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Diego Ripley
2026-02-19 20:48:27 -05:00
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@@ -11,8 +11,8 @@ The goal of this project is to provide a consistent way to query metadata and ra
The client is designed to interface with modern data distribution protocols:
- **[STAC](https://stac-geoparquet.org/) for metadata discovery.
- **[GeoZarr](https://github.com/zarr-developers/geozarr-spec):** Fo high-performance multidimensional data access.
- **[STAC](https://stac-geoparquet.org/):** For metadata discovery.
- **[GeoZarr](https://github.com/zarr-developers/geozarr-spec):** For high-performance multidimensional data access.
- **HTTP & P2P:** For decentralized data distribution and efficient retrieval.
## Multi-Language Support
@@ -20,16 +20,16 @@ The client is designed to interface with modern data distribution protocols:
The core connectivity logic is written in Rust and exported to other languages. This ensures that API calls, authentication methods, and data handling remain identical across all platforms.
- **Rust:** The core crate for direct system-level access and performance-critical tasks.
- **Python:** Idiomatic bindings optimized for data science and machine learning workflows.
- **R:** Native wrappers designed for statistical analysis and reporting.
- **[Other](https://github.com/dataforcanada/d4c-api-statistical/issues)**
- **Python:** Idiomatic bindings.
- **R:** Native wrappers.
- **[Other](https://github.com/dataforcanada/d4c-api-statistical/issues)**.
## Repository Structure
We separate the shared core from the language-specific wrappers:
- **core/**: Rust source code handling HTTP requests, API authentication, and decentralized protocol logic.
- **bindings/**: Language-specific implementations for Python and R.
- **bindings/**: Language-specific implementations for Python, R, and **[Other](https://github.com/dataforcanada/d4c-api-statistical/issues)**.
- **labs/**: Experimental area for testing new API endpoints or protocol implementations.
## Contributing