Caiso ========================== .. py:module:: gridstatus.caiso Submodules ---------- .. toctree:: :titlesonly: :maxdepth: 1 caiso/index.rst caiso_constants/index.rst caiso_utils/index.rst Package Contents ---------------- Classes Summary ~~~~~~~~~~~~~~~ .. autoapisummary:: gridstatus.caiso.CAISO Contents ~~~~~~~~~~~~~~~~~~~ .. py:class:: CAISO Bases: :py:obj:`gridstatus.base.ISOBase` California Independent System Operator (CAISO) **Attributes** .. list-table:: :widths: 15 85 :header-rows: 0 * - **default_timezone** - 'US/Pacific' * - **interconnection_homepage** - 'https://rimspub.caiso.com/rimsui/logon.do' * - **iso_id** - 'caiso' * - **markets** - None * - **name** - 'California ISO' * - **status_homepage** - 'https://www.caiso.com/TodaysOutlook/Pages/default.aspx' * - **trading_hub_locations** - ['TH_NP15_GEN-APND', 'TH_SP15_GEN-APND', 'TH_ZP26_GEN-APND'] **Methods** .. autoapisummary:: :nosignatures: gridstatus.caiso.CAISO.get_as_prices gridstatus.caiso.CAISO.get_as_procurement gridstatus.caiso.CAISO.get_caiso_renewables_report gridstatus.caiso.CAISO.get_curtailed_non_operational_generator_report gridstatus.caiso.CAISO.get_curtailment gridstatus.caiso.CAISO.get_curtailment_legacy gridstatus.caiso.CAISO.get_fuel_mix gridstatus.caiso.CAISO.get_fuel_regions gridstatus.caiso.CAISO.get_gas_prices gridstatus.caiso.CAISO.get_ghg_allowance gridstatus.caiso.CAISO.get_interconnection_queue gridstatus.caiso.CAISO.get_intertie_constraint_shadow_prices_real_time_5_min gridstatus.caiso.CAISO.get_interval_nomogram_branch_shadow_prices_real_time_5_min gridstatus.caiso.CAISO.get_lmp gridstatus.caiso.CAISO.get_lmp_hasp_15_min gridstatus.caiso.CAISO.get_lmp_scheduling_point_tie_day_ahead_hourly gridstatus.caiso.CAISO.get_lmp_scheduling_point_tie_real_time_15_min gridstatus.caiso.CAISO.get_lmp_scheduling_point_tie_real_time_5_min gridstatus.caiso.CAISO.get_load gridstatus.caiso.CAISO.get_load_forecast gridstatus.caiso.CAISO.get_load_forecast_15_min gridstatus.caiso.CAISO.get_load_forecast_5_min gridstatus.caiso.CAISO.get_load_forecast_day_ahead gridstatus.caiso.CAISO.get_load_forecast_seven_day_ahead gridstatus.caiso.CAISO.get_load_forecast_two_day_ahead gridstatus.caiso.CAISO.get_load_hourly gridstatus.caiso.CAISO.get_nomogram_branch_shadow_price_forecast_15_min gridstatus.caiso.CAISO.get_nomogram_branch_shadow_prices_day_ahead_hourly gridstatus.caiso.CAISO.get_nomogram_branch_shadow_prices_hasp_hourly gridstatus.caiso.CAISO.get_oasis_dataset gridstatus.caiso.CAISO.get_pnodes gridstatus.caiso.CAISO.get_raw_interconnection_queue gridstatus.caiso.CAISO.get_renewables_forecast_dam gridstatus.caiso.CAISO.get_renewables_forecast_hasp gridstatus.caiso.CAISO.get_renewables_forecast_rtd gridstatus.caiso.CAISO.get_renewables_forecast_rtpd gridstatus.caiso.CAISO.get_renewables_hourly gridstatus.caiso.CAISO.get_stats gridstatus.caiso.CAISO.get_status gridstatus.caiso.CAISO.get_storage gridstatus.caiso.CAISO.get_system_load_and_resource_schedules_day_ahead gridstatus.caiso.CAISO.get_system_load_and_resource_schedules_hasp gridstatus.caiso.CAISO.get_system_load_and_resource_schedules_real_time_5_min gridstatus.caiso.CAISO.get_system_load_and_resource_schedules_ruc gridstatus.caiso.CAISO.get_tie_flows_real_time gridstatus.caiso.CAISO.get_tie_flows_real_time_15_min gridstatus.caiso.CAISO.list_oasis_datasets .. py:method:: get_as_prices(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, market: str = 'DAM', sleep: int = 4, verbose: bool = False) -> pandas.DataFrame Return AS prices for a given date for each region :param date: date to return data :type date: datetime.date, str :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: datetime.date, str :param market: DAM or HASP. Defaults to DAM. :type market: str :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :returns: A DataFrame of AS prices :rtype: pandas.DataFrame .. py:method:: get_as_procurement(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, market: str = 'DAM', sleep: int = 4, verbose: bool = False) -> pandas.DataFrame Get ancillary services procurement data from CAISO. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp | None, optional :param market: DAM or RTM. Defaults to "DAM". :type market: str, optional :param sleep: number of seconds to sleep between requests. Defaults to 4. :type sleep: int, optional :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :returns: A DataFrame of ancillary services data :rtype: pandas.DataFrame .. py:method:: get_caiso_renewables_report(date: pandas.Timestamp) -> dict[str, pandas.DataFrame] Fetches the CAISO daily renewable report for a given date and extracts data from all the charts into wide dataframes. .. py:method:: get_curtailed_non_operational_generator_report(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Return curtailed non-operational generator report for a given date. Earliest available date is June 17, 2021. :param date: date to return data :type date: str, pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str, pd.Timestamp, optional :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :returns: A DataFrame of curtailed non-operational generator report :rtype: pandas.DataFrame .. rubric:: Notes Column glossary: http://www.caiso.com/market/Pages/OutageManagement/Curtailed-OperationalGeneratorReportGlossary.aspx If requesting multiple days, you may want to run the following to remove outages that get reported across multiple days:: df.drop_duplicates( subset=["OUTAGE MRID", "CURTAILMENT START DATE TIME"], keep="last", ) .. py:method:: get_curtailment(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Return curtailment data for a given date :param date: date to return data :type date: datetime.date, str :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: datetime.date, str :param verbose: print out url being fetched. Defaults to False. :returns: A DataFrame of curtailment data :rtype: pandas.DataFrame .. py:method:: get_curtailment_legacy(date: str | pandas.Timestamp, verbose: bool = False) -> pandas.DataFrame Return curtailment data for a given date. .. note:: Data available from June 30, 2016 to May 31, 2025. For current data, please use ``get_curtailment``. :param date: Date to return data. :param verbose: Print out url being fetched. Defaults to False. :returns: A DataFrame of curtailment data. .. py:method:: get_fuel_mix(date: str | pandas.Timestamp, start: str | pandas.Timestamp | None = None, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get fuel mix in 5 minute intervals for a provided day. :param date: "latest", "today", or an object that can be parsed as a datetime for the day to return data. :param start: Start of date range to return. Alias for ``date`` parameter. Only specify one of ``date`` or ``start``. :param end: "today" or an object that can be parsed as a datetime for the day to return data. Only used if requesting a range of dates. :param verbose: Print verbose output. Defaults to False. :returns: A DataFrame with columns for Time and each fuel type. .. py:method:: get_fuel_regions(verbose: bool = False) -> pandas.DataFrame Retrieves the (mostly static) list of fuel regions with associated data. This file can be joined to the gas prices on Fuel Region Id .. py:method:: get_gas_prices(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, fuel_region_id: str | list = 'ALL', sleep: int = 4, verbose: bool = False) Return gas prices at a previous date :param date: date to return data :type date: datetime.date, str :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: datetime.date, str :param fuel_region_id: single fuel region id or list of fuel region ids to return data for. Defaults to ALL, which returns all fuel regions. :type fuel_region_id: str, or list :returns: A DataFrame of gas prices :rtype: pandas.DataFrame .. py:method:: get_ghg_allowance(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, sleep: int = 4, verbose: bool = False) Return ghg allowance at a previous date :param date: date to return data :type date: datetime.date, str :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: datetime.date, str .. py:method:: get_interconnection_queue(verbose: bool = False) -> pandas.DataFrame .. py:method:: get_intertie_constraint_shadow_prices_real_time_5_min(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get 5-min intertie constraint shadow prices from CAISO. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. :type verbose: bool, optional :returns: A DataFrame with the intertie constraint shadow prices :rtype: pandas.DataFrame .. py:method:: get_interval_nomogram_branch_shadow_prices_real_time_5_min(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get 5-min nomogram/branch shadow prices from CAISO. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. :type verbose: bool, optional :returns: A DataFrame with the shadow prices :rtype: pandas.DataFrame .. py:method:: get_lmp(date: str | pandas.Timestamp, market: str, locations: list = None, sleep: int = 5, end: str | pandas.Timestamp = None, verbose: bool = False) Get LMP pricing starting at supplied date for a list of locations. :param date: date to return data :type date: datetime.date, str :param market: market to return from. supports: :param locations: list of locations to get data from. If no locations are provided, defaults to NP15, SP15, and ZP26, which are the trading hub locations. USE "ALL_AP_NODES" for all Aggregate Pricing Node. Use "ALL" to get all nodes. For a list of locations, call ``CAISO.get_pnodes()`` :type locations: list :param sleep: number of seconds to sleep before returning to avoid hitting rate limit in regular usage. Defaults to 5 seconds. :type sleep: int :returns: A DataFrame of pricing data :rtype: pandas.DataFrame .. py:method:: get_lmp_hasp_15_min(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get LMP HASP 15-min data from CAISO. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :returns: A DataFrame of LMP HASP 15-min data :rtype: pandas.DataFrame .. py:method:: get_lmp_scheduling_point_tie_day_ahead_hourly(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame .. py:method:: get_lmp_scheduling_point_tie_real_time_15_min(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame .. py:method:: get_lmp_scheduling_point_tie_real_time_5_min(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get LMP scheduling point tie combination 5-min data from CAISO. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :returns: A DataFrame of LMP scheduling point tie combination 5-min data :rtype: pandas.DataFrame .. py:method:: get_load(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Return load at a previous date in 5 minute intervals .. py:method:: get_load_forecast(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame .. py:method:: get_load_forecast_15_min(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, sleep: int = 4, verbose: bool = False) -> pandas.DataFrame Returns 15-minute load forecast from the Real-Time Pre-Dispatch Market :param date: day to return :type date: str | pd.Timestamp :param end: end of date range to return. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp, optional :param sleep: seconds to sleep before returning to avoid rate limit. Defaults to 4. :type sleep: int :param verbose: print verbose output. Defaults to False. :type verbose: bool :returns: DataFrame with load forecast data :rtype: pd.DataFrame .. py:method:: get_load_forecast_5_min(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, sleep: int = 4, verbose: bool = False) -> pandas.DataFrame Returns 5-minute load forecast from the Real-Time Market :param date: day to return :type date: str | pd.Timestamp :param end: end of date range to return. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp, optional :param sleep: seconds to sleep before returning to avoid rate limit. Defaults to 4. :type sleep: int :param verbose: print verbose output. Defaults to False. :type verbose: bool :returns: DataFrame with load forecast data :rtype: pd.DataFrame .. py:method:: get_load_forecast_day_ahead(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, sleep: int = 4, verbose: bool = False) -> pandas.DataFrame Returns hourly day-ahead load forecast :param date: day to return :type date: str | pd.Timestamp :param end: end of date range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp, optional :param sleep: seconds to sleep before returning to avoid rate limit. Defaults to 4. :type sleep: int :param verbose: print verbose output. Defaults to False. :type verbose: bool :returns: DataFrame with load forecast data :rtype: pd.DataFrame .. py:method:: get_load_forecast_seven_day_ahead(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, sleep: int = 4, verbose: bool = False) -> pandas.DataFrame Returns hourly seven-day-ahead load forecast :param date: day to return :type date: str | pd.Timestamp :param end: end of date range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp, optional :param sleep: seconds to sleep before returning to avoid rate limit. Defaults to 4. :type sleep: int :param verbose: print verbose output. Defaults to False. :type verbose: bool :returns: DataFrame with load forecast data :rtype: pd.DataFrame .. py:method:: get_load_forecast_two_day_ahead(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, sleep: int = 4, verbose: bool = False) -> pandas.DataFrame Returns hourly two-day-ahead load forecast :param date: day to return :type date: str | pd.Timestamp :param end: end of date range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp, optional :param sleep: seconds to sleep before returning to avoid rate limit. Defaults to 4. :type sleep: int :param verbose: print verbose output. Defaults to False. :type verbose: bool :returns: DataFrame with load forecast data :rtype: pd.DataFrame .. py:method:: get_load_hourly(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, sleep: int = 4, verbose: bool = False) -> pandas.DataFrame Returns actual load values :param date: day to return :type date: str | pd.Timestamp :param end: end of date range to return. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp, optional :param sleep: seconds to sleep before returning to avoid rate limit. Defaults to 4. :type sleep: int :param verbose: print verbose output. Defaults to False. :type verbose: bool :returns: DataFrame with actual load data :rtype: pd.DataFrame .. py:method:: get_nomogram_branch_shadow_price_forecast_15_min(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Returns 15-minute nomogram/branch shadow price forecast from the Real-Time Pre-Dispatch Market. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. :type verbose: bool, optional :returns: A DataFrame with the shadow price forecast :rtype: pandas.DataFrame .. py:method:: get_nomogram_branch_shadow_prices_day_ahead_hourly(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Returns hourly day-ahead nomogram/branch shadow price forecast. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. :type verbose: bool, optional :returns: A DataFrame with the shadow price forecast :rtype: pandas.DataFrame .. py:method:: get_nomogram_branch_shadow_prices_hasp_hourly(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Returns nomogram/branch shadow price HASP hourly data from CAISO. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. :type verbose: bool, optional :returns: A DataFrame with the shadow price HASP data :rtype: pandas.DataFrame .. py:method:: get_oasis_dataset(dataset: str, date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, params: dict | None = None, raw_data: bool = True, sleep: int = 5, verbose: bool = False) -> pandas.DataFrame Return data from OASIS for a given dataset :param dataset: dataset to return data for. See CAISO.list_oasis_datasets for supported datasets :type dataset: str :param date: date to return data :type date: str, pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str, pd.Timestamp, optional :param params: dictionary of parameters to pass to dataset. See CAISO.list_oasis_datasets for supported parameters :type params: dict :param raw_data: return raw data from OASIS. Defaults to True. :type raw_data: bool, optional :param sleep: number of seconds to sleep between requests. Defaults to 5. :type sleep: int, optional :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :raises ValueError: if parameter is not supported for dataset :raises ValueError: if parameter value is not supported for dataset :returns: A DataFrame of data from OASIS :rtype: pd.DataFrame .. py:method:: get_pnodes(verbose: bool = False) -> pandas.DataFrame .. py:method:: get_raw_interconnection_queue(verbose: bool = False) -> pandas.DataFrame .. py:method:: get_renewables_forecast_dam(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Return DAM renewable forecast in hourly intervals Data at: http://oasis.caiso.com/mrioasis/logon.do at System Demand > DAM Renewable Forecast .. py:method:: get_renewables_forecast_hasp(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get solar and wind generation HASP hourly data from CAISO. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :returns: A DataFrame of solar and wind generation HASP hourly data :rtype: pandas.DataFrame .. py:method:: get_renewables_forecast_rtd(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get RTD renewable forecast from CAISO. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :returns: A DataFrame of RTD renewable forecast :rtype: pandas.DataFrame .. py:method:: get_renewables_forecast_rtpd(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get RTPD renewable forecast from CAISO. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :returns: A DataFrame of RTPD renewable forecast :rtype: pandas.DataFrame .. py:method:: get_renewables_hourly(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get wind and solar hourly actuals from CAISO. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :returns: A DataFrame of wind and solar hourly actuals :rtype: pandas.DataFrame .. py:method:: get_stats(verbose: bool = False) -> dict .. py:method:: get_status(date: str = 'latest', verbose: bool = False) -> str Get Current Status of the Grid. Only date="latest" is supported Known possible values: Normal, Restricted Maintenance Operations, Flex Alert .. py:method:: get_storage(date: str | pandas.Timestamp, verbose: bool = False) -> pandas.DataFrame Return storage charging or discharging for today in 5 minute intervals Negative means charging, positive means discharging :param date: date to return data :type date: datetime.date, str .. py:method:: get_system_load_and_resource_schedules_day_ahead(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get CAISO System Load and Resource Schedules Day-Ahead data from CAISO. .. py:method:: get_system_load_and_resource_schedules_hasp(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get CAISO System Load and Resource Schedules HASP data from CAISO. .. py:method:: get_system_load_and_resource_schedules_real_time_5_min(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get CAISO System Load and Resource Schedules Real Time data from CAISO. .. py:method:: get_system_load_and_resource_schedules_ruc(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Get CAISO System Load and Resource Schedules RUC data from CAISO. .. py:method:: get_tie_flows_real_time(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame Return real time tie flow data. :param date: date to return data :type date: str | pd.Timestamp :param end: last date of range to return data. If None, returns only date. Defaults to None. :type end: str | pd.Timestamp | None, optional :param verbose: print out url being fetched. Defaults to False. :type verbose: bool, optional :returns: A DataFrame of real time tie flow data :rtype: pd.DataFrame .. py:method:: get_tie_flows_real_time_15_min(date: str | pandas.Timestamp, end: str | pandas.Timestamp | None = None, verbose: bool = False) -> pandas.DataFrame .. py:method:: list_oasis_datasets(dataset: str | None = None) List all available OASIS datasets and their parameters. :param dataset: dataset to return data for. If None, returns all datasets. :type dataset: str, optional