nexa-marketdata

Unified API client for European power market data sources. One interface for Nord Pool, EPEX SPOT, ENTSO-E Transparency Platform, and EEX.

Python 3.11+ MIT License 0.1.0 Alpha

pip install nexa-marketdata

GitHub | PyPI

Why this exists

The European power market data landscape is fragmented. Every exchange has its own API, its own data format, its own quirks. The community alternatives (entsoe-py, kipe/nordpool) are volunteer-maintained and frequently break when APIs change.

nexa-marketdata provides a single, well-tested client that handles:

• Multiple exchanges through a consistent interface
• 15-minute MTU data natively (EU transition: 30 Sept 2025)
• Rate limiting so you do not get banned from ENTSO-E at 03:00
• Timezone normalisation across bidding zones
• Caching to avoid redundant API calls
• Proper error handling with meaningful exceptions, not silent failures

Quick start

Set your credentials as environment variables:

export NORDPOOL_USERNAME="your-username"
export NORDPOOL_PASSWORD="your-password"
export ENTSOE_API_KEY="your-key-here"

from nexa_marketdata import NexaClient
from nexa_marketdata.types import BiddingZone
import datetime

client = NexaClient()

# Fetch day-ahead prices for NO2 (South Norway)
prices = client.day_ahead_prices(
    zone=BiddingZone.NO2,
    start=datetime.date(2025, 10, 1),
    end=datetime.date(2025, 10, 7),
)

print(prices.head())
#             start                end  price_eur_mwh bidding_zone
# 0  2025-10-01 00:00+00:00  2025-10-01 00:15+00:00         42.31          NO2
# 1  2025-10-01 00:15+00:00  2025-10-01 00:30+00:00         41.88          NO2
# ...

Implementation status

Key features

DataFrame output

All data is returned as pandas DataFrames. Prices and volumes use Decimal, not float.

from nexa_marketdata import NexaClient
from nexa_marketdata.types import BiddingZone
import datetime

client = NexaClient()

prices = client.day_ahead_prices(
    zone=BiddingZone.NO1,
    start=datetime.date(2025, 10, 1),
    end=datetime.date(2025, 10, 2),
)

# Standard pandas operations work directly
hourly = prices.resample("h", on="start").mean(numeric_only=True)
print(f"Peak hour: {hourly['price_eur_mwh'].idxmax()}")

Type-safe bidding zones

Bidding zones are modelled as an enum, not raw strings. The library normalises zone identifiers across exchanges.

from nexa_marketdata.types import BiddingZone

# Nordic zones
BiddingZone.NO1  # South Norway
BiddingZone.NO2  # South-West Norway
BiddingZone.SE3  # Central Sweden
BiddingZone.FI   # Finland

# Central European zones
BiddingZone.DE_LU  # Germany-Luxembourg
BiddingZone.FR     # France

MTU-aware resolution

The library handles the 30 September 2025 transition from hourly to 15-minute MTUs. Historical data is returned in the resolution it was published; post-transition data is 15-minute by default.

Configuration

Credentials are read from environment variables. You can also use a .env file:

NORDPOOL_USERNAME=your-username
NORDPOOL_PASSWORD=your-password
ENTSOE_API_KEY=your-key-here

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