Speedup getting available datasets

[hagenw]

Use 10 workers to speed up audb.available().

[sourcery-ai]

Reviewer's guide (collapsed on small PRs)

Reviewer's Guide

This PR speeds up building the list of available datasets for the Sphinx docs by invoking audb.available() with parallel workers, while preserving the existing filtering and sorting logic.

Sequence diagram for using parallel workers in audb.available during Sphinx build

sequenceDiagram
    participant SphinxBuilder as builder_inited
    participant audb as audb

    SphinxBuilder->>audb: available(only_latest=True, num_workers=10)
    audb-->>SphinxBuilder: DataFrame df
    SphinxBuilder->>SphinxBuilder: df.index.duplicated(keep="first") filter
    SphinxBuilder->>SphinxBuilder: df.sort_index()

Loading

File-Level Changes

Change	Details	Files
Speed up retrieval of available datasets during Sphinx build by enabling parallel workers in audb.available().	Pass num_workers=10 to audb.available() in the Sphinx builder_inited hook Keep existing options (only_latest) and subsequent de-duplication and sorting of the resulting DataFrame unchanged	audbcards/sphinx/__init__.py

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[sourcery-ai]

Hey - I've left some high level feedback:

• Hardcoding num_workers=10 might not suit all environments; consider deriving the worker count from CPU resources (e.g., os.cpu_count() capped at a reasonable maximum) or making it configurable.
• It may be worth handling the case where the environment running Sphinx (e.g. CI or low-resource machines) cannot support the chosen worker count, either by catching errors or falling back to a single-worker call.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- Hardcoding `num_workers=10` might not suit all environments; consider deriving the worker count from CPU resources (e.g., `os.cpu_count()` capped at a reasonable maximum) or making it configurable.
- It may be worth handling the case where the environment running Sphinx (e.g. CI or low-resource machines) cannot support the chosen worker count, either by catching errors or falling back to a single-worker call.

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[hagenw]

We are using threads here to wait for network traffic. This will even provide a speed up on a singel CPU and will not harm.