semantic-pydantic 0.0.4
Integration between the Bioregistry and Pydantic type annotations.
Requires Python: >=3.10
Keywords: snekpack, cookiecutter, pydantic, bioregistry, fastapi

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<p align="center">
  <img src="https://github.com/cthoyt/semantic-pydantic/raw/main/docs/source/logo.png" height="150">
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<h1 align="center">
  Semantic Pydantic
</h1>

<p align="center">
    <a href="https://github.com/cthoyt/semantic-pydantic/actions/workflows/tests.yml">
        <img alt="Tests" src="https://github.com/cthoyt/semantic-pydantic/actions/workflows/tests.yml/badge.svg" /></a>
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Annotate your data models in Pydantic and APIs in FastAPI with the Bioregistry to make them more FAIR

## 💪 Getting Started

You can use one of the several extensions to Pydantic and FastAPI's `Field` classes.

```python
from pydantic import BaseModel, Field

from semantic_pydantic import SemanticField


class Scholar(BaseModel):
    """A model representing a researcher, who might have several IDs on different services."""

    orcid: str = SemanticField(..., prefix="orcid")
    name: str = Field(..., example="Charles Tapley Hoyt")

    wos: str | None = SemanticField(default=None, prefix="wos.researcher")
    dblp: str | None = SemanticField(default=None, prefix="dblp.author")
    github: str | None = SemanticField(default=None, prefix="github")
    scopus: str | None = SemanticField(default=None, prefix="scopus")
    semion: str | None = SemanticField(default=None, prefix="semion")
    publons: str | None = SemanticField(default=None, prefix="publons.researcher")
    authorea: str | None = SemanticField(default=None, prefix="authorea.author")
```

Similarly, this can be used in FastAPI.

```python
from fastapi import FastAPI
from semantic_pydantic import SemanticPath

app = FastAPI(title="Semantic Pydantic Demo")
Scholar = ...  # defined before


@app.get("/api/orcid/{orcid}", response_model=Scholar)
def get_scholar_from_orcid(orcid: str = SemanticPath(prefix="orcid")):
    """Get xrefs for a researcher in Wikidata, given ORCID identifier."""
    ...  # full implementation in https://github.com/cthoyt/semantic-pydantic
    return Scholar(...)
```

Here's what the Swagger UI looks like, including all the annotations on both the data model and endpoint arguments.

![](/docs/source/img/api-1.png)

The demo can be run by cloning the repository, installing its requirements, and
running the self-contained `demo.py`.

## 🚀 Installation

The most recent release can be installed from
[PyPI](https://pypi.org/project/semantic_pydantic/) with:

```console
$ python3 -m pip install semantic_pydantic
```

The most recent code and data can be installed directly from GitHub with:

```shell
$ python3 -m pip install git+https://github.com/cthoyt/semantic-pydantic.git
```

## 👐 Contributing

Contributions, whether filing an issue, making a pull request, or forking, are appreciated. See
[CONTRIBUTING.md](https://github.com/cthoyt/semantic-pydantic/blob/master/.github/CONTRIBUTING.md)
for more information on getting involved.

## 👋 Attribution

### ⚖️ License

The code in this package is licensed under the MIT License.

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### 📖 Citation

Citation goes here!
-->

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### 🎁 Support

This project has been supported by the following organizations (in alphabetical order):

- [Biopragmatics Lab](https://biopragmatics.github.io)

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### 💰 Funding

This work was initially funded by the Chan Zuckerberg Initiative (CZI) under award 2023-329850.

### 🍪 Cookiecutter

This package was created with [@audreyfeldroy](https://github.com/audreyfeldroy)'s
[cookiecutter](https://github.com/cookiecutter/cookiecutter) package using [@cthoyt](https://github.com/cthoyt)'s
[cookiecutter-snekpack](https://github.com/cthoyt/cookiecutter-snekpack) template.

## 🛠️ For Developers

<details>
  <summary>See developer instructions</summary>

The final section of the README is for if you want to get involved by making a code contribution.

### Development Installation

To install in development mode, use the following:

```console
git clone git+https://github.com/cthoyt/semantic-pydantic.git
cd semantic-pydantic
python3 -m pip install -e .
```

### Updating Package Boilerplate

This project uses `cruft` to keep boilerplate (i.e., configuration, contribution guidelines, documentation
configuration)
up-to-date with the upstream cookiecutter package. Update with the following:

```console
python3 -m pip install cruft
cruft update
```

More info on Cruft's update command is
available [here](https://github.com/cruft/cruft?tab=readme-ov-file#updating-a-project).

### 🥼 Testing

After cloning the repository and installing `tox` with
`python3 -m pip install tox tox-uv`,
the unit tests in the `tests/` folder can be run reproducibly with:

```console
tox -e py
```

Additionally, these tests are automatically re-run with each commit in a
[GitHub Action](https://github.com/cthoyt/semantic-pydantic/actions?query=workflow%3ATests).

### 📖 Building the Documentation

The documentation can be built locally using the following:

```console
git clone git+https://github.com/cthoyt/semantic-pydantic.git
cd semantic-pydantic
tox -e docs
open docs/build/html/index.html
```

The documentation automatically installs the package as well as the `docs`
extra specified in the [`pyproject.toml`](pyproject.toml). `sphinx` plugins
like `texext` can be added there. Additionally, they need to be added to the
`extensions` list in [`docs/source/conf.py`](docs/source/conf.py).

The documentation can be deployed to [ReadTheDocs](https://readthedocs.io) using
[this guide](https://docs.readthedocs.io/en/stable/intro/import-guide.html).
The [`.readthedocs.yml`](.readthedocs.yml) YAML file contains all the configuration you'll need.
You can also set up continuous integration on GitHub to check not only that
Sphinx can build the documentation in an isolated environment (i.e., with `tox -e docs-test`)
but also that [ReadTheDocs can build it too](https://docs.readthedocs.io/en/stable/pull-requests.html).

#### Configuring ReadTheDocs

1. Log in to ReadTheDocs with your GitHub account to install the integration
   at https://readthedocs.org/accounts/login/?next=/dashboard/
2. Import your project by navigating to https://readthedocs.org/dashboard/import then clicking the plus icon next to
   your repository
3. You can rename the repository on the next screen using a more stylized name (i.e., with spaces and capital letters)
4. Click next, and you're good to go!

### 📦 Making a Release

#### Configuring Zenodo

[Zenodo](https://zenodo.org) is a long-term archival system that assigns a DOI to each release of your package.

1. Log in to Zenodo via GitHub with this link: https://zenodo.org/oauth/login/github/?next=%2F. This brings you to a
   page that lists all of your organizations and asks you to approve installing the Zenodo app on GitHub. Click "grant"
   next to any organizations you want to enable the integration for, then click the big green "approve" button. This
   step only needs to be done once.
2. Navigate to https://zenodo.org/account/settings/github/, which lists all of your GitHub repositories (both in your
   username and any organizations you enabled). Click the on/off toggle for any relevant repositories. When you make
   a new repository, you'll have to come back to this

After these steps, you're ready to go! After you make "release" on GitHub (steps for this are below), you can navigate
to https://zenodo.org/account/settings/github/repository/cthoyt/semantic-pydantic
to see the DOI for the release and link to the Zenodo record for it.

#### Registering with the Python Package Index (PyPI)

You only have to do the following steps once.

1. Register for an account on the [Python Package Index (PyPI)](https://pypi.org/account/register)
2. Navigate to https://pypi.org/manage/account and make sure you have verified your email address. A verification email
   might not have been sent by default, so you might have to click the "options" dropdown next to your address to get to
   the "re-send verification email" button
3. 2-Factor authentication is required for PyPI since the end of 2023 (see
   this [blog post from PyPI](https://blog.pypi.org/posts/2023-05-25-securing-pypi-with-2fa/)). This means
   you have to first issue account recovery codes, then set up 2-factor authentication
4. Issue an API token from https://pypi.org/manage/account/token

#### Configuring your machine's connection to PyPI

You have to do the following steps once per machine.

```console
$ uv tool install keyring
$ keyring set https://upload.pypi.org/legacy/ __token__
$ keyring set https://test.pypi.org/legacy/ __token__
```

Note that this deprecates previous workflows using `.pypirc`.

#### Uploading to PyPI

After installing the package in development mode and installing
`tox` with `python3 -m pip install tox tox-uv`,
run the following from the console:

```console
tox -e finish
```

This script does the following:

1. Uses [bump-my-version](https://github.com/callowayproject/bump-my-version) to switch the version number in
   the `pyproject.toml`, `CITATION.cff`, `src/semantic_pydantic/version.py`,
   and [`docs/source/conf.py`](docs/source/conf.py) to not have the `-dev` suffix
2. Packages the code in both a tar archive and a wheel using
   [`uv build`](https://docs.astral.sh/uv/guides/publish/#building-your-package)
3. Uploads to PyPI using [`uv publish`](https://docs.astral.sh/uv/guides/publish/#publishing-your-package).
4. Push to GitHub. You'll need to make a release going with the commit where the version was bumped.
5. Bump the version to the next patch. If you made big changes and want to bump the version by minor, you can
   use `tox -e bumpversion -- minor` after.

#### Releasing on GitHub

1. Navigate
   to https://github.com/cthoyt/semantic-pydantic/releases/new
   to draft a new release
2. Click the "Choose a Tag" dropdown and select the tag corresponding to the release you just made
3. Click the "Generate Release Notes" button to get a quick outline of recent changes. Modify the title and description
   as you see fit
4. Click the big green "Publish Release" button

This will trigger Zenodo to assign a DOI to your release as well.

</details>