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You know that beautiful moment when your code runs flawlessly on your machine? All tests passing, no errors, pure bliss. Then you ship it to a colleague or deploy it to production and suddenly it's like you've summoned a demon from the depths of dependency hell.
The existential crisis hits hard when you realize their Python version is 0.0.1 different, they're missing that one obscure system library you installed three years ago and forgot about, or—plot twist—they're running Windows while you've been vibing on Linux this whole time. Suddenly you're the bear at the laptop, gesturing wildly trying to explain why "works on my machine" is a perfectly valid defense.
Docker containers exist for this exact reason, but let's be honest—we all still ship code with a silent prayer and hope for the best.
