eia-ng-client 0.1.71

A Python client for the EIA v2 natural gas API with structured access to production, storage, flows, prices, and gas-fired electricity generation.

eia-ng

A Python client for the EIA v2 natural gas API with structured access to production, storage, consumption, imports, exports, prices, and natural-gas-fired electricity generation.

EIA API Documentation

This library is built on top of the official U.S. Energy Information Administration (EIA) Open Data API.

For detailed information about datasets, endpoints, parameters, and data definitions, refer to the official EIA API documentation:

https://www.eia.gov/opendata/documentation.php

Installation

pip install eia-ng-client

3. API key setup

You need a free EIA API key.

1. Register at: https://www.eia.gov/opendata/register.php
2. Set the key as an environment variable:

export EIA_API_KEY="your_api_key_here"

---

4. Quick start

from eia_ng import EIAClient

client = EIAClient()

# U.S. natural gas production (monthly)
production = client.natural_gas.production(start="2020-01")
print(production[:3])

# Lower 48 natural gas storage (weekly)
weekly_storage = client.natural_gas.weekly_working_storage(start="2022-01-01")
print(weekly_storage[:3])

# Henry Hub spot prices (daily)
prices = client.natural_gas.spot_prices(start="2023-01-01")
print(prices[:3])

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5. Natural gas API overview

Natural Gas Data

The natural_gas source provides access to:

• Production (U.S. total and by state)
• Consumption (U.S. total and by state)
• Weekly working gas storage (by region)
• Underground storage all operators (by geography and metric)
• Imports (pipeline, LNG, compressed)
• Exports (pipeline, LNG, truck, compressed)
• Spot prices (Henry Hub)
• Futures prices (front-month and deferred contracts)

Production by State

# Texas natural gas production
tx_prod = client.natural_gas.production(
    start="2020-01",
    state="tx",
)

Weekly working storage by region

# Lower 48 weekly working gas storage
weekly_storage = client.natural_gas.weekly_working_storage(
    start="2022-01-01",
    region="lower48",
)

Underground storage all operators

# Texas monthly working gas in underground storage
texas_working_gas = client.natural_gas.underground_storage_all_operators(
    start="2020-01",
    geography="tx",
    metric_type="working_gas",
    frequency="monthly",
)

# U.S. working gas percent change from year ago
us_yoy_pct = client.natural_gas.underground_storage_all_operators(
    start="2020-01",
    geography="us_total",
    metric_type="working_gas_yoy_pct_change",
    frequency="monthly",
)

# Thin wrapper example
base_gas = client.natural_gas.underground_storage_base_gas(
    start="2020-01",
    geography="pa",
)

Underground storage by type

# U.S. monthly working gas by storage type dataset
storage_type_working_gas = client.natural_gas.underground_storage_type(
    start="2020-01",
    storage_type="working_gas",
    frequency="monthly",
)

# U.S. annual salt cavern withdrawals
salt_withdrawals = client.natural_gas.underground_storage_type(
    start="2015",
    storage_type="salt_withdrawals",
    frequency="annual",
)

Underground storage capacity and count

# U.S. monthly total underground storage capacity
total_capacity = client.natural_gas.underground_storage_capacity(
    start="2020-01",
    geography="us_total",
    type="total",
    frequency="monthly",
)

# Texas annual working gas storage capacity
tx_working_capacity = client.natural_gas.underground_storage_capacity(
    start="2015",
    geography="tx",
    type="working_gas",
    frequency="annual",
)

# Lower 48 monthly storage field count
lower48_storage_count = client.natural_gas.underground_storage_count(
    start="2020-01",
    geography="lower48",
    frequency="monthly",
)

Imports / exports

# Pipeline imports from Canada
imports = client.natural_gas.imports(
    start="2021-01",
    country="canada_pipeline",
)

# Pipeline exports to Mexico
exports = client.natural_gas.exports(
    start="2021-01",
    country="mexico_pipeline",
)

Futures prices

# Front-month natural gas futures
futures = client.natural_gas.futures_prices(
    start="2023-01-01",
    contract=1,
)

Exploration & Reserves (Annual)

The exploration_and_reserves method provides access to EIA Exploration & Reserves (Form-23) data. This data is annual only and represents reserve stocks or expected future production, not current output.

Supported categories:

• Proved associated natural gas reserves (wet)
• Proved nonassociated natural gas reserves (wet)
• Proved natural gas plant liquids (NGL) reserves
• Expected future production of dry natural gas

Proved associated natural gas reserves

# U.S. total proved associated natural gas reserves (annual)
reserves_us = client.natural_gas.exploration_and_reserves(
    start="2010",
    resource_category="proved_associated_gas",
)
print(reserves_us[:3])

# Texas proved associated natural gas reserves
reserves_tx = client.natural_gas.exploration_and_reserves(
    start="2010",
    state="tx",
    resource_category="proved_associated_gas",
)
print(reserves_tx[:3])

# Pennsylvania proved nonassociated gas reserves
pa_nonassoc = client.natural_gas.exploration_and_reserves(
    start="2010",
    state="pa",
    resource_category="proved_nonassociated_gas",
)


# U.S. proved NGL reserves
ngl_reserves = client.natural_gas.exploration_and_reserves(
    start="2010",
    resource_category="proved_ngl",
)

# Expected future production of dry natural gas (U.S.)
efp = client.natural_gas.exploration_and_reserves(
    start="2010",
    resource_category="expected_future_gas_production",
)

---

7. Electricity generation (Natural Gas)

# U.S. electricity generation from natural gas
gen_us = client.electricity.generation_natural_gas(
    start="2020-01",
)

# Utah electricity generation from natural gas
gen_ut = client.electricity.generation_natural_gas(
    start="2020-01",
    state="UT",
)

Returned Data Format

All methods return a list of dictionaries corresponding to rows returned by the EIA API.

You can easily convert the results to pandas using this approach.

import pandas as pd
df = pd.DataFrame(production)

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🧪 Testing

This project uses pytest for unit and integration tests and runs inside the Poetry virtual environment.

Run the full test suite with:

poetry run pytest -q

License

MIT