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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                3246 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–‘   25.85 % 
πŸŒ† Daytime                5676 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–‘   45.21 % 
πŸŒƒ Evening                3275 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   26.09 % 
πŸŒ™ Night                  358 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–‘   02.85 % 

πŸ“Š This Week I Spent My Time On

πŸ•‘οΈŽ Time Zone: Europe/Kyiv

πŸ’¬ Programming Languages: 
Markdown                 12 hrs 35 mins      β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   37.85 % 
YAML                     7 hrs 33 mins       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–‘   22.73 % 
Other                    6 hrs 25 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–‘   19.32 % 
JSON                     1 hr 23 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–‘   04.17 % 
Bash                     1 hr 15 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–‘   03.77 % 

πŸ”₯ Editors: 
Claude Code              29 hrs 2 mins       β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘   87.25 % 
Zed                      2 hrs 53 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–‘   08.70 % 
Zsh                      55 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–‘   02.77 % 
Emacs                    14 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–‘   00.70 % 
Codex Exec               8 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–‘   00.44 % 

πŸ’» Operating System: 
Linux                    33 hrs 16 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: 30 hrs 41 mins (92.2%)

✍️ 2,322 lines written by AI, 1,319 lines written by hand (63.77% AI-written)

πŸ”€ 13,104,003 Input Tokens, 1,970,094 Output Tokens

πŸ’΅ $463.82 Estimated AI Cost This Week

🧠 28 AI Sessions, 461 AI Prompts

Opus                     1,694 lines         β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   69.88 % 
Sonnet                   646 lines           β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   26.65 % 
GPT                      84 lines            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–‘   03.47 % 
Fable                    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 % 
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 % 

πŸ”Ž AI Coding Insights:
βš–οΈ Balanced with AI β€” 63.77% of written lines came from AI
πŸ“„ Detailed Prompter β€” average 627 characters per prompt
πŸ” Iterative Prompter β€” average 16 prompts per session
πŸš€ High AI Trust β€” 35.89% of changed lines were hand-edited

Last Updated on 04/10/2026 03:20:31 UTC

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