spgci
SPGCI is an API Client for the S&P Commodity Insights REST API
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has low install friction, carries no known vulnerabilities, and uses a permissive license. Install it if you need programmatic access to S&P Global Commodity Insights data and have valid API credentials; the pandas integration and automatic token handling make it substantially easier than calling the REST API directly.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >= 3.9.0 and valid S&P Global Commodity Insights API credentials (username and password or environment variables SPGCI_USERNAME and SPGCI_PASSWORD).
- Low install friction with a pure Python wheel and six common dependencies (pandas, requests, tqdm, typing-extensions, tenacity, packaging).
- Active maintenance with a recent release (3 days old) and ongoing repository activity.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions—suitable for most projects.
last release 2026-08-11 (3 days) · last repo commit 2026-08-11 · 10 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 90,296 downloads/mo, #13,604 on PyPI
Alternatives
Verify before relying
pip install spgci
import spgci as ci
ci.set_credentials(username, password)
mdd = ci.MarketData()
df = mdd.get_assessments_by_symbol_current(symbol=["PCAAS00", "PCAAT00"])- Whether API rate limits or quota constraints apply to typical usage patterns.
- Performance characteristics when paginating large result sets or querying multiple symbols.
- Availability and completeness of historical data across all supported datasets.
What it is and what it does
SPGCI is a Python wrapper around the S&P Global Commodity Insights REST API, designed to simplify access to commodity market data, energy forecasts, and refining analytics. It handles authentication token generation automatically, returns results as pandas DataFrames by default, and supports optional auto-pagination and type coercion for date fields. The library covers multiple datasets including market assessments, forward curves, energy price forecasts, refinery data, world oil supply, LNG analytics, and market insights.
The package is built on standard dependencies (pandas for data handling, requests for HTTP calls, tenacity for retry logic) and accepts native Python types—lists and pandas Series are automatically converted to filter expressions. It requires API credentials from S&P Global and targets developers working with commodity markets, energy trading, or supply-chain analytics who want programmatic access to Platts data without writing raw HTTP clients.
Use it for
- Fetch current crude oil assessments and forward curves for a portfolio of trading symbols in a single DataFrame.
- Build automated energy price forecasts by querying monthly and annual predictions across multiple sectors and regions.
- Retrieve refinery operational data (yields, runs, outages) and refining margins for a specific location or time period.
- Search and download market commentary, subscriber notes, and energy insights articles filtered by keyword and date range.
- Construct historical demand and supply models by querying archived scenarios and reference data for countries and products.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has low install friction, carries no known vulnerabilities, and uses a permissive license. Install it if you need programmatic access to S&P Global Commodity Insights data and have valid API credentials; the pandas integration and automatic token handling make it substantially easier than calling the REST API directly.
Install
spgci on PyPI
Before you install
Low install friction with a pure Python wheel and six common dependencies (pandas, requests, tqdm, typing-extensions, tenacity, packaging). Active maintenance with a recent release (3 days old) and ongoing repository activity.
Requires Python >= 3.9.0 and valid S&P Global Commodity Insights API credentials (username and password or environment variables SPGCI_USERNAME and SPGCI_PASSWORD).
License in practice
Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions—suitable for most projects.
Quickstart
pip install spgci
import spgci as ci
ci.set_credentials(username, password)
mdd = ci.MarketData()
df = mdd.get_assessments_by_symbol_current(symbol=["PCAAS00", "PCAAT00"])Verify before relying
- Whether API rate limits or quota constraints apply to typical usage patterns.
- Performance characteristics when paginating large result sets or querying multiple symbols.
- Availability and completeness of historical data across all supported datasets.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <4.0.0,>=3.9.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagespandasrequeststqdmtyping-extensionstenacitypackaging |
| Maintenance | Actively maintained 3 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 90,296 / month, #13,604 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9 |
Evidence: spgci-0.0.100-py3-none-any.whl
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