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Liquicomun

License: GNU Affero General Public License v3.0

Python 100.00%

ree esios parser api python hacktoberfest

liquicomun's Introduction

Liquicomun lib

It provides a simple interface to reach ESIOS Liquicomun data.

Handled data:

Perdidas (losses)
Precios (prices)

Installation

pip install liquicomun

Usage

Fetch all available losses for a concrete date

It provides an iterator that handle all the available losses for the requested scenario.

For each iteration it return the related next Perdida instance (loss).

Start and end dates are mandatory.

Tariffs and subsystems list are optional, and override the default list of elements to process.

from liquicomun import Perdidas

scenario = {
    'date_start': '20171001',
    'date_end': '20171031',
    #'tariffs': ['2.0A'],                   # Optional tariffs list
    #'subsystems': ["baleares", "ceuta"],   # Optional subsystems list
}

losses = Perdidas(**scenario)

# Iterate losses
for a_loss in losses:
    current_tariff = a_loss.tariff
    current_subsystem = a_loss.subsystem
    data_matrix = a_loss.matrix
    data_version = a_loss.version

Fetch just the losses for one tariff and subsystem

It return a Loss instance

The expected tariff, start and end dates are mandatory.

Subsystem and version are optional. If no subsystem is provided will fetch the peninsular data.

from liquicomun import Perdida

scenario = {
    'date_start': '20171001',
    'date_end': '20171031',
    'tariff': '2.0A',
    #'subsystem': "baleares",              # default "" -> peninsula
}

a_loss = Perdida(**scenario)

data_matrix = a_loss.matrix
data_version = a_loss.version
current_tariff = a_loss.tariff
current_subsystem = a_loss.subsystem

liquicomun's People

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liquicomun's Issues

Integrate subsytems losses

Losses by subsystem must be integrated.

So far, just central losses has been integrated.

Provide an intelligent Perdidas class

Provide an intelligent Perdidas class that auto-use the expected Class depending on the asked filename.

Losses iterator

Provide an iterator to handle all the available (in-scope) losses for a requested scenario (dates, subsystems, tariffs).

This will simplify the processal of all the available losses directly iterating a Perdidas instance.

Create library migrating from libfacturacioATR

Split lliquicomun functionality from https://github.com/gisce/libfacturacioATR. See https://github.com/gisce/libFacturacioATR/issues/70

Ensure that is compatible with py2.7 and 3.6

Improve losses import method

OrakWlum only allows to import the ESIOS loss coefficients until the C3 version of each month, since later versions (from C4 to C5) do not include the fileCX_perdXXX_AAAMM01_AAAMMUU.

A good proposal to be able to use up to the C5 file, and therefore the real losses, would be to replace the way in which the losses are imported in the system.

Old method

Losses are read and imported hour by hour for each day of the month from the perdXXX_AAAMM01_AAAMMUU file downloaded from ESIOS.

Proposed method

Losses are read, calculated and imported hour by hour for each day of the month through the following formula, using the KEST and KREAL files downloaded from ESIOS:

coef_tariff= K * coef_boe

where:

coef_tariff is the loss coefficient that will be applied for the current tariff.
K is the coefficient KEST (estimated, from A1 to C2) or KREAL (real, from C3 to C5).
coef_boe is the percentage of loss per tariff and period set via BOE (A-2014-1052).