Sharing Time: Concurrency & Multithreading

Debugging production race conditions and deadlocks, and reasoning correctly about shared state. Python examples.

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01Chapter 1: Concurrency vs. Parallelism, and Why It's Hard 02Chapter 2: Processes vs. Threads, Revisited for Concurrency 03Chapter 3: The Core Hazards: Race Conditions, Deadlock, Livelock, Starvation 04Chapter 4: Synchronization Primitives: Locks, Semaphores, Monitors, Condition Variables 05Chapter 5: Designing for Thread Safety: Immutability, Confinement, Thread-Safe Collections 06Chapter 6: Classic Patterns: Producer-Consumer, Reader-Writer, Thread Pools 07Chapter 7: Higher-Level Models: Async/Await, Event Loops, Coroutines, Actors, Channels 08Chapter 8: Memory Models and Visibility: Happens-Before, Volatile, Atomics 09Chapter 9: Lock-Free and Wait-Free Programming Basics 10Chapter 10: How Concurrency Differs Across Runtimes: JVM Threads, Python's GIL, Go's Goroutines, JavaScript's Event Loop 11Chapter 11: Debugging and Testing Concurrent Code 12Chapter 12: Classic Interview Problem: Producer-Consumer 13Chapter 13: Classic Interview Problem: Dining Philosophers 14Chapter 14: Classic Interview Problem: Readers-Writers 15Chapter 15: Concurrency in System Design and Production Debugging

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Python DSA — Course Python DSA — Interview Prep Python DSA — Beginner Python Syntax & DSA Reference Git Mastery Cognitive Skills & Mental Tools Code Optimization Rules Objects First: OOP Fundamentals Patterns of Good Design Under the Hood: Operating Systems How the Bytes Travel: Networking Data at Rest, Data in Motion: Databases Clean by Default: Coding Standards The Review: Code Review From Idea to Production: the SDLC Designing at Scale: System Design Whiteboard to Blueprint: HLD & LLD Built to Last: Reliability & Scaling Tell Me About a Time: Behavioral Interviews