Metadata-Version: 2.4
Name: pydantic_espresso
Version: 0.0.1.dev0
Summary: Pydantic models for Quantum ESPRESSO
Keywords: snekpack,cookiecutter
Author: Edward Linscott
Author-email: Edward Linscott <edwardlinscott@gmail.com>
License-File: LICENSE
Classifier: Development Status :: 1 - Planning
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Framework :: Pytest
Classifier: Framework :: tox
Classifier: Framework :: Sphinx
Classifier: Natural Language :: English
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Typing :: Typed
Requires-Dist: pydantic
Requires-Dist: packaging
Requires-Dist: click ; extra == 'dev'
Requires-Dist: python-gitlab ; extra == 'dev'
Requires-Dist: defusedxml>=0.7.1 ; extra == 'dev'
Maintainer: Edward Linscott
Maintainer-email: Edward Linscott <edwardlinscott@gmail.com>
Requires-Python: >=3.10
Project-URL: Bug Tracker, https://github.com/elinscott/pydantic-espresso/issues
Project-URL: Homepage, https://github.com/elinscott/pydantic-espresso
Project-URL: Repository, https://github.com/elinscott/pydantic-espresso.git
Project-URL: Documentation, https://pydantic_espresso.readthedocs.io
Project-URL: Funding, https://github.com/sponsors/elinscott
Provides-Extra: dev
Description-Content-Type: text/markdown

<!--
<p align="center">
  <img src="https://github.com/elinscott/pydantic-espresso/raw/main/docs/source/logo.png" height="150">
</p>
-->

<h1 align="center">
  pydantic-espresso
</h1>

<p align="center">
    <a href="https://github.com/elinscott/pydantic-espresso/actions/workflows/tests.yml">
        <img alt="Tests" src="https://github.com/elinscott/pydantic-espresso/actions/workflows/tests.yml/badge.svg" /></a>
    <a href="https://pypi.org/project/pydantic_espresso">
        <img alt="PyPI" src="https://img.shields.io/pypi/v/pydantic_espresso" /></a>
    <a href="https://pypi.org/project/pydantic_espresso">
        <img alt="PyPI - Python Version" src="https://img.shields.io/pypi/pyversions/pydantic_espresso" /></a>
    <a href="https://github.com/elinscott/pydantic-espresso/blob/main/LICENSE">
        <img alt="PyPI - License" src="https://img.shields.io/pypi/l/pydantic_espresso" /></a>
    <a href='https://pydantic_espresso.readthedocs.io/en/latest/?badge=latest'>
        <img src='https://readthedocs.org/projects/pydantic_espresso/badge/?version=latest' alt='Documentation Status' /></a>
    <a href="https://codecov.io/gh/elinscott/pydantic-espresso/branch/main">
        <img src="https://codecov.io/gh/elinscott/pydantic-espresso/branch/main/graph/badge.svg" alt="Codecov status" /></a>  
    <a href="https://github.com/cthoyt/cookiecutter-python-package">
        <img alt="Cookiecutter template from @cthoyt" src="https://img.shields.io/badge/Cookiecutter-snekpack-blue" /></a>
    <a href="https://github.com/astral-sh/ruff">
        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json" alt="Ruff" style="max-width:100%;"></a>
    <a href="https://github.com/elinscott/pydantic-espresso/blob/main/.github/CODE_OF_CONDUCT.md">
        <img src="https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg" alt="Contributor Covenant"/></a>
    <!-- uncomment if you archive on zenodo
    <a href="https://zenodo.org/badge/latestdoi/XXXXXX">
        <img src="https://zenodo.org/badge/XXXXXX.svg" alt="DOI"></a>
    -->
</p>

Pydantic models for `Quantum ESPRESSO`.

The models are auto-generated from the `INPUT_*.def` files shipped with
Quantum ESPRESSO. Supported QE versions are 7.6 and newer (the schema for
older releases lacks the structured `<units>`, `<dimensionality>`, and
`<default kind="...">` metadata that the generator depends on).

## 💪 Getting Started

```python
from pydantic_espresso.models.pw.develop import PWInput

inp = PWInput(
    system={"ibrav": 0, "nat": 1, "ntyp": 1, "ecutwfc": 30.0},
    cell_parameters={"unit": "alat", "vectors": [[1, 0, 0], [0, 1, 0], [0, 0, 1]]},
    atomic_positions={
        "unit": "alat",
        "positions": [{"species": "H", "position": [0.0, 0.0, 0.0]}],
    },
    k_points={"kind": "gamma"},
)

# Pydantic enforces both the QE input schema and the field constraints:
inp.system.ibrav = -1          # ValidationError: invalid Bravais lattice index
inp.system.nbnd = "a"          # ValidationError: not an int
inp.control.calculation = "bands"   # OK
```

Each numeric field carries its physical units and dimensionality as
`Quantity` metadata, threaded into both the pydantic field info and the
JSON schema:

```python
from pydantic_espresso.models.pw.develop import SystemNamelist
from pydantic_espresso.quantity import quantity_for

q = quantity_for(SystemNamelist.model_fields["ecutwfc"])
# Quantity(units='Ry', dimensionality='energy')

PWInput.model_json_schema()["$defs"]["SystemNamelist"]["properties"]["ecutwfc"]
# {'type': 'number', 'units': 'Ry', 'dimensionality': 'energy', ...}
```

QE namelist branches with mutually-exclusive layouts (e.g. PP's `PLOT`
namelist discriminated on `iflag`) are exposed as pydantic discriminated
unions, so the right variant is picked automatically from the input data.

### Readable error reports

Construction raises a standard `pydantic.ValidationError`. Pass the caught
error to `pydantic_espresso.errors.explain` for a grouped, recursive summary
that names each missing input together with its type, units, and help text:

```python
from pydantic import ValidationError
from pydantic_espresso.errors import explain
from pydantic_espresso.models.pw.develop import PWInput

try:
    inp = PWInput(
        system={"ibrav": 0, "ecutwfc": 30.0},                     # missing nat, ntyp
        cell_parameters={"vectors": [[1, 0, 0], [0, 1, 0], [0, 0, 1]]},  # missing 'unit'
        k_points={"kind": "automatic"},                           # missing grid
        # atomic_positions omitted entirely
    )
except ValidationError as exc:
    print(explain(exc, PWInput))
```

```text
PWInput is missing required inputs:
  system:
      - nat (int): number of atoms in the unit cell (ALL atoms, except if space_group is set, in
        which case, INEQUIVALENT atoms)
      - ntyp (int): number of types of atoms in the unit cell
  atomic_positions: required — choose 'unit': ['alat', 'bohr', 'angstrom', 'crystal', 'crystal_sg']
  k_points [kind='automatic']:
      - grid (tuple[int, int, int]): Monkhorst-Pack mesh dimensions (nk1, nk2, nk3): number of
        k-points along each reciprocal-lattice direction of the uniform grid.
  cell_parameters: missing discriminator 'unit' (one of ['alat', 'bohr', 'angstrom'])
```

### Command Line Interface

The `pydantic_espresso` command line tool ships with the package but requires
the optional `dev` extra (which pulls in `click`, `python-gitlab`, and
`defusedxml`). Install it with `pip install pydantic_espresso[dev]` or
`uv pip install "pydantic_espresso[dev]"`.

It can be used from the console with the `--help` flag to show all subcommands:

```console
$ pydantic_espresso --help
```

The JSON schema for `pw.x` can be generated with the command

```console
$ pydantic_espresso schema pw
```

## 🚀 Installation

<!-- Uncomment this section after your first ``tox -e finish``
The most recent release can be installed from
[PyPI](https://pypi.org/project/pydantic_espresso/) with uv:

```console
$ uv pip install pydantic_espresso
```

or with pip:

```console
$ python3 -m pip install pydantic_espresso
```
-->

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

```console
$ uv pip install git+https://github.com/elinscott/pydantic-espresso.git
```

or with pip:

```console
$ python3 -m pip install git+https://github.com/elinscott/pydantic-espresso.git
```

## 👐 Contributing

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

## 👋 Attribution

### ⚖️ License

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

<!--
### 📖 Citation

Citation goes here!
-->

<!--
### 🎁 Support

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

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

-->

<!--
### 💰 Funding

This project has been supported by the following grants:

| Funding Body  | Program                                                      | Grant Number |
|---------------|--------------------------------------------------------------|--------------|
| Funder        | [Grant Name (GRANT-ACRONYM)](https://example.com/grant-link) | ABCXYZ       |
-->

### 🍪 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/elinscott/pydantic-espresso.git
$ cd pydantic-espresso
$ uv pip install -e .
```

Alternatively, install using pip:

```console
$ 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. Install cruft with either `uv tool install cruft` or
`python3 -m pip install cruft` then run:

```console
$ 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
`uv tool install tox --with tox-uv` or
`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/elinscott/pydantic-espresso/actions?query=workflow%3ATests).

### 📖 Building the Documentation

The documentation can be built locally using the following:

```console
$ git clone git+https://github.com/elinscott/pydantic-espresso.git
$ cd pydantic-espresso
$ 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/elinscott/pydantic-espresso
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 `uv tool install tox --with tox-uv` or
`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/pydantic_espresso/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/elinscott/pydantic-espresso/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>
