vortexasdk.endpoints.anywhere_freight_pricing_top_ports_destination

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AnywhereFreightPricingTopPortsDestination

AnywhereFreightPricingTopPortsDestination(self)

Anywhere Freight Pricing Top Ports Destination endpoint.

List top destination ports. A top destination port refers to the port with the greatest volume of incoming voyages from vessels in a specified class.

Please note, a subscription to our Anywhere Freight Pricing module is required to access Anywhere Freight Pricing.

search

AnywhereFreightPricingTopPortsDestination.search(
    origin_id: str,
    vessel_class:
    typing_extensions.Literal['oil_coastal', 'oil_specialised', 'oil_handysize_mr1', 'oil_handymax_mr2', 'oil_panamax_lr1', 'oil_aframax_lr2', 'oil_suezmax_lr3', 'oil_vlcc'],
    product: typing_extensions.Literal['clean', 'dirty', 'crude'],
    unit:
    typing_extensions.Literal['usd_per_tonne', 'usd_per_barrel'] = 'usd_per_tonne',
    avoid_zone:
    typing.Optional[typing.List[typing_extensions.Literal['Panama Canal', 'Suez Canal']]] = None
)

List top destination ports from a given origin.

A top destination port refers to the port with the greatest volume of incoming voyages from vessels in a specified class.

Arguments

origin_id: Geographical ID of the origin port.

vessel_class: The vessel class for the route. Must be one of:
    `'oil_coastal'`, `'oil_specialised'`, `'oil_handysize_mr1'`,
    `'oil_handymax_mr2'`, `'oil_panamax_lr1'`, `'oil_aframax_lr2'`,
    `'oil_suezmax_lr3'`, `'oil_vlcc'`.

product: The product type. Must be one of: `'clean'`, `'dirty'`, `'crude'`.

unit: The unit for pricing. Must be one of: `'usd_per_tonne'`, `'usd_per_barrel'`.
    Defaults to `'usd_per_tonne'`.

avoid_zone: Routing zones to avoid. Options: `'Panama Canal'`, `'Suez Canal'`.

Returns

AnywhereFreightPricingResult

Example

Get top destination ports for clean products from Houston using MR2 vessels.

>>> from vortexasdk import AnywhereFreightPricingTopPortsDestination
>>> result = AnywhereFreightPricingTopPortsDestination().search(
...     origin_id="7f314ba0a498c36359b1c88781e94a73e19dcc9bbb030ec6b82f944a73d4da2f",
...     vessel_class="oil_handymax_mr2",
...     product="clean",
...     unit="usd_per_tonne",
... )
>>> df = result.to_df()

Returns a DataFrame with columns including geography info, rates, lumpsums, and confidence values:

	geography_name	date	rate	lumpsum	confidence
0	Callao [PE]	2024-01-01	63.55	2351511.83	2