt('You are using expert software development knowledge to help software developers of varying levels of experience')
    ->setTextPrompt('Which programming language will outlive humanity?');

$response = $prompt->send($request);

echo 'Used input tokens: ' . $response->getUsage()->getInputTokens() . \PHP_EOL;
echo 'Used output tokens: ' . $response->getUsage()->getOutputTokens() . \PHP_EOL;
echo 'Response from AI: ' . $response->getContent() . \PHP_EOL; // Output: 'Mocked response here!'

print_r($response->getHistory());

Development

Getting Started

PHP 8.3 or above and Composer is expected to be installed.

Installing Composer

For instructions on how to install Composer visit getcomposer.org.

Installing

After cloning this repository, change into the newly created directory and run:

composer install

or if you have installed Composer locally in your current directory:

php composer.phar install

This will install all dependencies needed for the project.

Henceforth, the rest of this README will assume composer is installed globally (ie. if you are using composer.phar you will need to use composer.phar instead of composer in your terminal / command-line).

Running the Tests

Unit tests

Unit testing in this project is via PHPUnit.

All unit tests can be run by executing:

composer phpunit

Debugging

To have PHPUnit stop and report on the first failing test encountered, run:

composer phpunit:debug

Code formatting

A standard for code style can be important when working in teams, as it means that less time is spent by developers processing what they are reading (as everything will be consistent).

Code formatting is automated via PHP-CS-Fixer. PHP-CS-Fixer will not format line lengths which do form part of the PSR-2 coding standards so these will product warnings when checked by PHP Code Sniffer.

These can be run by executing:

composer phpcs

Running everything

All the tests can be run by executing:

composer test

Outdated dependencies

Checking for outdated Composer dependencies can be performed by executing:

composer outdated

Validating Composer configuration

Checking that the composer.json is valid can be performed by executing:

composer validate --no-check-publish

Running via GNU Make

If GNU Make is installed, you can replace the above composer command prefixes with make.

All the tests can be run by executing:

make test

Running the tests on a Continuous Integration platform (eg. Github Actions)

Specific output formats better suited to CI platforms are included as Composer scripts.

To output unit test coverage in text and Clover XML format (which can be used for services such as Coveralls):

composer phpunit:ci

To output PHP-CS-Fixer (dry run) and PHPCS results in checkstyle format (which GitHub Actions will use to output a readable format):

composer phpcs:ci

Github Actions

Look at the example in .github/workflows/php.yml.

Built With

• PHP
• Composer
• PHPUnit
• PHP Code Sniffer
• GNU Make

License

This project is licensed under the MIT License - see the LICENCE.md file for details.