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Data Structures: Advanced

Specialized collections and scale

Specialized collections and scale

Category
Python
Difficulty
advanced
Duration
29 minutes
Challenges
0 hands-on challenges

Topics covered: The collections Module, Custom Structures, Performance Profiling, Caching Strategies, Choosing for Scale

Lesson Sections

  1. The collections Module

    Counter: Counting Made Easy defaultdict: Auto Defaults deque: Double-Ended Queue namedtuple: Lightweight

  2. Custom Structures

    When named tuples are too rigid and plain dicts are too loose, Python offers dataclasses and custom classes with __slots__. These give you mutable records with type hints, default values, comparison methods, and memory optimization - all with minimal boilerplate. dataclasses: Modern Records Frozen Dataclasses __slots__ for Memory

  3. Performance Profiling

    Timing Operations Memory Profiling Profiling should always come before optimization. Measure first, then target the specific bottleneck. Optimizing without data often means spending time on code that is not actually the performance problem.

  4. Caching Strategies

    Caching is one of the most impactful performance techniques in data engineering. By storing the results of expensive computations or database queries, you avoid repeating work. Python provides built-in caching tools, and understanding how to build custom caches using data structures gives you fine-grained control over eviction policies, size limits, and expiration. Using functools.lru_cache Building a Custom LRU Cache The LRU eviction policy works well for workloads with temporal locality - rece

  5. Choosing for Scale

    Concurrent Access Patterns Data Structure at Scale The table below summarizes when to reach for each specialized structure based on your system requirements. These are the patterns that appear in production systems processing millions of records. These patterns are not theoretical. They power some of the largest Python applications in the world. Architecture Example Let us walk through a realistic data pipeline that combines multiple specialized structures. This pattern appears in event processi