The main package __init__.py module bootstraps the data model system at import time.

pvgisprototype ¶

Dynamic Data Model Initialization

This module generates PVGIS-native data model classes (in fact Pydantic data models) from centralized definitions and registers them into the global namespace. The generated models are then exposed at the package level, so applications usually import them directly from pvgisprototype rather than from this module.

Architecture

The initialization process follows these steps :

Import data model definitions from PVGIS_DATA_MODEL_DEFINITIONS.
For each data model definition, ask DataModelFactory to build the corresponding data model class.
Register each generated data model class into the module's global namespace
Remove the raw definitions to keep the public API clean.

This approach provides several benefits:

Centralized Configuration: All data model schemas defined in one place
Dynamic Generation: Models created at import time from declarative definitions
Clean Namespace: Generated models appear as if directly defined in the module
Consistency: Factory-based approach avoids repetitive boilerplate

Usage

In normal use, models are imported from the top-level package

>>> from pvgisprototype import SomeDataModel
>>> instance = SomeDataModel(field_1=value_1, field_2=value_2, ...)

Direct imports from this __init__ module are typically not required.

Implementation Details

Uses DataModelFactory.get_data_model() to construct data model classes
Modifies globals() to register models at module level
Definitions are deleted after generation to reduce memory footprint

Name	Description
`algorithms`
`api`
`cli`
`core`
`log`	Unified Logger for PVGIS¶
`validation`
`web_api`

Name	Description
`generate_data_models`	Generate and register data model classes from definitions.

generate_data_models ¶

generate_data_models(data_model_definitions: dict)

Generate and register data model classes from definitions.

Iterates through the provided data model definitions dictionary and generates corresponding model classes using the DataModelFactory. Each generated data model class is injected into the caller's global namespace, making it accessible as a module-level attribute.

Parameters:

Name	Type	Description	Default
`data_model_definitions`	`dict`	Dictionary mapping data model names (str) to their configuration/schema definitions. Keys become the class names, values define model structure.	required

Returns:

Type	Description
`None`	Models are registered as side effects in the global namespace.

Notes

This function modifies the global namespace by calling globals()[name] = model. It should typically only be called once during module initialization.

Examples:

>>> definitions = {
...     'UserModel': {'fields': [...], 'validators': [...]},
...     'ProductModel': {'fields': [...], 'validators': [...]}
... }
>>> generate_data_models(definitions)
>>> # UserModel and ProductModel are now available as module attributes

Source code in pvgisprototype/__init__.py

def generate_data_models(data_model_definitions: dict):
    """
    Generate and register data model classes from definitions.

    Iterates through the provided data model definitions dictionary and
    generates corresponding model classes using the DataModelFactory. Each
    generated data model class is injected into the caller's global namespace,
    making it accessible as a module-level attribute.

    Parameters
    ----------
    data_model_definitions : dict
        Dictionary mapping data model names (str) to their configuration/schema
        definitions. Keys become the class names, values define model structure.

    Returns
    -------
    None
        Models are registered as side effects in the global namespace.

    Notes
    -----
    This function modifies the global namespace by calling `globals()[name] = model`.
    It should typically only be called once during module initialization.

    Examples
    --------
    >>> definitions = {
    ...     'UserModel': {'fields': [...], 'validators': [...]},
    ...     'ProductModel': {'fields': [...], 'validators': [...]}
    ... }
    >>> generate_data_models(definitions)
    >>> # UserModel and ProductModel are now available as module attributes
    """
    for data_model_name in data_model_definitions.keys():
        globals()[data_model_name] = DataModelFactory.get_data_model(
                data_model_name=data_model_name,
                data_model_definitions=data_model_definitions
                )

pvgisprototype ¶

Unified Logger for PVGIS¶

generate_data_models ¶