#javascript environment variable

[codeonedigest]

Access Environment Variable in Nodejs JavaScript Application | Reading ENV Variable Example

Full Video Link https://youtu.be/dxrNopL1sbQ Hello friends, new #video on #reading #accessing #environmentvariables in #nodejs #projeect #application #tutorial #examples is published on #codeonedigest #youtube channel. @java #java #aws #a

In this video, we will read the environment variable in nodejs javascript project. We will learn what “dotenv” module in nodejs javascript. How to use “dotenv” package in our nodejs javascript project. ** Important Nodejs Javascript Packages or Modules ** Dotenv – DotEnv is a lightweight npm package that automatically loads environment variables from a .env file into the process.env object. To…

[izicodes]

Convert HTML to Image: A Step-by-Step Guide ✨

Do you want to turn some HTML code you've made that's on your website and have a way to convert it into an image for you to save?

Well, look no further! I too wanted to do the same thing but funny enough, there weren't any straightforward tutorials out there that could show you how! After hours of searching, I finally discovered the solution~!

This is an old tutorial I made 🐼

💛 Set your environment

Before we dive into the conversion process, I'll assume you already have your HTML code ready. What you want to learn is how to turn it into an image file. You should have a good grasp of HTML and JavaScript. For this tutorial, we'll use the following HTML code example:

We won't include the CSS code, as it doesn't affect this tutorial. The JavaScript file (script.js) at the bottom of the body element is where we'll add the functionality for the conversion.

Your page should resemble the following:

As you can see, the "Click me" button will handle the conversion. We aim to convert everything within the div.info-div into an image.

💛 Using the html2canvas JavaScript Library

The html2canvas library allows you to take screenshots of webpages and target specific elements on a screen. Here are the steps to include the library in your project:

The steps to put the library in your project:

Visit the html2canvas website for more information.

Copy the CDN link from here

and include it in a script tag in your project's head tag in the HTML file:

That's it for including the library on the HTML side. Now, let's move on to the JavaScript code.

💛 JavaScript Functionality

Here's the JavaScript code to handle the conversion:

In this code, I want to turn the whole div.info-div into an image, I put it into a variable in const div = document.querySelector(".info-div");.

I also put the button into a variable in const button = document.querySelector("button");

I added a click event listener to the button so when the user clicks the button, it will follow the code inside of the event listener!

You can find similar code like this in the documentation of the html2canvas library:

What is happening here is:

We add the div (or what the element we want to take an image of) into the html2canvas([element]).then((canvas)

Added the image file type url to a variable = const imageDataURL = canvas.toDataURL("image/png"); - You can replace the png to other image file types such as jpg, jpeg etc

Created an anchor/link tag, added the href attribute to imageDataURL

The download attribute is where we will give the default name to the image file, I added "dog.png"

Perform the click() function to the anchor tag so it starts to download the image we created

And that's it!

💛 The End

And that's it! You've successfully learned how to turn your HTML into an image. It's a great way to save and share your web content in a unique format.

If you have any questions or need further clarification, please comfortable to ask. Enjoy converting your HTML into images! 💖🐼

[agatedragongames]

Learn how to code the object pool pattern by pre-allocating memory and reusing objects. Which can greatly improve performance when reusing short lived objects like bullets and particles.

This tutorial will show you how to create and manage a pool of bullet objects. For example, this is useful in shooter and bullet hell games which have thousands of bullets on the screen.

The tutorial is written in the Java programming language, and uses the free Processing graphics library and integrated development environment.

The object pool pattern can be especially useful with programming languages which use automatic garbage collection like Java, C#, JavaScript, Python, etc.

Since automatic garbage collection can stall your program and reduce your frame rates. The object pool pattern gives you more control over when the garbage collector comes to reclaim the memory.

The downside of the object pool pattern is that it complicates the life cycle of the object. Meaning you need to reset the variables of the object before you can reuse it. Since its variables are unlikely to match the defaults after repeated use.

There are a few ways to implement the object pool pattern, this tutorial will show you one method.

Walkthrough and full code example on the blog:

[downupti]

Boost Shopify Revenue with A/B Testing

Boost your Shopify revenue with A/B testing experiments and data-driven insights to increase conversions and optimize your store.

Source: https://cro.media/insights/ab-tests/boost-shopify-revenue-ab-testing/

A/B testing is a powerful tool to increase your Shopify store's revenue by helping you make data-driven decisions. By running native A/B testing experiments on your Shopify store, you can optimize your customer experience and turn more visitors into paying customers. With easy-to-use features, you can start testing without any hassle.

Effortless Tracking with Instant A/B Testing

With Instant A/B Testing, there's no need for a JavaScript pixel to get started. The visual editor allows you to create and manage tests easily within minutes. This seamless setup ensures that you can test different variations of your Shopify store with zero technical headaches.

Smooth Experiment Operation

Run your A/B tests without worrying about disrupting your users' experience. The app is designed to serve experiments to the right audience and prevents redirects, making sure that your customers experience no interruptions while browsing your store.

Full Control Over Your Tests

Create separate URLs for each test to ensure a flawless and clean testing environment. By running your tests on individual pages, you can isolate variables and measure the success of each experiment with higher accuracy.

Easy Traffic Split

You have complete control over how much traffic goes to each version of your test. Define the percentage of traffic directed to each variant (A and B), allowing you to balance the experiment and gather precise insights.

Precision Insights Across the Funnel

Gain in-depth analytics with a full funnel view of your A/B tests. Track key metrics such as add-to-cart rates, checkout progression, and completed transactions to measure the true impact of your experiments on revenue.

Why Use Instant A/B Testing for Shopify?

Instant A/B Testing offers a 100% free solution to run experiments on your Shopify store, and no credit card is required to get started. This allows you to experiment with various store elements at zero cost while gathering valuable data that can drive better conversions.

Frequently Asked Questions

Do I need to subscribe to any service? No, Instant A/B Testing is completely free, with no subscription required.

How does it integrate with other apps? Instant A/B Testing works well with Instant Page Builder. You can easily create variants of your pages, publish them to your Shopify store, and test which version converts better.

Does A/B Testing affect my SEO? Since experiments run on separate URLs, there’s minimal risk to SEO performance. The app ensures that crawlers do not get redirected and uses Shopify Webpixel for tracking, keeping everything optimized for search engines.

Can I track custom redirects or use existing URLs? Yes, you can use both custom redirects and existing URLs for your A/B tests.

Do I need to enable app embeds? Yes, enabling app embeds is the only step needed to get started with A/B testing.

Start Your A/B Testing Today

Increase your Shopify store's revenue and conversion rates by running native A/B testing experiments. Take advantage of this free Shopify app to optimize your store with precision and ease. For businesses looking to optimize not just their A/B testing but their entire digital presence, consider exploring additional services like Shopify SEO Audit, Shopify CRO Audit, or Custom Shopify Development. These expert services can elevate your online store's performance even further.

If you're looking for more comprehensive solutions for Shopify, Shopify Services offers a range of professional services to boost your store's functionality and success.

[lunarsilkscreen]

JavaScript Frameworks

Step 1) Polyfill

Most JS frameworks started from a need to create polyfills. A Polyfill is a js script that add features to JavaScript that you expect to be standard across all web browsers. Before the modern era; browsers lacked standardization for many different features between HTML/JS/and CSS (and still do a bit if you're on the bleeding edge of the W3 standards)

Polyfill was how you ensured certain functions were available AND worked the same between browsers.

JQuery is an early Polyfill tool with a lot of extra features added that makes JS quicker and easier to type, and is still in use in most every website to date. This is the core standard of frameworks these days, but many are unhappy with it due to performance reasons AND because plain JS has incorporated many features that were once unique to JQuery.

JQuery still edges out, because of the very small amount of typing used to write a JQuery app vs plain JS; which saves on time and bandwidth for small-scale applications.

Many other frameworks even use JQuery as a base library.

Step 2) Encapsulated DOM

Storing data on an element Node starts becoming an issue when you're dealing with multiple elements simultaneously, and need to store data as close as possible to the DOMNode you just grabbed from your HTML, and probably don't want to have to search for it again.

Encapsulation allows you to store your data in an object right next to your element so they're not so far apart.

HTML added the "data-attributes" feature, but that's more of "loading off the hard drive instead of the Memory" situation, where it's convenient, but slow if you need to do it multiple times.

Encapsulation also allows for promise style coding, and functional coding. I forgot the exact terminology used,but it's where your scripting is designed around calling many different functions back-to-back instead of manipulating variables and doing loops manually.

Step 3) Optimization

Many frameworks do a lot of heavy lifting when it comes to caching frequently used DOM calls, among other data tools, DOM traversal, and provides standardization for commonly used programming patterns so that you don't have to learn a new one Everytime you join a new project. (you will still have to learn a new one if you join a new project.)

These optimizations are to reduce reflowing/redrawing the page, and to reduce the plain JS calls that are performance reductive. A lot of these optimatizations done, however, I would suspect should just be built into the core JS engine.

(Yes I know it's vanilla JS, I don't know why plain is synonymous with Vanilla, but it feels weird to use vanilla instead of plain.)

Step 4) Custom Element and component development

This was a tool to put XML tags or custom HTML tags on Page that used specific rules to create controls that weren't inherent to the HTML standard. It also helped linked multiple input and other data components together so that the data is centrally located and easy to send from page to page or page to server.

Step 5) Back-end development

This actually started with frameworks like PHP, ASP, JSP, and eventually resulted in Node.JS. these were ways to dynamically generate a webpage on the server in order to host it to the user. (I have not seen a truly dynamic webpage to this day, however, and I suspect a lot of the optimization work is actually being lost simply by programmers being over reliant on frameworks doing the work for them. I have made this mistake. That's how I know.)

The backend then becomes disjointed from front-end development because of the multitude of different languages, hence Node.JS. which creates a way to do server-side scripting in the same JavaScript that front-end developers were more familiar with.

React.JS and Angular 2.0 are more of back end frameworks used to generate dynamic web-page without relying on the User environment to perform secure transactions.

Step 6) use "Framework" as a catch-all while meaning none of these;

Polyfill isn't really needed as much anymore unless your target demographic is an impoverished nation using hack-ware and windows 95 PCs. (And even then, they could possible install Linux which can use modern lightweight browsers...)

Encapsulation is still needed, as well as libraries that perform commonly used calculations and tasks, I would argue that libraries aren't going anywhere. I would also argue that some frameworks are just bloat ware.

One Framework I was researching ( I won't name names here) was simply a remapping of commands from a Canvas Context to an encapsulated element, and nothing more. There was literally more comments than code. And by more comments, I mean several pages of documentation per 3 lines of code.

Custom Components go hand in hand with encapsulation, but I suspect that there's a bit more than is necessary with these pieces of frameworks, especially on the front end. Tho... If it saves a lot of repetition, who am I to complain?

Back-end development is where things get hairy, everything communicates through HTTP and on the front end the AJAX interface. On the back end? There's two ways data is given, either through a non-html returning web call, *or* through functions that do a lot of heavy lifting for you already.

Which obfuscates how the data is used.

But I haven't really found a bad use of either method. But again; I suspect many things about performance impacts that I can't prove. Specifically because the tools in use are already widely accepted and used.

But since I'm a lightweight reductionist when it comes to coding. (Except when I'm not because use-cases exist) I can't help but think most every framework work, both front-end and Back-end suffers from a lot of bloat.

And that bloat makes it hard to select which framework would be the match for the project you're working on. And because of that; you could find yourself at the tail end of a development cycle realizing; You're going to have to maintain this as is, in the exact wrong solution that does not fit the scope of the project in anyway.

Well. That's what junior developers are for anyway...

[trendingnewsinsight009]

GitHub Repositories Hit by Password-Stealing Commits Disguised as Dependabot Contributions

A new deceptive campaign has been observed hijacking GitHub accounts and committing malicious code disguised as Dependabot contributions with an aim to steal passwords from developers.

"The malicious code exfiltrates the GitHub project's defined secrets to a malicious C2 server and modify any existing javascript files in the attacked project with a web-form password-stealer malware code effecting any end-user submitting its password in a web form," Checkmarx said in a technical report

The malware is also designed to capture GitHub secrets and variables to a remote server by means of a GitHub Action.

The software supply chain security firm said it observed the atypical commits to hundreds of public and private GitHub repositories between July 8 and 11, 2023.

It has emerged that the victims had their GitHub personal access tokens stolen and used by the threat actors to make falsified code commits to users' repositories by posing as Dependabot.

Dependabot is designed to alert users of security vulnerabilities in a project's dependencies by automatically generating pull requests to keep them up-to-date.

"The attackers accessed the accounts using compromised PATs (Personal Access Token) -- most likely exfiltrated silently from the victim's development environment," the company said. Most compromised users are located in Indonesia.

However, the exact method by which this theft may have taken place is currently unclear, although it's suspected that it may have involved a rogue package inadvertently installed by the developers.

This is evidenced by a new data exfiltration campaign targeting both npm and PyPI that uses as many as 39 counterfeit packages to gather sensitive machine information and transmit the details to a remote server.

The development highlights the continued attempts on part of threat actors to poison open-source ecosystems and facilitate supply chain compromises.

[techspark1]

How to Use an API Key for Your ChatGPT Clone

Building a ChatGPT clone can be a game-changer for your business, product, or app. At the heart of this process lies one critical component — the API key. In this blog, you’ll learn what an API key is, how to get one, and how to use it effectively to power your custom chatbot solution.

Table of Contents

What is an API Key?

Why You Need an API Key for a ChatGPT Clone

How to Get an API Key from OpenAI

How to Use the API Key in Your ChatGPT Clone

Securing Your API Key

Alternatives to Manual Setup

Final Thoughts

Keyword Ideas

What is an API Key?

An API key is a unique code used to authenticate and interact with APIs. In the context of a GPT chatbot, this key allows your app to access and use the capabilities of the OpenAI language model, such as generating human-like responses or processing queries in natural language.

Why You Need an API Key for a ChatGPT Clone

When creating a ChatGPT clone, your backend will communicate with the GPT engine via API calls. Every request made to OpenAI's servers must be authenticated using a valid API key. Without it, your chatbot won’t be able to generate responses.

If you're using a ready-to-go ChatGPT clone, the platform might include API integration options that make the process even easier.

How to Get an API Key from OpenAI

Here’s a quick guide to obtaining your API key:

Create an OpenAI account at https://platform.openai.com

Verify your email and identity, if required

Navigate to your API Keys dashboard

Click on “Create new secret key”

Copy and save the key securely — it won’t be shown again

Note: Some usage may incur costs, depending on how much you use the API.

How to Use the API Key in Your ChatGPT Clone

Once you have the key, you can integrate it into your code. Here's an example in JavaScript using fetch():

javascript

CopyEdit

const response = await fetch("https://api.openai.com/v1/chat/completions", {

  method: "POST",

  headers: {

    "Content-Type": "application/json",

    "Authorization": "Bearer YOUR_API_KEY"

  },

  body: JSON.stringify({

    model: "gpt-3.5-turbo",

    messages: [{ role: "user", content: "Hello!" }]

  })

});

Replace "YOUR_API_KEY" with your actual API key. You can do the same in Python, Node.js, or any language that supports HTTP requests.

Securing Your API Key

Never expose your API key in frontend code, public repositories, or browser-based scripts. Use environment variables or a secure backend to store and access the key. If compromised, someone could use your key and rack up charges on your account.

Alternatives to Manual Setup

Not comfortable with coding? No problem. Use platforms that offer pre-built solutions. A customizable ChatGPT clone comes with built-in API integration and features like chat UI, admin panel, and user authentication — all without the need to build from scratch.

Final Thoughts

Using an API key is a simple but crucial step when developing a ChatGPT clone. Whether you’re building a chatbot for customer service, productivity, or just experimenting with AI, securing and integrating your API key ensures your application runs smoothly. For a faster start, consider using a complete ChatGPT clone solution designed to work out of the box.

Reach out to the Miracuves team to start the conversation:

Website: https://miracuves.com Email: biz@miracuves.com Contact (US): +15162023950, (India): +91–983000–9649

[vytcdc1]

The journey to mastering full-stack development often begins with choosing the right combination of technologies. For many developers, Python, Vue.js, and PostgreSQL form a powerful and versatile stack. This trio provides a robust backend, a dynamic front end, and a reliable database. Whether you’re a budding developer enrolled in an FSD Python course or a seasoned programmer exploring new frameworks, this guide will provide the foundational steps to set up a full-stack project. 

Why Choose Python, Vue.js, and PostgreSQL?

Python: Known for its simplicity and versatility, Python is a favorite for backend development. Frameworks like Flask and Django make it easy to build scalable APIs and web applications. 

Vue.js: Vue.js is a progressive JavaScript framework for building user interfaces. Its simplicity, flexibility, and reactive components make it ideal for crafting modern, dynamic frontends. 

PostgreSQL: As one of the most advanced open-source relational database systems, PostgreSQL is renowned for its scalability, reliability, and extensive feature set. 

Step 1: Plan Your Project Structure 

In a standard full-stack project using Python, Vue.js, and PostgreSQL, the project structure is typically organized into several main directories. The backend directory contains the Python-based backend code, which could use frameworks like Django or Flask. The frontend directory holds the Vue.js frontend code and is responsible for the user interface. The database directory includes scripts and configuration files for setting up and managing the PostgreSQL database. The environment directory stores configuration files, such as environment variables and deployment settings. Finally, the docs directory is dedicated to documentation and notes related to the project. This structure ensures clarity and separation of concerns, making the project easier to manage and scale. 

Step 2: Set Up the Backend with Python 

Choose a Python Framework:  

Flask: Lightweight and flexible for simple APIs. 

Django: A full-fledged web framework with built-in features for authentication, ORM, and more. 

Create the Virtual Environment:  

Using virtual environments ensures project dependencies remain isolated, a key concept covered in any Python FSD curriculum. 

Install Necessary Packages:  

For Flask: Flask, Flask-Cors, and SQLAlchemy. 

For Django, use core Django packages and DRF (Django Rest Framework) for API handling. 

API Design:  

Develop RESTful endpoints to handle CRUD operations. 

Implement authentication mechanisms like JWT for user management. 

Step 3: Develop the Frontend with Vue.js 

Set Up the Vue.js Environment:  

Use Vue CLI to scaffold your application. This creates a starter project with essential configurations. 

Design Components:  

Break down your application into modular components (e.g., header, footer, forms). 

Use Vue’s data-binding and state management to handle user interactions. 

API Integration:  

Axios or Fetch can be used to connect the Vue.js frontend with your Python backend. 

Styling:  

Choose between frameworks like Vuetify, Tailwind CSS, or Bootstrap to style your application. 

Step 4: Configure the PostgreSQL Database 

Install PostgreSQL:  

Ensure PostgreSQL is installed and running on your system. Tools like pgAdmin simplify database management. 

Set Up the Database:  

Define your schema and relationships. Django’s ORM or Flask’s SQLAlchemy can streamline this process. 

Database Connection:  

Configure your backend to connect to PostgreSQL using libraries like psycopg2. 

Migrations:  

Use migration tools provided by your framework (e.g., Django’s migrate command) to keep your database schema synchronized. 

Step 5: Link the Frontend and Backend 

Cross-Origin Resource Sharing (CORS):  

Enable CORS in your backend to allow API requests from your frontend. 

Environment Variables:  

Use .env files to securely manage API keys, database credentials, and other sensitive information. 

Serve the Frontend:  

Deploy your Vue.js application and configure the backend to serve the frontend (or use a separate web server). 

Step 6: Deployment 

Containerization:  

Use Docker to containerize your application for consistent deployment across environments. 

Hosting Platforms:  

For the backend, consider platforms like Heroku, AWS, or Azure. 

For the front end, platforms like Vercel or Netlify are excellent choices. 

Database Hosting:  

Host PostgreSQL on cloud platforms like AWS RDS or DigitalOcean for better scalability. 

Conclusion

Setting up a full-stack project with Python, Vue.js, and PostgreSQL may seem complex initially, but with proper guidance and practice, it becomes a manageable and rewarding process. Whether you’re enrolled in a Python Full Stack Development Course or self-learning, this stack equips you with the tools to build modern, scalable web applications. 

Each step in this guide provides a foundation for exploring and implementing advanced features like authentication, real-time updates, or cloud deployment. With persistence and curiosity, you’ll be well on your way to mastering full-stack development. 

Contact Us: 

Phone 

+917338811773 

+918925903732 

Email: careers@vytcdc.com 

[imtrinity94]

Get Orchestrator Hostname and IP using JavaScript

To get the vRealize Orchestrator (vRO) appliance’s hostname using JavaScript within a vRO workflow, there is no official API call for this purpose, but there are practical workarounds: Method 1: Parse Environment Variables In vRO 8.x (containerized), you might be able to extract the hostname from JVM arguments in the environment: Prerequisite: Enable local process execution. JavaScriptvar com…

[blockchaindevelopmenttechnology]

How to Build a Solana Trading Bot: A Complete Guide

Introduction

In today’s rapidly evolving crypto landscape, algorithmic trading is no longer just for hedge funds—it’s becoming the norm for savvy traders and developers. Trading bots are revolutionizing how people interact with decentralized exchanges (DEXs), allowing for 24/7 trading, instant decision-making, and optimized strategies.

If you're planning to build a crypto trading bot, Solana blockchain is a compelling platform. With blazing-fast transaction speeds, negligible fees, and a thriving DeFi ecosystem, Solana provides the ideal environment for high-frequency, scalable trading bots.

In this blog, we'll walk you through the complete guide to building a Solana trading bot, including tools, strategies, architecture, and integration with Solana DEXs like Serum and Raydium.

Why Choose Solana for Building a Trading Bot?

Solana has quickly emerged as one of the top platforms for DeFi and trading applications. Here’s why:

🚀 Speed: Handles over 65,000 transactions per second (TPS)

💸 Low Fees: Average transaction cost is less than $0.001

⚡ Fast Finality: Block confirmation in just 400 milliseconds

🌐 DeFi Ecosystem: Includes DEXs like Serum, Orca, and Raydium

🔧 Developer Support: Toolkits like Anchor, Web3.js, and robust SDKs

These characteristics make Solana ideal for real-time, high-frequency trading bots that require low latency and cost-efficiency.

Prerequisites Before You Start

To build a Solana trading bot, you’ll need:

🔧 Technical Knowledge

Blockchain basics

JavaScript or Rust programming

Understanding of smart contracts and crypto wallets

🛠️ Tools & Tech Stack

Solana CLI – For local blockchain setup

Anchor Framework – If using Rust

Solana Web3.js – For JS-based interactions

Phantom/Sollet Wallet – To sign transactions

DeFi Protocols – Serum, Raydium, Orca

APIs – RPC providers, Pyth Network for price feeds

Set up a wallet on Solana Devnet or Testnet before moving to mainnet.

Step-by-Step: How to Build a Solana Trading Bot

Step 1: Define Your Strategy

Choose a trading strategy:

Market Making: Providing liquidity by placing buy/sell orders

Arbitrage: Exploiting price differences across DEXs

Scalping: Taking advantage of small price changes

Momentum/Trend Trading: Based on technical indicators

You can backtest your strategy using historical price data to refine its effectiveness.

Step 2: Set Up Development Environment

Install the essentials:

Solana CLI & Rust (or Node.js)

Anchor framework (for smart contract development)

Connect your wallet to Solana devnet

Install Serum/Orca SDKs for DEX interaction

Step 3: Integrate with Solana DeFi Protocols

Serum DEX: For order-book-based trading

Raydium & Orca: For AMM (Automated Market Maker) trading

Connect your bot to fetch token pair information, price feeds, and liquidity data.

Step 4: Build the Trading Logic

Fetch real-time price data using Pyth Network

Apply your chosen trading algorithm (e.g., RSI, MACD, moving averages)

Trigger buy/sell actions based on signals

Handle different order types (limit, market)

Step 5: Wallet and Token Management

Use SPL token standards

Manage balances, sign and send transactions

Secure private keys using wallet software or hardware wallets

Step 6: Testing Phase

Test everything on Solana Devnet

Simulate market conditions

Debug issues like slippage, front-running, or network latency

Step 7: Deploy to Mainnet

Move to mainnet after successful tests

Monitor performance using tools like Solana Explorer or Solscan

Add dashboards or alerts for better visibility

Key Features to Add

For a production-ready Solana trading bot, include:

✅ Stop-loss and take-profit functionality

📈 Real-time logging and analytics dashboard

🔄 Auto-reconnect and restart scripts

🔐 Secure environment variables for keys and APIs

🛠️ Configurable trading parameters

Security & Risk Management

Security is critical, especially when handling real assets:

Limit API calls to prevent bans

Secure private keys with hardware or encrypted vaults

Add kill-switches for extreme volatility

Use rate limits and retries to handle API downtime

Consider smart contract audits for critical logic

Tools & Frameworks to Consider

Anchor – Solana smart contract framework (Rust)

Solana Web3.js – JS-based blockchain interaction

Serum JS SDK – Interface with Serum’s order books

Pyth Network – Live, accurate on-chain price feeds

Solscan/Solana Explorer – Track transactions and wallet activity

Real-World Use Cases

Here are examples of Solana trading bots in action:

Arbitrage Bots: Profiting from price differences between Raydium and Orca

Liquidity Bots: Maintaining order books on Serum

Oracle-Driven Bots: Reacting to real-time data via Pyth or Chainlink

These bots are typically used by trading firms, DAOs, or DeFi protocols.

Challenges to Be Aware Of

❗ Network congestion during high demand

🧩 Rapid updates in SDKs and APIs

📉 Slippage and liquidity issues

🔄 DeFi protocol changes requiring frequent bot updates

Conclusion

Building a trading bot on Solana blockchain is a rewarding venture—especially for developers and crypto traders looking for speed, cost-efficiency, and innovation. While there are challenges, Solana's robust ecosystem, coupled with developer support and toolkits, makes it one of the best choices for automated DeFi solutions.

If you're looking to take it a step further, consider working with a Solana blockchain development company to ensure your bot is scalable, secure, and production-ready.

[moonstone987]

Best Python Training Institute in Kochi: A Complete Guide for Aspiring Developers

Python has become a global phenomenon. Whether it’s powering AI-driven applications, automating mundane tasks, supporting web development, or handling complex data science projects, Python is everywhere. For anyone eager to build a career in software development, machine learning, data science, or web technologies, mastering Python is crucial.

If you are searching for the Best Python Training Institute in Kochi, you’re already on the right track. Kochi, with its growing tech scene, offers an ideal environment for tech enthusiasts and professionals who want to upskill or begin a promising career in Python development.

In this article, we’ll dive deep into why Python is a must-learn language, what an ideal Python training course should offer, how to identify the Best Python Training Institute in Kochi, and why Zoople Technologies stands tall as a top choice.

Why Python is Essential in Today’s Tech Industry

Python's popularity stems from its:

Simplicity and Readability: Its syntax closely resembles English, making it perfect for beginners.

Versatility: Python is used in web development, data science, artificial intelligence, automation, app development, and more.

Huge Community Support: With millions of developers using Python, support is just a click away.

High Demand and Salary: Python developers enjoy lucrative salaries and tremendous job opportunities globally.

Cross-Platform Compatibility: Python runs seamlessly across different platforms like Windows, MacOS, and Linux.

Given these advantages, enrolling in the Best Python Training Institute in Kochi can unlock many career doors for you.

What Should the Best Python Training Program Cover?

When looking for the Top-most Python Training Institute in Kochi, ensure that the training program offers a comprehensive curriculum. Here’s what a solid program should include:

1. Core Python Programming

Variables, Data Types, and Operators

Control Flow (if, else, loops)

Functions, Modules, and Packages

Object-Oriented Programming (OOP)

2. Advanced Python Topics

File Handling

Exception Handling

Regular Expressions

Working with APIs

3. Web Development with Python

Django and Flask frameworks

Frontend basics (HTML, CSS, JavaScript) integration

Building real-world web applications

4. Data Handling

Working with libraries like Pandas and NumPy

Data visualization using Matplotlib and Seaborn

5. Practical Exposure

Hands-on projects and mini-projects

Capstone project to consolidate learning

6. Additional Skills

Version control systems like Git and GitHub

Deployment of web applications

Interview preparation and soft skills training

A truly comprehensive course ensures that students are job-ready, not just theoretically knowledgeable.

Career Opportunities After Python Training

Completing a Python course from the Best Python Training Institute in Kochi can lead to multiple career paths, including:

Python Developer

Full-Stack Developer (Python specialization)

Data Scientist

Machine Learning Engineer

Backend Developer

Automation Engineer

Web Developer

The IT industry in Kochi, particularly in hubs like Infopark, SmartCity, and several tech startups, is actively seeking Python-skilled professionals. With the right skills and guidance, you could land rewarding job offers right after completing your course.

Why Choose Kochi for Python Training?

Kochi, often dubbed Kerala’s IT capital, is an emerging hotspot for technology education and innovation. Here’s why pursuing Python training here makes sense:

Growing IT Sector: Companies like TCS, Cognizant, and a host of startups are creating a demand for skilled tech workers.

Affordable Cost of Living and Training: Compared to cities like Bangalore or Hyderabad, Kochi offers a quality lifestyle at a lower cost.

Networking Opportunities: Tech meetups, seminars, and workshops happen regularly, helping you build a strong professional network.

Relaxed Lifestyle: Great food, beautiful landscapes, and a vibrant culture provide a perfect balance between study and life.

Choosing the Best Python Training Institute in Kochi ensures you make the most of these opportunities.

How to Identify the Best Python Training Institute in Kochi

When selecting an institute, look for:

Experienced Trainers: Professionals with real industry exposure.

Hands-On Training: A strong focus on projects and live coding sessions.

Industry-Relevant Curriculum: Updated course content aligned with current industry standards.

Placement Support: Resume building, interview prep, and placement assistance.

Positive Student Reviews: Testimonials and success stories from alumni.

A good training program doesn’t just teach you how to code; it prepares you to become a professional developer ready to take on real-world challenges.

Zoople Technologies: The Best Python Training Institute in Kochi

When it comes to finding the Best Python Training Institute in Kochi, Zoople Technologies shines as a top choice for serious learners.

Why Zoople Technologies?

Industry-Experienced Faculty: Zoople’s instructors are seasoned professionals who bring real-world knowledge to the classroom.

Comprehensive Curriculum: The course covers everything from basics to advanced topics, with specialized modules for web development and data science.

Hands-On Projects: Students work on real-time projects, building practical experience that employers value highly.

Flexible Learning Options: Zoople offers both classroom and online learning modes to suit students' schedules.

Placement Assistance: With dedicated career services, Zoople ensures you are interview-ready and connects you with leading companies.

Supportive Learning Environment: Zoople fosters a culture of mentorship, continuous learning, and professional growth.

At Zoople Technologies, the mission is not just to deliver training but to build successful tech careers. Their commitment to quality education, industry partnerships, and student success has rightly earned them the title of the Best Python Training Institute in Kochi.

If you are serious about stepping into the world of technology with strong foundational skills and real-world experience, Zoople Technologies is your ultimate destination. Enroll today and set yourself up for a rewarding future in tech!

[engineeringenigma]

So I work as a programmer, and the languages I use and the manner I use them in get kind of weird:

- I use python, but only to program the one robot that internally runs python. The dev environment is “here’s a box you can put text, see if you get runtime errors”. If you want a proper dev environment, you can copy-paste code from the robot program into an editor of your choice. They do have a top-level graphical interface if you want each line of code to take up 10% of your screen.

- There’s a language that’s not quite C++ that we use for a different control box. That one’s dev environment will tell you if you made an error when you try to download. Specifically it tells you the first error, and you have to fix it and try to download again to get the second error. The download process takes 20 seconds. If you try to compile offline you get separate errors.

- On the more normal side of things, we have an SQL/ajax/javascript/html thing for handling some of our internal processes. As a change of pace my problems for this one are self-inflicted, because I never figured out how to set up a proper dev environment and just edit everything in notepad++. Someone else finally showed me how to do local environment testing so I no longer take our internal website down if I miss a close bracket.

- We do a ton of stuff in .NET framework, because 20 years ago my work was using VB6 and we never bothered to migrate to C#. I actually have a real dev environment for this one with autocomplete and syntax checking, so of course it’s my favorite. My boss wants to switch this all over to javascript so we can do android/linux deployment.

- A different robot has an internal language that’s not quite python. This one also has a graphical interface that I won’t use because I want more information to fit on my screen. This one also only tells you about syntax errors during runtime, but the most noteworthy thing about it is that the command to move the robot in a straight line is bugged. I think they fixed it to the point where you can’t reboot the controller by telling it to move in a straight line, but you can make it slowly drift off into space until it faults.

- The ladder logic we use is actually normal (for AB, not Seimen’s), but I did add basically a secondary control layer built out of function blocks to handle sequencing. It is very well-documented, a fact that no one cares about when they ask what the heck I am doing with so many function blocks.

- The ladder logic was a little too normal (expensive) so they also make us use the budget version. It’s very similar except there are no keyboard shortcuts, everything takes more clicks, and instead of changing code live you have to reboot everything and wait about 30 seconds if you want to change something.

- There’s a language we use for one of our internal products that I created over about three days because I didn’t want to worry about malicious external code or figuring out a compiler. The parser is just squashed into an entirely different program so that program can control stuff in the background. It does not have arrays or loops, and I didn’t give it string handling for about a year. There’s no dev environment because it’s not a real language. Something like a quarter of the stuff we sell now uses it.

- One of the robots requires programming via menus. If you want to add an if statement, the menu shortcut is F1 -> 4 -> 8. The end if is F1 -> 4 -> 0 -> 1. The program to let you type is a paid add-on. Exponents and absolute values are also paid add-ons. You get 200 numerical memory registers and can’t have local variables. There is no else if.

[xpredatorvccffsd]

Introduction to JavaScript Compilers

JavaScript is one of the most widely used programming languages, powering web applications, servers, and even mobile apps. But how does JavaScript code transform from human-readable text into executable instructions? The answer lies in the JavaScript compiler.

A JavaScript compiler translates high-level JavaScript code into optimized machine code or bytecode, improving performance and efficiency. In this article, we’ll explore how JavaScript compilers work, their key components, and their role in modern web development.

What Is a JavaScript Compiler?

A compiler is a software tool that converts source code written in a high-level programming language (like JavaScript) into a lower-level representation (such as machine code or bytecode). Unlike interpreters, which execute code line by line, compilers process the entire codebase at once, optimizing it for better performance.

JavaScript engines like V8 (Chrome), SpiderMonkey (Firefox), and JavaScriptCore (Safari) use Just-In-Time (JIT) compilation to execute JavaScript efficiently.

How Does a JavaScript Compiler Work?

The JavaScript compilation process involves several stages:

1. Parsing (Lexical Analysis & Syntax Tree Generation)

The compiler first breaks down the code into tokens (keywords, variables, operators).

It then constructs an Abstract Syntax Tree (AST), a structured representation of the code’s logic.

2. Compilation (Bytecode or Machine Code Generation)

Modern JavaScript engines use JIT compilation, which combines interpretation and compilation.

The engine converts the AST into bytecode (an intermediate low-level code) or directly into machine code for execution.

3. Optimization (Inlining, Dead Code Elimination, etc.)

The compiler applies optimizations like:

Inline Caching: Speeds up property access.

Hidden Classes: Optimizes object property access.

Dead Code Elimination: Removes unused code.

4. Execution

The optimized code runs in the browser or Node.js environment.

[conneqtion]

Common Challenges in Oracle Forms to APEX Migrations—and How to Solve Them

Migrating from Oracle Forms to Oracle APEX is not just a technology shift—it's a transformation of how your business applications work, look, and scale. While Oracle Forms has served enterprises reliably for decades, it's built on a client-server architecture that doesn't align with modern, web-first expectations.

Oracle APEX, on the other hand, offers a low-code, browser-based environment with rich UI capabilities, tight PL/SQL integration, and excellent support for modern development practices.

But let’s be honest—Forms to APEX migration isn't a plug-and-play process. It comes with real-world challenges that, if not addressed properly, can lead to delays, frustration, or missed opportunities.

In this post, we'll explore the most common challenges in migrating Oracle Forms to APEX—and, more importantly, how to solve them.

Challenge 1: Understanding the Legacy Code and Business Logic

📌 The Problem:

Many Forms applications have evolved over decades, often with minimal documentation. The logic is tightly bound to the UI, buried in triggers, program units, and PL/SQL blocks.

✅ The Solution:

Perform a full inventory of all Forms modules.

Use tools like Oracle Forms2XML or third-party scanners to extract and analyze code.

Identify reusable business logic and move it to database packages, separating logic from UI.

Document core workflows before rewriting in APEX.

Pro tip: Establish a “Forms-to-APEX Reference Map” to track where each legacy feature is being re-implemented or redesigned.

⚠️ Challenge 2: UI/UX Differences Between Forms and APEX

📌 The Problem:

Forms applications often use canvases, blocks, and modal windows—none of which translate 1:1 into APEX. Users familiar with old-school layouts may resist change.

✅ The Solution:

Focus on functionality parity, not screen-by-screen cloning.

Reimagine the UI with APEX Interactive Reports, Dialogs, and Faceted Search.

Use the Redwood Light theme in APEX to deliver a clean, modern experience.

Conduct end-user workshops to involve them early in the redesign process.

Remember: This is a chance to improve UX, not just replicate the past.

⚠️ Challenge 3: Handling Triggers and Built-in Events

📌 The Problem:

Forms relies heavily on triggers like WHEN-VALIDATE-ITEM, PRE-INSERT, or KEY-NEXT-ITEM. These don't exist in APEX in the same way.

✅ The Solution:

Move data validation logic into database triggers or packages.

Use Dynamic Actions, Process Handlers, and Validations in APEX to simulate similar behaviors.

Create custom JavaScript where necessary for field-level interactions.

Keep business logic in PL/SQL, and use APEX to handle client-side workflows.

⚠️ Challenge 4: List of Values (LOVs) and Pop-Ups

📌 The Problem:

Oracle Forms uses LOVs and pop-up windows extensively. These may not behave the same in APEX without thoughtful redesign.

✅ The Solution:

Replace Forms LOVs with APEX’s popup LOV or select list components.

Use shared LOVs to centralize list management.

For cascading LOVs, use Dynamic Actions to update values based on selections.

APEX provides more flexibility—but you may need to rethink the user flow.

⚠️ Challenge 5: State Management and Navigation

📌 The Problem:

Forms is stateful; APEX is stateless. In Forms, navigation and state retention happen automatically. In APEX, every action reloads a page or region.

✅ The Solution:

Use session state variables and hidden items to manage state across pages.

Apply branching logic and URL parameters for navigation control.

Embrace modal dialogs for maintaining context.

Design with the web in mind—shorter tasks, fewer clicks, intuitive flow.

⚠️ Challenge 6: Training & Developer Mindset Shift

📌 The Problem:

Developers accustomed to Forms development need to shift from procedural to declarative, low-code development in APEX.

✅ The Solution:

Provide hands-on training and access to APEX learning resources.

Create internal sandboxes for experimenting with APEX features.

Promote code reusability, templates, and UI best practices.

APEX is powerful—but it takes time to shift the mindset from "Form triggers" to "Dynamic Actions and page processes."

✅ Conclusion

Oracle Forms to APEX migration is a rewarding journey—but like any transformation, it comes with technical and cultural challenges. The key is to approach it methodically:

Analyze and document before you migrate.

Modernize, don’t just replicate.

Train your team, and embrace the new development model.

Done right, the migration leads to modern, maintainable, and scalable applications that align with today’s business and user expectations.

[codebriefly]

New Post has been published on https://codebriefly.com/building-and-deploying-angular-19-apps/

Building and Deploying Angular 19 Apps

Efficiently building and deploying Angular 19 applications is crucial for delivering high-performance, production-ready web applications. In this blog, we will cover the complete process of building and deploying Angular 19 apps, including best practices and optimization tips.

Table of Contents

Toggle

Why Building and Deploying Matters

Preparing Your Angular 19 App for Production

Building Angular 19 App

Key Optimizations in Production Build:

Configuration Example:

Deploying Angular 19 App

Deploying on Firebase Hosting

Deploying on AWS S3 and CloudFront

Automating Deployment with CI/CD

Example with GitHub Actions

Best Practices for Building and Deploying Angular 19 Apps

Final Thoughts

Why Building and Deploying Matters

Building and deploying are the final steps of the development lifecycle. Building compiles your Angular project into static files, while deploying makes it accessible to users on a server. Proper optimization and configuration ensure faster load times and better performance.

Preparing Your Angular 19 App for Production

Before building the application, make sure to:

Update Angular CLI: Keep your Angular CLI up to date.

npm install -g @angular/cli

Optimize Production Build: Enable AOT compilation and minification.

Environment Configuration: Use the correct environment variables for production.

Building Angular 19 App

To create a production build, run the following command:

ng build --configuration=production

This command generates optimized files in the dist/ folder.

Key Optimizations in Production Build:

AOT Compilation: Reduces bundle size by compiling templates during the build.

Tree Shaking: Removes unused modules and functions.

Minification: Compresses HTML, CSS, and JavaScript files.

Source Map Exclusion: Disables source maps for production builds to improve security and reduce file size.

Configuration Example:

Modify the angular.json file to customize production settings:

"configurations": "production": "optimization": true, "outputHashing": "all", "sourceMap": false, "namedChunks": false, "extractCss": true, "aot": true, "fileReplacements": [ "replace": "src/environments/environment.ts", "with": "src/environments/environment.prod.ts" ]

    Deploying Angular 19 App

Deployment options for Angular apps include:

Static Web Servers (e.g., NGINX, Apache)

Cloud Platforms (e.g., AWS S3, Firebase Hosting)

Docker Containers

Serverless Platforms (e.g., AWS Lambda)

Deploying on Firebase Hosting

Install Firebase CLI:

npm install -g firebase-tools

Login to Firebase:

firebase login

Initialize Firebase Project:

firebase init hosting

Deploy the App:

firebase deploy

Deploying on AWS S3 and CloudFront

Build the Project:

ng build --configuration=production

Upload to S3:

aws s3 sync ./dist/my-app s3://my-angular-app

Configure CloudFront Distribution: Set the S3 bucket as the origin.

Automating Deployment with CI/CD

Setting up a CI/CD pipeline ensures seamless updates and faster deployments.

Example with GitHub Actions

Create a .github/workflows/deploy.yml file:

name: Deploy Angular App on: [push] jobs: build-and-deploy: runs-on: ubuntu-latest steps: - uses: actions/checkout@v2 - name: Set up Node.js uses: actions/setup-node@v2 with: node-version: '18' - run: npm install - run: npm run build -- --configuration=production - name: Deploy to S3 run: aws s3 sync ./dist/my-app s3://my-angular-app --delete

Best Practices for Building and Deploying Angular 19 Apps

Optimize for Production: Always use AOT and minification.

Use CI/CD Pipelines: Automate the build and deployment process.

Monitor Performance: Utilize tools like Lighthouse to analyze performance.

Secure the Application: Enable HTTPS and configure secure headers.

Cache Busting: Use hashed filenames to avoid caching issues.

Containerize with Docker: Simplifies deployments and scales easily.

Final Thoughts

Building and deploying Angular 19 applications efficiently can significantly enhance performance and maintainability. Following best practices and leveraging cloud hosting services ensure that your app is robust, scalable, and fast. Start building your next Angular project with confidence!

Keep learning & stay safe 😉

You may like:

Testing and Debugging Angular 19 Apps

Performance Optimization and Best Practices in Angular 19

UI/UX with Angular Material in Angular 19

[souhaillaghchimdev]

Digital Marketing Application Programming

In today's tech-driven world, digital marketing is no longer just about catchy ads and engaging posts—it's about smart, automated, data-driven applications. Whether you're a developer building a marketing automation platform or a digital marketer looking to leverage tech, understanding how to program marketing applications is a game changer.

What Is Digital Marketing Application Programming?

Digital Marketing Application Programming refers to the development of tools, systems, and scripts that help automate, optimize, and analyze digital marketing efforts. These applications can handle tasks like SEO analysis, social media automation, email campaigns, customer segmentation, and performance tracking.

Key Areas of Digital Marketing Applications

Email Marketing Automation: Schedule and personalize email campaigns using tools like Mailchimp API or custom Python scripts.

SEO Tools: Build bots and crawlers to check page speed, backlinks, and keyword rankings.

Social Media Automation: Use APIs (e.g., Twitter, Instagram, Facebook) to schedule posts and analyze engagement.

Analytics and Reporting: Integrate with Google Analytics and other platforms to generate automated reports and dashboards.

Ad Campaign Management: Use Google Ads API or Meta Ads API to manage and analyze advertising campaigns.

Popular Technologies and APIs

Python: Great for automation, scraping, and data analysis.

JavaScript/Node.js: Excellent for real-time applications, chatbots, and front-end dashboards.

Google APIs: For accessing Google Ads, Google Analytics, and Google Search Console data.

Facebook Graph API: For managing posts, ads, and analytics across Facebook and Instagram.

Zapier/IFTTT Integration: No-code platforms for connecting various marketing tools together.

Example: Sending an Automated Email with Python

import smtplib from email.mime.text import MIMEText def send_email(subject, body, to_email): msg = MIMEText(body) msg['Subject'] = subject msg['From'] = 'you@example.com' msg['To'] = to_email with smtplib.SMTP('smtp.example.com', 587) as server: server.starttls() server.login('you@example.com', 'yourpassword') server.send_message(msg) send_email("Hello!", "This is an automated message.", "client@example.com")

Best Practices

Use APIs responsibly and within rate limits.

Ensure user privacy and comply with GDPR/CCPA regulations.

Log all automated actions for transparency and debugging.

Design with scalability in mind—marketing data grows fast.

Secure API keys and sensitive user data using environment variables.

Real-World Use Cases

Marketing dashboards pulling real-time analytics from multiple platforms.

Automated tools that segment leads based on behavior.

Chatbots that qualify sales prospects and guide users.

Email drip campaigns triggered by user activity.

Dynamic landing pages generated based on campaign source.

Conclusion

Digital marketing is being transformed by smart programming. Developers and marketers working together can create systems that reduce manual labor, improve targeting, and increase ROI. Whether you're automating emails, analyzing SEO, or building AI chatbots—coding skills are a superpower in digital marketing.