
Developed an enhancement for the supervisely/developer-portal repository by introducing the api.dataset.tree feature to the Python SDK, enabling retrieval of nested datasets with full path resolution in hierarchical structures. This update addressed the need for more efficient data access compared to the previous api.dataset.get_list approach. The work included comprehensive updates to Markdown-based documentation and tutorials, providing concrete examples and expected outputs to streamline developer onboarding. By focusing on both Python SDK development and clear documentation practices, the contribution improved data accessibility and usability for developers working with complex dataset hierarchies, while maintaining a guidance-driven approach to technical communication and adoption.
March 2025: Implemented a significant enhancement to the Python SDK to support nested datasets retrieval via api.dataset.tree, with accompanying documentation updates. This enables accurate path resolution in hierarchical datasets and provides an efficient alternative to api.dataset.get_list. Documentation and tutorials now include concrete examples and expected outputs to accelerate developer adoption. Overall, this month focused on elevating data accessibility and developer experience in the portal.
March 2025: Implemented a significant enhancement to the Python SDK to support nested datasets retrieval via api.dataset.tree, with accompanying documentation updates. This enables accurate path resolution in hierarchical datasets and provides an efficient alternative to api.dataset.get_list. Documentation and tutorials now include concrete examples and expected outputs to accelerate developer adoption. Overall, this month focused on elevating data accessibility and developer experience in the portal.

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