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Send Python HTTP queries and parse JSON rows ​

For a Python application using an HTTP client library, treat SQL errors and result data as different response paths. json_each_row produces one object per line, so parse each nonempty line rather than assuming the whole body is a single JSON array.

python
import json
import os
import requests

response = requests.post(
    os.environ['COORDINATOR_HTTP_URL'],
    params={'database': 'data'},
    auth=(os.environ['COORDINATOR_USER'], os.environ['COORDINATOR_PASSWORD']),
    data='SELECT 1 AS value FORMAT json_each_row',
    timeout=10,
)
query_id = response.headers.get('X-Coordinator-Query-Id')
response.raise_for_status()
rows = [json.loads(line) for line in response.text.splitlines() if line]
print(rows)

Keep failures diagnosable ​

Install the external requests package in the application's own environment. Store credentials outside source code and use external TLS protection for an untrusted network. Preserve a redacted error body and query identifier when raising an application error.

The timeout belongs to the HTTP client; SQL processing has a separate max_execution_time setting. Do not automatically replay a timed-out INSERT, since its result can be ambiguous. HTTP bound parameters and persistent sessions are unsupported. For application data, send encoded format input with SQL in the query URL parameter rather than concatenating values into SQL.

See HTTP uploads and metadata, JSON rows and execution deadlines.