Freight Rates API Example¶

Run this example in Colab¶

Setup¶

Install the Signal Ocean SDK:

pip install signal-ocean

Set your subscription key acquired here: https://apis.signalocean.com/profile

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pip install signal-ocean

pip install signal-ocean

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signal_ocean_api_key = '' #replace with your subscription key

signal_ocean_api_key = '' #replace with your subscription key

Freight Rates API¶

The Freight Rates API retrieves freight costs breakdown for a given load, discharge port and vessel class. First create connection towards Freight Rates API in order to find available ports and vessel classes:

In [2]:

from signal_ocean import Connection, FreightRatesAPI
from signal_ocean.freight_rates import PortFilter

connection = Connection(api_key=signal_ocean_api_key)
fr_api = FreightRatesAPI(connection)

from signal_ocean import Connection, FreightRatesAPI from signal_ocean.freight_rates import PortFilter connection = Connection(api_key=signal_ocean_api_key) fr_api = FreightRatesAPI(connection)

Find available ports and vessel classes¶

Now retrieve the available vessel classes and look if specific ports are available. If you want to get all the available ports do not pass any parameter to the corresponding method.

In [3]:

vessel_classes = fr_api.get_vessel_classes()
print(vessel_classes)

vessel_classes = fr_api.get_vessel_classes() print(vessel_classes)

('VLCC', 'Suezmax', 'Aframax', 'PanamaxTanker', 'MR2', 'MR1')

Get freight rates for specific ports and vessel class¶

In this example we retrieve today’s freight rate for Clean Panamax Amsterdam - Lome:

In [4]:

from signal_ocean.freight_rates.utils import create_dataframe
from signal_ocean.plots import styled_table, line_chart

amsterdam = fr_api.get_ports(PortFilter(name_like='Amsterdam'))[0]
lome = fr_api.get_ports(PortFilter(name_like='Lome'))[0]
fr = fr_api.get_freight_pricing(load_ports=[amsterdam.id],
                                discharge_ports=[lome.id],
                                vessel_classes=["PanamaxTanker"],
                                is_clean=True)
df = create_dataframe(fr)
styled_table(df.T)

from signal_ocean.freight_rates.utils import create_dataframe from signal_ocean.plots import styled_table, line_chart amsterdam = fr_api.get_ports(PortFilter(name_like='Amsterdam'))[0] lome = fr_api.get_ports(PortFilter(name_like='Lome'))[0] fr = fr_api.get_freight_pricing(load_ports=[amsterdam.id], discharge_ports=[lome.id], vessel_classes=["PanamaxTanker"], is_clean=True) df = create_dataframe(fr) styled_table(df.T)

We can also plot the freight rates for the same combination from 1st of January until today:

In [5]:

from datetime import date, timedelta
import pandas as pd

dates = [date(2021, 4, 1) + timedelta(days=i) for i in
         range((date.today()-date(2021, 4, 1)).days + 1)]
cpc = fr_api.get_ports(PortFilter(name_like='CPC'))[0]
augusta = fr_api.get_ports(PortFilter(name_like='Augusta'))[0]
rates = []

for day in dates:
    frates = fr_api.get_freight_pricing(load_ports=[cpc.id],
                                        discharge_ports=[augusta.id],
                                        vessel_classes=["Aframax"],
                                        is_clean=False,
                                        date=day)
    rates.append(frates[0].total_freight_rate)

df = pd.DataFrame({'Date':dates,'Rate':rates})

line_chart(df,'Date','Rate')

from datetime import date, timedelta import pandas as pd dates = [date(2021, 4, 1) + timedelta(days=i) for i in range((date.today()-date(2021, 4, 1)).days + 1)] cpc = fr_api.get_ports(PortFilter(name_like='CPC'))[0] augusta = fr_api.get_ports(PortFilter(name_like='Augusta'))[0] rates = [] for day in dates: frates = fr_api.get_freight_pricing(load_ports=[cpc.id], discharge_ports=[augusta.id], vessel_classes=["Aframax"], is_clean=False, date=day) rates.append(frates[0].total_freight_rate) df = pd.DataFrame({'Date':dates,'Rate':rates}) line_chart(df,'Date','Rate')

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