Thursday, 30 October 2025

Embracing Microservices with Django for Modern Web Applications


Transitioning from a monolithic architecture to a microservices architecture involves several considerations, especially when incorporating technologies like Django, React, Angular, and potentially other back-end technologies like GoLang, FastAPI, or Java Spring. This post explores a practical approach to building a microservices-based system with Django and how to structure such an architecture effectively.

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Wednesday, 29 October 2025

Analyzing Security Insights Using GCP Cloud Build

Building, testing, and deploying secure applications is essential for maintaining trust and reliability in software systems. Google Cloud Build offers a streamlined way to containerize applications and analyze their security with built-in tools like Security Insights. This blog provides a step-by-step guide to containerizing applications using Cloud Build, leveraging two repositories: the popular Juice Shop app and a Flask-based web application repository.

Step 1: Log in to Google Cloud Platform

Begin by logging into Google Cloud Platform (GCP) with the provided credentials. After logging in:

  1. On the “Welcome to your new account” screen, review the text and click I understand.
  2. On the “Welcome Cloud Student!” screen, select your country and agree to the terms of service.
  3. Click AGREE AND CONTINUE to proceed.
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Monday, 27 October 2025

Working with Nested Arrays in Python: Practical Examples

Nested arrays, or arrays of arrays, are a fundamental concept in programming, often used to represent matrices, grids, or any multi-dimensional data. In Python, nested arrays can be efficiently managed using lists, or for more complex applications, with libraries like NumPy. In this blog post, we’ll explore how to create, manipulate, and utilize nested arrays in Python through practical examples.

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Saturday, 25 October 2025

Understanding self and $this in PHP: When to Use Each


In PHP, understanding when to use self versus $this is crucial for correctly referencing the context within a class—whether it pertains to the current instance or the class itself. This distinction is especially important in object-oriented programming as it affects how properties and methods are accessed and manipulated.

self: Referencing the Current Class

  • Usage Context: self is used to refer to the current class itself, not an instance of the class. It’s typically used in static methods or when referring to static properties.
  • Keyword Type: Non-variable (does not use a dollar sign $).
  • Common Use Cases:
    • Accessing static properties.
    • Calling static methods.
    • Referring to constants within the class.

Example of self Usage:

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Friday, 24 October 2025

Understanding Type Hints in Python 3.5: A Comprehensive Guide

Python is loved for its dynamic nature, allowing developers to quickly write and execute code without worrying about strict typing rules. However, as projects grow in size and complexity, managing types can become a challenge, especially in large codebases. To address this, Python 3.5 introduced type hints — a way to annotate expected types for variables, function parameters, and return values. While these hints don’t change Python’s dynamic behavior, they offer numerous advantages for improving code readability, debugging, and collaboration.

In this blog post, we’ll dive into what type hints are, how to use them effectively, and when they might be overkill. We’ll also explore some examples to see type hints in action.

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Thursday, 23 October 2025

Understanding Shifting Operators in Python

Python, like many other programming languages, provides a set of bitwise operators that allow you to manipulate data at the binary level. Among these operators are the shifting operators, which are used to shift the bits of a number to the left or right. These operators are particularly useful in low-level programming, cryptography, and optimization tasks.

In this blog post, we’ll dive deep into the two shifting operators in Python:

  1. Left Shift Operator (<<)
  2. Right Shift Operator (>>)

1. What Are Shifting Operators?

Shifting operators are used to move the bits of a binary number to the left or right. This operation effectively multiplies or divides the number by powers of 2, depending on the direction of the shift.

  • Left Shift (<<): Shifts the bits of a number to the left and fills the vacant positions with 0. This is equivalent to multiplying the number by (2^n), where (n) is the number of positions shifted.

  • Right Shift (>>): Shifts the bits of a number to the right and fills the vacant positions based on the sign bit (for signed integers). This is equivalent to dividing the number by (2^n), where (n) is the number of positions shifted.

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Saturday, 18 October 2025

Implement an ORM (Object-Relational Mapping) in a Perl Catalyst application using complex DBIx::Class Module

Here's a detailed example using a simple "events" table to demonstrate how to work with DBIx::Class in a Catalyst application.


Step 1: Define Your Database Schema

For this example, let's use a simple `events` table with the following schema:

CREATE TABLE events (

    id INTEGER PRIMARY KEY AUTOINCREMENT,

    title VARCHAR(255) NOT NULL,

    start_date DATE NOT NULL,

    end_date DATE NOT NULL,

    description TEXT

);

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Friday, 17 October 2025

How to Get File Creation and Modification Dates/Times in Shell/Bash

 When working with files in a shell or bash environment, it’s often useful to retrieve metadata such as file creation and modification dates/times. Below are several methods to achieve this across different platforms like Linux and Windows.

1. Modification Date/Time

Retrieving the modification date and time of a file is straightforward and works across both Linux and Windows platforms.

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Wednesday, 15 October 2025

lets Solve Conda Activation Issues on Windows


If you’re a Windows user getting into Python and data science, you’ve likely encountered Miniconda or Anaconda during your setup. These tools are fantastic for managing packages and environments, but occasionally, you might bump into some hitches when setting up or switching environments, especially on Windows. Today, let’s dive into a common issue where users are unable to activate a new conda environment, repeatedly prompted to run conda init.

Understanding the Issue

When trying to activate a conda environment (conda activate test_env), users are sometimes met with an error suggesting they should run conda init. Running conda init seemingly has no effect, as the error persists.

The root of this issue often lies in the integration of conda with your shell (in this case, Bash running on Cmder in Windows). Even after including Miniconda in the PATH as instructed during installation, the shell might not properly recognize conda commands.

Steps to Resolve the Issue

Here’s a more detailed guide on how to ensure your environment can be activated without repeatedly seeing the conda init prompt:

Step 1: Re-run Conda Initialization

Instead of just running conda init, specify your shell directly to ensure the correct initialization scripts are modified. For Bash in Cmder, use:

conda init bash

This command attempts to configure your Bash shell to integrate properly with conda, modifying necessary startup scripts like .bashrc.

Step 2: Verify and Modify PATH Manually

Even after running conda init, sometimes the PATH isn’t correctly set. You need to ensure that the directory containing conda is indeed in your PATH. You can check this by opening a new command prompt and typing:

echo %PATH%

If you do not see paths leading to your Miniconda/Anaconda directories, you need to add them manually. Here’s how you can do it:

  1. Right-click on ‘This PC’ or ‘My Computer’.

  2. Click on ‘Properties’.

  3. Navigate to ‘Advanced system settings’ and then ‘Environment Variables’.

  4. In the ‘System variables’ pane, find and select the ‘Path’ variable, then click ‘Edit’.

  5. Add new entries for the following paths (replace C:\Users\Username\miniconda3 with your actual installation path):

    • C:\Users\Username\miniconda3
    • C:\Users\Username\miniconda3\Scripts
    • C:\Users\Username\miniconda3\Library\bin
  6. Confirm all dialogs by clicking ‘OK’.

Step 3: Restart Your Shell

After adjusting your PATH and running conda init for your specific shell, close your command line interface (Cmder, in this case) completely and reopen it. This ensures all changes take effect.

Step 4: Activate Your Environment

Now, try activating your environment again:

conda activate test_env

This should work without prompting you to run conda init again. If it does, you are now ready to use your conda environment!

Troubleshooting Persistent Issues

If you still encounter issues, it might be a good idea to check for any conda updates or reinstall Miniconda, ensuring that you follow the installation prompts carefully. Sometimes, starting afresh removes any configuration errors introduced during the initial setup.

Setting up conda on Windows can occasionally test your patience, but with a careful approach to initializing conda and setting up your PATH, these initial hurdles can be overcome. Remember, accurate configuration at the start can save a lot of time and frustration later!

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Monday, 13 October 2025

10 Free Projects to Get Started with AWS

Are you interested in learning more about Amazon Web Services (AWS) but not sure where to start? Look no further! In this blog post, we'll explore 10 free projects that you can build using AWS services. These projects cover a range of topics, from serverless computing to machine learning, and everything in between. By the end of this post, you'll have a better understanding of the capabilities of AWS and have some hands-on experience to boot!


Build a Serverless Web Application:

Serverless computing is all the rage these days, and AWS Lambda is at the forefront of this trend. With Lambda, you can run code without provisioning or managing servers, making it easy to build scalable web applications. In this project, you'll learn how to create a simple web application using AWS Lambda and API Gateway. You'll also get familiar with the basics of serverless architecture and how to deploy your application to production. 

Get started here:  https://lnkd.in/gCgdvmYK

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Thursday, 9 October 2025

Top Free DevOps Tutorials and Courses on Udemy

Are you looking to learn DevOps but not sure where to start? Look no further! This article will provide you with a list of top free DevOps tutorials and courses available on Udemy. Whether you're a beginner or an experienced professional, these courses will help you enhance your skills and knowledge in DevOps practices and tools.


1. Introduction to DevOps, Habits and Practices:

This course is perfect for those who are new to DevOps. It covers the basics of DevOps, its habits, and practices. You'll learn how to create world-class agile, lean, and continuous delivery teams that can deliver high-quality software quickly and efficiently. Check it out here: https://lnkd.in/dsvQQcYj

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Tuesday, 7 October 2025

GraphQL vs REST API: A Comparative Study

GraphQL and REST are two prominent approaches for building APIs. REST has been around for a long time, offering a simple way to structure and interact with web services. GraphQL, developed by Facebook in 2012, is a more modern alternative that addresses some of the limitations of REST. This blog post provides a comparative analysis of GraphQL and REST APIs in tabular format, along with examples of input endpoints and their respective outputs.

Comparative Analysis

1. Data Fetching

Aspect GraphQL REST
Querying Data Allows querying multiple resources in a single request Requires multiple requests to different endpoints for related data

Example Query { user(id: "1") { name, email, posts { title } } }

GET /user/1 and then GET /user/1/posts

Example Output {"data": {"user": {"name": "John", "email": "john@example.com", "posts": [{"title": "First Post"}]}}} {"name": "John", "email": "john@example.com"} / [{"title": "First Post"}]

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Saturday, 4 October 2025

The Git & Github Bootcamp Part 7- Master on essentials and the tricky bits: rebasing, squashing, stashing, reflogs, blobs, trees, & more!


The Power of Reflogs - Retrieving “Lost” Work

1. Introducing Reflogs

Reflogs are a mechanism in Git that records updates to refs (branch heads, tags, etc.), effectively logging every state your repository has been in. This includes commits, merges, and even failed attempts at rewriting history.

2. The Limitations of Reflogs

Reflogs are local to your repository; they are not shared when you push or pull changes. They’re meant for recovering local changes that may have been lost or mistakenly altered. Additionally, entries in reflogs expire after a certain period (default is 90 days for commits that can no longer be reached and 30 days for reachable commits).

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Thursday, 2 October 2025

5 Fresh Project Ideas for Data Analysts to Explore

The world of data analysis is dynamic and continuously evolving. For data analysts looking to expand their portfolio or gain new insights, working on real-world datasets can be both enlightening and challenging. Here are five fresh project ideas that offer a wealth of information to analyze, visualize, and model.

🏠 Airbnb Open Data

Dataset: Airbnb Open Data on Kaggle
Project: Analyze the vibrant homestay landscape of New York City through Airbnb’s open data. From pricing strategies to seasonal availability, dive deep into what makes a successful Airbnb listing stand out in the bustling Big Apple.

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