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# Tutorial: Integrating multiple packages in a workspace | ||
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In this tutorial, we will show you how to integrate multiple pixi packages into a single workspace. | ||
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## Why is this useful? | ||
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Pixi builds upon the conda ecosystem, which allows you to create a Python environment with all the dependencies you need. | ||
Unlike PyPI, the conda ecosystem is cross-language and also offers packages written in Rust, R, C, C++ and many other languages. | ||
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By building a Python package with pixi, you can: | ||
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1. manage Python packages and packages written in other languages in the same workspace | ||
2. build both conda and Python packages with the same tool | ||
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In this tutorial we will focus on point 1. | ||
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## Let's get started | ||
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First, we create a simple Python package with a `pyproject.toml` and a single Python file. | ||
The package will be called `rich_example`, so we will create the following structure | ||
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```shell | ||
├── src # (1)! | ||
│ └── rich_example | ||
│ └── __init__.py | ||
└── pyproject.toml | ||
``` | ||
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1. This project uses a src-layout, but pixi supports both [flat- and src-layouts](https://packaging.python.org/en/latest/discussions/src-layout-vs-flat-layout/#src-layout-vs-flat-layout). | ||
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The Python package has a single function `main`. | ||
Calling that, will print a table containing the name, age and city of three people. | ||
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```py title="src/rich_example/__init__.py" | ||
--8<-- "docs/source_files/pixi_projects/pixi_build_python/src/rich_example/__init__.py" | ||
``` | ||
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The metadata of the Python package is defined in `pyproject.toml`. | ||
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```toml title="pyproject.toml" | ||
--8<-- "docs/source_files/pixi_projects/pixi_build_python/pyproject.toml" | ||
``` | ||
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1. We use the `rich` package to print the table in the terminal. | ||
2. By specifying a script, the executable `rich-example-main` will be available in the environment. When being called it will in return call the `main` function of the `rich_example` module. | ||
3. One can choose multiple backends to build a Python package, we choose `hatchling` which works well without additional configuration. | ||
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### Adding a `pixi.toml` | ||
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What we have in the moment, constitutes a full Python package. | ||
It could be uploaded to [PyPI](https://pypi.org/) as-is. | ||
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However, we still need a tool to manage our environments and if we want other pixi projects to depend on our tool, we need to include more information. | ||
We will do exactly that by creating a `pixi.toml`. | ||
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!!! note | ||
The pixi manifest can be in its own `pixi.toml` file or integrated in `pyproject.toml` | ||
In this tutorial, we will use `pixi.toml`. | ||
If you want everything integrated in `pyproject.toml` just copy the content of `pixi.toml` in this tutorial to your `pyproject.toml` and append `tool.pixi` to each table. | ||
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The file structure will then look like this: | ||
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```shell | ||
├── src | ||
│ └── rich_example | ||
│ └── __init__.py | ||
├── pixi.toml | ||
└── pyproject.toml | ||
``` | ||
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This is the content of the `pixi.toml`: | ||
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```toml title="pixi.toml" | ||
--8<-- "docs/source_files/pixi_projects/pixi_build_python/pixi.toml" | ||
``` | ||
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1. In `workspace` information is set that is shared across all packages in the workspace. | ||
2. In `dependencies` you specify all of your pixi packages. Here, this includes only our own package that is defined further below under `package` | ||
3. We define a task that runs the `rich-example-main` executable we defined earlier. You can learn more about tasks in this [section](../features/advanced_tasks.md) | ||
4. In `package` we define the actual pixi package. This information will be used when other pixi packages or workspaces depend on our package or when we upload it to a conda channel. | ||
5. The same way, Python uses build backends to build a Python package, pixi uses build backends to build pixi packages. `pixi-build-python` creates a pixi package out of a Python package. | ||
6. In `host-dependencies`, we add Python dependencies that are necessary to build the Python package. By adding them here as well, the dependencies will come from the conda channel rather than PyPI. | ||
7. In `run-dependencies`, we add the Python dependencies needed during runtime. | ||
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When we now run `pixi run start`, we get the following output: | ||
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``` | ||
┏━━━━━━━━━━━━━━┳━━━━━┳━━━━━━━━━━━━━┓ | ||
┃ name ┃ age ┃ city ┃ | ||
┡━━━━━━━━━━━━━━╇━━━━━╇━━━━━━━━━━━━━┩ | ||
│ John Doe │ 30 │ New York │ | ||
│ Jane Smith │ 25 │ Los Angeles │ | ||
│ Tim de Jager │ 35 │ Utrecht │ | ||
└──────────────┴─────┴─────────────┘ | ||
``` | ||
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## Conclusion | ||
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In this tutorial, we created a pixi package based on Python. | ||
It can be used as-is, to upload to a conda channel or to PyPI. | ||
In another tutorial we will learn how to add multiple pixi packages to the same workspace and let one pixi package use another. | ||
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Thanks for reading! Happy Coding 🚀 | ||
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Any questions? Feel free to reach out or share this tutorial on [X](https://twitter.com/prefix_dev), [join our Discord](https://discord.gg/kKV8ZxyzY4), send us an [e-mail](mailto:hi@prefix.dev) or follow our [GitHub](https://github.com/prefix-dev). |
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