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tests.py
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tests.py
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import unittest
import pandas as pd
from bs4 import BeautifulSoup
from entsoe import EntsoeRawClient, EntsoePandasClient
from entsoe.exceptions import NoMatchingDataError
from settings import *
class EntsoeRawClientTest(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.client = EntsoeRawClient(api_key=api_key)
cls.start = pd.Timestamp('20180101', tz='Europe/Brussels')
cls.end = pd.Timestamp('20180107', tz='Europe/Brussels')
cls.country_code = 'BE'
def test_datetime_to_str(self):
start_str = self.client._datetime_to_str(dtm=self.start)
self.assertIsInstance(start_str, str)
self.assertEqual(start_str, '201712312300')
def test_basic_queries(self):
queries = [
self.client.query_day_ahead_prices,
self.client.query_load,
self.client.query_wind_and_solar_forecast,
self.client.query_load_forecast,
self.client.query_generation,
self.client.query_generation_forecast,
self.client.query_installed_generation_capacity,
# these give back a zip so disabled for testing right now
#self.client.query_imbalance_prices,
#self.client.query_imbalance_volumes,
self.client.query_net_position
]
for query in queries:
text = query(country_code=self.country_code, start=self.start,
end=self.end)
self.assertIsInstance(text, str)
try:
BeautifulSoup(text, 'html.parser')
except Exception as e:
self.fail(f'Parsing of response failed with exception: {e}')
def query_crossborder_flows(self):
text = self.client.query_crossborder_flows(
country_code_from='BE', country_code_to='NL', start=self.start,
end=self.end)
self.assertIsInstance(text, str)
try:
BeautifulSoup(text, 'html.parser')
except Exception as e:
self.fail(f'Parsing of response failed with exception: {e}')
def test_query_unavailability_of_generation_units(self):
text = self.client.query_unavailability_of_generation_units(
country_code='BE', start=self.start,
end=self.end)
self.assertIsInstance(text, bytes)
def test_query_withdrawn_unavailability_of_generation_units(self):
with self.assertRaises(NoMatchingDataError):
self.client.query_withdrawn_unavailability_of_generation_units(
country_code='BE', start=self.start, end=self.end)
def test_query_procured_balancing_capacity(self):
text = self.client.query_procured_balancing_capacity(
country_code='CZ',
start=pd.Timestamp('20210101', tz='Europe/Prague'),
end=pd.Timestamp('20210102', tz='Europe/Prague'),
process_type='A51'
)
self.assertIsInstance(text, bytes)
try:
BeautifulSoup(text, 'html.parser')
except Exception as e:
self.fail(f'Parsing of response failed with exception: {e}')
class EntsoePandasClientTest(EntsoeRawClientTest):
@classmethod
def setUpClass(cls):
cls.client = EntsoePandasClient(api_key=api_key)
cls.start = pd.Timestamp('20180101', tz='Europe/Brussels')
cls.end = pd.Timestamp('20180107', tz='Europe/Brussels')
cls.country_code = 'BE'
def test_basic_queries(self):
pass
def test_basic_series(self):
queries = [
self.client.query_day_ahead_prices,
self.client.query_generation_forecast,
self.client.query_net_position
]
for query in queries:
ts = query(country_code=self.country_code, start=self.start,
end=self.end)
self.assertIsInstance(ts, pd.Series)
def query_crossborder_flows(self):
ts = self.client.query_crossborder_flows(
country_code_from='BE', country_code_to='NL', start=self.start,
end=self.end)
self.assertIsInstance(ts, pd.Series)
def test_basic_dataframes(self):
queries = [
self.client.query_load,
self.client.query_load_forecast,
self.client.query_wind_and_solar_forecast,
self.client.query_generation,
self.client.query_installed_generation_capacity,
self.client.query_imbalance_prices,
self.client.query_imbalance_volumes,
self.client.query_unavailability_of_generation_units
]
for query in queries:
ts = query(country_code=self.country_code, start=self.start,
end=self.end)
self.assertIsInstance(ts, pd.DataFrame)
def test_query_unavailability_of_generation_units(self):
pass
def test_query_procured_balancing_capacity(self):
ts = self.client.query_procured_balancing_capacity(
country_code='CZ',
start=pd.Timestamp('20210101', tz='Europe/Prague'),
end=pd.Timestamp('20210102', tz='Europe/Prague'),
process_type='A51'
)
self.assertIsInstance(ts, pd.DataFrame)
def test_year_limited_truncation(self):
"""
This is a specific example of polish operator correcting the data
i.e. there was an additional monthly auction for this period.
This results in duplicated time indices.
source: https://www.pse.pl/web/pse-eng/cross-border-electricity-exchange/auction-office/rzeszow-chmielnicka-interconnection/auction-results # noqa
"""
start = pd.Timestamp('2023-07-17 00:00:00', tz='Europe/Warsaw')
end = pd.Timestamp('2023-08-01 00:00:00', tz='Europe/Warsaw')
ts = self.client.query_offered_capacity(
'UA_IPS', 'PL',
start=start, end=end,
contract_marketagreement_type='A03',
implicit=False
)
total_hours = int((end - start).total_seconds()/60/60)
# Expected behaviour is to keep both initial data and corrections
# and leave the deduplication to the user.
self.assertEqual(total_hours*2, ts.shape[0])
def test_documents_limited_truncation(self):
ts = pd.DatetimeIndex(
["2022-03-01", "2022-03-11", "2022-03-21", "2022-04-01"],
tz="Europe/Berlin"
)
part_dfs = []
for i in range(len(ts) - 1):
df = self.client.query_contracted_reserve_prices(
'DE_LU', start=ts[i], end=ts[i+1],
type_marketagreement_type='A01'
)
part_dfs.append(df)
df_parts = pd.concat(part_dfs)
df_full = self.client.query_contracted_reserve_prices(
'DE_LU', start=ts[0], end=ts[-1],
type_marketagreement_type='A01'
)
self.assertEqual(df_parts.shape, df_full.shape)
self.assertTrue(all(df_parts.isna().sum() == df_full.isna().sum()))
if __name__ == '__main__':
unittest.main()