MirahLabs Engineering Blog
Technical insights, architectural deep-dives, and system designs authored by our product engineers and AI research leads.
Writing C Extensions in Python: Cython, Pybind11, and Ctypes
When Python is too slow, compile key functions to C. Compare Cython, Pybind11, and ctypes for raw performance speedups in numeric and CPU-bound algorithms.
Python Performance Profiling: Finding and Fixing Bottlenecks
Before optimizing Python code, measure first. Learn how to use cProfile, py-spy, memory_profiler, and line_profiler to identify real bottlenecks—not the ones you assume.
Python Memory Management: Reference Counting and Generational Garbage Collection
Deep dive into CPython's memory management model: reference counting, memory allocation arenas, and how generational garbage collection resolves cyclic references.
Load Testing Your API with Locust: From Basics to CI Integration
Load testing reveals performance bottlenecks before your users do. Learn how to write realistic Locust test scenarios, interpret results, and integrate load tests into your CI/CD pipeline.
PostgreSQL Full-Text Search: FTS vs pgvector vs Elasticsearch
Full-text search can be implemented several ways in a PostgreSQL-based stack. Compare native FTS, vector semantic search with pgvector, and Elasticsearch for your search requirements.
Async Python with asyncio and aiohttp: Building High-Concurrency APIs
Python's asyncio enables non-blocking I/O that handles thousands of concurrent connections with a single thread. Learn async patterns, event loops, and building async REST APIs.