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Laravel Octane

Laravel Octane is an official package for the Laravel framework that dramatically boosts application performance by running Laravel on high-performance application servers like Swoole or RoadRunner.


What Makes Laravel Octane Special?

Instead of reloading the Laravel framework on every HTTP request (as with traditional PHP-FPM setups), Octane keeps the application in memory, avoiding repeated bootstrapping. This makes your Laravel app much faster.


🔧 How Does It Work?

Laravel Octane uses persistent worker servers (e.g., Swoole or RoadRunner), which:

  1. Bootstrap the Laravel application once,

  2. Then handle incoming requests repeatedly without restarting the framework.


🚀 Benefits of Laravel Octane

Benefit Description
Faster performance Up to 10x faster than traditional PHP-FPM setups
🔁 Persistent workers No full reload on every request
🌐 WebSockets & real-time support Built-in support via Swoole/RoadRunner
🧵 Concurrency Parallel task handling possible
🔧 Built-in tools Task workers, route reload watching, background tasks, etc.

RoadRunner

RoadRunner is a high-performance PHP application server developed by Spiral Scout. It serves as a replacement for traditional PHP-FPM (FastCGI Process Manager) and offers a major performance boost by keeping your PHP application running persistently — especially useful with frameworks like Laravel or Symfony.


🚀 What Makes RoadRunner Special?

Worker-Based Performance

  • PHP scripts are not reloaded on every request. Instead, they run continuously in persistent worker processes (similar to Node.js or Swoole).

  • This eliminates the need to re-bootstrap the framework on every request — resulting in significantly faster response times than with PHP-FPM.

Built with Go

  • RoadRunner is written in the programming language Go, which provides high concurrency, easy deployment, and great stability.

Features

  • Native HTTP server (with HTTPS, Gzip, CORS, etc.)

  • PSR-7 and PSR-15 middleware support

  • Supports:

    • Queues (e.g., Redis, RabbitMQ)

    • gRPC

    • WebSockets

    • Static file serving

    • Prometheus metrics

    • RPC between Go and PHP

  • Hot reload support with a watch plugin


⚙️ How Does It Work?

  1. RoadRunner starts PHP worker processes.

  2. These workers load your full framework bootstrap once.

  3. Incoming HTTP or gRPC requests are forwarded to the PHP workers.

  4. The response is returned through the Go layer — fast and concurrent.


📦 Common Use Cases:

  • Laravel + RoadRunner (instead of Laravel + PHP-FPM)

  • High-traffic applications and APIs

  • Microservices

  • Real-time apps (e.g., using WebSockets)

  • Low-latency, serverless-like services


📉 RoadRunner vs PHP-FPM

Feature PHP-FPM RoadRunner
Bootstraps per request Yes No (persistent workers)
Speed Good Excellent
WebSocket support No Yes
gRPC support No Yes
Language C Go

GitHub Actions

🛠️ What is GitHub Actions?

GitHub Actions is a feature of GitHub that lets you create automated workflows for your software projects—right inside your GitHub repository.


📌 What can you do with GitHub Actions?

You can build CI/CD pipelines (Continuous Integration / Continuous Deployment), such as:

  • ✅ Automatically test code (e.g. with PHPUnit, Jest, Pytest)

  • 🛠️ Build your app on every push or pull request

  • 🚀 Automatically deploy (e.g. to a server, cloud platform, or DockerHub)

  • 📦 Create releases (e.g. zip packages or version tags)

  • 🔄 Run scheduled tasks (cronjobs)


🧱 How does it work?

GitHub Actions uses workflows, defined in a YAML file inside your repository:

  • Typically stored as .github/workflows/ci.yml

  • You define events (like push, pull_request) and jobs (like build, test)

  • Each job consists of steps, which are shell commands or prebuilt actions

Example: Simple CI Workflow for Node.js

name: CI

on: [push]

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-node@v3
        with:
          node-version: '20'
      - run: npm install
      - run: npm test

🧩 What are "Actions"?

An Action is a single reusable step in a workflow. You can use:

  • Prebuilt actions (e.g. actions/checkout, setup-node, upload-artifact)

  • Custom actions (e.g. shell scripts or Docker-based logic)

You can explore reusable actions in the GitHub Marketplace.


💡 Why use GitHub Actions?

  • Saves time by automating repetitive tasks

  • Improves code quality through automated testing

  • Enables consistent, repeatable deployments

  • Integrated directly in GitHub—no need for external CI tools like Jenkins or Travis CI


Entity Manager

💡 What is an Entity Manager?

An Entity Manager is a core component of ORM (Object-Relational Mapping) frameworks, especially in Java (JPA – Java Persistence API), but also in other languages like PHP (Doctrine ORM).


📦 Responsibilities of an Entity Manager:

  1. Persisting:

  2. Finding/Loading:

    • Retrieves an object by its ID or other criteria.

    • Example: $entityManager->find(User::class, 1);

  3. Updating:

    • Tracks changes to objects and writes them to the database (usually via flush()).

  4. Removing:

    • Deletes an object from the database.

    • Example: $entityManager->remove($user);

  5. Managing Transactions:

    • Begins, commits, or rolls back transactions.

  6. Handling Queries:


🔁 Entity Lifecycle:

The Entity Manager tracks the state of entities:

  • managed (being tracked),

  • detached (no longer tracked),

  • removed (marked for deletion),

  • new (not yet persisted).


🛠 Example with Doctrine (PHP):

$user = new User();
$user->setName('Max Mustermann');

$entityManager->persist($user); // Mark for saving
$entityManager->flush();        // Write to DB

✅ Summary:

The Entity Manager is the central component for working with database objects — creating, reading, updating, deleting. It abstracts SQL and provides a clean, object-oriented way to interact with your data layer.


Doctrine Database Abstraction Layer - DBAL

Doctrine DBAL (Database Abstraction Layer) is a PHP library that provides an abstraction layer for database access. It is part of the Doctrine project (a popular ORM for PHP), but it can be used independently of the ORM.


Purpose and Benefits of Doctrine DBAL:

Doctrine DBAL offers a unified API to interact with different databases (such as MySQL, PostgreSQL, SQLite, etc.) without writing raw SQL specific to each database system.


Key Features of Doctrine DBAL:

  • Connection Management
    • Easily configure and manage connections to various database systems.

    • Supports connection pooling, transactions, and more.

  • SQL Query Builder
    • Build SQL queries programmatically using an object-oriented API:

$qb = $conn->createQueryBuilder();
$qb->select('u.id', 'u.name')
   ->from('users', 'u')
   ->where('u.age > :age')
   ->setParameter('age', 18);
$stmt = $qb->executeQuery();
  • Database Independence

    • The same code works with different database systems (e.g., MySQL, PostgreSQL) with minimal changes.

  • Schema Management

    • Tools to create, update, and compare database schemas.

    • Useful for migrations and automation.

  • Data Type Conversion

    • Automatically converts data between PHP types and database-native types.

 

use Doctrine\DBAL\DriverManager;

$conn = DriverManager::getConnection([
    'dbname' => 'test',
    'user' => 'root',
    'password' => '',
    'host' => 'localhost',
    'driver' => 'pdo_mysql',
]);

$result = $conn->fetchAllAssociative('SELECT * FROM users');

When to Use DBAL Instead of ORM:

You might choose DBAL without ORM if:

  • You want full control over your SQL.

  • Your project doesn't need complex object-relational mapping.

  • You're working with a legacy database or custom queries.


Summary:

Doctrine DBAL is a powerful tool for clean, portable, and secure database access in PHP. It sits between raw PDO usage and a full-featured ORM like Doctrine ORM, making it ideal for developers who want abstraction and flexibility without the overhead of ORM logic.

 


Aspect Oriented Programming - AOP

Aspect-Oriented Programming (AOP) is a programming paradigm focused on modularizing cross-cutting concerns—aspects of a program that affect multiple parts of the codebase and don't fit neatly into object-oriented or functional structures.


💡 Goal:

Typical cross-cutting concerns include logging, security checks, error handling, transaction management, or performance monitoring. These concerns often appear in many classes and methods. AOP allows you to write such logic once and have it automatically applied where needed.


🔧 Key Concepts:

  • Aspect: A module that encapsulates a cross-cutting concern.

  • Advice: The actual code to be executed (e.g., before, after, or around a method call).

  • Join Point: A point in the program flow where an aspect can be applied (e.g., method execution).

  • Pointcut: A rule that defines which join points are affected (e.g., "all methods in class X").

  • Weaving: The process of combining aspects with the main program code—at compile-time, load-time, or runtime.


🛠 Example (Java with Spring AOP):

@Aspect
public class LoggingAspect {
    @Before("execution(* com.example.service.*.*(..))")
    public void logBeforeMethod(JoinPoint joinPoint) {
        System.out.println("Calling method: " + joinPoint.getSignature().getName());
    }
}

This code automatically logs a message before any method in the com.example.service package is executed.


✅ Benefits:

  • Improved modularity

  • Reduced code duplication

  • Clear separation of business logic and system-level concerns


❌ Drawbacks:

  • Can reduce readability (the flow isn't always obvious)

  • Debugging can become more complex

  • Often depends on specific frameworks (e.g., Spring, AspectJ)


Assertion

Assertions are programming constructs used to check assumptions about the state of a program. An assertion tests whether a specific condition is true—if it isn't, an error is typically raised and the program stops.

x = 10
assert x > 0   # passes
assert x < 5   # raises AssertionError, since x is not less than 5

Purpose of Assertions:

  • They help with debugging: you can verify that certain conditions in code hold true during development.

  • They document implicit assumptions, e.g., “At this point, the list must have at least one item.”

  • They are mainly used during development—assertions are often disabled in production code.

Key Difference from Regular Error Handling:

Assertions are meant to catch programmer errors, not user input or external failures. For example:

  • assert age > 0 → inappropriate if age comes from user input.

  • Instead, use: if age <= 0: raise ValueError("Age must be positive.")

 


Design by Contract - DbC

Design by Contract (DbC) is a concept in software development introduced by Bertrand Meyer. It describes a method to ensure the correctness and reliability of software by defining clear "contracts" between different components (e.g., methods, classes).

Core Principles of Design by Contract

In DbC, every software component is treated as a contract party with certain obligations and guarantees:

  1. Preconditions
    Conditions that must be true before a method or function can execute correctly.
    → Responsibility of the caller.

  2. Postconditions
    Conditions that must be true after the execution of a method or function.
    → Responsibility of the method/function.

  3. Invariant (Class Invariant)
    Conditions that must always remain true throughout the lifetime of an object.
    → Responsibility of both the method and the caller.

Goal of Design by Contract

  • Clear specification of responsibilities.

  • More robust and testable software.

  • Errors are detected early (e.g., through contract violations).

Example in Pseudocode

class BankAccount {
    private double balance;

    // Invariant: balance >= 0

    void withdraw(double amount) {
        // Precondition: amount > 0 && amount <= balance
        if (amount <= 0 || amount > balance) throw new IllegalArgumentException();

        balance -= amount;

        // Postcondition: balance has been reduced by amount
    }
}

Benefits

  • Clear contracts reduce misunderstandings.

  • Easier debugging, as violations are detected immediately.

  • Supports defensive programming.

Drawbacks


Perl Compatible Regular Expressions - PCRE

Perl Compatible Regular Expressions (PCRE) are a type of regular expression syntax and engine that follows the powerful and flexible style of the Perl programming language. They offer advanced features that go beyond the basic regular expressions found in many older systems.


Why "Perl Compatible"?

Perl was one of the first languages to introduce highly expressive regular expressions. The PCRE library was created to bring those capabilities to other programming languages and tools, including:

  • PHP

  • Python (similar via the re module)

  • JavaScript (with slight differences)

  • pcregrep (a grep version supporting PCRE)

  • Editors like VS Code, Sublime Text, etc.


Key Features of PCRE:

Lookahead & Lookbehind:

  • (?=...) – positive lookahead

  • (?!...) – negative lookahead

  • (?<=...) – positive lookbehind

  • (?<!...) – negative lookbehind

Non-greedy quantifiers:

  • *?, +?, ??, {m,n}?

Named capturing groups:

  • (?P<name>...) or (?<name>...)

Unicode support:

  • \p{L} matches any kind of letter in any language

Assertions and anchors:

  • \b, \B, \A, \Z, \z

Inline modifiers:

  • (?i) for case-insensitive

  • (?m) for multiline matching, etc.

(?<=\buser\s)\w+

This expression matches any word that follows "user " using a lookbehind assertion.


Summary:

PCRE are like the "advanced edition" of regular expressions — highly powerful, widely used, and very flexible. If you're working in an environment that supports PCRE, you can take advantage of rich pattern matching features inspired by Perl.


Guard

In software development, a guard (also known as a guard clause or guard statement) is a protective condition used at the beginning of a function or method to ensure that certain criteria are met before continuing execution.

In simple terms:

A guard is like a bouncer at a club—it only lets valid input or states through and exits early if something is off.

Typical example (in Python):

def divide(a, b):
    if b == 0:
        return "Division by zero is not allowed"  # Guard clause
    return a / b

This guard prevents the function from attempting to divide by zero.


Benefits of guard clauses:

  • Early exit on invalid conditions

  • Improved readability by avoiding deeply nested if-else structures

  • Cleaner code flow, as the "happy path" (normal execution) isn’t cluttered by edge cases


Examples in other languages:

JavaScript:

function login(user) {
  if (!user) return; // Guard clause
  // Continue with login logic
}

Swift (even has a dedicated guard keyword):

func greet(person: String?) {
  guard let name = person else {
    print("No name provided")
    return
  }
  print("Hello, \(name)!")
}

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