The Practical DeveloperModify

2026-01-24 15:38:36

GraphQL isn't better than REST. REST isn't better than GraphQL. They solve different problems, and the "right" choice depends entirely on what you're building.

The debates online are mostly ideology. What actually matters is matching the tool to your situation.

The Decision Framework

Before diving into trade-offs, here's the shortest possible answer:

If you're not sure, start with REST. It's simpler, and you can add GraphQL later for specific use cases that need it.

What Each Actually Does

REST is resource-based. Each endpoint returns a complete resource. You call /users/123 and get the full user object. You call /orders and get all orders. Simple, predictable, stateless.

GraphQL is query-based. You write a query specifying exactly what you want, and you get exactly that—nothing more, nothing less. Multiple resources can come back in a single request.

Neither approach is inherently faster or more "modern." They're different mental models for organizing API access.

When REST Wins

Simplicity

REST is HTTP. Everyone knows HTTP. Your junior dev knows HTTP. The contractor you just hired knows HTTP. The curl examples in documentation just work.

GraphQL requires learning a query language, understanding schemas, and often using specialized client libraries. That's not prohibitive, but it's overhead.

Caching

REST endpoints can be cached by URL. Any HTTP cache—CDN, browser, proxy—understands how to cache GET /api/users/123. You get caching infrastructure for free.

GraphQL uses POST requests with query bodies. Standard HTTP caching doesn't work. You need specialized solutions like persisted queries or normalized client caches (Apollo, urql). More power, more complexity.

Debugging

When a REST call fails, you know exactly which resource failed. The URL tells you everything.

When a GraphQL query fails, you might get partial success—some fields resolve, others don't. Your error handling needs to account for this. It's more powerful (you still get the data that worked) but also more complex.

Tooling and Integration

Every tool supports REST. Postman, curl, Zapier, Make, Power Automate, webhook systems—they all speak REST natively.

GraphQL support is growing but not universal. If you're building integrations with no-code tools or need broad compatibility, REST is safer.

When GraphQL Wins

Multiple Resources Per Request

This is GraphQL's killer feature. Instead of calling three endpoints and stitching responses together, you write one query that returns exactly what you need.

For a dashboard showing user info, recent orders, and notifications, REST means three round trips. GraphQL means one.

On fast connections, this difference is minor. On mobile networks or high-latency connections, it's significant. Fewer round trips = faster perceived performance.

Precise Data Fetching

REST endpoints return complete resources. If you only need a user's name and email, you still get their address, preferences, metadata, and everything else.

GraphQL lets you request exactly the fields you need. For bandwidth-sensitive applications (mobile, IoT, high-volume), this matters.

Evolving APIs Without Versioning

With REST, changing a response structure often means versioning (/v1/users, /v2/users). Old clients break if you remove fields.

GraphQL clients specify what they need. You can add fields freely, and deprecate old ones gradually. Clients only break if they ask for something removed—and you can track exactly who's using what.

Complex, Nested Data

When your data is deeply nested—users with orders with line items with products—REST requires either multiple calls or custom "include" parameters.

GraphQL handles nesting naturally. You describe the shape you want, traversing relationships in a single query.

The Trade-Off Table

The Cost Question

On APIVerve, GraphQL has a pricing difference worth knowing:

• REST calls: Each API costs its normal credit amount
• GraphQL queries: Each API in your query costs its credit, plus 1 credit for orchestration

So a GraphQL query hitting 3 APIs costs 4 credits, while 3 REST calls cost 3 credits.

You're paying for the convenience of single-request aggregation. Whether that's worth it depends on what you value—lower latency or lower cost.

The Hybrid Approach

You don't have to pick one for everything. Many applications use both:

• REST for simple, single-resource operations
• REST for webhook integrations and third-party tools
• GraphQL for complex dashboard pages
• GraphQL for mobile clients where round trips hurt

This isn't indecision—it's pragmatism. Use the right tool for each situation.

Common Mistakes

Switching for the Wrong Reasons

"GraphQL is newer" isn't a reason. "Netflix uses it" isn't a reason. "It feels more sophisticated" definitely isn't a reason.

Switch when you have a concrete problem GraphQL solves: too many round trips, too much overfetching, too much complexity managing multiple API calls.

Over-Engineering from Day One

Starting a new project? Use REST. Get something working. Ship it.

If you later discover that your dashboard makes 8 API calls per page load and performance suffers, then consider GraphQL for that specific page. Don't architect for problems you don't have yet.

Ignoring Your Team

If your team knows REST and doesn't know GraphQL, factor in the learning curve. The best technology choice is one your team can execute well.

Quick Reference

APIVerve REST:

GET https://api.apiverve.com/v1/randomquote
Header: x-api-key: YOUR_KEY

APIVerve GraphQL:

POST https://api.apiverve.com/v1/graphql
Header: x-api-key: YOUR_KEY
Body: {"query": "{ randomquote { quote author } }"}

Same API key. Same underlying APIs. Different access patterns.

The right answer isn't REST or GraphQL. It's understanding what each does well and choosing based on your actual constraints—team expertise, performance requirements, integration needs, and development velocity.

Most projects work fine with REST. Some benefit from GraphQL. Very few need to go all-in on either.

Check out the GraphQL documentation when you're ready to experiment, or start with the REST quickstart. Grab your API key and build something.

Originally published at APIVerve Blog

2026-01-24 15:35:34

A friend runs an online store selling specialty coffee equipment. Ships worldwide. Most of his traffic comes from outside the US, but for three years, his site only showed USD prices.

One day he added a currency switcher. Same products, same prices, just displayed in the visitor's local currency.

Conversions from international visitors went up 34%.

That's it. That's the whole story. He didn't lower prices. Didn't change shipping. Didn't run any promotions. Just stopped making European customers do mental math to figure out how much a grinder costs in euros.

Why Local Currency Matters

Here's what happens in a customer's brain when they see "$249.99":

If they think in USD: "Two fifty, reasonable for a grinder."

If they think in EUR: "Two fifty... divide by... what's the rate... maybe €230? Or €210? Let me Google it... actually, maybe I'll buy this later."

That "maybe later" is a lost sale. Every second of friction is a customer who might not come back.

Studies consistently show:

• 33% of shoppers abandon carts when prices aren't in their local currency
• 92% prefer to shop on sites that price in their currency
• Conversion rates increase 20-40% when local currency is shown

You're not just being helpful. You're removing a barrier that costs you money.

The Basic Implementation

Here's the simplest version: detect the visitor's location, convert your prices, display in their currency.

async function getVisitorCurrency(ip) {
  const res = await fetch(
    `https://api.apiverve.com/v1/iplookup?ip=${ip}`,
    { headers: { 'x-api-key': process.env.APIVERVE_KEY } }
  );
  const { data } = await res.json();

  // Map country to currency (simplified - you'd want a full mapping)
  const currencyMap = {
    'United States': 'USD',
    'United Kingdom': 'GBP',
    'Germany': 'EUR',
    'France': 'EUR',
    'Japan': 'JPY',
    'Canada': 'CAD',
    'Australia': 'AUD'
    // ... etc
  };

  return currencyMap[data.country] || 'USD';
}

async function convertPrice(amount, fromCurrency, toCurrency) {
  if (fromCurrency === toCurrency) return amount;

  const res = await fetch(
    `https://api.apiverve.com/v1/currencyconverter?value=${amount}&from=${fromCurrency}&to=${toCurrency}`,
    { headers: { 'x-api-key': process.env.APIVERVE_KEY } }
  );
  const { data } = await res.json();

  return data.convertedValue;
}

// Usage
const visitorCurrency = await getVisitorCurrency(req.ip);
const localPrice = await convertPrice(249.99, 'USD', visitorCurrency);

console.log(`$249.99 = ${formatCurrency(localPrice, visitorCurrency)}`);
// $249.99 = €228.42 (for EUR visitor)

Don't Convert Every Request

The code above works, but calling the API on every page load is wasteful. Exchange rates don't change every second. Cache them.

const rateCache = new Map();

async function getExchangeRate(from, to) {
  const key = `${from}:${to}`;
  const cached = rateCache.get(key);

  // Rates cached for 1 hour
  if (cached && Date.now() - cached.timestamp < 3600000) {
    return cached.rate;
  }

  const res = await fetch(
    `https://api.apiverve.com/v1/exchangerate?currency1=${from}&currency2=${to}`,
    { headers: { 'x-api-key': process.env.APIVERVE_KEY } }
  );
  const { data } = await res.json();

  rateCache.set(key, {
    rate: data.rate,
    timestamp: Date.now()
  });

  return data.rate;
}

function convertPrice(amount, rate) {
  return amount * rate;
}

// Fetch rate once, use for all products
const rate = await getExchangeRate('USD', 'EUR');
const prices = products.map(p => ({
  ...p,
  localPrice: convertPrice(p.price, rate)
}));

Now you're making one API call per currency pair per hour, instead of thousands.

The Currency Switcher

Automatic detection is great, but some customers prefer manual control. Maybe they're traveling. Maybe they're buying a gift for someone abroad. Give them a dropdown.

// React component
function CurrencySwitcher({ currentCurrency, onCurrencyChange }) {
  const currencies = [
    { code: 'USD', symbol: '$', name: 'US Dollar' },
    { code: 'EUR', symbol: '€', name: 'Euro' },
    { code: 'GBP', symbol: '£', name: 'British Pound' },
    { code: 'CAD', symbol: 'CA$', name: 'Canadian Dollar' },
    { code: 'AUD', symbol: 'A$', name: 'Australian Dollar' },
    { code: 'JPY', symbol: '¥', name: 'Japanese Yen' }
  ];

  return (
    <select
      value={currentCurrency}
      onChange={e => onCurrencyChange(e.target.value)}
    >
      {currencies.map(c => (
        <option key={c.code} value={c.code}>
          {c.symbol} {c.code} - {c.name}
        </option>
      ))}
    </select>
  );
}

Store the selection in a cookie or localStorage so it persists across visits:

function setCurrencyPreference(currency) {
  localStorage.setItem('preferredCurrency', currency);
  document.cookie = `currency=${currency}; path=/; max-age=31536000`; // 1 year
}

function getCurrencyPreference() {
  return localStorage.getItem('preferredCurrency') ||
         document.cookie.match(/currency=([A-Z]{3})/)?.[1] ||
         null;
}

The logic becomes: Use stored preference → fall back to auto-detect → default to USD.

Pricing Psychology: Round Numbers vs Precision

Here's where it gets interesting. When you convert $249.99 USD to EUR, you might get €228.47. That looks... weird. It screams "this was converted from another currency."

You have two options:

Option 1: Show exact conversion (transparent)

formatCurrency(228.47, 'EUR'); // €228.47

Pros: Honest, matches what they'll actually pay, no surprises at checkout.

Option 2: Round to psychological price points

function roundToPsychPrice(price) {
  if (price < 10) return Math.ceil(price) - 0.01;      // €8.99
  if (price < 100) return Math.ceil(price / 5) * 5 - 0.01;  // €44.99
  return Math.ceil(price / 10) * 10 - 0.01;            // €229.99
}

roundToPsychPrice(228.47); // €229.99

Pros: Looks more "native," feels like local pricing, standard retail practice.

The second option means you might charge slightly more (or less) than the exact conversion. Most retailers do this—they set different prices for different markets rather than converting dynamically.

My recommendation: Be transparent. Show the exact conversion, note that it's converted from USD, and make it clear the charge will be in your base currency. Customers appreciate honesty.

The Checkout Problem

Here's a trap: you show EUR prices, but you charge in USD because that's what your payment processor is set up for.

Customer sees: €228.47
Customer gets charged: $249.99 (converted by their bank to ~€231.20)

They feel cheated. They might dispute the charge. At minimum, they won't buy from you again.

Solutions:

1. Show both currencies at checkout

   Total: €228.47
   (approximately $249.99 USD - you will be charged in USD)

1. Use a payment processor that supports multi-currency
   Stripe, PayPal, and others let you charge in the customer's currency. You receive your preferred currency; they handle the conversion.

2. Set fixed prices in each currency
   Instead of converting dynamically, set specific prices for each market:

   • US: $249.99
   • EU: €229.99
   • UK: £199.99

Update periodically when exchange rates shift significantly.

Option 3 is what big retailers do. It's more work but gives you control over pricing in each market.

Complete Implementation

Here's a full multi-currency service:

class CurrencyService {
  constructor(baseCurrency = 'USD') {
    this.baseCurrency = baseCurrency;
    this.rates = new Map();
    this.lastUpdate = 0;
  }

  async refreshRates() {
    // Fetch rates for common currencies
    const currencies = ['EUR', 'GBP', 'CAD', 'AUD', 'JPY', 'CHF', 'CNY', 'INR'];

    await Promise.all(currencies.map(async (currency) => {
      try {
        const res = await fetch(
          `https://api.apiverve.com/v1/exchangerate?currency1=${this.baseCurrency}&currency2=${currency}`,
          { headers: { 'x-api-key': process.env.APIVERVE_KEY } }
        );
        const { data } = await res.json();
        this.rates.set(currency, data.rate);
      } catch (err) {
        console.error(`Failed to fetch ${currency} rate:`, err);
      }
    }));

    this.rates.set(this.baseCurrency, 1); // Base currency rate is 1
    this.lastUpdate = Date.now();
  }

  async getRate(targetCurrency) {
    // Refresh if rates are older than 1 hour
    if (Date.now() - this.lastUpdate > 3600000) {
      await this.refreshRates();
    }

    return this.rates.get(targetCurrency) || 1;
  }

  async convertPrice(amount, targetCurrency) {
    const rate = await this.getRate(targetCurrency);
    return amount * rate;
  }

  async convertPrices(products, targetCurrency) {
    const rate = await this.getRate(targetCurrency);

    return products.map(product => ({
      ...product,
      displayPrice: product.price * rate,
      displayCurrency: targetCurrency,
      originalPrice: product.price,
      originalCurrency: this.baseCurrency
    }));
  }
}

// Initialize once
const currencyService = new CurrencyService('USD');

// Pre-fetch rates on server start
currencyService.refreshRates();

// Schedule hourly refresh
setInterval(() => currencyService.refreshRates(), 3600000);

// Use in route
app.get('/products', async (req, res) => {
  const currency = req.cookies.currency ||
                   await detectCurrencyFromIP(req.ip) ||
                   'USD';

  const products = await getProducts();
  const localizedProducts = await currencyService.convertPrices(products, currency);

  res.json({
    products: localizedProducts,
    currency,
    exchangeRate: await currencyService.getRate(currency),
    rateUpdated: new Date(currencyService.lastUpdate).toISOString()
  });
});

Formatting Currencies Correctly

Different currencies have different conventions:

function formatCurrency(amount, currencyCode) {
  return new Intl.NumberFormat(getCurrencyLocale(currencyCode), {
    style: 'currency',
    currency: currencyCode,
    minimumFractionDigits: currencyCode === 'JPY' ? 0 : 2,
    maximumFractionDigits: currencyCode === 'JPY' ? 0 : 2
  }).format(amount);
}

function getCurrencyLocale(currencyCode) {
  const locales = {
    'USD': 'en-US',
    'EUR': 'de-DE',
    'GBP': 'en-GB',
    'JPY': 'ja-JP',
    'CAD': 'en-CA',
    'AUD': 'en-AU',
    'CHF': 'de-CH',
    'CNY': 'zh-CN'
  };
  return locales[currencyCode] || 'en-US';
}

// Results:
formatCurrency(1234.56, 'USD');  // $1,234.56
formatCurrency(1234.56, 'EUR');  // 1.234,56 €
formatCurrency(1234.56, 'GBP');  // £1,234.56
formatCurrency(1234.56, 'JPY');  // ¥1,235 (no decimals)

Note: EUR uses comma for decimals and period for thousands (in Germany). Japanese Yen doesn't use decimals. Get this wrong and you look like an amateur.

Common Mistakes

Showing converted prices but charging in base currency without warning. This is the fastest way to get chargebacks and angry customers. Always be clear about what currency they'll actually be charged in.

Not handling currency in the cart. If someone adds an item at €228 and the rate changes before checkout, what happens? Pick a strategy: lock the rate at add-to-cart, or clearly show that prices may fluctuate.

Forgetting about taxes. VAT in Europe, GST in Australia, sales tax in US states. Currency conversion is only part of international pricing.

Updating rates too frequently. Hourly is fine. Daily is fine. Every request is wasteful and can cause prices to flicker confusingly.

Not rounding sensibly. €228.47192 is not a price. Neither is €228.471923847. Round to two decimals (or zero for JPY).

Multi-currency support isn't just a nice-to-have for international stores. It's table stakes. Every competitor who shows local prices is stealing your customers.

The good news: it's not that hard. Detect location, fetch exchange rates, cache them, display converted prices. A weekend project that pays for itself in the first month.

The Currency Converter and Exchange Rate APIs handle the conversion. The IP Lookup API tells you where your visitors are. Combine them and you've got localized pricing.

Get your API key and stop losing international sales.

Originally published at APIVerve Blog

2026-01-24 15:22:34

If you are reading this, you are likely part of the massive wave of system administrators exiting the VMware ecosystem following the recent Broadcom pricing changes. You are looking for a stable, cost-effective alternative, and Proxmox VE is the answer.

In this guide, we will walk you through the exact process of migrating a production Virtual Machine (VM) from ESXi to Proxmox VE. Whether you are moving a single server or an entire datacenter, this tutorial covers the most reliable methods for 2026: the native Import Wizard and the manual CLI method.

Prerequisites: What You Need Before You Start

Before we touch the terminal, ensure you have the following ready. A failed migration is usually due to skipping these checks.

• Source Host: Access to your VMware ESXi host (v6.5, 7.0, or 8.0) with root credentials.
• Destination Server: A server with Proxmox VE 8.x (or newer) installed.
• Connectivity: Both servers must be able to communicate over the network. Ideally, they should be on the same LAN or connected via a fast private network/VPN to speed up data transfer.
• Backup: Critical. Never migrate a live VM without a fresh backup. Use Veeam, Active Backup, or a manual OVF export before proceeding.

Hardware Tip: Migration involves heavy disk I/O. For production workloads, we strongly recommend using Enterprise NVMe storage.

Step 1: Preparing the Proxmox Environment

First, let’s make sure your destination server is ready to accept the new data.

1. Update Your System

Log in to your Proxmox server (via SSH or Console) and run:

apt update && apt dist-upgrade -y

2. Check Storage Configuration

For the best reliability with imported VMs, we recommend using ZFS.

Why ZFS? It provides protection against bit rot (data corruption) during transfer and allows for instant snapshots.

Note: If you are setting up a new server at Bytesrack, our default deployment includes ZFS optimization for virtualization workloads.

Step 2: The Migration Process

In 2026, Proxmox introduced significant improvements to the migration workflow. You have two options: The Easy Way (Import Wizard) or The Manual Way (CLI).

Option A: The Proxmox Import Wizard (Recommended)

Best for: Moving standard VMs quickly without leaving the GUI.

1. Add ESXi as Storage:

   • Navigate to Datacenter > Storage > Add > ESXi.
   • ID: Enter a name (e.g., esxi-source).
   • Server: Enter the IP address of your ESXi host.
   • Username/Password: Enter your ESXi root credentials.
   • Certificate: Check "Skip Certificate Verification" if you are using self-signed certs (common in internal networks).

2. Select the VM:

   • Once added, click on the new esxi-source storage icon in the left sidebar.
   • Wait a moment for Proxmox to fetch the VM list from VMware.

3. Start the Import:

   • Right-click the target VM and select Import.
   • Target Storage: Choose your local ZFS or LVM store.
   • Format: Select QCOW2 (recommended for snapshot support) or Raw (best performance on ZFS).
   • Click Import.

Pro Tip: There is a "Live Import" checkbox. While tempting, we recommend leaving it unchecked for production data. It is safer to let the data fully sync before booting the VM to avoid disk consistency issues.

Option B: Manual CLI Migration (The "Power User" Method)

Best for: .vmdk / .ova files, offline backups, or if the Wizard fails.

If you have a disk file exported from VMware, use the qm importdisk command. This is the "universal adapter" of Proxmox migrations.

1. Upload the Disk
Transfer your .vmdk file to the Proxmox server using SCP or WinSCP. Let's assume the file is at /root/server-disk.vmdk.

2. Create a "Shell" VM
In the Proxmox GUI, create a new VM.

• Match the CPU and RAM settings of the old VM.
• Important: Do not create a hard disk (delete the default disk if created).
• Note the new VM ID (e.g., 105).

3. Run the Import Command
Open the Proxmox Shell and run:

# Syntax: qm importdisk [VM-ID] [Path-to-Source] [Target-Storage]
qm importdisk 105 /root/server-disk.vmdk local-zfs --format qcow2

4. Attach the Disk

• Go to VM 105 > Hardware.
• You will see an "Unused Disk." Double-click it and click Add.
• Go to Options > Boot Order, enable the new disk, and move it to the top.

Step 3: Network & Driver Configuration (Crucial)

The migration is done, but the VM might not boot or connect to the internet yet. This is because VMware uses different hardware drivers than Proxmox (KVM).

Fix 1: Change the Network Interface

VMware uses vmxnet3 or e1000. Proxmox works best with VirtIO.

1. Go to Hardware > Network Device.
2. Edit and change the Model to VirtIO (paravirtualized).

Note: For Windows VMs, if you don't have VirtIO drivers installed yet, keep this as Intel E1000 temporarily until you install them.

Fix 2: Windows "Inaccessible Boot Device" (BSOD)

If a Windows VM Blue Screens on boot, it’s because it lacks the VirtIO storage drivers.

1. Change the Hard Disk Bus back to IDE or SATA.
2. Boot the VM.
3. Mount the virtio-win.iso (Download from Proxmox site) to the CD-ROM.
4. Install the VirtIO drivers inside Windows.
5. Shut down, change the Disk Bus to SCSI (VirtIO SCSI), and boot again.

Step 4: Post-Migration Cleanup

Once the VM is running:

1. Install QEMU Guest Agent: This allows Proxmox to see the VM's IP address and shut it down gracefully.
   • Linux: apt install qemu-guest-agent
   • Windows: Install via the VirtIO ISO.
2. Remove VMware Tools: Uninstall the old VMware tools to prevent driver conflicts.
3. Update Network Config: In Linux, your interface name may have changed from ens192 to ens18. Update your Netplan or /etc/network/interfaces file accordingly.

Conclusion

Migrating from ESXi to Proxmox is no longer the complex task it used to be. With tools like the Import Wizard and robust hardware support, you can move away from licensing fees and gain the flexibility of open-source infrastructure.

Need High-Performance Infrastructure for your Cluster?

While Proxmox runs on almost anything, production workloads demand enterprise stability.

At Bytesrack, we specialize in Virtualization-Ready Dedicated Servers.

• Zero Licensing Fees: We love Open Source.
• High I/O: All servers come with Enterprise NVMe storage to ensure your VMs run faster than they did on ESXi.
• Custom Builds: We configure the hardware specifically for Proxmox requirements.

👉 View Bytesrack Dedicated Servers

Don't want to handle the migration yourself?
Our team performs hundreds of migrations annually. Order a Managed Dedicated Server, and let the Bytesrack engineering team handle the transfer for you—zero headaches, zero downtime risks.

Contact Bytesrack Support

2026-01-24 15:22:16

Microsoft Excel is one of the most widely used tools for basic data analysis. It is easy to learn for a beginner, requires no programming skills and is powerful enough to analyze, report and visualize everyday business data. In this article, we’ll explore how beginners can use Excel for data analytics step by step.

Microsoft Excel is a spreadsheet application that allows you to:

• Store data
• Organize information
• Perform calculations
• Analyze trends
• Create visual reports

Excel data is arranged in Columns (vertical), Rows (horizontal) and
Cells (where a row and column meet).

Organizing data for analysis

It is important to note that for Excel to work well as an analytics tool, data must be structured properly.

• Each column should have one clear header
• Each row should represent one record
• Avoid blank rows or columns inside your data

Example dataset:

Basic data cleaning in excel

Clean data leads to better analysis.

Common data-cleaning tasks:

• Removing duplicates
• Fixing data types (dates as Dates, numeric fields as numbers)
• Handling missing values

Sorting and filtering data

Sorting and filtering help you focus on specific information or data.
Examples:

• Sort salary from highest to lowest - highlight all data (Ctrl + A) and click data then sort

Basic calculations using formulas

Excel allows you to perform calculations using formulas and a formula always starts with an equals sign (=).

Common beginner formulas:

=SUM(E2:E10)      // Total salary
=AVERAGE(E2:E10)  // Average salary
=COUNT(E2:E10)    // Number of values
=MAX(E2:E10)      // Highest salary amount
=MIN(E2:E10)      // Lowest salary amount

Visualizing data with charts

Charts help turn numbers into visual insights.

Common chart types:

• Column charts - compare values
• Line charts - show trends over time
• Pie charts - show proportions

How to create a chart:

• Select your data
• Click Insert then click Chart
• Choose a chart type

For example, I will visualize salary by employee using a column chart

Using pivot tables for data analysis

PivotTables are one of Excel’s most powerful features for analytics. They allow you to summarize large datasets without writing formulas.

Pivot tables can answer questions like:

• Total salary by department
• Salary by employee
• Average salary by department

How to create a pivot table:

• Select inside your data
• Click Insert → pivot table
• Drag fields into rows and values

Why Excel is great for beginner data analysts

Excel is ideal for beginners because:

• No coding required
• Easy to learn
• Widely used in organizations
• Strong analytical features for small and medium datasets

Many data professionals start with Excel before moving to tools like SQL, Power BI or Python.

In conclusion, Microsoft Excel is a powerful entry point into data analytics. By learning how to organize data, apply formulas, create charts and use PivotTables, beginners like me can gain valuable analytical skills and make data-driven decisions using Excel.

Feel free to comment & happy analyzing!!

2026-01-24 15:16:34

When I started building backend services in Spring Boot, I thought REST APIs were only about creating endpoints.

But in real-world projects, you often need the opposite too:

✅ Your service must call other services
✅ Your backend must consume external APIs
✅ Your application must handle HTTP responses + errors properly

That’s where I discovered RestClient — and honestly, it feels way cleaner.

🧠 What is RestClient in Spring Boot?

RestClient is a synchronous HTTP client with a modern, fluent API.

It provides a clean abstraction over HTTP libraries and helps you:

✅ Convert Java objects into HTTP requests
✅ Convert HTTP responses back into Java objects
✅ Write readable and maintainable API-call code

In simple terms:

RestClient makes calling APIs from Spring Boot easier and cleaner.

🏗️ Building a RestClient

You typically create a RestClient using a builder.

Example:

RestClient restClient = RestClient.builder()
    .baseUrl(BASE_URL)
    .defaultHeader(HttpHeaders.AUTHORIZATION,
        encodeBasic(properties.getUsername(), properties.getPassword())
    )
    .build();

What I like here:

• baseUrl keeps calls consistent
• defaultHeader avoids repeating auth in every request
• The builder feels very readable

✅ Using RestClient (GET Example)

Once built, using it feels super fluent:

CustomerResponse customer = restClient.get()
    .uri("/{id}", 3)
    .accept(MediaType.APPLICATION_JSON)
    .retrieve()
    .body(CustomerResponse.class);

What’s happening here:

• .get() sends a GET request
• .uri("/{id}", 3) builds dynamic URLs
• .retrieve() executes the request
• .body(CustomerResponse.class) maps response into your Java class

This is exactly how a clean backend should consume APIs.

🔁 RestClient Supports More Than Just GET

Apart from get(), RestClient supports:

✅ post()
✅ put()
✅ patch()
✅ delete()

So it fits perfectly for full CRUD interactions with external services.

🚨 Handling Errors in RestClient

Calling external APIs isn’t always smooth.

Sometimes the response is:

• 4xx (client errors)
• 5xx (server errors)

RestClient allows handling these cleanly using onStatus().

Example (DELETE + error handling):

ResponseEntity response = restClient.delete()
    // ...
    .onStatus(HttpStatusCode::is4xxClientError,
        (req, res) ->
            logger.error("Couldn't delete " + res.getStatusText())
    )
    .toBodilessEntity();

This makes error handling:
✅ explicit
✅ readable
✅ maintainable

And most importantly:

It prevents silent failures.

🧠 Why This Matters in Real Projects

Most real backend projects are not standalone.

They talk to:

• payment services
• authentication servers
• notification APIs
• microservices
• third-party providers

A clean HTTP client is essential, and RestClient fits perfectly into modern Spring Boot development.

🚀 Final Thoughts

RestClient is one of those tools that feels small…

…but improves your backend workflow massively.

If you’re building Spring Boot applications that consume APIs:
✅ try RestClient
✅ set a baseUrl
✅ handle errors properly
✅ keep responses typed

This post is part of my learning-in-public journey while exploring Spring Boot and real-world backend development.

Do you use RestTemplate, WebClient, or RestClient in your Spring Boot projects?

2026-01-24 15:16:16

In JavaScript, you can design a sum() function that accepts any number of arguments using the rest parameter.

Here are three different patterns to compute the total:-

1. Using a for Loop (Traditional Method)

function sum(...args) {
  let arr = [...args];
  if (arr.length <= 0) return 0;

  let sum = 0;

  for (let i = 0; i < arr.length; i++) {
    sum += arr[i];
  }

  console.log(sum);
}

sum(3, -4, 5);

1. Using map() Method (Less Common but Works)

function sum(...args) {
  let arr = [...args];
  if (arr.length <= 0) return 0;

  let sum = 0;

  arr.map((val) => (sum += val));

  console.log(sum);
}

sum(3, -4, 5);

1. Using reduce() (Best & Cleanest)

function sum(...args) {
  let arr = [...args];
  if (arr.length <= 0) return 0;

  const total = arr.reduce((acc, curr) => acc + curr, 0);

  console.log(total);
}

sum(3, -4, 5);

Final Thoughts

• for loop → good for beginners
• map() → not ideal for summing
• reduce() → clean, functional, professional approach