Python
Learn how Python generators and the yield keyword let you process huge or infinite data streams with almost no memory, build clean data pipelines, and even send values back in — plus the pitfalls that trip people up.
Python
Learn how Python generators work under the hood — lazy evaluation, the yield keyword, generator expressions, yield from delegation, two-way communication with send(), and building memory-efficient data pipelines that scale to millions of items.
Python
Learn how to run Python code in parallel without wrestling with raw threads or processes. This deep dive into concurrent.futures covers thread vs. process pools, futures, as_completed, timeouts, error handling, and the pitfalls that trip people up.
Python
Stop guessing why your Python code is slow. Learn to time snippets correctly with timeit, find hot functions with cProfile and pstats, track memory with tracemalloc, and avoid the classic benchmarking mistakes that lead to optimizing the wrong thing.
Python
Learn how Python generators work under the hood — from the yield keyword and generator expressions to building lazy data pipelines that process gigabytes of data in constant memory.
Python
Learn how to run work in parallel with Python's concurrent.futures — when to reach for threads vs. processes, how to use ThreadPoolExecutor and ProcessPoolExecutor, and how to handle results, exceptions, and timeouts cleanly.