spg_api 0.1.1

S&P Global API Client

S&P Global API Package

A powerful Python package for accessing S&P Global (formerly IHS Markit) energy and climate data services. Specifically designed for CCUS (Carbon Capture, Utilization, and Storage), Upstream, and Climate Scenario analytics.

Description

This package provides a unified, high-level interface for interacting with various S&P Global API products. It abstracts the complexity of different API architectures (OData vs. standard REST) and provides automated tools for data retrieval, mapping, and standardized styling.

Key Features

• Unified API Client: A single SPGlobalAPIClient class that handles authentication and URL construction for multiple data clusters.
• Auto-Pagination: Large datasets (1M+ rows) are automatically fetched in chunks using the fetch_all method.
• Smart Filtering: Supports complex dictionary-based filters and raw OData query strings.
• Mapping Utilities: Specialized tools for creating interactive geospatial visualizations with Folium and GeoPandas.
• S&P Global Styling: Apply consistent, publication-ready visualization styles for charts and presentations.
• Metadata Discovery: Built-in support for retrieving dataset schemas and view definitions.

Installation

Requirements

• Python >= 3.12
• Dependencies: pandas, requests, matplotlib, geopandas, folium, python-dotenv

Install from PyPI

pip install spg_api

Configuration

Option 1: .env File

Create a .env file in your project root:

CONNECT_KEY=your_api_key
CONNECT_PW=your_api_password

Option 2: Manual Configuration

You can also set credentials directly in your code:

import spg_api
spg_api.username = "your_api_key"
spg_api.password = "your_api_password"

Usage

1. Unified API Client

The SPGlobalAPIClient is the primary entry point for all data retrieval.

import spg_api

# Initialize for Energy/Climate Scenarios
client = spg_api.SPGlobalAPIClient("energyandclimatescenarios")

# Fetch data
df = client.retrieve_data(
    view_name="coal_markets",
    filters={"Country": "China"},
    select=["Year", "Value"]
)

2. Publication-Ready Styling

Apply standardized S&P Global styling to your Matplotlib charts.

import matplotlib.pyplot as plt
import spg_api.spg_style as spg_style

style = spg_style.SpglobalStyle(theme='light')
fig, ax = plt.subplots(figsize=spg_style.get_edp_figsize())

# ... plotting logic ...

style.add_footnotes(fig, source="S&P Global Market Intelligence")

Project Structure

spg_api/
├── spg_api/
│   ├── url_generator.py    # Core Unified Client (SPGlobalAPIClient)
│   ├── analysis.py         # Specialized scenario analysis classes
│   ├── spg_style.py        # S&P Global visualization styling
│   ├── map.py              # Geospatial mapping utilities
│   ├── utils.py            # API request and response helpers
│   └── const.py            # Constants and styling tokens
├── README.md               # Documentation
└── pyproject.toml          # Build configuration

Contact

For questions or support, contact the maintainer at [e-mail].

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Proprietary to S&P Global. Reproduction without permission is prohibited.