Add async client support for improved performance

[anjor]

Description

The foundry-platform-python SDK provides AsyncFoundryClient for asynchronous operations. Adding async support to the CLI could significantly improve performance for batch operations and large data processing tasks.

Benefits

• Improved Performance: Concurrent operations for batch processing
• Better Resource Utilization: Non-blocking I/O operations
• Enhanced User Experience: Progress indicators during long-running operations
• Scalability: Handle larger datasets and bulk operations more efficiently

Use Cases

• Batch dataset operations (upload/download multiple files)
• Bulk ontology object processing
• Large-scale SQL query execution
• Mass admin operations (user/group management)
• Concurrent folder operations

Implementation Considerations

• Add async variants of existing commands (e.g., --async flag)
• Implement progress bars for long-running async operations
• Handle async error management and cleanup
• Consider thread pool configuration for optimal performance
• Maintain backward compatibility with synchronous operations

Technical Requirements

• AsyncFoundryClient integration
• Progress tracking and reporting
• Proper error handling for concurrent operations
• Configuration options for concurrency limits
• Testing framework for async operations

Example Commands

# Async batch file upload
pltr dataset upload --async --files *.csv --dataset-rid ri.foundry.main.dataset.123

# Concurrent folder operations
pltr folder create --async --batch folders.json

# Bulk ontology object queries
pltr ontology objects list --async --batch-size 1000

References

• SDK AsyncFoundryClient documentation
• Current synchronous implementations in src/pltr/services/