Performance Review

You can detect N+1 database queries in Python code by running a static code review that analyzes function logic for iterative query calls, returning a JSON report with severity grades and batch operation suggestions.

Static complexity analysis is the process of examining source code without execution to detect costly algorithmic patterns like O(n^2) loops and exponential recursion. It surfaces performance hotspots to prevent runtime slow-downs.

Yes, you can identify memory leaks and inefficient I/O during a code review by scanning Python functions for unbounded collections, unnecessary file loads, and sub-optimal streaming. The analysis returns a graded report with concrete remediation suggestions.

The performance review tool works on any Python file by analyzing functions for performance anti-patterns like quadratic algorithms and excessive memory use. It requires no external dependencies to generate its JSON-formatted report.

The best way to find performance anti-patterns before production is to run a static code review on your data-processing pipelines. This identifies hidden issues like N+1 queries and inefficient I/O, providing prioritized remediation suggestions.