Are you willing to track precise movements of a container vessel around the world and follow up which ports it calls over time?
This code captures 4 months of history (with 4 points per day) for a containership deployed on a “North Europe – Far East” trade.
The result enables you to easily plug the data on a map to visualize the vessel’s passage as per screenshot.
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import requests
import pandas as pd
token = "INSERT MY TOKEN" # your personal token for AXSMarine apihub
vessel_imo = 9839272 # The IMO of the vessel you want to track
# For all API call to AXSMarine apihub, you need to send your token in the Authorization header
headers = {
"Authorization": "Bearer {}".format(token)
}
#Calling the Ship Status API
url = "https://apihub.axsmarine.com/global/ship-status/v1"
variables = {
"first": 5000,
"after": None,
"snapshotTime": {
"from": "2024-12-01"
},
"vesselImos": [vessel_imo],
}
query = """
query ($first: Int, $after: String, $snapshotTime: RangeDate, $vesselImos: [Int]) {
historicalStatuses(
first: $first
after: $after
snapshotTime: $snapshotTime
vesselImos: $vesselImos
) {
pageInfo {
endCursor
}
edges {
node {
time
ais {
latitude
longitude
speed
}
}
}
}
}
"""
data = None
while True:
response = requests.post(url, json={'query': query, 'variables': variables}, headers=headers)
response.raise_for_status()
json = response.json()['data']['historicalStatuses']
data = pd.concat([data, pd.json_normalize([i['node'] for i in json['edges']])])
if len(json['edges']) < variables['first']:
break
variables['after'] = json['pageInfo']['endCursor']
data.to_csv(f"{vessel_imo}_history.csv", index=False)POST
/
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