Getting Started¶

This guide introduces you to the basics of using the gfw-api-python-client. For detailed and alternative installation instructions, please refer to the Installation section. Here is a Jupyter Notebook version for this guide.

Authorization¶

Before using the gfw-api-python-client, you need to obtain an API access token from the Global Fishing Watch API portal. This token is crucial for authenticating your requests. For security and convenience, it’s highly recommended to set your access token as an environment variable.

Linux/macOS¶

export GFW_API_ACCESS_TOKEN="<PASTE_YOUR_GFW_API_ACCESS_TOKEN_HERE>"

Windows¶

$env:GFW_API_ACCESS_TOKEN = "<PASTE_YOUR_GFW_API_ACCESS_TOKEN_HERE>"

Installation¶

The gfw-api-python-client can be easily installed using pip:

pip install gfw-api-python-client

For more detailed installation instructions, including setting up a virtual environment, please see the dedicated Installation section.

Basic Usage¶

Once installed, you can import and use gfw-api-python-client in your Python codes:

import os

import gfwapiclient as gfw


access_token = os.environ.get(
    "GFW_API_ACCESS_TOKEN",
    "<OR_PASTE_YOUR_GFW_API_ACCESS_TOKEN_HERE>",
)

gfw_client = gfw.Client(
    access_token=access_token,
)

Making API Requests¶

Searching for a Vessel by MMSI¶

vessel_search_result = await gfw_client.vessels.search_vessels(
    query="368045130",
    datasets=["public-global-vessel-identity:latest"],
    includes=["MATCH_CRITERIA", "OWNERSHIP", "AUTHORIZATIONS"],
)

vessel_ids = [
    self_reported_info.id
    for vessel in vessel_search_result.data()
    for self_reported_info in vessel.self_reported_info
]

print(vessel_ids)

Output:

["3312b30d6-65b6-1bdb-6a78-3f5eb3977e58", "126221ace-e3b5-f4ed-6150-394809737c55"]

Getting Fishing Events for the Searched Vessels¶

events_result = await gfw_client.events.get_all_events(
    datasets=["public-global-fishing-events:latest"],
    start_date="2024-03-01",
    end_date="2025-03-31",
    vessels=vessel_ids,
)

events_df = events_result.df()

print(events_df.info())

Output:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3 entries, 0 to 2
Data columns (total 14 columns):
 #   Column        Non-Null Count  Dtype
---  ------        --------------  -----
 0   start         3 non-null      datetime64[ns, UTC]
 1   end           3 non-null      datetime64[ns, UTC]
 2   id            3 non-null      object
 3   type          3 non-null      object
 4   position      3 non-null      object
 5   regions       3 non-null      object
 6   bounding_box  3 non-null      object
 7   distances     3 non-null      object
 8   vessel        3 non-null      object
 9   encounter     0 non-null      object
 10  fishing       3 non-null      object
 11  gap           0 non-null      object
 12  loitering     0 non-null      object
 13  port_visit    0 non-null      object
dtypes: datetime64[ns, UTC](2), object(12)
memory usage: 468.0+ bytes

Next Steps¶

This guide has provided you with the fundamental steps to install and use the gfw-api-python-client for making basic API requests.

To further explore the capabilities of our APIs (4Wings, Vessels, Events, Insights, References, etc.), please refer to the detailed Usage Guides. These guides delve into specific use cases and demonstrate how to effectively leverage the gfw-api-python-client for your data exploration needs.

Happy coding and data exploring!