import pandas as pd
import pytest
import gridstatus
from gridstatus.base import Markets
from gridstatus.tests.test_isos import check_status
[docs]def test_nyiso_date_range():
iso = gridstatus.NYISO()
df = iso.get_fuel_mix(start="Aug 1, 2022", end="Oct 22, 2022")
assert df.shape[0] >= 0
[docs]def test_get_nyiso_historical_status():
iso = gridstatus.NYISO()
date = "20220609"
status = iso.get_status(date)
check_status(status)
start = "2022-05-01"
end = "2022-10-02"
status = iso.get_status(start=start, end=end)
check_status(status)
[docs]def test_nyiso_get_historical_lmp_with_range():
iso = gridstatus.NYISO()
start = "2021-12-01"
end = "2022-2-02"
df = iso.get_lmp(
start=start,
end=end,
market=Markets.REAL_TIME_5_MIN,
)
assert df.shape[0] >= 0
[docs]def test_nyiso_edt_to_est():
# number of rows hardcoded based on when this test was written. should stay same
iso = gridstatus.NYISO()
date = "Nov 7, 2021"
df = iso.get_status(date=date)
assert df.shape[0] >= 1
df = iso.get_fuel_mix(date=date)
assert df.shape[0] >= 307
df = iso.get_load_forecast(date=date)
assert df.shape[0] >= 145
df = iso.get_lmp(date=date, market=Markets.REAL_TIME_5_MIN)
assert df.shape[0] >= 4605
df = iso.get_lmp(date=date, market=Markets.DAY_AHEAD_HOURLY)
assert df.shape[0] >= 375
df = iso.get_load(date=date)
assert df.shape[0] >= 307
[docs]def test_nyiso_est_to_edt():
# number of rows hardcoded based on when this test was written. should stay same
iso = gridstatus.NYISO()
date = "March 14, 2021"
df = iso.get_status(date=date)
assert df.shape[0] >= 5
df = iso.get_lmp(date=date, market=Markets.REAL_TIME_5_MIN)
assert df.shape[0] >= 4215
df = iso.get_lmp(date=date, market=Markets.DAY_AHEAD_HOURLY)
assert df.shape[0] >= 345
df = iso.get_load_forecast(date=date)
assert df.shape[0] >= 143
df = iso.get_fuel_mix(date=date)
assert df.shape[0] >= 281
df = iso.get_load(date=date)
assert df.shape[0] >= 281
[docs]def test_location_type_parameter():
iso = gridstatus.NYISO()
date = "2022-06-09"
df_zone = iso.get_lmp(
date=date,
market=Markets.DAY_AHEAD_HOURLY,
location_type="zone",
)
assert (df_zone["Location Type"] == "Zone").all()
df_gen = iso.get_lmp(
date=date,
market=Markets.DAY_AHEAD_HOURLY,
location_type="generator",
)
assert (df_gen["Location Type"] == "Generator").all()
df_zone = iso.get_lmp(
date="today",
market=Markets.DAY_AHEAD_HOURLY,
location_type="zone",
)
assert (df_zone["Location Type"] == "Zone").all()
df_gen = iso.get_lmp(
date="today",
market=Markets.DAY_AHEAD_HOURLY,
location_type="generator",
)
assert (df_gen["Location Type"] == "Generator").all()
df_zone = iso.get_lmp(
date="latest",
market=Markets.DAY_AHEAD_HOURLY,
location_type="zone",
)
assert (df_zone["Location Type"] == "Zone").all()
df_gen = iso.get_lmp(
date="latest",
market=Markets.DAY_AHEAD_HOURLY,
location_type="generator",
)
assert (df_gen["Location Type"] == "Generator").all()
with pytest.raises(ValueError):
df = iso.get_lmp(
date="latest",
market=Markets.DAY_AHEAD_HOURLY,
location_type="dummy",
)
[docs]def test_nyiso_get_generators():
iso = gridstatus.NYISO()
df = iso.get_generators()
columns = [
"Generator Name",
"PTID",
"Subzone",
"Zone",
"Latitude",
"Longitude",
]
assert set(df.columns).issuperset(set(columns))
assert df.shape[0] >= 0
[docs]def test_nyiso_get_loads():
iso = gridstatus.NYISO()
df = iso.get_loads()
columns = [
"Load Name",
"PTID",
"Subzone",
"Zone",
]
assert set(df.columns) == set(columns)
assert df.shape[0] >= 0
[docs]def test_nyiso_interconnection_queue():
iso = gridstatus.NYISO()
df = iso.get_interconnection_queue()
[docs]def test_nyiso_get_capacity_prices():
iso = gridstatus.NYISO()
df = iso.get_capacity_prices(verbose=True)
assert not df.empty, "Dataframe came back empty"
