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Searge/README.md

Hi, I'm Searge Vulcan salute

DevOps Engineer at Smile Ukraine

Stand With Ukraine @Searge@hachyderm.io

# %%
"""Creating a class for keeping track of knowledge."""
import json
from dataclasses import asdict, make_dataclass

from rich import print

person = make_dataclass(
    "Person",
    [
        ("nick", str),
        ("name", str),
        ("pipelines", list[str]),
        ("web_services", list[str]),
        ("languages", list[str]),
        ("databases", list[str]),
        ("misc", list[str]),
        ("ongoing", list[str]),
    ],
    namespace={"to_json": lambda self: json.dumps(asdict(self), indent=4)},
)

# %%
# @title Initializing classes and creating lists
if __name__ == "__main__":
    pipelines    = ['GitLab Ci', 'GitHub Actions', 'AWS CodePipeline', 'Jenkins']
    web_services = ['nginx', 'apache', 'varnish', 'fastly', 'elastic', 'solr']
    languages    = ['YAML', 'Bash', 'Python', 'JS', 'Web']
    databases    = ['SQLite', 'PostgreSQL', 'Percona', 'DynamoDB', 'Redis']
    misc         = ['Ansible', 'Linux', 'LXC', 'Docker', 'Terraform', 'AWS']
    ongoing      = ['LPIC', 'Full Stack Web', 'AWS']

    me = person('@Searge', 'Sergij Boremchuk',
                pipelines, web_services, languages, databases, misc, ongoing)

    print(me.to_json())

# %%

Thanks @rednafi for idea of script πŸ˜‰

Statistics

Skyline for 2021

Visitors

Code Time

AI Code Time

I'm an Early 🐀

🌞 Morning                3169 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   25.92 % 
πŸŒ† Daytime                5523 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   45.18 % 
πŸŒƒ Evening                3176 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   25.98 % 
πŸŒ™ Night                  356 commits         β–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   02.91 % 

πŸ“Š This Week I Spent My Time On

πŸ•‘οΈŽ Time Zone: Europe/Kyiv

πŸ’¬ Programming Languages: 
Markdown                 9 hrs 39 mins       β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   42.41 % 
Org                      4 hrs 39 mins       β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   20.44 % 
YAML                     3 hrs 4 mins        β–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   13.51 % 
Other                    1 hr 29 mins        β–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   06.56 % 
Python                   53 mins             β–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   03.89 % 

πŸ”₯ Editors: 
Claude Code              16 hrs 16 mins      β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘   71.51 % 
Zed                      3 hrs 18 mins       β–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   14.54 % 
Emacs                    1 hr 34 mins        β–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   06.90 % 
Codex Unknown            47 mins             β–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   03.50 % 
Zsh                      22 mins             β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   01.65 % 

πŸ’» Operating System: 
Linux                    22 hrs 45 mins      β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ   100.00 % 

πŸ€– AI Coding This Week

⏱ AI Coding Time: 20 hrs 15 mins (89.02%)

✍️ 3,831 lines written by AI, 39 lines written by hand (98.99% AI-written)

πŸ”€ 11,556,001 Input Tokens, 1,088,253 Output Tokens

πŸ’΅ $289.06 Estimated AI Cost This Week

🧠 29 AI Sessions, 267 AI Prompts

Fable                    2,476 lines         β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   60.97 % 
Opus                     947 lines           β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   23.32 % 
GPT                      638 lines           β–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   15.71 % 
Codex-Exec               0 lines             β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   00.00 % 
Haiku                    0 lines             β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   00.00 % 

πŸ”Ž AI Coding Insights:
πŸ€– AI-Driven β€” 98.99% of written lines came from AI
πŸ“š Verbose Prompter β€” average 1,851 characters per prompt
πŸ” Iterative Prompter β€” average 9 prompts per session
πŸš€ High AI Trust β€” 1.43% of changed lines were hand-edited

Last Updated on 30/08/2026 02:15:58 UTC

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