Metadata-Version: 2.3
Name: xpypact
Version: 0.12.9
Summary: "Python workflow framework for FISPACT."
Keywords: nuclide,FISPACT,activation,duckdb,polars
Author: dvp2015
Author-email: dvp2015 <dmitri_portnov@yahoo.com>
License: MIT
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Programming Language :: Python :: 3
Requires-Dist: duckdb>=1.0.0
Requires-Dist: mckit-nuclides>=0.3.2
Requires-Dist: multipledispatch>=0.6.0
Requires-Dist: numpy>=2.3.1
Requires-Dist: polars[all]>=1.12.0
Requires-Dist: pyarrow>=18.0.0
Requires-Dist: msgspec>=0.19.0
Requires-Python: >=3.11, <3.14
Project-URL: Changelog, https://github.com/MC-kit/xpypact/releases
Project-URL: documentation, https://xpypact.readthedocs.io
Project-URL: homepage, https://github.com/MC-kit/xpypact
Project-URL: repository, https://github.com/MC-kit/xpypact
Description-Content-Type: text/x-rst

==============================================================================
*xpypact*: FISPACT output to Polars or DuckDB datasets converter
==============================================================================

Aggregate results of `FISPACT <https://fispact.ukaea.uk/>`_ runs to efficient datasets.


|Maintained| |License| |Versions| |PyPI| |Docs|

.. contents::


.. note::

    This document is in progress.

Description
-----------

The module loads FISPACT JSON output files and converts to `Polars <https://pola.rs/>`_ dataframes
with minor data normalization. The dataframes can be stored either to `parquet <https://parquet.apache.org>`_
files or `DuckDb <https://duckdb.org/>`_ database.
This allows efficient data aggregation and analysis.
**Multiple** JSON files for different
FISPACT runs can be combined using simple additional identification.
So far, we use just two-dimensional identification by material
and *case*. The *case* usually identifies certain neutron flux energy distribution.


Implemented functionality
-------------------------

- export to DuckDB
- export to parquet files
- neutron flux presentation conversion


Installation
------------

From PyPI

.. code-block::

    pip install xpypact


As dependency

.. code-block::

    poetry add xpypact


From source

.. code-block::

    pip install htpps://github.com/MC-kit/xpypact.git


Examples
--------

.. code-block::

    from xpypact import FullDataCollector, Inventory

    def get_material_id(p: Path) -> int:
        ...

    def get_case_id(p: Path) -> int:
        ...

    jsons = [path1, path2, ...]
    material_ids = {p: get_material_id(p) for p in jsons }
    case_ids = {c: get_case_id(p) for p in jsons }

    collector = FullDataCollector()

    if sequential_load:
        for json in jsons:
            inventory = Inventory.from_json(json)
            collector.append(inventory, material_id=material_ids[json], case_id=case_ids[json])

    else:  # multithreading is allowed for collector as well

        task_list = ...  # list of tuples[directory, case_id, tasks_sequence]
        threads = 16  # whatever

        def _find_path(arg) -> tuple[int, int, Path]:
            _case, path, inventory = arg
            json_path: Path = (Path(path) / inventory).with_suffix(".json")
            if not json_path.exists():
                msg = f"Cannot find file {json_path}"
                raise FindPathError(msg)
            try:
                material_id = int(inventory[_LEN_INVENTORY:])
                case_str = json_path.parent.parts[-1]
                case_id = int(case_str[_LEN_CASE:])
            except (ValueError, IndexError) as x:
                msg = f"Cannot define material_id and case_id from {json_path}"
                raise FindPathError(msg) from x
            if case_id != _case:
                msg = f"Contradicting values of case_id in case path and database: {case_id} != {_case}"
                raise FindPathError(msg)
            return material_id, case_id, json_path

        with futures.ThreadPoolExecutor(max_workers=threads) as executor:
            mcp_futures = [
                executor.submit(_find_path, arg)
                for arg in (
                    (task_case[0], task_case[1], task)
                    for task_case in task_list
                    for task in task_case[2].split(",")
                    if task.startswith("inventory-")
                )
            ]

        mips = [x.result() for x in futures.as_completed(mcp_futures)]
        mips.sort(key=lambda x: x[0:2])  # sort by material_id, case_id

        def _load_json(arg) -> None:
            collector, material_id, case_id, json_path = arg
            collector.append(from_json(json_path.read_text(encoding="utf8")), material_id, case_id)

        with futures.ThreadPoolExecutor(max_workers=threads) as executor:
            executor.map(_load_json, ((collector, *mip) for mip in mips))


    collected = collector.get_result()

    # save to parquet files

    collected.save_to_parquets(Path.cwd() / "parquets")

    # or use DuckDB database

    import from xpypact.dao save
    import duckdb as db

    con = db.connect()
    save(con, collected)

    gamma_from_db = con.sql(
        """
        select
        g, rate
        from timestep_gamma
        where material_id = 1 and case_id = 54 and time_step_number = 7
        order by g
        """,
    ).fetchall()


Contributing
------------

.. image:: https://github.com/MC-kit/xpypact/workflows/Tests/badge.svg
   :target: https://github.com/MC-kit/xpypact/actions?query=workflow%3ATests
   :alt: Tests
.. image:: https://codecov.io/gh/MC-kit/xpypact/branch/master/graph/badge.svg?token=P6DPGSWM94
   :target: https://codecov.io/gh/MC-kit/xpypact
   :alt: Coverage
.. image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white
   :target: https://github.com/pre-commit/pre-commit
   :alt: pre-commit
.. image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v2.json
   :target: https://github.com/astral-sh/ruff
   :alt: linter & style


Just follow ordinary practice:

    - `Commit message <https://github.com/angular/angular/blob/22b96b9/CONTRIBUTING.md#-commit-message-guidelines>`_
    - `Conventional commits <https://www.conventionalcommits.org/en/v1.0.0/#summary>`_


References
----------

    - `FISPACT <https://fispact.ukaea.uk/>`_
    - `FISPACT-II tools (including pypact) repositories <https://github.com/fispact>`_
    - `FISPACT at NEA/OECD <https://oecd-nea.org/tools/abstract/detail/NEA-1890>`_
    - `FISPACT introduction <https://indico.ictp.it/event/7994/session/5/contribution/24/material/slides/0.pdf>`_


.. Substitutions


.. |Maintained| image:: https://img.shields.io/badge/Maintained%3F-yes-green.svg
   :target: https://github.com/MC-kit/xpypact/graphs/commit-activity
.. |Tests| image:: https://github.com/MC-kit/xpypact/workflows/Tests/badge.svg
   :target: https://github.com/MC-kit/xpypact/actions?workflow=Tests
   :alt: Tests
.. |License| image:: https://img.shields.io/github/license/MC-kit/xpypact
   :target: https://github.com/MC-kit/xpypact
.. |Versions| image:: https://img.shields.io/pypi/pyversions/xpypact
   :alt: PyPI - Python Version
.. |PyPI| image:: https://img.shields.io/pypi/v/xpypact
   :target: https://pypi.org/project/xpypact/
   :alt: PyPI
.. |Docs| image:: https://readthedocs.org/projects/xpypact/badge/?version=latest
   :target: https://xpypact.readthedocs.io/en/latest/?badge=latest
   :alt: Documentation Status
