User Guide Overview

Epochly is a transparent performance optimization framework for Python. It accelerates code without requiring modifications to existing codebases.

What Epochly Does

Progressive Enhancement: Gradually increases optimization levels based on workload stability
Transparent Operation: Works via decorators, context managers, or CLI
Intelligent Selection: Chooses appropriate optimization strategies automatically
Safe Fallback: Reverts to baseline if optimizations cause issues

Design Philosophy

Zero-Configuration Operation

import epochly
@epochly.optimize
def my_function():
    pass

No configuration required. Epochly automatically detects workload characteristics and selects optimization strategies.

Progressive Enhancement

Stage	Action	Goal
1	Monitor	Collect baseline metrics
2	Apply safe optimizations	Minimal risk improvements
3	Apply advanced optimizations	Maximum performance
4	Monitor for regressions	Ensure stability

When to Use Epochly

CPU-Bound Numerical Code

@epochly.optimize
def compute_statistics(data):
    total = sum(data)
    mean = total / len(data)
    variance = sum((x - mean) ** 2 for x in data) / len(data)
    return mean, variance ** 0.5

JIT compilation provides 58–193x speedup on numerical loops.

Parallel Workloads

@epochly.optimize
def process_batch(items):
    results = []
    for item in items:
        results.append(heavy_computation(item))
    return results

Multicore provides near-linear scaling.

When Epochly May Not Help

Already-optimized code: NumPy, Pandas operations
Memory-bound operations: Limited by RAM speed
Network-bound: External service latency
Python object manipulation: Strings, dicts, custom objects