🚀 Hello, world! I'm a Newbie Developer, and my ideas keep me up at night
Hello everyone! 👋 I'm a newbie developer named LAG (LAG-Lagendary), and I have a blast coming up with all sorts of projects. I think every idea deserves to be realized (or at least uploaded to GitHub before my laptop dies after another "crazy experiment" 😂).
Nice to meet you all! I really hope my little projects outlive my computer.
✨ My latest "crazy" projects on GitHub
I just posted a couple of my projects and wanted to share them. Maybe they'll inspire someone, or you'd just like to give me some feedback!
📡 Project 1: Signal to Space
Repository: https://github.com/LAG-Lagendary/signal_to_space
This project is a series of simple but engaging Python scripts for monitoring the network availability of key public DNS servers: Quad9, Google, Yandex, and others.
What's the gist?
Continuous monitoring: Scripts like ping_counter_Quad9.py or ping_counter_yandex.py continuously send PING requests to a target IP address (e.g., 9.9.9.9 or 77.88.8.8) at a set interval (5 seconds).
Data collection: They record the status (success/error) and, for Linux/macOS, the response latency.
Automation: I use the start_monitoring.sh script to run all counters in the background, and their output is saved in log files.
This is my way of ensuring that my "connection to the outside world" is working properly and collecting statistics for future network experiments!
🌍 Project 2: Geo Ping Analyzer
Repository: https://github.com/LAG-Lagendary/Geo-Ping-Analyzer
This tool allows me to roughly determine the geographic location of my network connection. How does it work?
Global Coverage: The geo_ping_analyzer_ru.py script pings over 10 public DNS servers around the world (North and South America, Europe, Asia, Africa, Oceania).
Latency Measurement: It measures the average latency (RTT) and packet loss for each target.
Score: The lowest ping indicates that this server is physically closest to me.
Conclusion: Based on the closest point, the script infers my approximate location (continent/region).
This is a cool way to visualize network distances and routing!
🤝 Let's Chat!
If you're interested in network experiments, Python, or just "crazy" ideas, let me know in the comments! I'm open to advice, criticism, and collaboration.
I always believe the best place for ideas is GitHub!
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