Swedish Energy Agency Statistics Connector

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Connector Details

Type

Virtual machines, Single VM , BYOL

Runs on

Google Compute Engine

Last Update

24 October, 2024

Category

Overview

The Swedish Energy Agency Statistics Connector is a specialized middleware service that provides streamlined access to Sweden’s official energy statistics. The service enables users to discover and explore various statistical databases containing critical energy data, from consumption patterns to production figures.
The connector allows for browsing available data tables, retrieving detailed metadata, and executing specific queries against the statistical databases. This unified interface ensures consistent and reliable access to authoritative energy information without exposing clients to backend complexity. It serves as a crucial bridge for applications needing to incorporate official Swedish energy statistics for analysis, reporting, or decision-making purposes.

Integration Overview

This document provides a comprehensive guide for the Swedish Energy Agency Statistics Connector’s architecture, configuration, and endpoint implementations. The connector supports HTTP GET and POST operations with automatic header propagation, parameter forwarding, and secure API key management through environment variables.

Supported Integration Action Points

list_databases: Retrieves a list of available databases from the Energy API
list_tables: Retrieves a list of tables within a specified database
get_table_metadata: Retrieves metadata for a specific table within a database
query_table: Executes queries against a specific table using POST requests

Detailed Integration Documentation

2.1 Environment Configuration

Purpose	Configures the connector with essential environment variables for API endpoints, ports, and authentication credentials. Ensures flexible deployment across different environments without code changes.
Configuration	`# Default values provided for development ENERGY_BASE_URL = os.environ.get("CONNECTOR_ENV_ENERGY_BASE_URL") PORT = int(os.environ.get("CONNECTOR_ENV_PORT", "8081").strip('"'))`
Parameters	Required: CONNECTOR_ENV_ENERGY_BASE_URL – Base URL for the Energy API. CONNECTOR_ENV_PORT – Port number for the Flask application (integer, e.g., 8081). Optional: CONNECTOR_ENV_ENERGY_API_KEY – API key for Energy API authentication (string).
Workflow Example	Set environment variables in the deployment environment. The application automatically reads configuration at startup. API endpoints are configured with the specified base URL and port.

2.2 Request Forwarding Infrastructure

Action / Core Functions	`forward_get()` and `forward_post()`
Purpose	Handles forwarding HTTP requests to the target API, manages headers, parameters, API key injection, and response handling.
Parameters	forward_get: path (string, required) – API endpoint path headers (dict, optional) – HTTP headers to forward params (dict, optional) – Query parameters forward_post: path (string, required) – API endpoint path headers (dict, optional) – HTTP headers to forward json_data (dict, optional) – JSON payload for POST
Authentication	Automatically injects API key from `CONNECTOR_ENV_ENERGY_API_KEY`. Adds key to headers (`Ocp-Apim-Subscription-Key`) and query parameters (`subscription-key`).
Security	SSL verification disabled for debugging (`verify=False`). Enable in production environments.
Output	Successful: Flask Response object containing original response content, status code, and Content-Type header. Failure: Propagates error response from target API with original status code and error details.

2.3 Database Listing Endpoint

Action	list_databases
Purpose	Retrieves a list of available databases from the Energy API, serving as the primary entry point for discovering data sources.
Endpoint	GET /api/v1/en/
Parameters	Query: subscription-key – API key for authentication Headers: Accept – Content type (default: application/json)
Output	Successful: JSON with database list. Failure: Error response with status code from Energy API.
Workflow Example	Client sends GET request to `/api/v1/en/`. Connector forwards request with authentication. Response returned to client with original content and headers.

2.4 Table Listing Endpoint

Action	list_tables
Purpose	Retrieves a list of tables within a specified database for data discovery.
Endpoint	GET /api/v1/en/<database>
Parameters	Path: database – Database identifier (required) Query: subscription-key – API key for authentication Headers: Accept – Content type
Output	Successful: JSON response containing table list. Failure: Error response for invalid database or authentication issues.
Workflow Example	Client requests tables for a specific database (e.g., GET /api/v1/en/energy_db). Connector forwards to Energy API. Table list returned to client.

2.5 Table Metadata Retrieval

Action	get_table_metadata
Purpose	Retrieves detailed metadata for a table, including columns, data types, and structure.
Endpoint	GET /api/v1/en/<database>/<table>
Parameters	Path: database – Database identifier (required) Path: table – Table name (required) Query: subscription-key – API key for authentication Headers: Accept – Content type
Output	Successful: JSON with table schema and metadata. Failure: Error response for invalid table or access restrictions.

2.6 Table Query Execution

Action	query_table
Purpose	Executes queries against a table using POST requests with JSON payloads for filters and parameters.
Endpoint	POST /api/v1/en/<database>/<table>
Parameters	Path: database – Database identifier (required) Path: table – Table name (required) Headers: Content-Type (default: application/json), Accept Body: JSON payload with query parameters and filters
Output	Successful: JSON results from Energy API query. Failure: Error response with query execution details.

Workflow Creation with the Connector

Example Workflow: Swedish Energy Agency Statistics Connector

Discover Available Data Sources	Use `list_databases` action to fetch available databases. Identify relevant databases for analysis (e.g., `energy_consumption`).
Explore Database Structure	Execute `list_tables` action with `database="energy_consumption"`. Review available tables and their purposes.
Understand Data Schema	Use `get_table_metadata` with `database="energy_consumption"` and `table="household_usage"`. Analyze column definitions and data types for query planning.
Execute Data Queries	Use `query_table` action with JSON payload to retrieve specific data. Apply filters, sorting, and aggregation as needed. Process results for visualization or further analysis.
Integration with Analytics Tools	Connect business intelligence tools to connector endpoints. Build dashboards using the standardized API interface. Automate data extraction for reporting pipelines.

Pricing

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