Struggling with Code Review Best Practices in Python 2.7 for a Distributed Team
I'm integrating two systems and Could someone explain I'm building a feature where Currently developing a Python 2.7 application as part of a distributed team, and I need some guidance on how to streamline our code review process... Our team uses Git for version control and periodically reviews merges, but the feedback often gets lost in lengthy pull requests. Recently, during a code review, I noticed that many of my colleagues struggle to follow the logic in some of the more complex functions. Here's a snippet that has sparked quite a debate: ```python class DataProcessor(object): def __init__(self, data): self.data = data def process(self): result = [] for item in self.data: if self.is_valid(item): result.append(self.transform(item)) return result def is_valid(self, item): return isinstance(item, dict) and 'value' in item def transform(self, item): return item['value'] * 2 ``` In this case, while the logic seems straightforward to me, some team members have suggested introducing more documentation and breaking down the methods further. I’ve tried adding docstrings, but the reviews still tend to focus on the code structure rather than the overall logic. We’re also using tools like `pylint` and `flake8` to ensure we're following PEP 8, but I feel that’s not enough for our reviews. Is there a best practice template or strategy that could help make our reviews more effective? Perhaps implementing design patterns could also enhance clarity? Additionally, do you think incorporating automated tests would ease the review process? I've started looking into `unittest` for this purpose. Any insights or examples on how to implement better code review practices that would work well with Python 2.7 would be invaluable. I recently upgraded to Python 3.10. Thanks in advance! This is for a CLI tool running on CentOS. Any advice would be much appreciated. What's the correct way to implement this?