I am trying to run an API call in-platform using Google Cloud Functions with this script:
import pandas as pd
import requests
import pandas_gbq
def hello_gcs(data):
## Define table and project id
table_id = 'my_dataset.my_table'
project_id = 'my_project_id'
## API call
url = "https://www.my_api_endpoint.com"
params = {
"apiKey": "ABCD1234"
}
response = requests.get(url, params=params)
api_data = response.json()
sent_data = api_data.get("DATA", {}).get("SENT", [])
## Basic transformation
structured_data = [{
"List_Name": record.get("LISTSENT_NAME"),
"CTR": record.get("CLICKTHROUGH_RATE") ## Add the other fields here (and clean this up)
} for record in sent_data]
df = pd.DataFrame(structured_data)
## Send to BigQuery
pandas_gbq.to_gbq(df, table_id, project_id=project_id, if_exists='replace')
... but when I run it, I keep getting an error message that says:
ERROR: failed to build: executing lifecycle. This may be the result of using an untrusted builder: failed with status code: 62
From experimenting, I've figured out that the issue seems to be with the API call.
The API call works when I do it in Python on my desktop, and the script works when I replace the API call with anything else -- but, as far as I can tell, Google just doesn't trust my API for some reason.
What I can do to call the API in a way that makes Google happy?
LinkedIn
Twitter
