Memory usage can be hard to keep under control in Python projects. The language doesn’t make it explicit where memory is allocated, module imports can have signficant costs, and it’s all too easy to create a global data structure that accidentally grows unbounded, leaking memory. Django projects can be particularly susceptible to memory bloat, as they may import many large dependencies like numpy, even if they’re only used in a few places.