d4c-api-statistical

A multi-language client for accessing Canadian statistical web data. This repository provides a unified interface to fetch statistical data processed by the d4c-datapkg-statistical repository.

Purpose

The goal of this project is to provide a consistent way to query statistical metadata and raw tables across different programming environments. As the connectivity and retrieval layer for the Data for Canada (d4c) project, this API facilitates access to a decentralized, cloud-native open data infrastructure for Canada.

Core Technologies

The client is designed to interface with modern data distribution protocols:

STAC & GeoZarr: For metadata discovery and high-performance multidimensional data access.
HTTP Seeding & BitTorrent: For decentralized data distribution and efficient retrieval.

Multi-Language Support

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

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.
labs/: Experimental area for testing new API endpoints or protocol implementations.

Contributing

New features or bug fixes for API connections should be implemented in the core/ directory. Enhancements to the user experience for a specific language should be made in the bindings/ folder.

All contributors must be verified via Vouch before their pull requests are reviewed.

2.2 KiB Raw Blame History