Timeseries Insights API - Create Dataset

create_tsi_dataset.py

# TODO - REPLACE WITH SA ACCOUNT KEY
KEY_FILE = '/<path-to-your-service-account-file>/file.json' #REPLACE THIS WITH PROJECT SPECIFIC SERVICE ACCOUNT KEY
ts_endpoint =  f'https://timeseriesinsights.googleapis.com/v1/projects/{PROJECT_ID}/datasets'

# Helper function
def query_ts(method, endpoint, data, auth_token):
    data = str(data)
    headers = {'Content-type': 'application/json', "Authorization": f"Bearer {auth_token}"}
    
    if method == "GET":
        resp = requests.get(endpoint, headers=headers)
    if method == "POST":
        resp = requests.post(endpoint, data=data, headers=headers)
    if method == "DELETE":
        resp = requests.delete(endpoint, headers=headers)
    return(resp.json())
  
  
# Authentication
!gcloud auth activate-service-account --key-file {key_file}
token_array = !gcloud auth print-access-token 


# Create dataset using API
file_data = {
    "name": "sensor-data", # TSI dataset name
    "ttl": "30000000s",  # time to live - this is used for streaming inserts. Indicates what records to discard 
    "dataNames": [
        "measure",
        "Humidity",
        "Light",
        "h2_raw",
        "temp",
    ],
    "dataSources": [
        {"uri": "gs://<your-bucket-name-here>/transformed.json"} #sample of data in Cloud Storage transformed JSON file
    ], 
} 
res = query_ts(method="POST", endpoint=ts_endpoint, data=file_data, auth_token=token_array[0])
res