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(
filter_products: typing.Union[str, typing.List[str], NoneType] = None,
filter_vessels: typing.Union[str, typing.List[str], NoneType] = None,
filter_vessel_classes: typing.Union[str, typing.List[str], NoneType] = None,
filter_vessel_status: typing.Optional[str] = None,
filter_vessel_location:
typing.Union[str, typing.List[str], NoneType] = None,
filter_owners: typing.Union[str, typing.List[str], NoneType] = None,
filter_effective_controllers:
typing.Union[str, typing.List[str], NoneType] = None,
filter_destination: typing.Union[str, typing.List[str], NoneType] = None,
filter_region: typing.Optional[str] = None,
filter_port: typing.Optional[str] = None,
use_reference_port: bool = False,
filter_days_to_arrival:
typing.Optional[typing.List[typing.Dict[str, int]]] = None,
filter_vessel_dwt_min: typing.Optional[int] = None,
filter_vessel_dwt_max: typing.Optional[int] = None,
filter_vessel_age_min: typing.Optional[int] = None,
filter_vessel_age_max: typing.Optional[int] = None,
filter_vessel_idle_min: typing.Optional[int] = None,
filter_vessel_idle_max: typing.Optional[int] = None,
filter_vessel_scrubbers: str = 'disabled',
filter_recent_visits: typing.Optional[str] = None,
filter_vessel_flags: typing.Union[str, typing.List[str], NoneType] = None,
filter_vessel_ice_class:
typing.Union[str, typing.List[str], NoneType] = None,
filter_vessel_tags:
typing.Union[typing.List[vortexasdk.api.shared_types.Tag], vortexasdk.api.shared_types.Tag, NoneType] = None,
filter_vessel_risk_level:
typing.Union[str, typing.List[str], NoneType] = None,
exclude_products: typing.Union[str, typing.List[str], NoneType] = None,
exclude_vessels: typing.Union[str, typing.List[str], NoneType] = None,
exclude_vessel_classes:
typing.Union[str, typing.List[str], NoneType] = None,
exclude_vessel_status: typing.Optional[str] = None,
exclude_vessel_location:
typing.Union[str, typing.List[str], NoneType] = None,
exclude_owners: typing.Union[str, typing.List[str], NoneType] = None,
exclude_effective_controllers:
typing.Union[str, typing.List[str], NoneType] = None,
exclude_destination: typing.Union[str, typing.List[str], NoneType] = None,
exclude_filter_vessel_flags:
typing.Union[str, typing.List[str], NoneType] = None,
exclude_filter_vessel_ice_class:
typing.Union[str, typing.List[str], NoneType] = None,
exclude_filter_vessel_tags:
typing.Union[typing.List[vortexasdk.api.shared_types.Tag], vortexasdk.api.shared_types.Tag, NoneType] = None,
exclude_filter_vessel_risk_level:
typing.Union[str, typing.List[str], NoneType] = None)
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_effective_controllers: An effective controller ID, or list of effective controller 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_vessel_flags: A flag ID, or list of flag IDs to filter on.
filter_vessel_ice_class: An ice class ID, or list of ice class IDs to filter on.
filter_vessel_tags: A tag ID, or list of tag IDs to filter on.
filter_vessel_risk_level: A risk level ID, or list of risk level IDs to filter on.
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_effective_controllers: An effective controller ID, or list of effective controller 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.
exclude_filter_vessel_flags: A flag ID, or list of flag IDs to exclude.
exclude_filter_vessel_ice_class: An ice class ID, or list of ice class IDs to exclude.
exclude_filter_vessel_tags: A tag ID, or list of tag IDs to exclude.
exclude_filter_vessel_risk_level: A risk level ID, or list of risk level IDs to exclude.
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 |