DEV Community: Amelia

How to Analyze Your Competitor's Content Strategy Using Python

Amelia — Sat, 27 Jun 2026 08:39:50 +0000

When you're trying to figure out why a competitor keeps ranking above you, the first instinct is to manually dig through their blog posts, check their backlinks, and guess their keyword targets. But that approach is slow, subjective, and often incomplete.

Most developers know that content strategy is a major ranking factor, but reverse-engineering it at scale is tough. Competitors might publish dozens of articles a month, each targeting different keywords with varying structures and internal linking patterns.

This is where automated analysis becomes a game-changer. Instead of manually tracking every post, you can use a tool that scans a competitor's domain, identifies their content feed, and extracts the underlying SEO strategy.

Here's a simple Python script to get a basic content inventory from a competitor's sitemap:

python
import requests
import xml.etree.ElementTree as ET
from urllib.parse import urlparse

def get_competitor_urls(sitemap_url):
try:
response = requests.get(sitemap_url, timeout=10)
root = ET.fromstring(response.content)
namespace = {'ns': 'http://www.sitemaps.org/schemas/sitemap/0.9'}
urls = [loc.text for loc in root.findall('.//ns:loc', namespace)]
return urls[:20] # Limit for demo
except Exception as e:
print(f"Error fetching sitemap: {e}")
return []

Example usage

competitor_sitemap = "https://example-competitor.com/sitemap.xml"
urls = get_competitor_urls(competitor_sitemap)
for url in urls:
print(url)

This gives you a list of their published pages. But to truly understand their strategy—like which keywords they target, how often they publish, and what content formats they use—you need deeper analysis.

Tools like the SERPSpur Competitor Content Radar automate this entire process. You enter a competitor's domain, and the AI analyst finds their content feed, identifies topic clusters, and reverse-engineers their SEO approach. It surfaces patterns in keyword targeting, content length, and publishing frequency.

Why does this matter for your SEO? Knowing what works for your competitors lets you replicate successful strategies, find content gaps they missed, and avoid wasting time on low-opportunity topics. It turns competitor research from a guessing game into a data-driven process.

Whether you're building an SEO tool or just doing routine competitive analysis, having automated content radar can save hours and reveal insights you'd never spot manually.

The Easiest Way to Find Hidden Sitemaps for SEO Audits

Amelia — Sat, 27 Jun 2026 01:24:18 +0000

Ever spent hours hunting for a website's sitemap.xml only to hit a 404? I’ve been there. It’s frustrating when you’re doing SEO audits or competitor analysis and can’t find the exact URL structure.

Here’s a quick, developer-friendly way to programmatically detect sitemaps—and a free tool that saves you even more time.

First, the manual method. Most sitemaps live at predictable paths. In Python, you can try:

import requests

def find_sitemap(domain):
    common_paths = [
        "/sitemap.xml",
        "/sitemap_index.xml",
        "/sitemap/",
        "/robots.txt"
    ]
    for path in common_paths:
        url = f"https://{domain}{path}"
        try:
            resp = requests.get(url, timeout=5)
            if resp.status_code == 200 and 'xml' in resp.headers.get('Content-Type', ''):
                return url
        except requests.exceptions.RequestException:
            continue
    return None

print(find_sitemap("example.com"))

But what if the site uses dynamic sitemaps or multiple ones? Checking robots.txt is better:

def parse_robots_sitemap(domain):
    url = f"https://{domain}/robots.txt"
    resp = requests.get(url, timeout=5)
    if resp.status_code == 200:
        for line in resp.text.splitlines():
            if line.lower().startswith("sitemap:"):
                return line.split(":", 1)[1].strip()
    return None

This works for most cases, but sometimes you need a broader scan—especially when analyzing hundreds of domains for a client or personal project. That’s when I turn to a dedicated tool.

I’ve been using the SERPSpur Free Sitemap Finder Tool (https://serpspur.com/tool/free-sitemap-finder-tool/) for quick checks. It does exactly what my Python script does, but without the setup. You drop in a URL, it scans common paths and robots.txt, and returns all detected sitemaps in seconds. It’s handy for spot-checking during audits or when you’re on a machine without Python.

The real power comes from combining both approaches. Use the tool for instant checks, then automate bulk analysis with the code above. For example, I run a cron job weekly that uses the Python script to check my client sites and logs any missing sitemaps. Then I use the tool to manually verify edge cases.

Pro tip: Always check for gzip-compressed sitemaps too. Some servers return them with Content-Encoding: gzip. Your requests library handles that automatically, but the tool might not display the raw XML—just the URL.

Whether you’re a dev automating SEO tasks or a marketer doing manual analysis, finding sitemaps shouldn’t be a treasure hunt. Have a reliable method, and keep that tool bookmarked for when you need a quick answer.

How to Export Backlinks from Multiple Domains in Minutes

Amelia — Wed, 24 Jun 2026 04:52:00 +0000

Ever tried manually exporting backlinks from 50 different domains for a client audit? I did that once. Took me three hours, and I still missed a column. Not my proudest moment.

If you're doing any serious SEO work, you know that backlink data is messy. You pull it from Ahrefs, SEMrush, or Majestic, but getting it into a clean, sortable spreadsheet for every domain in your portfolio is a pain. That's where a bulk backlink exporter becomes your best friend.

Let me walk you through a simple Python script that can automate this. We'll use pandas for data manipulation and requests to interact with APIs. First, install the dependencies:

pip install pandas requests

Now, here's a basic structure. I'm assuming you have a CSV with a column "domain" and an API key for a backlink provider. The idea is to loop through each domain, fetch the backlinks, and append them to a master DataFrame.

import pandas as pd
import requests
import time

def fetch_backlinks(domain, api_key):
    # Placeholder for your actual API call
    url = f"https://api.backlinkprovider.com/v1/backlinks?domain={domain}&apikey={api_key}"
    response = requests.get(url)
    if response.status_code == 200:
        return response.json()['data']  # Adjust based on actual response
    else:
        print(f"Error for {domain}: {response.status_code}")
        return []

# Load domains
domains_df = pd.read_csv('domains.csv')
all_backlinks = []

for domain in domains_df['domain']:
    data = fetch_backlinks(domain, 'YOUR_API_KEY')
    for link in data:
        link['source_domain'] = domain  # Tag which domain it came from
        all_backlinks.append(link)
    time.sleep(1)  # Be polite to the API

# Export to CSV
final_df = pd.DataFrame(all_backlinks)
final_df.to_csv('bulk_backlinks_export.csv', index=False)
print(f"Exported {len(all_backlinks)} backlinks from {len(domains_df)} domains.")

This script is minimal but functional. You'll need to adapt the API endpoint and response parsing to whatever tool you're using. The key is the loop and the aggregation.

For a more robust solution, you might want to add error handling, rate limiting, and maybe even a progress bar. But this gets you started.

Now, if you're not a coder or just want something ready-to-go, there are tools out there. I recently tried the Bulk Backlink Exporter from SERP Spur. It does exactly this without writing a line of code. You upload a list of domains, hit export, and it gives you a clean CSV with all backlinks, anchor text, and domain authority. Handy for quick audits.

But knowing the logic behind it? That's what makes you a better SEO. Automate the tedious parts, focus on the analysis. Your clients (and your sanity) will thank you.

Manual Schema Markup Is Holding Back Your SEO: Here's a Better Approach

Amelia — Mon, 22 Jun 2026 09:25:19 +0000

Implementing structured data manually can be one of the most frustrating parts of technical SEO. While schema markup helps search engines better understand website content and can improve visibility in search results, maintaining it by hand often creates more problems than it solves.

The Challenges of Manual Schema Management

Many website owners and SEO professionals still rely on manually adding schema markup to their pages. This process usually involves copying code snippets, editing values, and updating markup whenever content changes. Over time, this becomes difficult to manage, especially on large websites with hundreds or thousands of pages.

Even small mistakes can lead to validation errors, missing properties, or outdated information being presented to search engines. The repetitive copy-and-paste workflow also increases the risk of human error.

How Headless CMS Platforms Simplify Structured Data

A growing number of teams are moving to headless CMS solutions that include built-in structured data fields. Instead of manually editing schema code, content creators can simply fill out predefined fields while the system automatically generates the correct markup.

This approach offers several advantages:

Consistent schema implementation across pages
Reduced risk of formatting errors
Faster content publishing workflows
Easier maintenance and updates
Better collaboration between SEO and development teams

By centralizing structured data management, organizations can ensure schema remains accurate and scalable as their websites grow.

The Importance of Automated Schema Testing

While automation helps reduce errors, validation should still be part of the development process. Many modern teams are now incorporating schema testing directly into their CI/CD pipelines.

Automated tests can verify:

Schema syntax and validity
Required property presence
Structured data consistency
Rich result eligibility
Compliance with schema standards

By catching issues before deployment, automated testing prevents broken markup from reaching production environments and affecting search performance.

The Future of Structured Data Workflows

As websites become more complex, relying solely on manual schema implementation is becoming increasingly inefficient. Combining a headless CMS with automated validation and CI/CD testing creates a more reliable and scalable approach to structured data management.
https://serpspur.com/

The Hidden Risk Most Domain Investors Ignore

Amelia — Fri, 19 Jun 2026 06:50:30 +0000

When flipping domains on Flippa, I always run a bot traffic check first. Here's a simple Python script to automate that with the SerpSpur Bot Traffic Detector:

python
import requests

def check_bot_traffic(domain):
url = f"https://serpspur.com/tool/bot-traffic-detector/?domain={domain}"
response = requests.get(url)
if response.status_code == 200:
data = response.json()
if data['bot_percentage'] > 50:
print(f"🚫 {domain} has {data['bot_percentage']}% bot traffic.")
else:
print(f"✅ {domain} looks authentic.")
else:
print("API error")

check_bot_traffic('example.com')

This tool saved me from buying a domain with 90% fake traffic. Always verify audience authenticity before any investment.

Why Quality Ironmongery Matters in Home Renovation Projects

Amelia — Mon, 15 Jun 2026 09:24:37 +0000

When renovating an older property, every detail matters. From flooring and paint colors to furniture and lighting, homeowners spend countless hours perfecting the look of their space. However, one area that is often overlooked is ironmongery and hardware.

During the renovation of a Victorian terrace, I quickly discovered that not all door hardware is created equal. While it may be tempting to choose cheaper handles, hinges, and fittings to save money, these small details can have a significant impact on both the appearance and functionality of a home.

The Difference Quality Hardware Makes

Door handles, cabinet knobs, hinges, and bolts are used every day. Poor-quality products can become loose, tarnished, or fail over time, creating frustration and diminishing the overall feel of a room.

In contrast, well-crafted ironmongery offers durability, reliability, and a premium appearance that enhances the character of a property. This is especially important in period homes where authentic details help preserve the building's original charm.

Combining Style and Function

The best hardware doesn't just perform well—it also complements your interior design.

Black metal finishes, for example, have become increasingly popular because they provide a timeless look that works beautifully in both traditional and modern spaces. Whether installed on doors, cabinets, or gates, quality black ironmongery adds sophistication and visual impact without overwhelming a room.

Essential Hardware for Renovation Projects

When updating a property, several hardware elements deserve special attention:

Gate Latches

A sturdy gate latch provides security while contributing to the property's exterior character. Well-designed latches combine practicality with traditional styling.

Iron Bolts

Iron bolts are ideal for adding extra security and authenticity, particularly in period properties where classic details are highly valued.

Cabinet Knobs

Cabinet hardware may seem like a small detail, but it can dramatically transform kitchens, bathrooms, and storage areas. Quality knobs create a refined finish and improve everyday usability.

Hinges and Door Furniture

Strong hinges and matching door furniture ensure smooth operation while maintaining a cohesive design throughout the home.

A Long-Term Investment

One of the biggest lessons learned during renovation was that quality hardware is an investment rather than an expense. Durable materials last longer, require less maintenance, and continue looking attractive for years.

Instead of replacing worn-out fittings every few years, choosing premium ironmongery from the start can save both time and money in the long run.

Final Thoughts

Successful renovations are built on attention to detail. While large design elements often receive the most attention, it's the smaller finishing touches that truly bring a space together.
https://infinitydecor.co.uk/collections/ironmongery

Elevate Your Interiors with the Right Door Hardware

Amelia — Mon, 15 Jun 2026 05:33:40 +0000

Looking for the perfect finishing touch for your doors? At Infinity Decor, we've curated a stunning collection that balances style and function. From sleek black finishes that add modern edge to vintage designs that whisper character, every handle is a detail worth considering. The Art Deco styles are particularly striking—they bring a geometric elegance that stands out without being loud. Mortice knobs and lever on rose options offer flexibility for any room, whether you're renovating a period property or updating a contemporary home. The right handle changes how you experience a space; it's a small change with a big impact. Explore the range and find your fit: https://infinitydecor.co.uk #DoorHandles #InteriorDesign #HomeRenovation

SERPSpur Invoice to CSV Converter: A Simple Solution for Bulk Invoice Processing

Amelia — Thu, 11 Jun 2026 01:59:13 +0000

Another approach for invoice conversion—I've been using the SERPSpur Invoice to CSV Converter to batch process HTML invoices from my e-commerce platform. Here's a script that handles multiple formats at once:

python
import requests
import csv

API_KEY = "your_api_key_here"

def batch_convert(directory):
import os
for filename in os.listdir(directory):
if filename.endswith((".pdf", ".xls", ".xlsx", ".html")):
filepath = os.path.join(directory, filename)
with open(filepath, 'rb') as f:
response = requests.post(
"https://api.serpspur.com/v1/invoice-to-csv",
headers={"Authorization": f"Bearer {API_KEY}"},
files={"file": f},
params={"output_format": "csv"}
)
if response.status_code == 200:
output_name = filename.rsplit('.', 1)[0] + ".csv"
with open(output_name, 'w') as out:
out.write(response.text)
print(f"Converted {filename} -> {output_name}")

Example usage

batch_convert("/path/to/invoices")

This tool handles HTML invoices surprisingly well, which is rare. What formats do you typically need to convert? https://serpspur.com

How I Debugged Local SEO Rankings Using Puppeteer Location Spoofing

Amelia — Tue, 02 Jun 2026 08:45:12 +0000

I was trying to debug why my client's bakery in Berlin wasn't showing up in local search results for their own city. Turns out, Google was serving me results based on my IP in Munich. Classic.

So I built a quick script using Puppeteer to spoof my location and see what locals actually see. Here's the core idea:

javascript
const puppeteer = require('puppeteer');

async function spoofLocation(url, lat, lng) {
const browser = await puppeteer.launch({ headless: true });
const page = await browser.newPage();
await page.goto(url);
await page.evaluate((coords) => {
navigator.geolocation.getCurrentPosition = (success) => success({ coords });
}, { latitude: lat, longitude: lng });
// Now search and capture results
const results = await page.evaluate(() => {
return Array.from(document.querySelectorAll('.g')).map(el => el.innerText);
});
console.log(results);
await browser.close();
}

spoofLocation('https://www.google.com', 52.5200, 13.4050); // Berlin

This works for quick checks, but for more robust testing across multiple locations and languages, I've been using a tool that handles this natively without browser automation headaches. It's saved me hours when auditing international SEO setups.

https://serpspur.com

A Tiny Node.js Trick for Instant API Endpoints

Amelia — Sat, 30 May 2026 07:45:30 +0000

Ever needed to quickly prototype an API endpoint but didn't want to set up a full Express server? I've been using a tiny Node.js script with the built-in http module for quick testing. Here's a minimal example that handles GET and POST:

javascript
const http = require('http');

const server = http.createServer((req, res) => {
const { method, url } = req;

if (method === 'GET' && url === '/api/hello') {
res.writeHead(200, { 'Content-Type': 'application/json' });
res.end(JSON.stringify({ message: 'Hello World' }));
} else if (method === 'POST' && url === '/api/data') {
let body = '';
req.on('data', chunk => body += chunk);
req.on('end', () => {
const data = JSON.parse(body);
res.writeHead(200, { 'Content-Type': 'application/json' });
res.end(JSON.stringify({ received: data }));
});
} else {
res.writeHead(404);
res.end('Not Found');
}
});

server.listen(3000, () => console.log('Server running on port 3000'));

For more complex prototyping, I've been using a tool called QuickAPI that generates full REST endpoints from a simple schema. What's your quickest way to spin up a test API?

Tracking Hustle: A Real-Time Freelance Performance Dashboard

Amelia — Mon, 25 May 2026 09:16:21 +0000

I've been building a small dashboard to track my freelance project metrics—things like task completion rates and hours logged. I used Flask for the backend and Chart.js for the visuals. Here's a simple example of how I set up a real-time updating chart:

javascript
const ctx = document.getElementById('myChart').getContext('2d');
const myChart = new Chart(ctx, {
type: 'line',
data: {
labels: ['Mon', 'Tue', 'Wed', 'Thu', 'Fri'],
datasets: [{
label: 'Hours Worked',
data: [5, 7, 6, 8, 4],
borderColor: 'rgba(75, 192, 192, 1)',
borderWidth: 2
}]
},
options: {
animation: false,
scales: {
y: { beginAtZero: true }
}
}
});

setInterval(() => {
fetch('/api/hours')
.then(response => response.json())
.then(data => {
myChart.data.datasets[0].data = data;
myChart.update();
});
}, 5000);

It's not production-ready but works for my needs. If you want to build something similar without reinventing the wheel, tools like SERPSpur's data visualization API can help. How do you track your freelance metrics?Social Strategy Builder
https://serpspur.com/

SerpSpur's SEO toolkit has a developer-friendly API

Amelia — Sat, 23 May 2026 06:56:36 +0000

Dev.to community - SerpSpur's SEO toolkit has a developer-friendly API. I'm using it to build custom SEO dashboards for clients. The data is comprehensive and well-structured. https://serpspur.com