tree-timer 0.1.0

A hierarchical performance timer for structured profiling

TreeTimer

A hierarchical performance timer for measuring nested execution scopes in Python.
Supports context-based timing, named sub-scopes, repeated series tracking, and structured reporting.

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Features

• ⏱ Simple with-based timing API
• 🌲 Tree-style nested timing scopes
• 🔁 Support for repeated timing series (e.g. epochs, batches)
• 📦 to_dict() output for visualization or structured logging

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Installation

pip install tree-timer

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Usage

1. Simple use

from tree_timer import TreeTimer
import time

with TreeTimer() as timer:
    time.sleep(0.1)

print(timer)

root: 0.100123s

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2. Nested scopes with add_scope()

with TreeTimer() as timer:
    with timer.add_scope("load_data"):
        time.sleep(0.05)
    with timer.add_scope("process_data"):
        time.sleep(0.08)

print(timer)

root: 0.130456s
  load_data: 0.050123s
  process_data: 0.080333s

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3. Loop timing with add_series()

with TreeTimer() as timer:
    steps = timer.add_series("steps", 3)
    for step in steps:
        with step:
            time.sleep(0.03)

print(timer)

root: 0.090876s
  steps: 0.090876s
    [0]: 0.030141s
    [1]: 0.030251s
    [2]: 0.030484s

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4. Combined use with parallel execution

from tree_timer import TreeTimer
from concurrent.futures import ThreadPoolExecutor
import time

def run_task(timer):
    with timer:
        time.sleep(0.03)

with TreeTimer() as timer:
    with timer.add_scope("pipeline") as pipeline:
        with pipeline.add_scope("load"):
            time.sleep(0.02)

        steps = pipeline.add_series("parallel_steps", 4)
        with ThreadPoolExecutor() as executor:
            executor.map(run_task, steps)

        with pipeline.add_scope("finalize"):
            time.sleep(0.01)

print(timer)

root: 0.063421s
  pipeline: 0.063421s
    load: 0.020114s
    parallel_steps: 0.120548s
      [0]: 0.030102s
      [1]: 0.030184s
      [2]: 0.030120s
      [3]: 0.030142s
    finalize: 0.010216s

💡 Tasks in parallel_steps run concurrently using ThreadPoolExecutor, while the surrounding load and finalize scopes are timed sequentially.

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License

MIT