How to efficiently track changes in a Python dictionary for an evolving API feature?
I'm deploying to production and I'm working on a project and hit a roadblock... Currently developing a new feature for our API that requires tracking changes in a dictionary, specifically capturing when values are updated or keys are added. The use case involves maintaining a state snapshot of user preferences that can change frequently, and we need to ensure that we're efficiently recording those changes without imposing a heavy performance burden. I initially tried a straightforward approach of using a standard dictionary and implementing a wrapper class to monitor updates, but I found that tracking changes manually can quickly lead to cumbersome and error-prone code. Here's what I started with: ```python class TrackedDict: def __init__(self): self.data = {} self.changes = [] def set_item(self, key, value): if key in self.data: self.changes.append((key, self.data[key], value)) # Track the old and new value self.data[key] = value def get_changes(self): return self.changes ``` While this works for basic use cases, performance issues arise when dealing with a large number of keys and frequent updates. Profiling the application revealed that the overhead from appending to the `changes` list could become significant. Trying another approach, I implemented a decorator to wrap the dictionary methods. However, this increased the complexity of the codebase and made debugging harder, especially when it interacts with other third-party libraries that expect standard dictionary behavior. Here's a simple version of that: ```python from functools import wraps def track_changes(func): @wraps(func) def wrapper(self, *args, **kwargs): result = func(self, *args, **kwargs) # Capture changes here return result return wrapper class TrackedDict: def __init__(self): self.data = {} @track_changes def __setitem__(self, key, value): self.data[key] = value # Additional methods... ``` This method still didn't resolve the underlying issue of performance, leading me to consider using `collections.defaultdict` or even implementing a more sophisticated observer pattern where listeners can subscribe to changes. However, with the latter, I worry about introducing unnecessary complexity and potential memory leaks. Could anyone share insights or best practices for efficiently tracking changes in Python dictionaries, especially in high-frequency update scenarios? Are there existing libraries or patterns that could simplify this process? Any guidance on how to balance efficiency with maintainability would be greatly appreciated. My development environment is Linux. Thanks in advance! I'm working on a web app that needs to handle this. I'd really appreciate any guidance on this. I'm working on a application that needs to handle this. How would you solve this? I'm working on a mobile app that needs to handle this. Am I approaching this the right way?