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Python classes for working with DDC calibration data

Project description

dccQuantities

dccQuantities is a Python library designed for users of PTB’s Digital Calibration Certificates (DCC) in XML format. It provides an object‑oriented interface to parse, serialize, and manipulate calibration data with full support for uncertainties and units. Arithmetic works naturally on scalars, scalar‑vector mixes, and same‑length vectors element‑wise, preserving uncertainty propagation and metadata throughout.

PyPI Release pipeline status Coverage (main) Docs


Key Features

  • DCC XML Parsing & Serialization
    Import certificates from XML into Python objects and export back to XML, JSON, CSV, Excel, or pandas DataFrames.

  • Uncertainty & Unit Awareness
    All quantity objects wrap values as ufloat (via metas_unclib) and units via dsi_unit, ensuring correct propagation in calculations.

  • Object‑Oriented Arithmetic
    Standard operators (+, -, *, /, **) are overloaded on:

    • DccQuantityType: single or tabulated quantities
    • SiRealList, SiComplexList, SiHybrid: 1D/2D arrays
  • Tables & Fancy Indexing The classes DccLongTable and DccFlatTable transparently implement numpy like indexing on efficient table structures described in the table document. Fancy indexing is supported, return type are always new tables.


Linux dependencies

The package requires the Linux .NET library. For that reason, it is required to have installed the mono library:

sudo apt install mono-runtime

Installation

There are multiple ways to install the package. Read them all and choose the best one for your case:

  1. From PyPI (core functionality):
pip install dccQuantities

This will install the latest released changes at the 'main' branch.

  1. Installing unreleased changes:
pip install git+https://gitlab1.ptb.de/digitaldynamicmeasurement/dcc-and-dsi/dccQuantities.git@devel

Please consider that unreleased changes might be unstable and can break your code.

  1. Cloning the repository:
git clone https://gitlab1.ptb.de/digitaldynamicmeasurement/dccQuantities.git
cd dccQuantities
pip install -e .

This is the best option for developers.

Deploy local documentation

It is possible to deploy and read the local documentation. To do so, it is required to clone the repository as stated at '2.' in the Installation section.

Once the repository is cloned and the current working directory is dccQuantities/, install the optional dependencies for documentation:

pip install .[docs]

Now you can deploy and open the documentation by running the following command at your terminal:

quantity-docs

Under the Hood (Test‑Driven Behavior)

The library’s design is guided by its test suite:

  1. Core Parsing (tests/test_parser.py): reads <DccQuantityTable> and <DccQuantityType> elements, building Python objects.
  2. Naming (tests/test_dccName.py): parses and normalizes <DccLangName> entries for multilingual support.
  3. Quantity Discovery (tests/test_quantityTypeCollector.py): auto‑registers data handlers via AbstractQuantityTypeData subclasses.
  4. List Types (tests/test_SiRealList_*.py): handles real, complex, and hybrid lists, including broadcasting and label merging.
  5. Table Flattening (tests/test_tables.py): cover the tables.
  6. Round‑Trip Serialization (tests/test_serilizer.py): ensures parse→serialize yields equivalent XML.
  7. JSON Interchange (tests/test_dccQuantTabJSONDumpingAndLoadingFromFile.json): lossless JSON dump/load.

Contributing & Contact

We welcome improvements, bug reports, and new features. To contribute:

  1. Fork the repository.
  2. Create a feature branch.
  3. Add tests for new functionality.
  4. Submit a merge request.

We highly encourage direct personal contact for design discussions or questions. Feel free to create Issues, even if you think your question/comment is not worth an issue, it is allways!

Or reach out to the maintainer:

License

This project is licensed under the LGPL‑2.1‑or‑later.

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