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Adaptive thread pool executor with dynamic scaling policies

Project description

Adaptive Executor

Adaptive thread pool executor that scales concurrency based on policies.

Features

  • Time-based scaling
  • CPU & memory criteria
  • Multi-criterion aggregation
  • Graceful shutdown

Installation

Minimal Installation (Core Only)

pip install adaptive-executor

Feature-Specific Installations

# Time-based scaling only
pip install adaptive-executor[time]

# CPU/Memory monitoring only
pip install adaptive-executor[cpu]

# Complete feature set (recommended)
pip install adaptive-executor[standard]

# Development with all tools
pip install adaptive-executor[dev]

Quick Start

from adaptive_executor import AdaptiveExecutor, MultiCriterionPolicy
from adaptive_executor.criteria import TimeCriterion, CpuCriterion
from datetime import time

# Create scaling criteria
time_policy = TimeCriterion(
    worker_count=8,
    active_start=time(22, 0),
    active_end=time(6, 0),
    timezone="UTC",
)
cpu_policy = CpuCriterion(threshold=75, workers=4)

# Combine criteria
policy = MultiCriterionPolicy([time_policy, cpu_policy], hard_cap=10)

# Create and use executor
executor = AdaptiveExecutor(max_workers=15, policy=policy)

# Submit tasks
def my_task(task_id):
    print(f"Processing task {task_id}")

for i in range(5):
    executor.submit(my_task, i)

executor.join()
executor.shutdown()

Development Setup

This project uses setuptools with a src/ package layout (src/adaptive_executor).

git clone https://github.com/Teut2711/adaptive-executor.git
cd adaptive-executor
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install -e ".[dev]"

Logging Configuration

The adaptive-executor provides comprehensive logging that can be configured to suit your needs. By default, it logs to the console with INFO level.

Basic Logging Control

from adaptive_executor import setup_logger

# Disable all logging
setup_logger(level=logging.CRITICAL)

# Or set a specific log level
import logging
setup_logger(level=logging.WARNING)  # Only show warnings and above

Advanced Logging Configuration

You can also configure file logging with rotation:

# Configure file logging with rotation (10MB per file, keep 5 backups)
setup_logger(
    level=logging.DEBUG,
    log_file="/var/log/adaptive_executor.log",
    max_bytes=10*1024*1024,  # 10MB
    backup_count=5
)

Environment Variables

You can control logging via environment variables:

# Set log level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
ADAPTIVE_EXECUTOR_LOG_LEVEL=WARNING

# Enable file logging
ADAPTIVE_EXECUTOR_LOG_FILE=/path/to/logfile.log

# Set max log file size (in bytes)
ADAPTIVE_EXECUTOR_LOG_MAX_BYTES=10485760  # 10MB

# Set number of backup files to keep
ADAPTIVE_EXECUTOR_LOG_BACKUP_COUNT=5

Disabling Logging Completely

To completely disable all logging:

import logging
logging.getLogger('adaptive_executor').addHandler(logging.NullHandler())
logging.getLogger('adaptive_executor').propagate = False

Documentation

Full documentation is available at https://Teut2711.github.io/adaptive-executor

License

MIT License - see LICENSE file for details.

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