Modenization

[emptymalei]

No description provided.

[Copilot]

Pull Request Overview

This PR modernizes the Python package by migrating from setup.py-based configuration to Poetry's pyproject.toml format. The changes streamline dependency management and introduce modern development tooling.

Key changes:

• Migrated from setup.py to Poetry configuration with pyproject.toml
• Replaced requirements files with Poetry dependency groups
• Added pre-commit hooks for code quality automation

Reviewed Changes

Copilot reviewed 10 out of 12 changed files in this pull request and generated 1 comment.

Show a summary per file

File	Description
setup.py	Removed legacy setuptools configuration
requirements.extras.txt	Removed in favor of Poetry dependency groups
pyproject.toml	Added Poetry configuration with dependencies and build system
mkdocs.yml	Updated mkdocstrings configuration for modern syntax
haferml/version.py	Removed version file (now managed in pyproject.toml)
haferml/preprocess/pipeline.py	Added new SimpleProcessor class and updated example call
haferml/preprocess/dataframe.py	Added new DataFrame transformation classes
haferml/blend/config.py	Added TrainConfig class for training configuration
haferml/init.py	Removed version import
.pre-commit-config.yaml	Added pre-commit configuration for code quality

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[Copilot]

The TrainConfig class docstring is incomplete. It should include parameter descriptions and usage examples for better API documentation.

Suggested change

	"""
	"""
	TrainConfig manages configuration files for the training stage.
	This class provides methods to initialize, read, update, and save configuration files used during training.
	:param config_path: Path to the configuration file. Can be a local path or a cloud path.
	:type config_path: AnyPath
	Example usage:
	>>> from haferml.blend.config import TrainConfig
	>>> tc = TrainConfig("train_config.json")
	>>> tc.init() # Initializes an empty config file
	>>> tc.save({"lr": 0.001, "epochs": 10})
	>>> print(tc.config)
	{'lr': 0.001, 'epochs': 10}
	>>> tc.update({"lr": 0.002})
	>>> print(tc.config)
	{'lr': 0.002, 'epochs': 10}
	"""