Tʜᴜɴᴅᴇʀ // dev.log

Why Python

Python is the language I reach for first. It reads almost like plain English, which means the gap between "I have an idea" and "I have working code" is small. That matters more than people admit — a language that gets out of your way lets you spend your time solving the actual problem instead of fighting syntax.

It's also genuinely everywhere. Automation scripts, backend APIs with Flask or FastAPI, Telegram bots (which I use a lot for OSXSPACE and StarkXHub), data work with pandas, and even small games with pygame — one language covers all of it. The standard library alone ("batteries included") handles files, networking, JSON, dates, and more without a single external package.

# a five line Telegram-style bot skeleton

import requests

def send_message(token, chat_id, text):

    url = f"https://api.telegram.org/bot{token}/sendMessage"

    return requests.post(url, data={"chat_id": chat_id, "text": text})

What makes Python 90% of my stack isn't just familiarity — it's that it scales down for a quick script and scales up for a real backend. Same language, both ends.

Where Java fits

Java is stricter and more verbose than Python, but that strictness is a feature once a project grows. Static typing catches whole categories of bugs before the code ever runs, and the JVM's tooling — build systems like Maven / Gradle, and mature IDEs — makes large, multi-person codebases easier to reason about than looser dynamic languages.

I use Java mainly for Android-adjacent tools and anything that needs to run predictably at scale: object-oriented design, interfaces, and strong typing force you to plan a structure up front instead of discovering it halfway through, which is a different (and useful) way of thinking compared to Python's "just start writing" style.

Python → fast to write, flexible, great for scripts / bots / APIs
Java → structured, verbose, great for large or long-lived applications
C++ → closer to the hardware, used when speed and memory control actually matter
HTML/CSS/JS → the front door — what a user actually sees and clicks

Express.js — how I use it for the web side

When a project needs a lightweight web server or API instead of a full Python backend, I reach for Express, a minimal Node.js framework. It's a thin layer over Node's built-in HTTP server that gives you routing, middleware, and JSON handling without much boilerplate.

// install

npm init -y

npm install express

// server.js — a minimal Express app

const express = require("express");

const app = express();

app.use(express.json());

app.get("/", (req, res) => {

    res.send("Tʜᴜɴᴅᴇʀ's server is live");

});

app.listen(3000, () => console.log("Running on port 3000"));

// run it

node server.js

That's the whole shape of it: define routes (GET, POST, etc.), attach middleware for things like JSON parsing or auth, and let Express handle the request/response cycle. It pairs naturally with a Python backend for heavier logic — Express handles the web-facing layer, Python handles processing, bots, or data work behind it.

Cloning a repo from my GitHub

Once a repo is public, getting a local copy is three commands:

# 1. clone the repository

git clone https://github.com/<username>/<repo-name>.git

# 2. move into the project folder

cd <repo-name>

# 3. install dependencies, then run

npm install    # if it's a Node/Express project

pip install -r requirements.txt    # if it's Python

My previous main repository has been suspended, so it isn't live right now. A new one is being rebuilt from the ground up and will be made public soon — once it's up, the clone command above will point straight to it.