Набор простых и удобных утилит для Python, который избавляет от рутины при работе с конфигурацией и логированием в новых проектах.
Project description
chutils: Stop the Routine!
chutils is a set of simple utilities for Python designed to eliminate the repetitive setup of configuration, logging, and secrets in your projects.
Start a new project and focus on what matters, not the routine.
Full documentation is available on our website (currently in Russian).
The Problem
Every time you start a new project, you have to solve the same tasks:
- How to conveniently read settings from a configuration file?
- How to configure logging to write messages to both the console and a file with daily rotation?
- How to securely store API keys without hardcoding them in the code?
- How to make it all work "out of the box" without manually defining paths?
chutils offers ready-made solutions for all these problems.
Key Features
- ✨ Zero Configuration: The library automatically finds your project root and the
config.ymlorconfig.inifile. It uses lazy initialization — no heavy operations until you actually need them. - ⚙️ Flexible Configuration: Support for
YAMLandINIformats. Simple functions for retrieving typed data. - ✍️ Advanced Logger: The
setup_logger()function configures logging to the console and rotating files out of the box. It returns a custom logger with additional debug levels (devdebug,mediumdebug). - 🔒 Secure Secret Storage: The
secret_managermodule provides a simple interface for saving and retrieving secrets via the systemkeyring, with a fallback to.envfiles. - 🔄 Hot-Reload: Support for automatic configuration reloading on file changes without restart (requires
pip install chutils[watch]). - ⚡ Async Ready: Most core functions have asynchronous versions (prefixed with
a) for non-blocking execution. - 🚀 Ready to Use: Just install and use.
Command Line Interface (CLI)
The library provides a chutils console command for convenient secret management without writing code.
Secret Management
# Save a secret to the system storage (keyring)
chutils secrets set MY_API_KEY "super-secret-value"
# Delete a secret
chutils secrets delete MY_API_KEY
# Explicitly specify service name
chutils secrets set DB_PASSWORD "12345" --service my_custom_app
Installation
poetry add chutils
Or using pip:
pip install chutils
Examples
In the /examples folder, you will find ready-to-run scripts demonstrating the library's key features.
Each example focuses on a specific task.
Quick Start
1. Working with Configuration
-
(Optional) Create a
config.ymlfile in your project root:# config.yml Database: host: localhost port: 5432
-
Get values in your code:
from chutils import get_config_value, get_config_int db_host = get_config_value("Database", "host", fallback="127.0.0.1") db_port = get_config_int("Database", "port", fallback=5432)
Validation via Pydantic (Optional)
For strict typing and validation, you can use Pydantic models (requires
pip install chutils[pydantic]):from pydantic import BaseModel from chutils import get_config class AppConfig(BaseModel): app_name: str version: str # Returns an instance of AppConfig cfg = get_config(model=AppConfig) print(cfg.app_name)
You can also validate specific sections:
from chutils import get_config_section db_cfg = get_config_section("Database", model=MyDbModel)
Overriding Configuration with Local Files (
config.local.yml)You can create a
config.local.ymlnext to your main file. Values from the local file will override corresponding values from the main file. This is perfect for local development or storing sensitive data (ensure*.local.*is in your.gitignore).
2. Hot-Reload
You can make your application react to configuration file changes in real-time.
from chutils import start_config_watcher, on_config_change, get_config_value
def reload_logic():
print("Configuration updated!")
# Update app state here
db_url = get_config_value("Database", "url")
# Register callback
on_config_change(reload_logic)
# Start watcher (requires watchdog package)
start_config_watcher()
To use this feature, install watchdog:
pip install chutils[watch]
3. Logging Setup
-
Configure and use the logger:
from chutils import setup_logger, ChutilsLogger # Automatically reads settings from [Logging] section in config.yml logger: ChutilsLogger = setup_logger() logger.info("Application started.") logger.devdebug("Deep debug message (level 9).")
Structured Logging (JSON)
If you need to output logs in JSON format for ELK, Splunk, or cloud logging (requires
pip install chutils[json]):# Via code logger = setup_logger(json_format=True) # Or via config in the [Logging] section # json_format: true
Contextual Logging (ContextVar)
You can bind metadata to the current execution context (thread or coroutine), and it will be automatically included in all log messages.
from chutils import setup_logger, bind_context logger = setup_logger() # Bind request ID and user to the current context bind_context(request_id="REQ-123", user="admin") logger.info("Action performed") # Text: ... [request_id=REQ-123 user=admin] Action performed # JSON: {..., "message": "Action performed", "context": {"request_id": "REQ-123", "user": "admin"}}
Controlling Logging via Environment Variables
CH_LOG_JSON=true: Forces JSON format.CH_LOG_NO_TIME=true: Removes the date/time from the log format (for clean Docker logs).CH_LOG_NO_FILE=true: Disables creating log files.
These variables have highest priority and override any code or config settings.
3. Secret Management
SecretManager looks for secrets in the following order: Keyring > .env File > Environment Variables.
from chutils import SecretManager
secrets = SecretManager("my_awesome_app")
# Save once
secrets.save_secret("API_KEY", "secret-value-123")
# Use everywhere
key = secrets.get_secret("API_KEY")
Disabling Keyring (Optional)
In environments like Docker or CI/CD where keyring is unavailable, you can suppress warnings and skip the check:
- Set
CH_DISABLE_KEYRING_WARNING=truein environment. - Or add
disable_keyring: trueundersecretssection inconfig.yml.
API Overview
Configuration (chutils.config)
get_config_value(section, key, fallback)/aget_config()get_config_int,get_config_boolean,get_config_list,get_config_pathsave_config_value(section, key, value, notify=True)/asave_config_value()- Use
notify=Falseto update the file without triggering Hot-Reload callbacks.
Logging (chutils.logger)
setup_logger(name, log_level, log_file_name, rotation_type, compress, ...)- Levels:
logger.devdebug(9),logger.mediumdebug(15), and all standard ones.
Secret Management (chutils.secret_manager)
SecretManager(service_name, prefix)save_secret/asave_secretget_secret/aget_secretdelete_secret/adelete_secret
Decorators (chutils.decorators)
@log_function_details: Logs arguments, execution time, and result (usesDEVDEBUGlevel).@timeout(seconds, fallback): Limits function execution time. Supports sync/async and optional fallback.@retry: Automatically retries a function if it fails. Supports sync/async, backoff, jitter, and exception filtering.
Example of @retry usage:
from chutils.decorators import retry
@retry(retries=3, delay=1.0, backoff=2.0)
def fetch_data():
# Will be retried up to 3 times on any Exception
...
License
The project is distributed under the MIT License.
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