Automatey is a lightweight Python library designed to simplify the management of configurations and the execution of tasks as a Directed Acyclic Graph (DAG). It provides robust configuration handling, flexible logging, and utility features to streamline automation workflows.

Features

• Configuration Management: Automatically discovers and loads configuration files (automatey.toml) from the current or parent directories.
• Logging: Configurable logging with support for both console and file handlers.
• Singleton Design: Ensures only one instance of the Automatey class is created during runtime.
• Execution Timer: Tracks and logs the total execution time of your script when it exits.

Installation

Automatey is not yet published to PyPI, so you can clone this repository to use it locally:

git clone https://github.com/your-username/automatey.git
cd automatey

Ensure you are using Python 3.11 or later, as specified in the .python-version file.

Usage

Getting Started

1. Initialize Automatey: Import and create an instance of the Automatey class. This will automatically load the configuration file (automatey.toml) and set up logging.

   from automatey import Automatey
   
   auto = Automatey()

2. Access Configuration: Use the get_config method to retrieve values from the loaded configuration.

   # Example: Access the DAG name from the configuration
   dag_name = auto.get_config('automatey', 'dag', 'name')
   print(f"DAG Name: {dag_name}")

3. Logging: Automatey provides a pre-configured logger. Use it to log messages.

   auto.logger.info("This is an info log message.")
   auto.logger.error("This is an error log message.")

4. Execution Timer: Automatey automatically logs the total execution time of your script when it exits.

Configuration File

Automatey expects a TOML configuration file named automatey.toml. Here’s an example configuration:

foo = "bar"

[automatey.dag]
name = "ETL Pipeline"

[[automatey.dag.tasks]]
name = "extract"
depends_on = []

[[automatey.dag.tasks]]
name = "transform"
depends_on = ["extract"]

[[automatey.dag.tasks]]
name = "load"
depends_on = ["transform"]

Logging Configuration

You can customize logging behavior in the automatey.toml file. For example:

[automatey.logging]
enable_file_handler = true
filename = "./Log/automatey_<YYYY><MM><DD>.log"
filemode = "a"
format = "%(asctime)s: %(levelname)s: %(message)s"
datefmt = "%Y-%m-%d %H:%M:%S"
encoding = "utf-8"
level = "INFO"

• enable_file_handler: Enables logging to a file.
• filename: Specifies the log file name. You can use placeholders like <YYYY>, <MM>, <DD>, <DATE>, and <TIME> for dynamic filenames.
• level: Sets the logging level (e.g., INFO, DEBUG, ERROR).

Example Script

Here’s a complete example of using Automatey:

from automatey import Automatey

# Initialize Automatey
auto = Automatey()

# Access configuration
dag_name = auto.get_config('automatey', 'dag', 'name')
print(f"DAG Name: {dag_name}")

# Log messages
auto.logger.info("Starting the ETL pipeline...")
auto.logger.info(f"DAG Name: {dag_name}")
auto.logger.info("ETL pipeline completed successfully.")

Project Structure

# Updated to specify language as plaintext
plaintext
automatey/
├── LICENSE
├── README.md
├── automatey.toml
├── pyproject.toml
├── src/
│   └── automatey/
│       ├── __init__.py
│       ├── automatey.py
│       ├── cli.py
│       └── ui.py
├── tests/
│   └── test_automatey.py
└── Log/
    ├── automatey_20250922.log
    └── automatey_20250928.log

Testing

Automatey includes a basic test file in tests/test_automatey.py. To run the test:

python -m unittest discover tests

Future Enhancements

• Task Execution: Extend Automatey to execute tasks defined in the DAG configuration.
• CLI Support: Implement a command-line interface for managing tasks.
• UI Integration: Build a user interface for visualizing and managing DAGs.

License

This project is licensed under the MIT License. See the LICENSE file for details.