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。

Today, I would like to share about 7 Django packages that developers should know. Let’s take a look.

1. Django REST framework

It is to build any HTTP-based REST API, providing powerful and flexible tools as well as impressive usability, authentication policies, serialization, and extensive documentation.

2. Django GUID

It is a library enabling matching a single HTTP request with all messages coming from logs. Django GUID is WSGI-supported and also ASGI-supported.

3. Django Debug Toolbar

It is a toolbar that helps debug a Django application in the browser, offering many built-in as well as third-party panels. It works on Django versions 2.2, 3.0, and 3.1.

4. Sentry

It is a service meant to monitor a running application and errors that occur when it’s working.

5. Graphene-Django

It’s about making Django data available through an interface based on GraphQL. Some tips on how to add GraphQL functionality to a Django project may be found here.

6. Django Channels

WebSocket async support in Django, available via several locations. User-friendly, flexible, allowing for customizability.

7. Django-baton

A handy, cutting-edge, responsive, and user-friendly interface for a Django admin, based on Bootstrap 5. It was created with Python, JavaScript, SCSS, HTML, and some other languages.

This is all for now. Hope you enjoy that.

By Asahi

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To take screenshots of your website without using third-party services, we recommend using the html2canvas library. You can use this script to take a “screenshot” of a web page or part of it directly in the user’s browser.

As mentioned above, use the html2canvas library to take screenshots of the elements in the DOM. You can download this library with npm using the following command

npm install html2canvas

Or you can just include the asset file like this

<script src="/path/to/html2canvas.min.js"></script>

You can visit to the official Github repo here. I will add some samples working around to capture or download the screenshot.

Taking Screenshot

html2canvas(document.body).then(function(canvas) {
    var base64img = canvas.toDataURL("image/png");
    window.open(base64img);
});

Downloading with blob method

html2canvas(document.body).then(function(canvas) {
    canvas.toBlob(function(blob) {
        window.saveAs(blob, "ss.png");
    });
});

But you have to be aware of this blob method might not be available for all browsers. If you want to use the blob method , you may have to use this canvas-blob library to be able to support at all browsers.

Yuuma

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今回も、Laravelの知っておいた方がいいとおもったことをいくつか紹介します。

#Laravel #Implicit Binding

Implicit Bindingは、ルートやコントローラのアクションで定義されたEloquentモデルを自動的に解決します。

Laravel 5.3で導入されましたが、もっと多くの人に知ってもらいたい素晴らしい機能です。

//Implicit route model binding
Route::get('api/posts/{post}', function (App\Post $post) {
    return $post->title;
});

ということで、今回はこれで終わります。

金曜担当 – Ami

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Today, I would like to share about 3 ways to group routes in laravel. Let’s take a look.

1. Route::resource

We can create a resource controller and group routes for CRUD actions of that controller as follow.

Route::resource('books', BookController::class);

2. Route groups within another route group

We can groups routes within another route groups like nested ones.

Route::middleware('auth')->group(function() {
 
    Route::middleware('admin')->prefix('admin')->group(function() {
    	Route::get(...) 
    });
 
    Route::middleware('member')->prefix('member')->group(function() {
    	Route::get(...) 
    });
});

3. Route::controller() in Laravel 9

In laravel 9, we can group the routes without repeating controller name for the same controller.

Route::controller(PostController::class)->group(function() {
    Route::get('posts', 'getPosts');
    Route::put('posts/update', 'updatePost');
    Route::delete('posts/delete/{id}', 'deletePost');
});

This is all for now. Hope you enjoy that.

By Asahi

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ONNX is a machine learning framework which acts like a medium to convert between different machine learning frameworks.

ONNX is designed to enable framework interoperability. There are many great machine learning libraries in multiple languages — PyTorch, TensorFlow, MXNet, and Caffe are just a few of the most popular ones in recent years, but there are many others.
The idea is that you can use one stack of tools to train your model and use another for inference and prediction to expand your model.

For example, once you’ve trained your model, you need to deploy it to a new iOS app so that anyone with a previously trained model can see the safety of their food. I first trained my model with PyTorch, but iOS expects to use CoreML for use within the app. ONNX is an intermediate representation of the model that allows you to easily move from one environment to another.

With tools such as ONNX-CoreML, you can now easily convert pre-trained models to files, import them into XCode, and integrate them seamlessly with your application.

This is just an overview of what ONNX is about. I will talk more detail in future.

Yuuma

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