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Python client for the ENTSO-E Transparency Platform API

Project description

python-entsoe

Python client for the ENTSO-E Transparency Platform API.

Typed, namespace-organized access to European electricity market data — load, prices, generation, transmission, and balancing.

pip install python-entsoe

Quick Start

from entsoe import Client

client = Client()  # reads ENTSOE_API_KEY from environment

df = client.load.actual("2024-06-01", "2024-06-08", country="FR")

Strings are interpreted as timestamps in Europe/Brussels (CET — the ENTSO-E standard). You can override this per-client or pass pd.Timestamp objects directly:

client = Client(tz="UTC")  # override default timezone

# pd.Timestamp still works — its timezone takes priority
import pandas as pd
start = pd.Timestamp("2024-06-01", tz="Europe/Paris")
df = client.load.actual(start, "2024-06-08", country="FR")

Every method returns a pandas.DataFrame with a timestamp column (UTC) and a value column.

Authentication

Get a free API key at https://transparency.entsoe.eu/ (register, then request a token via email).

Set it as an environment variable:

export ENTSOE_API_KEY=your-token-here

Or pass it directly:

client = Client(api_key="your-token-here")

API Reference

client.load

Method Description Parameters
actual(start, end, country) Actual total system load country: ISO code (e.g., "FR")
forecast(start, end, country) Day-ahead load forecast country: ISO code
df = client.load.actual(start, end, country="FR")
df = client.load.forecast(start, end, country="FR")

client.prices

Method Description Parameters
day_ahead(start, end, country) Day-ahead market prices (EUR/MWh) country: ISO code
df = client.prices.day_ahead(start, end, country="FR")
# Returns: timestamp, value, currency, price_unit

client.generation

Method Description Parameters
actual(start, end, country, psr_type=None) Actual generation per type psr_type: filter by fuel (optional)
forecast(start, end, country, psr_type=None) Wind & solar forecast psr_type: filter by fuel (optional)
installed_capacity(start, end, country, psr_type=None) Installed capacity per type psr_type: filter by fuel (optional)
per_plant(start, end, country, psr_type=None) Generation per production unit psr_type: filter by fuel (optional)
# All generation types
df = client.generation.actual(start, end, country="FR")

# Solar only
df = client.generation.actual(start, end, country="FR", psr_type="B16")

# Installed capacity
df = client.generation.installed_capacity(start, end, country="FR")

client.transmission

Method Description Parameters
crossborder_flows(start, end, country_from, country_to) Physical cross-border flows Two country codes
scheduled_exchanges(start, end, country_from, country_to) Scheduled commercial exchanges Two country codes
net_transfer_capacity(start, end, country_from, country_to) Day-ahead NTC Two country codes
df = client.transmission.crossborder_flows(
    start, end, country_from="FR", country_to="ES"
)

client.balancing

Method Description Parameters
imbalance_prices(start, end, country) System imbalance prices country: ISO code
imbalance_volumes(start, end, country) System imbalance volumes country: ISO code
df = client.balancing.imbalance_prices(start, end, country="FR")

Country Codes

Use standard ISO codes. Some bidding zones have specific codes:

Code Area
FR France
DE_LU Germany/Luxembourg (bidding zone)
ES Spain
NL Netherlands
BE Belgium
IT Italy
IT_NORTH Italy North
NO_1 .. NO_5 Norway zones
SE_1 .. SE_4 Sweden zones
DK_1, DK_2 Denmark zones

Note: For day-ahead prices and balancing data, use DE_LU instead of DE. See data availability notes for details.

Full list of 60+ supported areas in _mappings.py.

PSR Types (Fuel Types)

Use PSR codes to filter generation by fuel type:

Code Fuel Type
B01 Biomass
B04 Fossil Gas
B05 Fossil Hard coal
B06 Fossil Oil
B10 Hydro Pumped Storage
B11 Hydro Run-of-river
B12 Hydro Water Reservoir
B14 Nuclear
B16 Solar
B18 Wind Offshore
B19 Wind Onshore

Full list in _mappings.py. Human-readable names available via:

from entsoe._mappings import PSR_TYPES
print(PSR_TYPES["B16"])  # "Solar"

Timestamps

All start and end parameters accept date strings or tz-aware pd.Timestamp objects:

# Simple — just strings (uses client's default tz: Europe/Brussels)
df = client.load.actual("2024-01-01", "2024-01-07", country="FR")

# pd.Timestamp with explicit timezone — takes priority over default
df = client.load.actual(
    pd.Timestamp("2024-01-01", tz="Europe/Paris"),
    pd.Timestamp("2024-01-07", tz="Europe/Paris"),
    country="FR",
)

# Mixing is fine
df = client.load.actual("2024-01-01", pd.Timestamp("2024-01-07", tz="UTC"), country="FR")

# Naive pd.Timestamp (no tz) — still raises InvalidParameterError
start = pd.Timestamp("2024-01-01")  # ← no tz, will error

Returned timestamps are always in UTC.

Features

  • Autocomplete-friendly — type client. and see all domains, then drill into methods
  • Automatic year-splitting — requests spanning more than 1 year are split transparently
  • ZIP handling — endpoints returning compressed responses are decompressed automatically
  • Retry with backoff — rate-limited requests (HTTP 429) are retried with exponential backoff
  • Clear errorsNoDataError, InvalidParameterError, RateLimitError with descriptive messages

Error Handling

from entsoe import Client, NoDataError, InvalidParameterError

client = Client()

try:
    df = client.prices.day_ahead(start, end, country="FR")
except NoDataError:
    print("No data available for this period")
except InvalidParameterError as e:
    print(f"Bad parameters: {e}")

Examples

See the examples/ directory for Jupyter notebooks with plotly visualizations:

Development

git clone https://github.com/jsulopzs/python-entsoe.git
cd python-entsoe
uv sync

# Run tests (requires ENTSOE_API_KEY in .env)
uv run pytest tests/ -v

# Regenerate example notebooks
uv run python scripts/generate_notebooks.py

License

MIT

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