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Hartmut Goebel - Hacker and Python Developer — Crazy Compilers — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Programming Languages →

DomainMatchTitleCountry/LangCategoryAI filesContactAI-protection
mbrindustrial.com 69 match
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1 shared topics
Saad Benchakroun | Python Developer & IT Student en programming-languages robotsllmsaihumans emailphone partial · 8
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1 shared topics
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ctoassembly.com 66 match
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bensamy.com 66 match
1 shared topics
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aliduman.tech 65 match
1 shared topics
Ali Duman | Android Developer en programming-languages robotsllmsaihumans emailphone none
1ob.com 65 match
1 shared topics
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arkhypkoshel.com 65 match
1 shared topics
Arkhyp Koshel – iOS Engineer and .NET Developer en programming-languagesWordPressWooCommerce robotsllmsaihumans emailphone none
neos.dev 65 match
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neos ⚛ Universal Compiler and Bytecode JIT en programming-languages robotsllmsaihumans emailphone none
deepdivepython.com 65 match
1 shared topics
Deep Dive Python – Techniques and Best Practices for Developers | Adarsh Divakaran en programming-languages robotsllmsaihumans emailphone none
milanlaslop.dev 65 match
1 shared topics
Milan Laslop – C++, Android and .NET developer en programming-languages robotsllmsaihumans emailphone none
ctxgo.ai 65 match
1 shared topics
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dvdphobia.dev 64 match
1 shared topics
DVDphobia | Developer & Builder en programming-languages robotsllmsaihumans emailphone partial · 8
gleanko.com 64 match
1 shared topics
Home - Slava Shpigel - software developer en programming-languagesWordPressWooCommerce robotsllmsaihumans emailphone none
lzszt.info 64 match
1 shared topics
Software Developer | Felix Leitz en programming-languages robotsllmsaihumans emailphone none
decoratory.app 64 match
1 shared topics
Python Decorators — Decoratory en programming-languages robotsllmsaihumans emailphone none
sqldbo.org 64 match
1 shared topics
SQL for Application Developers | Master the Query en programming-languages robotsllmsaihumans emailphone none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.