# Vessels API Open In Colab This guide provides detailed instructions on how to use the [gfw-api-python-client](https://github.com/GlobalFishingWatch/gfw-api-python-client) to access information about vessels. The Vessels API allows you to search for vessels, retrieve lists of vessels by their IDs, and get detailed information for a specific vessel, drawing from various datasets like identity, authorizations, and ownership. Here is a [Jupyter Notebook](https://github.com/GlobalFishingWatch/gfw-api-python-client/blob/develop/notebooks/usage-guides/vessels-api.ipynb) version of this guide with more usage examples. ## Prerequisites - You have installed the `gfw-api-python-client`. Refer to the [Getting Started](../getting-started) guide for installation instructions. ## Getting Started To interact with the Vessels endpoints, you first need to instantiate the `gfw.Client` and then access the `vessels` resource: ```python import os import gfwapiclient as gfw access_token = os.environ.get( "GFW_API_ACCESS_TOKEN", "", ) gfw_client = gfw.Client( access_token=access_token, ) ``` The `gfw_client.vessels` object provides methods to search for and retrieve vessel information. Each of these methods returns a `result` object, which offers convenient ways to access the data as Pydantic models using `.data()` or as pandas DataFrames using `.df()`. ## Searching for Vessels (`search_vessels`) The `search_vessels()` method allows you to find vessels based on a query and various filters within specified datasets. ```python vessel_search_result = await gfw_client.vessels.search_vessels( where="ssvid='775998121' AND shipname='DON TITO'", datasets=["public-global-vessel-identity:latest"], includes=["MATCH_CRITERIA", "OWNERSHIP"], ) ``` ### Access the list of vessel as Pydantic models ```python vessel_search_data = vessel_search_result.data() vessel = vessel_search_data[-1] print((vessel.dataset, vessel.self_reported_info[-1].id)) print(vessel.model_dump()) ``` **Output:** ``` ('public-global-vessel-identity:v3.0', 'bae8f325c-cf0a-01fe-6d1a-9a275588d4ff') ``` ### Access the vessels as a DataFrame ```python vessel_search_df = vessel_search_result.df() print(vessel_search_df.info()) print(vessel_search_df.head()) ``` **Output:** ``` RangeIndex: 2 entries, 0 to 1 Data columns (total 8 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 dataset 2 non-null object 1 registry_info_total_records 2 non-null int64 2 registry_info 2 non-null object 3 registry_owners 2 non-null object 4 registry_public_authorizations 0 non-null object 5 combined_sources_info 2 non-null object 6 self_reported_info 2 non-null object 7 matchCriteria 2 non-null object dtypes: int64(1), object(7) memory usage: 260.0+ bytes ``` ## Getting a List of Vessels by IDs (`get_vessels_by_ids`) The `get_vessels_by_ids()` method retrieves information for a list of vessels given their GFW Vessel IDs. ```python vessels_result = await gfw_client.vessels.get_vessels_by_ids( ids=[ "8c7304226-6c71-edbe-0b63-c246734b3c01", "6583c51e3-3626-5638-866a-f47c3bc7ef7c", "71e7da672-2451-17da-b239-857831602eca", ], datasets=["public-global-vessel-identity:latest"], ) ``` ### Access the list of vessel as Pydantic models ```python vessels_data = vessels_result.data() vessel = vessels_data[-1] print((vessel.dataset, vessel.self_reported_info[-1].id)) print(vessel.model_dump()) ``` **Output:** ``` ('public-global-vessel-identity:v3.0', '0cb77880e-ee49-2ce4-a849-c0b413b6ec89') ``` ### Access the vessels as a DataFrame ```python vessel_search_df = vessels_result.df() print(vessel_search_df.info()) print(vessel_search_df.head()) ``` **Output:** ``` RangeIndex: 3 entries, 0 to 2 Data columns (total 7 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 dataset 3 non-null object 1 registry_info_total_records 3 non-null int64 2 registry_info 3 non-null object 3 registry_owners 3 non-null object 4 registry_public_authorizations 3 non-null object 5 combined_sources_info 3 non-null object 6 self_reported_info 3 non-null object dtypes: int64(1), object(6) memory usage: 300.0+ bytes ``` ## Getting a Vessel by ID (`get_vessel_by_id`) The `get_vessel_by_id()` method retrieves detailed information for a specific vessel using its GFW Vessel ID. ```python vessel_result = await gfw_client.vessels.get_vessel_by_id( id="c54923e64-46f3-9338-9dcb-ff09724077a3", dataset="public-global-vessel-identity:latest", ) ``` ### Access the vessel as Pydantic model ```python vessel = vessel_result.data() print((vessel.dataset, vessel.self_reported_info[-1].id)) print(vessel.model_dump()) ``` **Output:** ``` ('public-global-vessel-identity:v3.0', 'c54923e64-46f3-9338-9dcb-ff09724077a3') ``` ### Access the vessel as a DataFrame ```python vessel_df = vessel_result.df() print(vessel_df.info()) print(vessel_df.head()) ``` **Output:** ``` RangeIndex: 1 entries, 0 to 0 Data columns (total 7 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 dataset 1 non-null object 1 registry_info_total_records 1 non-null int64 2 registry_info 1 non-null object 3 registry_owners 1 non-null object 4 registry_public_authorizations 1 non-null object 5 combined_sources_info 1 non-null object 6 self_reported_info 1 non-null object dtypes: int64(1), object(6) memory usage: 188.0+ bytes ``` ## Next Steps Explore the [Usage Guides](index) for other API resources to understand how you can combine vessel data with information about events, and more. Check out the following resources: - [4Wings API](4wings-api) - [Events API](events-api) - [Insights API](insights-api) - [Datasets API](datasets-api) - [Reference Data API](references-data-api)