開発スタッフがアプリ関連の最新技術やニュースをご紹介します。

今回は、Laravelにおける定数の管理方法を紹介したいと思います。
各方法とその特徴、用途を以下にまとめます。

.env ファイルを使用する方法（環境変数）

環境ごとに異なる値（APIキー、DB接続情報など）を .env ファイルで管理します。

使用例

API_KEY=abcd1234

コントローラ内などで以下のように使用します。

$apiKey = env('API_KEY');

特徴
環境ごとに値を切り替えやすい（本番・開発など）
APIパスワードなどセキュアな情報をコードにハードコーディングせずにenvファイルに記述をおこない、gitignoreでコミット対象からも除外しておく。
キャッシュされないので変更が即時反映される

config/const.php ファイルを使う方法

独自の設定ファイルを config/const.php のように作成し、アプリ全体で共有したい定数を定義する。

例：config/const.php

return [
    'status' => [
        'active' => 1,
        'inactive' => 0,
        'deleted' => -1,
    ],
    'user_roles' => [
        'admin' => 1,
        'user' => 2,
    ],
];

使用方法：

$status = config('const.status.active'); // 1

特徴
アプリ内の定数をまとめて管理できる
配列構造で柔軟に対応できる
Laravelの php artisan config:cache によって高速アクセスが可能

define() 関数で定義（グローバル定数）

例：
define(‘APP_VERSION’, ‘1.0.0’);

使用方法：
echo APP_VERSION;

特徴・注意点
グローバルスコープで使用できる
Laravelでは基本的に config や env で管理することが多い

Enum を使う（PHP 8.1以上）

概要
PHP 8.1以降で導入された enum を使って型安全な定数を定義できる。

例：
app/Enums/UserStatus.php

enum UserStatus: int {
    case Active = 1;
    case Inactive = 0;
    case Deleted = -1;
}

使用方法：

$status = UserStatus::Active;

特徴
型安全（間違った値の代入を防げる）

木曜日担当：nishida

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今回はWindowsのDocker Desktopのコンテナ内でコマンドを実行する方法を紹介したいと思います。

1.Docker Desktopの起動をおこない、任意のコンテナを開始します。

2.コンテナ名を確認
以下のコマンドで現在起動しているコンテナの一覧が見られます。

docker ps

項目としては
CONTAINER ID、IMAGE、 COMMAND、NAMES が表示されますので、コマンドを実行したいコンテナのNAMEをメモしておきます。

3.コンテナ内でのコマンド実行方法
以下のようにコマンドを実行することができます。
※[NAME]箇所は上記で確認したコンテナのNAMEに書き換えます。

docker exec -it [NAME] ls

4.Laravelコンテナ内で artisan コマンドを実行するには、以下のように Docker の exec コマンドを使います。

docker exec -it [NAME] php artisan <コマンド>

よく使うartisanコマンド実行例

・Laravelのバージョン確認
docker exec -it [NAME] php artisan –version

・キャッシュクリア
docker exec -it [NAME] php artisan config:clear

・マイグレーション実行
docker exec -it [NAME] php artisan migrate

・シーディング実行
docker exec -it [NAME] php artisan db:seed

・サーバー起動（開発用）
docker exec -it [NAME] php artisan serve –port=8080

木曜日担当：nishida

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以下のように結果画面へ一時リダイレクトをかける場合に、httpsスキームが引き継がれない場合があります。

return redirect('result', 307);

その場合、以下のようにsecure()を使えば、常にhttpsへリダイレクトされます。

return redirect()->secure('result', 307);

JavaScriptのassetなどを読み込む際に以下のようにbladeディレクティブを使用する場合もhttpsスキームが引き継がれない場合があります。

<script src="{{ asset('common/js/xxxx.js') }}"></script>

その場合はLaravelのヘルパー関数 secure_asset() を使用することでhttpsでassetを読み込むことが可能になります。

<script src="{{ secure_asset('common/js/xxxx.js') }}"></script>

プロジェクト全体に対してグローバルに https を強制させたい場合は、Laravelの AppServiceProvider で設定が可能です。具体的には以下のように記述することですべての url() や asset() などが https を前提に生成されるようになります。

use Illuminate\Support\Facades\URL;

public function boot()
{
    if (app()->environment('production')) {
        URL::forceScheme('https');
    }
}

上記の例では、environment(‘production’)で本番環境のみ、httpsを強制するように設定しています。

木曜日担当：nishida

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In the digital age, we often find ourselves overwhelmed with files scattered across our computers. Whether it’s photos from last summer’s vacation, important documents for work, or music and videos for entertainment, keeping track of everything can be a challenge. But fear not! With the power of Python, you can automate the process of organizing your files into neat categories based on their types.

In this tutorial, we’ll walk you through a simple Python script that automatically organizes your files into categories like images, documents, videos, and more.

Before we dive in, make sure you have Python installed on your computer.

Step 1: Setting Up the Script

First, let’s create a Python script that will do the heavy lifting for us. Open your favorite text editor and copy the following code:

import os
import shutil

def classify_files(directory):
    # Dictionary of file categories and their extensions
    categories = {
        'Images': ['jpeg', 'jpg', 'png', 'gif', 'bmp'],
        'Documents': ['pdf', 'doc', 'docx', 'txt', 'rtf'],
        'Spreadsheets': ['xls', 'xlsx', 'csv'],
        'Videos': ['mp4', 'avi', 'mov', 'mkv'],
        'Music': ['mp3', 'wav', 'flac', 'aac'],
        'Archives': ['zip', 'rar', '7z', 'tar', 'gz']
    }

    # Create category directories if not exist
    for category in categories.keys():
        os.makedirs(os.path.join(directory, category), exist_ok=True)

    # List files in the directory
    files = os.listdir(directory)

    # Classify files
    for filename in files:
        # Get file extension
        _, ext = os.path.splitext(filename)
        ext = ext[1:].lower()  # Remove leading dot and convert to lowercase

        # Classify the file into appropriate category
        for category, extensions in categories.items():
            if ext in extensions:
                # Move the file to the corresponding category directory
                source_path = os.path.join(directory, filename)
                dest_path = os.path.join(directory, category, filename)
                shutil.move(source_path, dest_path)
                print(f"Moved '{filename}' to '{category}' category.")
                break  # Once classified, move to next file


def main():
    # Input directory path
    directory = input("Enter the directory path to classify files: ")

    # Check if directory exists
    if not os.path.exists(directory):
        print("Directory not found.")
        return

    # Classify files
    classify_files(directory)
    print("File classification completed.")


if __name__ == "__main__":
    main()

Save the file with a meaningful name like `organize_files.py`.

Step 2: Understanding the Code

Now, let’s break down what the code does:

– The script defines a dictionary of file categories and their corresponding extensions. For example, images have extensions like JPEG, PNG, etc.

– It prompts you to enter the directory path where your files are located.

– It creates category directories if they don’t exist already.

– It loops through all the files in the directory, classifies them into appropriate categories based on their extensions, and moves them to the respective category folders.

Step 3: Running the Script

Navigate to the directory where you saved the Python script using the command line or terminal. Then, run the script by typing `python organize_files.py` and press Enter.

Step 4: Sit Back and Relax

Watch as the script works its magic, organizing your files into tidy categories. Once it’s done, you will see your newly organized file system!

Conclusion

You’ve just automated the tedious task of file organization using Python. From now on, keeping your digital files organized will be a breeze. Feel free to customize the script to suit your specific needs and explore other ways Python can simplify your life.

Hope you enjoy that.

By Asahi

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In the realm of programming languages, each one comes with its own set of strengths and characteristics, tailored to suit different needs and preferences of developers. Two prominent languages that often find themselves in comparison are C and Go (or Golang). Let’s delve into the key differences between these two languages across various aspects.

1. Memory Management

– In C, developers need to manually manage memory, allocating and deallocating it for variables. This hands-on approach gives precise control but also opens doors to memory-related bugs.

– Go takes a different route with automatic garbage collection, simplifying memory management tasks for developers and reducing the likelihood of memory leaks.

2. Concurrency

– Go shines in this department with its built-in support for concurrency. Goroutines and channels make it easier to write concurrent programs without worrying about low-level threading intricacies.

– C, lacking built-in concurrency primitives, often resorts to external threading libraries like POSIX threads, which can be more complex and error-prone.

3. Type System

– C boasts a weak static type system, allowing implicit type conversions and offering limited type checking.

– Go’s strong static type system enhances type safety and reduces common programming errors by enforcing stricter type rules.

4. Error Handling

– Go introduces a unique error handling mechanism using return values, eschewing exceptions. This approach encourages explicit error handling, leading to more robust and predictable code.

– C relies on error codes, return values, and functions like perror() for error handling, which can be less structured and more error-prone compared to Go’s approach.

5. Standard Library

– C’s standard library is minimalistic, often necessitating reliance on third-party libraries for additional functionalities.

– Go boasts a rich standard library covering a wide range of tasks, from networking to encryption, reducing the need for external dependencies and streamlining development.

6. Memory Safety

– C’s flexibility comes at a cost, as direct memory manipulation can lead to common pitfalls like buffer overflows and dangling pointers.

– Go prioritizes memory safety, employing automatic bounds checking and garbage collection to mitigate memory-related bugs, enhancing overall code reliability.

In conclusion, while C and Go share some similarities, they diverge significantly in their approach to memory management, concurrency, type systems, error handling, standard libraries, and memory safety. Understanding these differences can help developers make informed decisions when selecting the right language for their projects, based on factors such as performance requirements, ease of development, and code reliability.

Hope you enjoy that.
Asahi

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