⚙️ Advanced Performance & Patterns — Optimization

Profile file I/O, implement design patterns, and optimize for production.

🎯 Profiling File Operations

import cProfile
import pstats

def process_large_file(filename):
    with open(filename, "r") as f:
        for line in f:
            process(line)

pr = cProfile.Profile()
pr.enable()
process_large_file("data.txt")
pr.disable()

ps = pstats.Stats(pr).sort_stats("cumulative")
ps.print_stats(10)

💡 Design Patterns

File Reader Pattern

class FileReader:
    def __init__(self, path, chunk_size=8192):
        self.path = path
        self.chunk_size = chunk_size

    def read_chunks(self):
        with open(self.path, "rb") as f:
            while True:
                chunk = f.read(self.chunk_size)
                if not chunk:
                    break
                yield chunk

Atomic Operations

class AtomicWriter:
    def __init__(self, path):
        self.path = Path(path)
        self.temp = Path(f"{path}.tmp")

    def __enter__(self):
        self.file = open(self.temp, "w")
        return self.file

    def __exit__(self, *args):
        self.file.close()
        self.temp.replace(self.path)

📊 Performance Tips

• Use generators for streaming

• Batch operations

• Choose correct encoding

• Memory-map for random access

• Profile before optimizing

🔑 Key Takeaways

• ✅ Profile actual code, don't guess

• ✅ Batch buffering for throughput

• ✅ Generators for memory efficiency

• ✅ Atomic operations for safety

• ✅ Choose strategy based on profile

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