Django 5.0: What is New in It?
Django is an open-source Python web framework. It makes the web development process fast and straightforward through its collection of modules. Since its initial release in 2005, the framework has come a long way. With every new update, it is getting more and more robust. Let’s discover what new features and updates it brings in Django 5.0. Significant Updates in Django 5.0 Released on 4 December 2023, Django 5.0 introduces numerous updates to enhance the web development experience. Some of the primary improvements in Django are as per below: Straightforward Rendering of Form Fields One of the notable improvements you can notice in Django 5.0 is that Form Fields are easy to render now. Form fields in Django have numerous elements, such as descriptive labels, help text, error labels, etc. It was always tiresome to lay out all manually. Thankfully in this new version, you don’t need to bother about it. Django 5 features field group templates. These templates simplify the rendering of all form field components, such as widgets, help text, labels, errors, and more. Earlier: <form> … <div> {{ form.name.label_tag }} {% if form.name.help_text %} <div class="helptext" id="{{ form.name.auto_id }}_helptext"> {{ form.name.help_text|safe }} </div> {% endif %} {{ form.name.errors }} {{ form.name }} <div class="row"> <div class="col"> {{ form.email.label_tag }} {% if form.email.help_text %} <div class="helptext" id="{{ form.email.auto_id }}_helptext"> {{ form.email.help_text|safe }} </div> {% endif %} {{ form.email.errors }} {{ form.email }} </div> <div class="col"> {{ form.password.label_tag }} {% if form.password.help_text %} <div class="helptext" id="{{ form.password.auto_id }}_helptext"> {{ form.password.help_text|safe }} </div> {% endif %} {{ form.password.errors }} {{ form.password }} </div> </div> </div> … </form> Now: <form> … <div> {{ form.name.as_field_group }} <div class="row"> <div class="col">{{ form.email.as_field_group }}</div> <div class="col">{{ form.password.as_field_group }}</div> </div> </div> … </form> Database Generated Model Field The database-generated model field is another prominent update you can notice in Django 5.0. The latest GeneratedField in Django lets users create database-generated columns. The good thing is that all database backends support it. It is going to be beneficial for fields computed from other fields. For example: from django.db import models from django.db.models import F class Square(models.Model): side = models.IntegerField() area = models.GeneratedField( expression=F("side") * F("side"), output_field=models.BigIntegerField(), db_persist=True, ) This function can significantly improve the efficiency of the database. Moreover, it maintains the integrity of data. Python Compatibility Django is keeping pace with the ever-evolving Python language. With Django 5.0, users can relish the latest Python features and improvements. This new version supports Python 3.10, 3.11, and 3.12. Not only does it ensure the best performance but also improves security. Now developers can relish the full potential of Django 5.0. Facet Filters in the Admin The Django 5.0 comes with facet counts for applied filters on the admin change list. Developers can toggle this feature using UI (User Interface). It improves the admin interface by presenting facet counts alongside filters. Users can now get a quick insight into the distribution of data. Write Field Choice Easily In the earlier version of Django, it was challenging to list field choices. Users had to make an inconvenient arrangement of 2-tuples or Enumeration subclasses to list the choices available to Field.choices and ChoiceField.choices objects. See the following example: HQ_LOCATIONS = [ ("United States", [("nyc", "New York"), ("la", "Los Angeles")]), ("Japan", [("tokyo", "Tokyo"), ("osaka", "Osaka")]), ("virtual", "Anywhere"), ] Nevertheless, this latest version lets you use concise declarations with the help of dictionary mappings: HQ_LOCATIONS = { "United States": {"nyc": "New York", "la": "Los Angeles"}, "Japan": {"tokyo": "Tokyo", "osaka": "Osaka"}, "virtual": "Anywhere", } It simplifies choices to encode as literals. AsyncClient Django 5.0 features additional asynchronous methods to the Client as well as AsyncClient. It supports asynchronous testing of Django applications. Users can now create tests that replicate the asynchronous behavior of the application. Database-Computed Default Values Django 5.0 lets you define database-computed default values. It means you get more powerful and accurate default settings. The new `Field.db_default` parameter enables users to set database-computed default values for model fields quickly. It is specifically helpful for time stamps or calculated fields. Although it is a minor change, it will have a substantial impact on the integrity of your data. Users can define default values using database functions. Features Deprecated in 5.0 Django 5.0 also has abolished a few old features. Therefore, you must check whether your code relies on any of them. If yes, you will need to update it accordingly. These features were depreciated in previous versions. Some notable ones include: Serialize test setting is no longer available. The undocumented django.utils.baseconv module is abolished. You can’t use undocumented django.utils.datetime_safe module anymore. The USE_TZ setting now has a default value of True. Earlier, it was false. Conclusion Django 5.0 introduces numerous updates and features that take the web development game to the next level. The platform has solidified its position as a powerful and versatile web framework. It has turned into a crucial tool for building websites and web applications. Enhanced flexibility in declaring field choices, improved performance, and numerous security features make it one of the best Python web frameworks. I’ve been working with Django since version 0.96 (2007), so if you need help with it, Contact Now
Bun 1.0: Unveiling the Ultimate Development Tool
Since its launch, Bun 1.0 has become the talk of town in the web development community. It is gaining popularity as an all-in-one tool for JavaScript and TypeScript development. If you haven’t used it yet and want to explore Bun 1.0 features, this post is for you. Before we jump into the Bun 1.0 features, let’s learn about it briefly. Overview of Bun and its Significance Bun is a renowned open-source bundler for JavaScript and TypeScript. Jarred Sumner is the key person behind the foundation of this JavaScript runtime. Unlike Node.js and Deno, the bundler uses JavaScriptCore as the JavaScript engine. Bun 1.0 was launched on September 8, 2023. It is a versatile tool to build, test, debug, and run JavaScript and TypeScript applications. Bun 1.0 is quite fast in comparison to Node.js and Deno. Let us uncover all the Bun 1.0 features one by one. Features of Bun 1.0 Universal Tool Bun 1.0 meets the requirements of both JavaScript and TypeScript developers. Whether you are working on a single-file project or developing a full-stack application, Bun provides an efficient development environment. Below are some features that make Bun 1.0 worth using: Bun supports quick command execution, thanks to npx. NPX is part of Bun. It eliminates the requirement of nodemon as it features a built-in watch mode. It is an ideal replacement for Node.js. Bun is capable of reading .env files. It means you don’t need any 3rd party configuration. You get support for various file formats such as .js, .ts, .cjs, .mjs., tsx, etc. Bun provides you with an integrated bundling solution. It replaces web pack, parcel, rollup, rebuild, etc. Bun 1.0 also features testing libraries that remove the requirement for jest and similar tools. Bun is an npm-compatible package manager. Therefore, it naturally reduces the need for yarn and npm. High Speed and Performance Speed and performance are other aspects of Bun impressing JavaScript developers. It lets you run your code at an excellent speed. Bun 1.0 is several times faster. You won’t need to use tools like yarn, npm, and pnpm. Bun takes about 0.36 seconds to compile a code. In the case of pnpm, compilation may take up to 6.44 seconds. With npm, code compilation takes 10.58 seconds, while Yarn takes 12.08 seconds for the same task. Compared to Node.js, Bun is about four times faster. Bun 1.0 provides top-notch performance, thanks to its advanced optimization technology and efficient code bundling. In addition, it minimizes the load times for web applications. As a result, it provides a better user experience. Built-in Support for JavaScript and TypeScript Bun 1.0 provides complete support for JavaScript and TypeScript. Developers can work with both languages without using any third-party transpilers. Bun makes it easy to set up your development process. You do not need to struggle with various tools. Bun handles everything so that you can focus on coding entirely. Hot Reloading Bun 1.0 allows you to see instant updates in applications as you make changes. All credit goes to hot reloading. Bun features built-in hot reloading that enhances the development process by providing real-time updates to code and configurations. As a result, you can quickly spot all issues and fix them. With Bun, you do not need Nodemon. It automatically refreshes the server when developers run TypeScript or JavaScript code. If you have been using npm rum, you can replace it with bun run. It will reduce command execution time by at least 150 milliseconds on every run. Installation Speed It can be frustrating and time-consuming to install development tools. Fortunately, Bun 1.0 supports lightning-fast installation that reduces the setup hassle. Bun uses a global module cache system to avoid redundant downloads from the npm registry. Consequently, it uses quick system calls, available in different operating systems. Compatibility Adaptability is one of the primary Bun 1.0 features that users appreciate. This open-source bundler can effortlessly integrate with well-known server frameworks such as Hono, Koa, and Express. Web developers also get support for applications built using full-stack frameworks, including Next.js, Nuxt, Astro, Vite, Remix, etc. In addition to this, Bun 1.0 is also compatible with ESM and CommonJS. It means you can use both of them together in the same file. This feature was missing in Node.js. Conclusion Bun 1.0 is an ideal choice for developers working on JavaScript and TypeScript. It has numerous built-in features, making it a game-changer in the ever-evolving web development era. The bundle ends your dependency on complex and slow fragmented tool chains. It won’t be wrong to mention that Bun has brought revolutionary changes in the development of JavaScript projects. So these are a few worth mentioning Bun 1.0 features.
Types of NoSQL Databases: Everything You Need to Know About Them
NoSQL or Not Only SQL is a renowned database management system (DBMS) that manages a large volume of unstructured or semi-structured data. Since it eliminates various limitations of conventional relational databases, the NoSQL database has become popular. Google, Facebook, Amazon, and Netflix are some reputable companies that use NoSQL. This blog makes you aware of different types of NoSQL databases. In addition, you will learn their features. Before we move further, let’s find out how NoSQL is diverse from SQL. SQL vs. NoSQL Databases: Quick Comparison Type SQL databases are Relational Databases, while NoSQL databases are known as non-relational databases. Language of Query SQL databases use a Structured Query Language to do jobs like Delete, Select, Update, and Insert. On the other hand, NoSQL has its query language for manipulating data. NoSQL works on a framework or API, depending on the type of database. Expandability Traditional SQL databases are vertically scalable. You can enhance their performance by upgrading hardware. On the contrary, NoSQL databases are horizontally scalable from the ground up. Consequently, they are better at handling large amounts of data and traffic. Property Followed SQL follows ACID (Atomicity, Consistency, Isolation, and Durability) transactions when it comes to managing data integrity. NoSQL databases use the CAP theorem (Consistency, Availability, and Partition Tolerance). Types of NoSQL Databases We can categorize NoSQL databases into the following 4 types. Each has its pros and limitations. You can choose them based on your requirements. Let us learn about them in detail. Key Value Pair Database Key-Value Pair Database is one of the simplest types of NoSQL Databases. It is a non-relational database storing data elements in key-value pairs. Key-Value Pair Database can handle heavy loads of data. It stores data as a hash map and has two columns, i.e., the Key and the Value. Each database key is different, while the value can be String, Binary Large Objects, or JavaScript Object Notation. The three major features of the Key Value Pair Database are speed, straightforwardness, and scalability. Generally, this type of database is used for creating dictionaries, user profiles, user preferences, etc. Graph-Based Database The graph-based database helps users store entities and relations between those entities. Commonly, this database is used to store data on social networking websites, fraud detection systems, healthcare networks, and more. The graph-based database stores the data as a node. The connections between nodes are known as edges. Every edge and node has a different identifier. The database allows users to find the relationship between the data with the help of links. Unlike relational databases, graph-based databases are multi-relational. A few well-known graph-based databases are Flock DB, Neo4J, Infinite Graph, etc. All-in-all, we can say that a graph-based database stores, manages, and queries data as a graph structure. Column Oriented Database Column Oriented Database is a non-relational database. The database lets you store data in rows and read it row by row. It is like a collection of columns like we see in a table. Each column stores one type of information. The database reads and retrieves the data at high speed. You can run analytics on a limited number of columns to read those columns without consuming memory on unwanted data. Column Oriented Database performs queries like Count, SUM, AVG, and MIN quite quickly. Therefore, the database is used for analytics and reporting, data warehousing, and library card catalogs. Document-Oriented Database A document-oriented database is one of the prominent types of NoSQL databases. It stores and manages data like we organize documents in the real world. Although the data is stored and retrieved as a key-value pair, the value is stored as a document. The database uses the JSON, XML, or BSON documents to store the data. Users can store and retrieve documents from their networks in a form that is closer to the data objects. Therefore, negligible translation is needed to access and use data in an application. Document-Oriented Database supports flexible schema, scalability, and quick retrieval. MongoDB and Couchbase are two fine examples of these databases. This database is used in CMS (Content Management Systems), E-commerce websites, gaming applications, collaboration tools, etc. So these are four types of NoSQL databases. Let’s find out why this database system is getting popular. Features of NoSQL NoSQL has several advancements over traditional databases. We have listed a few significant ones. Compatible with Multiple Data Models Like relational databases, NoSQL is not strict. It can handle multiple data models. Additionally, the database can manage structured, semi-structured, and unstructured data with the same speed. Schema Flexibility Unlike conventional database systems, Not SQL databases do not require a fixed schema. It supports relaxed schemas. NoSQL is capable of managing different data formats and structures. As it does not have a strict predefined schema, it permits changes in data models. Scalable As mentioned above, the NoSQL database is scalable. Users can scale it horizontally by adding more modes and servers. Consequently, it is suitable for websites and web applications with continuously growing data. Excellent Uptime NoSQL databases have excellent uptime. They support serverless architecture and create multiple copies of data on various nodes. Consequently, businesses manage their database smoothly with minimal downtime. If one note breaks down, another takes its place and gives access to the data copy. Examples of NoSQL Now you know the different types of NoSQL databases and their uses. Below are some examples of them. Document Database MongoDB is a well-known document-oriented database. It stores data in JSON-like documents. MongoDB is popular for its scalability and flexibility. Column Database Apache Cassandra is a well-known column-based database system that handles large amounts of data across different commodity servers. Graph Database Amazon Neptune is a managed graph database service by AWS. It can work with both RDF graph and property graph models. Key-Value Database Amazon DynamoDB is a database service that provides high uptime and low-latency key-value storage. This service from Amazon Web Service is the epitome of a Key-Value type database. Conclusion Various types of NoSQL databases are a crucial
Keras Core 3.0 — Pioneering the Next Frontier in Deep Learning APIs
In the dynamic landscape of artificial intelligence, where breakthroughs occur in rapid succession and the boundaries of what’s possible are constantly pushed, the Keras framework has emerged as a steadfast companion for machine learning practitioners and researchers. With the advent of Keras Core 3.0, the framework embarks on a transformative journey, poised to redefine the very essence of capabilities, performance, and adaptability, and solidify its position as a trailblazer in the realm of deep learning. This article delves into the evolution of Keras, highlights the remarkable features of version 3.0, and explores its compatibility with various backends. Understanding Keras — A Journey from Inception to Innovation Keras, born from the visionary mind of François Chollet in 2015, swiftly rose to prominence as a high-level neural networks API known for its intuitive design and unparalleled experimentation agility. Its initial incarnation and subsequent integration with TensorFlow marked a pivotal moment, propelling Keras into the limelight of machine learning tools. As the AI landscape evolved, Keras adapted in tandem, shaping itself to meet the diverse demands of an ever-expanding user community. Now, with the unveiling of Keras Core 3.0, this evolutionary saga culminates in a symphony of enhancements that not only elevate the framework’s capabilities but also redefine its role as an indispensable asset in the arsenal of AI practitioners. Redefining Possibilities — Unveiling Keras 3.0’s Game-Changing Features Embracing the Multi-Backend Landscape Keras 3.0 emerges as a trailblazer with its unprecedented support for multiple backends. While its roots are anchored in TensorFlow, this version casts a wider net, inviting frameworks like jAX and PyTorch into its fold. The result? A harmonious coexistence that empowers researchers and practitioners to wield their preferred framework without renouncing the prowess of Keras. Precision Perfected — Advanced Performance Optimization Keras Core 3.0 doubles down on performance optimization, seamlessly weaving techniques like mixed-precision training and distributed training into its fabric. The result is a turbocharged training process and maximized hardware resource utilization. These optimization strategies work behind the scenes, enabling users to focus on the art of model development and experimentation, confident that the framework is orchestrating the complex ballet beneath. Expanding the Horizons — A Flourishing Ecosystem The Keras ecosystem flourishes with renewed vigour in Keras 3.0. The framework’s enhanced support for KerasCV and KerasNLP, specialized libraries tailored for computer vision and natural language processing, empowers it to excel in these domains. This synergy doesn’t just streamline the development process; it equips users with an extensive toolkit to conquer the intricate challenges inherent in these fields. Uniting the Diverse — Cross-Framework Compatibility Keras Core 3.0 ushers in an era of harmony across deep learning frameworks. Models crafted in Keras effortlessly traverse the boundaries between TensorFlow, jAX, and PyTorch backends, reflecting a unification in an ecosystem historically divided. This seamless compatibility erases barriers, fostering an environment of collaboration and experimentation, where diverse tools coalesce to drive innovation. Evolution by Design — The Philosophy of Progressive Disclosure Keras 3.0 embodies the ethos of progressive disclosure, catering to both novices and seasoned practitioners. The API unfolds in a manner that facilitates the gentle onboarding of newcomers while gradually unveiling the advanced features craved by experts. This balanced approach ensures Keras remains accessible and indispensable, irrespective of users’ proficiency levels. A Stateless Symphony of Design — The Stateless API Paradigm The introduction of the stateless API marks a paradigm shift in Keras 3.0. Aligned with the trend of integrating functional programming concepts in deep learning, this design choice fosters modular architecture, encourages code reusability, and champions clean code organization. This leap not only elevates the development experience but also fortifies code maintenance and collaborative prowess. Navigating the Possibilities — Keras for TensorFlow, jAX, and PyTorch Embarking on the Voyage: Installation Embarking on the journey with Keras Core 3.0 is an effortless endeavour. Installation guides for each supported backend are readily available in the official documentation, providing users the freedom to opt for the backend that resonates with their ethos and project requisites. This adaptability cements Keras as an indispensable entity amid the ever-shifting currents of AI technology. For installation, $ pip install keras-core import keras_core as keras Aligning with the Core: Backend Configuration Configuring the backend is a seamless ritual, often requiring a mere few lines of code. This configuration determines the engine propelling Keras—be it TensorFlow, jAX, or PyTorch. This flexibility empowers users to fluidly transition between backends, paving the way for efficient exploration and experimentation. Run the following command for backend configuration: $ export KERAS_BACKEND="jax" $ python train.py Or $ KERAS_BACKEND=jax python train.py Mastery in Action: Integrating KerasCV and KerasNLP The integration of KerasCV and KerasNLP into Keras Core 3.0 paints a transformative landscape. KerasCV brings forth a symphony for computer vision tasks, providing dedicated APIs and pre-fabricated models for image classification, object detection, and segmentation. Meanwhile, KerasNLP empowers users to navigate the challenges of natural language processing with access to cutting-edge language models, tokenization tools, and sequence manipulation layers. And here is some KerasCV usage example: import keras_cv import keras_core as keras filepath = keras.utils.get_file(origin="https://i.imgur.com/gCNcJJI.jpg") image = np.array(keras.utils.load_img(filepath)) image_resized = ops.image.resize(image, (640, 640))[None, …] model = keras_cv.models.YOLOV8Detector.from_preset( "yolo_v8_m_pascalvoc", bounding_box_format="xywh", ) predictions = model.predict(image_resized) A Confluence of Innovation: In the ever-accelerating tapestry of deep learning, Keras Core 3.0 emerges as a beacon of innovation and adaptability. With its embrace of multiple backends, advanced performance optimization, amplified ecosystem, cross-framework harmony, philosophy of progressive disclosure, and the advent of the stateless API, Keras 3.0 redefines itself as the quintessential deep learning API. It resonates across the spectrum of users—novices venturing forth and experts charting the boundaries of possibility. As the grand symphony of deep learning unfolds, Keras Core 3.0 remains a steadfast companion, empowering developers to manifest their visions with unmatched finesse and precision.
How to choose the right NodeJS Framework
It’s a modern world full of real-time web applications whether we talk about online games or messengers. Well, most modern applications have Node.js under the hood offering a scalable JavaScript environment. A Node.js framework features built-in resources including routing, templating, and database connectivity. Whether you’re using an MVC, Full-Stack MVC, or REST API, all the Node.js frameworks promote efficient and productive development. So, it’s finally a question, how to choose the right Node.js framework in 2023? You asked for it and here we brought a complete guide to help you make the right decision. Before you pick a framework, let’s start with exploring the best options you have online. 6 Best Options in NodeJS Frameworks to Choose From Express.js When it comes to choosing a Node.js framework, Express.js might be the top preference of most users. That’s because of its popularity, MVC architecture, and supreme capabilities of client-server interaction. Thanks to its simple code structure, Express.js offers a great user experience making it the perfect choice for small and medium-sized web app development. Also, it becomes an ideal choice if your project demands routing, middleware, and templating support. Nest.js Nest.js is trailing Express.js as one of the most efficient Node.js frameworks in the industry. Especially if you’re looking to build complex yet efficient server-side applications, Nest.js got the drill. The credit goes to its support for object-oriented programming (OOP) and reactive programming. As it supports TypeScript and JavaScript, you can easily integrate Nest.js with Express.js and build multi-layered applications. Koa.js Developed by Express.js developers, Koa.js is a masterpiece framework with lighter interface and cascading middleware. What it does?… The cascading middleware allows you to personalize your webpage content for different users without compromising the user experience. Additionally, you get access to various plugins and libraries of Express.js with lower complexity. It means Koa.js can be a pick for you if you are more into customizations and maintainability. Feathers.js Feathers.js is another excellent option for Node.js frameworks, particularly if you’re aiming to build real-time applications. With its focus on simplicity and flexibility, Feathers.js enables you to create scalable and efficient server-side applications effortlessly. It also offers support for various databases, making it a versatile choice for handling different types of projects. If you prioritize real-time functionalities, Feathers.js might be the ideal fit for your needs. Hapi.js Hapi.js is a robust and extensible Node.js framework designed for building APIs. With a strong emphasis on configuration over code, Hapi.js makes it easier to develop well-organized and maintainable applications. It excels in providing security features and allows you to control request handling, making it suitable for large-scale projects with specific security requirements. Hapi.js is also a great option for teams that value code consistency and readability. Sails.js For developers seeking a full-featured and opinionated framework, Sails.js is worth considering. It follows the convention-over-configuration principle, which means you spend less time configuring and more time coding. Sails.js offers an integrated ORM (Object-Relational Mapping) and supports real-time updates, making it a solid choice for building data-intensive applications like chat applications or social networks. If you prefer rapid development with batteries included, Sails.js could be your framework of choice. Top 5 Tips to Choose the Right NodeJS Framework: Project Requirements When embarking on the journey of choosing a NodeJS framework, your project’s unique requirements should be the guiding light. Each application comes with its own set of challenges and goals, and understanding them is paramount. Whether you need real-time capabilities, robust data processing, or server-side rendering, tailoring your choice to match these needs ensures a harmonious development process and a successful end product. By thoroughly analyzing your project’s necessities, you can avoid the pitfalls of selecting an ill-fitting framework, saving time, effort, and resources. Easy to Learn and Use Simplicity and accessibility are virtues in the world of software development, and when it comes to choosing a NodeJS framework, ease of learning and usage become decisive factors. An intuitive framework with clear documentation, comprehensive tutorials, and a supportive community fosters a welcoming environment for developers of all levels of expertise. Learning curves can be reduced significantly, and teams can quickly adapt and become productive with a framework that offers well-designed interfaces and conventions. Smooth onboarding processes and streamlined workflows empower developers to focus on actual problem-solving rather than wrestling with complex setups and configurations. Scalability In the realm of modern web applications, scalability is the bedrock of sustainable success. When selecting a NodeJS framework, it is essential to consider its ability to scale effortlessly. A framework that can handle increased user loads and growing data volumes without sacrificing performance is an invaluable asset. Horizontal scaling, the ability to distribute the application across multiple servers, and efficient utilization of multi-core processors are crucial characteristics of a scalable framework. By choosing a framework that can grow with your application’s demands, you ensure a seamless user experience, better resource management, and future-proofing your project. Versions Upgrade The landscape of NodeJS development is ever-evolving, with new versions constantly being released, each bringing improvements, security fixes, and exciting features. When evaluating NodeJS frameworks, it is imperative to consider how well-maintained and updated they are to keep pace with the latest NodeJS releases. Additionally, it minimizes the risk of compatibility issues and security vulnerabilities. Being on the cutting edge of the NodeJS ecosystem translates to a more future-proof and efficient application, giving you a competitive advantage. Community Support The value of a strong and engaged community cannot be overstated when selecting a NodeJS framework. A vibrant community signifies the framework’s reliability, popularity, and potential for long-term viability. When you encounter challenges or have questions during the development process, a robust community can provide invaluable assistance, shared knowledge, and innovative solutions. Community support often comes in the form of online forums, chat groups, documentation contributions, and open-source collaborations. Conclusion: In conclusion, choosing the right Node.js framework for your project is a crucial decision that can significantly impact its success. The six frameworks discussed in this guide and each have their unique strengths and
An Ultimate Guide to AdminJS — Your Perfect Full-Stack Development Partner!
It’s no surprise that the front-office adds value to your web project but the back-office is no exception. An admin dashboard streamlines your CRUD operations ensuring efficiency and productivity. However, building a professional admin dashboard can be time-consuming unless you have a feature-rich tool. That’s where AdminJS kicks in reducing the time and effort to build an administration web app for your business. Whether you have a space for lead management or customer support, AdminJS can help you build a custom admin dashboard to your needs. In this guide, we have crafted an easy step-by-step process to build a custom admin interface using AdminJS. So, let’s make this count! AdminJS Explained: What Makes it Worth Using? AdminJS is a robust and versatile open-source framework designed to simplify the development of custom admin interfaces for web applications. It provides developers with a comprehensive set of tools and features to create intuitive and user-friendly admin dashboards. AdminJS is backend-agnostic, meaning it can be integrated with various backend frameworks and libraries. It supports popular backend technologies such as Node.js, Ruby on Rails, and others. This flexibility enables developers to choose their preferred backend technology and seamlessly integrate AdminJS into their existing stack. The tool supports multiple databases, including MongoDB, PostgreSQL, MySQL, and others, through dedicated adapters. These adapters simplify the process of connecting AdminJS to the chosen database, allowing developers to manage data effectively within the admin dashboard. It supports various authentication providers, such as email/password, OAuth, and JWT (JSON Web Tokens), making it easy to implement secure login mechanisms. Additionally, AdminJS allows developers to define granular access control rules, ensuring that the right permissions are assigned to each user. Building a Custom Admin Dashboard Interface Using Admin JS Set up AdminJS The first and foremost step to use AdminJS is to install the tool with the Express plugin and Prisma adapter. Use the below command to run the installation: yarn add adminjs @adminjs/express @adminjs/prisma Before you start coding, add TypeScript and Express Types as dev dependencies. Here’s how you can do it: yarn add -D @types/express ts-node Once you have installed the AdminJS, it’s time to initialize the panel with the app.ts file in the root directory. To initialize, import AdminJS from 'adminjs' import AdminJSExpress from '@adminjs/express' import express from 'express' const PORT = 3000 const start = async () => { const app = express() const admin = new AdminJS({}) const adminRouter = AdminJSExpress.buildRouter(admin) app.use(admin.options.rootPath, adminRouter) app.listen(PORT, () => { console.log(`AdminJS started on http://localhost:${PORT}${admin.options.rootPath}`) }) } start() Connect Database Admin JS supports various databases, and connecting to your preferred database is straightforward. For example, if you’re using MongoDB, install the MongoDB adapter by running the following command: npm install adminjs-mongoose Next, create a new file, `admin.js`, and add the following code to set up the database connection: const AdminJS = require('adminjs'); const MongooseAdapter = require('adminjs-mongoose'); const mongoose = require('mongoose'); const connection = mongoose.createConnection('mongodb://localhost/my-database'); AdminJS.registerAdapter(MongooseAdapter); const admin = new AdminJS({ databases: [connection], rootPath: '/admin', }); module.exports = admin; Add Authentication Securing your admin dashboard with authentication is essential. Admin JS provides built-in authentication features that can be easily integrated into your application. Let’s see an example of setting up authentication using Passport.js: const AdminJS = require('adminjs'); const { Authentication } = require('adminjs-passport'); const express = require('express'); const app = express(); AdminJS.registerAdapter(MongooseAdapter); const admin = new AdminJS({ databases: [connection], rootPath: '/admin', auth: { authenticate: async (email, password) => { const user = await User.findOne({ email }); if (user && await user.validPassword(password)) { return user; } return null; }, cookieName: 'adminjs', cookiePassword: 'supersecret', }, }); app.use(admin.options.rootPath, admin.router); app.listen(3000, () => console.log('Admin JS is running on http://localhost:3000/admin')); Override AdminJS Logo By default, Admin JS displays its logo on the admin dashboard. However, you can easily replace it with your custom logo. Add the following CSS snippet to your project’s CSS file: .ab-logo img { content: url('/path/to/your/logo.png'); } Make sure to replace `/path/to/your/logo.png` with the path to your actual logo file. Customize Admin Dashboard with React component Admin JS provides a React component called `AdminJS.bundle.js` that allows you to customize the admin dashboard further. Import this component into your React application and use it to render the admin dashboard: import React from 'react'; import { render } from 'react-dom'; import { AdminJS } from 'adminjs'; const App = () => { return ( <AdminJS /> ); }; render(<App />, document.getElementById('root')); Deploy the Dashboard Once you have built your custom admin dashboard using Admin JS, you can deploy it to your preferred hosting provider. You can use platforms like Heroku, AWS, or Netlify to host your application. Make sure to follow the deployment instructions specific to your chosen hosting provider. Conclusion: AdminJS is an excellent choice for building custom admin dashboards with ease. Its user-friendly interface, customization options, database support, authentication mechanisms, and extensibility make it a powerful full-stack development partner. By following the steps outlined in this guide, you can create a fully functional and customized admin dashboard using AdminJS. So, leverage the capabilities of AdminJS and streamline your admin dashboard development process today!
Django vs Flask — Which Python Framework is Perfect for Your Web Development Process?
When it comes to web development in Python, two prominent frameworks stand out: Django and Flask. These frameworks offer developers a robust foundation to build powerful web applications efficiently. Based on Model-View-Controller (MVC) architectural pattern, Django is favored for large-scale, complex projects. On the other hand, Flask is a microframework offering a lightweight and flexible approach, empowering developers to have greater control over the application structure. Both platforms have exclusive capabilities and drawbacks complicating the decision-making. In this article, we’ll delve into the technical aspects and industrial attributes of Django and Flask to help you make an informed decision for your web development endeavors. So, let’s get started! Django — Self-Sufficient Web Framework From the house of the Django Software Foundation, Django is a robust and scalable web framework known for its “batteries-included” philosophy. With built-in features and packages, Django promotes rapid development by minimizing the need for external dependencies. Its core components include an Object-Relational Mapping (ORM) layer, a template engine, form handling, authentication, and authorization. Django’s ORM simplifies database interactions, allowing seamless integration with various database systems. The framework follows the Model-View-Controller (MVC) architectural pattern, providing a clear separation of concerns. Additionally, the admin interface offers an out-of-the-box solution for managing application data, making it a popular choice for content-heavy websites. Flask — Minimalistic Microframework Flask is a lightweight and flexible micro-framework designed for simplicity and minimalism. Developed by Armin Ronacher, it provides a solid foundation for web development, offering developers greater control over the application structure. It follows a “micro” philosophy, providing essential tools and leaving the choice of additional libraries to the developers. Furthermore, the framework leverages the Werkzeug toolkit for handling routing and the Jinja2 template engine for rendering dynamic content. Its flexibility and scalability make Flask an excellent choice for small to medium-sized projects, RESTful APIs, and microservices. In addition to its features, the active community and extensive documentation ensure continuous support and updates, contributing to its widespread adoption. Comparison of Django and Flask Based on Industrial Attributes Development Capabilities Django’s batteries-included approach provides a wide array of built-in features, making development faster and more efficient. Its robust ORM simplifies database interactions, while the template engine streamlines UI development. Besides, Flask offers greater flexibility allowing developers to choose and integrate only the necessary components. This makes Flask ideal for lightweight and highly customizable applications. So, Django’s extensive feature set makes it better suited for complex projects that require rapid development and adherence to best practices. If you’re working on smaller projects that require fine-grained control over the application structure, Flask can be a great choice. Scalability Django’s scalability is what makes it a perfect choice for large-scale applications. With its ability to handle heavy workloads, Django’s robust architecture and efficient request handling ensure optimal performance. On the other hand, Flask is inherently scalable, allowing developers to add or remove components as needed. It features a modular design and customizable nature that enables developers to optimize performance for specific use cases. Architecture As discussed above, Django follows the Model-View-Controller (MVC) architectural pattern. This promotes code organization and maintainability, making it easier for multiple developers to collaborate on a project. By default, Flask works with the MVT pattern and offers a similar structure but with a more flexible design. Developers have more freedom to choose how to structure their projects and interact with components. Components and Reutilization Django is famous for its comprehensive set of built-in components, such as the ORM, template engine, and authentication system. As it reduces external dependencies, this promotes code reusability and reduces development time. While Flask provides greater flexibility, it still requires developers to rely on external packages for specific functionality. Flask’s modular design facilitates component reusability, enabling developers to build custom solutions tailored to their project requirements. Community and Support Django boasts a large and active community, with numerous contributors and a wealth of resources available. The community-driven nature of Django ensures continuous development, frequent updates, and comprehensive documentation. This support system provides assistance, encourages best practices, and addresses issues promptly. Flask also enjoys an active community, although smaller in comparison to Django. However, Flask’s community thrives on its simplicity and flexibility, offering extensive documentation and a range of community-contributed extensions. While Django’s larger community offers broader support, Flask’s community provides a close-knit environment for developers seeking minimalistic solutions. Establishment and Updates With its long history, Django has established itself as a mature and stable framework, trusted by many large-scale projects and enterprises. Its consistent updates, bug fixes, and security patches ensure reliability and compatibility with the latest technologies. Despite being a younger framework, Flask has also gained substantial popularity and has seen regular updates, although at a relatively smaller scale. Flask’s updates focus on maintaining stability and introducing new features based on community feedback. Testing Django provides a robust testing framework as part of its core, enabling developers to write comprehensive tests for their applications. Its testing utilities simplify unit testing, integration testing, and user interaction testing. Flask, being a microframework, does not include a built-in testing framework. However, Flask integrates seamlessly with popular Python testing libraries such as pytest and unittest, offering flexibility in choosing the desired testing approach. Both frameworks promote test-driven development and provide the necessary tools and extensions for efficient and thorough testing. End of the Line In conclusion, the choice between Django and Flask ultimately depends on the specific requirements and goals of your web development project. Django’s batteries-included approach, mature ecosystem, and adherence to MVC architecture make it an excellent choice for large-scale, complex applications On the other hand, Flask’s lightweight and flexible nature, coupled with its simplicity and customizability, make it ideal for smaller projects, RESTful APIs, and microservices. It empowers developers to have fine-grained control over the application structure and offers the freedom to choose and integrate only the necessary components. Consider your project’s scale, complexity, customization needs, and community support when making your decision, ensuring the best fit for your web development process.
