Sortium 2.1.0

A utility to sort files by type and date.

Sortium

Sortium is a high-performance Python utility for rapidly organizing file systems. It emphasizes a safe, preview-first workflow that lets you plan and review categorized moves (by type, date, or regex) before anything changes on disk.

Designed for both speed and safety, it is memory-efficient for handling massive directories and automatically prevents file overwrites.

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Table of Contents

• Key Features
• Installation
• Getting Started: Usage Examples
• Running Tests
• Documentation
• Contributing
• Author
• License

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Key Features

• Plan-first workflow – Every sort emits an editable JSON plan so you can audit, tweak, version, or share the intended moves before running them.
• Memory-efficient design – Uses generators and streaming I/O so it scales to very large trees without exhausting RAM.
• Flexible sorting strategies – Built-in helpers for sorting by file type, modification date, or arbitrary regex patterns.
• Collision-safe moves – Automatically generates unique destination names (e.g., image (1).jpg) to avoid overwriting files.
• In-place or cross-volume moves – Choose to tidy a directory in situ or relocate everything into a dedicated archive folder.
• Utility toolkit – FileUtils exposes recursive scanners, directory flattening, tree export, and reversible plan execution.

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Installation

From PyPI

To install the latest stable version from PyPI:

pip install sortium

From Source

To install the latest development version from the repository:

git clone https://github.com/Sarthak-G0yal/Sortium.git
cd Sortium
pip install -e .

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Getting Started: Usage Examples

Here are a few examples to get you started quickly.

Example 1: Sort Files by Type

This is the most common use case. It now works in two phases: generate a plan, review/edit the JSON (optional), then apply it when you're ready.

from sortium.sorter import Sorter

# The folder you want to clean up
source_directory = "./my_messy_downloads_folder"

# Create a Sorter instance
sorter = Sorter()

# Phase 1: Generate an editable JSON plan
plan_path = sorter.sort_by_type(
  source_directory,
  recursive=True,  # include nested folders
)

# (Optional) Inspect / edit the JSON plan here
# ...

# Phase 2: Apply the plan when you're satisfied
sorter.file_utils.apply_move_plan(str(plan_path))
print(f"Applied plan {plan_path}")

# Need to undo? Re-use the same plan with reverse=True
sorter.file_utils.apply_move_plan(str(plan_path), reverse=True)

# Prefer a shallow cleanup? Drop recursive=True (it defaults to False).

Example 2: Sort Files to a Different Destination

Organize files from a source folder and move the categorized results to a completely different location.

from sortium.sorter import Sorter

source_dir = "./my_source_files"
destination_dir = "./organized_archive"

sorter = Sorter()

# Generate plan targeted at `destination_dir`
plan_path = sorter.sort_by_type(
  source_dir,
  dest_folder_path=destination_dir,
  plan_output="./sorting_plan.json",
  recursive=True,
)

# Review/edit sorting_plan.json if needed, then execute
sorter.file_utils.apply_move_plan(str(plan_path))

Example 3: Advanced Sorting with Regex

Recursively scan a directory and sort files based on custom patterns. This is great for organizing project files, logs, or datasets.

from sortium.sorter import Sorter

project_folder = "./my_data_science_project"
sorted_output = "./sorted_project_files"

# Define categories and their corresponding regex patterns
regex_map = {
    "Datasets": r".*\.csv$",
    "Notebooks": r".*\.ipynb$",
    "Python_Code": r".*\.py$",
    "Final_Reports": r"final_report_.*\.pdf$"
}

sorter = Sorter()
plan_path = sorter.sort_by_regex(project_folder, regex_map, sorted_output)
sorter.file_utils.apply_move_plan(str(plan_path))

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Running Tests

To run the full test suite and generate a coverage report, first install the development dependencies:

pip install pytest pytest-cov

Then, from the project's root directory, run:

pytest --cov=sortium

For more details on the test structure, see the Test Suite README.

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Documentation

This project uses Sphinx for documentation.

• Online Documentation: View Documentation

• To build the documentation locally:

  # Navigate to the docs directory
  cd docs
  # Install documentation requirements
  pip install -r requirements.txt
  # Build the HTML pages
  make html
  

  View the generated files at docs/_build/html/index.html.

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Contributing

Contributions are welcome! Please follow these steps to contribute:

1. Fork the repository.
2. Create a new branch for your feature or fix (feature/my-feature or fix/my-fix).
3. Write tests that cover your changes.
4. Commit your changes using clear, conventional messages.
5. Open a pull request with a detailed description of your work.

Please follow the Conventional Commits specification. Ensure all code is linted and tested before submitting.

• For bugs and feature requests, please open an issue.

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Author

Sarthak Goyal

• Email: [e-mail]

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License

This project is licensed under the GNU General Public License v3.0.