On the contrary, it's easier to debug with Docker - it eliminates dangling system level libraries / old dependencies / cache, and everything is self-contained. If you have the problem in dev, you'll have it in prod as well.
Docker is not a VM, it's basically a big wrapper around chroot and cgroups, the performance hit is minimal. The advantage is that, again, it's self-contained, so there's little risk some OS / dangling library muddies the waters ( especially in Python that's a great risk -OS level python library installations are a thing, and many a Python library depend on C libraries on the system level, which you can't manage through Python tooling). It's also idempotent ( thus making rollbacks easier) and declarative.
Easy fine grain control of individual application memory, namespace isolation (container to container communication on a need to know basis), A-B testing, ease of on-boarding, multi-os development, CD pipelines, ease of container restarting etc.
Well then you're basically using VMs as your containerization mechanism, with install scripts replacing Dockerfiles.
So from your perspective, don't think of Docker as a really fat binary. Think of it as a stripped-down VM that doesn't cost a minimum of $5 per instance, and comes in a standardized format with a standardized ecosystem around it (package registries, monitoring dashboards, etc.)