Add Dataverse Hub endpoints

[JR-1991]

This PR introduces endpoints to interact with the Dataverse Hub server, which manages installation records and provides access to global metrics. It includes the implementation of request and response models using Pydantic, which has been added as a new dependency. These models ensure payload and response validation and offer a convenient interface for navigating response data.

Example

from pyDataverse.hub import HubApi

hub = HubApi()

installations = hub.get_installation_metrics_monthly(
    from_date="2020-01",
    to_date="2025-01",
)

for installation in installations:
    print(installation.name)
    print(installation.country)

Metric Filtering

The PR also adds the FilterMetrics class to simplify passing filter parameters to the metrics endpoint. This approach improves readability and scalability by avoiding a bloated method signature and making it easier to extend filtering options in the future.

hub = HubApi()
filter_by = FilterMetrics(launch_year=2025)
response = hub.get_installation_metrics(filter_by=filter_by)

TLDR

• Adds Dataverse Hub endpoints

• Responses and payloads as PyDantic models

• Tests to verify functionality

• Due to PyDantic dep --> Python 3.8 support needs to be dropped

• Closes client bindings based on https://hub.dataverse.org/openapi #218

[JR-1991]

By the way: This PR already adapts the PyDantic-based implementation I was envisioning at py.gdcc.io

[pdurbin]

As discussed today, we're thinking a separate package would be best. dataverse-hub on PyPI or something.