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A Python wrapper around the Kpler client API

Project description

The Kpler Python SDK provides access to Kpler data.

It can be easily integrated into notebooks, scripts, and applications.

It is available to all Kpler API clients (credentials required)

Documentation : https://python-sdk.dev.kpler.com

from kpler.sdk import Platform
from kpler.sdk.configuration import Configuration
from kpler.sdk.resources.trades import Trades
from datetime import date, timedelta

# Create configuration object
configuration = Configuration(Platform.Liquids, "<your email>", "<your password>")

# To change the platform use _change_platform method of Configuration class
configuration._change_platform(Platform.Liquids)

# Connect to one of the Kpler's client using your configuration object, ie: Trades
trades_client = Trades(configuration)

# Get all possible columns returned by the get_trades query
trades_columns = trades_client.get_columns()

# Do a get trades with default columns and with a maximum size of 5 for the dataframe
trades_df = trades_client.get(size=5)

# Get US imports over last week
us_imports = trades_client.get(
    to_zones=["United States"],
    products=["crude"],
    with_forecast=False,
    with_intra_country=True,
    start_date=date.today() - timedelta(days=7),
    columns=[
        "vessel_name",
        "closest_ancestor_product",
        "closest_ancestor_grade",
        "start",
        "end",
        "origin_location_name",
        "destination_location_name",
    ]
)

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