elexonpy is a Python package that provides a convenient interface to the ELEXON API.
This package is generated using Swagger Codegen, ensuring compatibility and ease of use with the ELEXON API services.
You can install the elexonpy
package via pip from PyPI.
pip install elexonpy
There are some examples in the examples
directory that demonstrate how to use the package to retrieve data from the Elexon API.
This example demonstrates how to use methods from the DemandApi
to retrieve various types of
demand data from the Elexon API and format it into a DataFrame.
# This script demonstrates the use of methods from the DemandApi
# to retrieve various types of demand data from the Elexon API.
from datetime import datetime
import pandas as pd
from elexonpy.api_client import ApiClient
from elexonpy.api.demand_api import DemandApi
# Initialize API client
api_client = ApiClient()
demand_api = DemandApi(api_client)
# Define date range for Actual Total Load Data
from_date = datetime(2024, 7, 1)
to_date = datetime(2024, 7, 2)
# Fetch Actual Total Load Data from API
df = demand_api.demand_actual_total_get(
_from=from_date,
to=to_date,
settlement_period_from=1,
settlement_period_to=48,
format='dataframe'
)
# Print Actual Total Load Data DataFrame
print("\n--- Actual Total Load Data ---")
print(df.head())
This example demonstrates how to use methods from the IndicativeImbalanceSettlementApi
to retrieve settlement system prices data from the Elexon API and format it into a DataFrame.
Example 2
# This script demonstrates the use of methods from the IndicativeImbalanceSettlementApi
# to retrieve settlement system prices data from the Elexon API.
from datetime import datetime
import pandas as pd
from elexonpy.api_client import ApiClient
from elexonpy.api.indicative_imbalance_settlement_api import IndicativeImbalanceSettlementApi
## Initialize API client
api_client = ApiClient()
imbalance_settlement_api = IndicativeImbalanceSettlementApi(api_client)
# Define settlement date
settlement_date = '2024-07-02'
# Fetch system prices data from API
df = imbalance_settlement_api.balancing_settlement_system_prices_settlement_date_get(
settlement_date=settlement_date,
format='dataframe'
)
# Print DataFrame
print("\n--- Settlement System Prices Data ---")
print(df.head())
This example demonstrates how to use methods from the GenerationForecastApi
to retrieve
day-ahead forecast data for wind and solar generation from the Elexon API and format it into a DataFrame.
Example 3
# This script demonstrates the use of methods from the GenerationForecastApi
# to retrieve day-ahead forecast data for wind and solar generation from the Elexon API.
from datetime import datetime
import pandas as pd
from elexonpy.api_client import ApiClient
from elexonpy.api.generation_forecast_api import GenerationForecastApi
# Initialize API client
api_client = ApiClient()
forecast_api = GenerationForecastApi(api_client)
# Define date range for fetching day-ahead wind and solar forecast data
from_date = datetime(2024, 7, 1)
to_date = datetime(2024, 7, 7) # Note: Maximum data output range is 7 days
# Fetch day-ahead forecast data for wind and solar from API
df = forecast_api.forecast_generation_wind_and_solar_day_ahead_get(
_from=from_date,
to=to_date,
process_type='day ahead',
format='dataframe'
)
# Print DataFrame
print("\n--- Day-Ahead Wind and Solar Forecast Data ---")
print(df.head())
Documentation for the API Endpoints can be found here
Documentation for the Models can be found here
All endpoints do not require authorization.
You dont need one. The Elexon API does not require an API key for access.
You currently have to write a loop yourself. We hope to incorporate this into the package in the future.
To install the package directly from the GitHub repository, use the following command:
pip install git+https://github.com/openclimatefix/Elexonpy.git
To run the tests, make sure you have pytest
installed
pip install pytest
and then you can run
pytest
- PR's are welcome! See the Organisation Profile for details on contributing
- Find out about our other projects in the OCF Meta Repo
- Check out the OCF blog for updates
- Follow OCF on LinkedIn
Thanks goes to these wonderful people (emoji key):
Richa 💻 |
Peter Dudfield 👀 |
Matthew Duffin 🤔 |
Jacqueline James 💻 |
Yousef Elsawy 📖 |
Utkarsh Verma 🚧 |
Anas Khan 🚧 |
This project follows the all-contributors specification. Contributions of any kind welcome!
Part of the Open Climate Fix community.