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How I built a 39 compression pipeline with AES-256-GCM in Python (and why the dictionary is everything)

Community description: I store LLM training data. Every tool I found either compresses it or encrypts it — nothing did...

Dev.to | Mar 7, 2026 | Naveen Badiger

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Standard Zstd builds a probability model from scratch every time. Result: 28. 46× with dict vs 14. 64× vanilla — +94. 4% improvement, 29% faster. The dictionary retrains automatically every 24h via APScheduler as new data arrives. nonce = os. urandom(12) # fresh per seal Every unseal verifies a Merkle proof before returning any data.

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