vortexasdk.endpoints.vessel_availability_breakdown

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VesselAvailabilityBreakdown

VesselAvailabilityBreakdown(self)

Please note: you will require a subscription to our Freight module to access this endpoint.

search

VesselAvailabilityBreakdown.search(self, filter_products: Union[str, List[str]] = None, filter_vessels: Union[str, List[str]] = None, filter_vessel_classes: Union[str, List[str]] = None, filter_vessel_status: str = None, filter_vessel_location: Union[str, List[str]] = None, filter_owners: Union[str, List[str]] = None, filter_destination: Union[str, List[str]] = None, filter_region: str = None, filter_port: str = None, use_reference_port: bool = False, filter_days_to_arrival: List[Dict[str, int]] = None, filter_vessel_dwt_min: int = None, filter_vessel_dwt_max: int = None, filter_vessel_age_min: int = None, filter_vessel_age_max: int = None, filter_vessel_idle_min: int = None, filter_vessel_idle_max: int = None, filter_vessel_scrubbers: str = 'disabled', filter_recent_visits: str = None, exclude_products: Union[str, List[str]] = None, exclude_vessels: Union[str, List[str]] = None, exclude_vessel_classes: Union[str, List[str]] = None, exclude_vessel_status: str = None, exclude_vessel_location: Union[str, List[str]] = None, exclude_owners: Union[str, List[str]] = None, exclude_destination: Union[str, List[str]] = None) -> vortexasdk.endpoints.timeseries_result.TimeSeriesResult

Number and DWT of all vessels that can be available to load a given cargo at a given port, grouped by the number of days to arrival.

Arguments

  • filter_owners: An corporation ID, or list of corporation IDs to filter on.

  • filter_destination: A geography ID, or list of geography IDs to filter on.

  • filter_products: A product ID, or list of product IDs to filter on.

  • filter_vessels: A vessel ID, or list of vessel IDs to filter on.

  • filter_vessel_classes: A vessel class, or list of vessel classes to filter on.

  • filter_vessel_status: The vessel status on which to base the filter. Enter 'vessel_status_ballast' for ballast vessels, 'vessel_status_laden_known' for laden vessels with known cargo (i.e. a type of cargo that Vortexa currently tracks) or 'any_activity' for any other vessels

  • filter_vessel_location: A location ID, or list of location IDs to filter on.

  • filter_port: Filter by port ID.

  • filter_region: Filter by region ID - takes precedence over filter_port if provided. This should be used in conjunction with use_reference_port

  • filter_days_to_arrival: Filter availability by time to arrival in days`

  • use_reference_port: If this flag is enabled, we will return data for the reference port instead of the user selected one,

  • filter_vessel_age_min: A number between 1 and 100 (representing years).

  • filter_vessel_age_max: A number between 1 and 100 (representing years).

  • filter_vessel_idle_min: A number greater than 0 (representing idle days).

  • filter_vessel_idle_max: A number greater than 0 and filter_vessel_idle_min (representing idle days).

  • filter_vessel_dwt_min: A number between 0 and 550000.

  • filter_vessel_dwt_max: A number between 0 and 550000.

  • filter_vessel_scrubbers: Either inactive 'disabled', or included 'inc' or excluded 'exc'.

  • filter_recent_visits: Filter availability by each vessel's recent visits

  • exclude_products: A product ID, or list of product IDs to exclude.

  • exclude_vessels: A vessel ID, or list of vessel IDs to exclude.

  • exclude_vessel_classes: A vessel class, or list of vessel classes to exclude.

  • exclude_vessel_status: The vessel status on which to base the filter. Enter 'vessel_status_ballast' for ballast vessels, 'vessel_status_laden_known' for laden vessels with known cargo (i.e. a type of cargo that Vortexa currently tracks) or 'any_activity' for any other vessels

  • exclude_owners: An owner ID, or list of owner IDs to exclude.

  • exclude_vessel_location: A location ID, or list of location IDs to filter on.

  • exclude_destination: A location ID, or list of location IDs to filter on.

Returns

TimeSeriesResult

Example

Breakdown of number and DWT of all vessels arriving at Rotterdam in the next 5 days.

>>> from vortexasdk import VesselAvailabilityBreakdown, Geographies
>>> rotterdam = [g.id for g in Geographies().search("rotterdam").to_list() if "port" in g.layer]
>>> df = VesselAvailabilityBreakdown().search(
...        filter_port=rotterdam[0],
...        filter_days_to_arrival={"min": 0, "max": 5}
... ).to_df()

Gives the following:

key value count
0 2021-06-23 00:00:00+00:00 2939754 34
1 2021-06-24 00:00:00+00:00 2676732 38
2 2021-06-25 00:00:00+00:00 6262914 74
3 2021-06-26 00:00:00+00:00 3445105 43
4 2021-06-27 00:00:00+00:00 3924460 51