# 🌟 Introduction

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> UniDep streamlines Python project dependency management by unifying Conda and Pip packages in a single system.
> [Learn when to use UniDep](faq.md#q-when-to-use-unidep) in our [FAQ](faq.md#faq).

Handling dependencies in Python projects can be challenging, especially when juggling Python and non-Python packages.
This often leads to confusion and inefficiency, as developers juggle between multiple dependency files.

- **📝 Unified Dependency File**: Use either `requirements.yaml` or `pyproject.toml` to manage both Conda and Pip dependencies in one place.
- **⚙️ Build System Integration**: Integrates with Setuptools and Hatchling for automatic dependency handling during `pip install ./your-package`.
- **💻 One-Command Installation**: `unidep install` handles Conda, Pip, and local dependencies effortlessly.
- **⚡️ Fast Pip Operations**: Leverages `uv` (if installed) for faster pip installations.
- **🏢 Monorepo-Friendly**: Render (multiple) `requirements.yaml` or `pyproject.toml` files into one Conda `environment.yaml` file and maintain fully consistent global *and* per sub package `conda-lock` files.
- **🌍 Platform-Specific Support**: Specify dependencies for different operating systems or architectures.
- **🔧 `pip-compile` Integration**: Generate fully pinned `requirements.txt` files from `requirements.yaml` or `pyproject.toml` files using `pip-compile`.
- **🔒 Integration with `conda-lock`**: Generate fully pinned `conda-lock.yml` files from (multiple) `requirements.yaml` or `pyproject.toml` file(s), leveraging `conda-lock`.
- **🤓 Nerd stats**: written in Python, >99% test coverage, fully-typed, all Ruff's rules enabled, easily extensible, and minimal dependencies

`unidep` is designed to make dependency management in Python projects as simple and efficient as possible.
Try it now and streamline your development process!

```{tip}
Check out the [example `requirements.yaml` and `pyproject.toml` below](requirementsyaml-and-pyprojecttoml-structure.md#example).
```

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