Python wrapper for RTE API requests.

1. Usage

pip install rtedata

1.1. Get RTE API credentials

You need to follow these first steps in order to setup your wrapper :

• create an account on the RTE platform
• create an application associated to your account (the name and description of the app is not relevant)
• collect your app IDs (ID Client and ID Secret) available in your application dashboard
• subscribe to the relevant APIs regarding the "data_type" you request (please refer to the table in the last section to get the associated links)

1.2. Generate a data retrieval

To retrieve data using the wrapper, follow this pipeline :

from rtedata import Client
client = Client(client_id="XXX", client_secret="XXX")
dfs = client.retrieve_data(start_date="2024-01-01 00:00:00", end_date="2024-01-02 23:59:00", data_type="actual_generations_per_unit", output_dir="./output")

where :

• start_date is the first date of the data retrieval (format YYYY-MM-DD HH:MM:SS)
• end_date is the last date of the data retrieval (format YYYY-MM-DD HH:MM:SS)
• data_type is the desired data to collect (a keyword list is given in the next section). It can be a single keyword "XXX" or a list of keyword separated by a comma "XXX,YYY,ZZZ"
• output_dir (optionnal): the output directory to store the results

The generic output format is a pandas dataframe / .csv file containing the data for all dates between start_date and end_date. It will generate one file per desired data_type and will store all of them in a ./results folder with the generic name "<data_type><start_date><end_date>.csv".

2. Available data_type options

It is possible to see the full options catalog using the client attribute catalog :

from rtedata import Client
client = Client(client_id="XXX", client_secret="XXX")
client.catalog

The following table is an exhaustive list of all possible (currently handled) options for the data_type argument for the retrieval, and the description of the associated data :

Generation Data

data_type	Catalog URL	Documentation URL
actual_generations_per_production_type	Link	Link
actual_generations_per_unit	Link	Link
generation_mix_15min_time_scale	Link	Link
capacities_per_production_unit	Link	Link
other_market_information	Link	Link
transmission_network_unavailabilities	Link	Link
generation_unavailabilities	Link	Link
forecasts	Link	Link

Market Data

data_type	Catalog URL	Documentation URL
volumes_per_energy_type	Link	Link
prices	Link	Link
imbalance_data	Link	Link
lead_times	Link	Link
volumes_per_entity_type	Link	Link
tso_offers	Link	Link
volumes_per_reasons	Link	Link

Consumption Data

data_type	Catalog URL	Documentation URL
signals	Link	Link
volumes	Link	Link
tempo_like_calendars	Link	Link
annual_forecasts	Link	Link
weekly_forecasts	Link	Link
short_term	Link	Link
consolidated_power_consumption	Link	Link
consolidated_energy_consumption	Link	Link