Python Client

Available in VPC

It describes how to use Python Client provided by Data Query.

Preparations

Python 3.9 or later must be installed in the environment where you will be using Python Client.

How to use

It describes how to use Data Query Python Client.

1. Install package

Install the ncp-dataquery package available on PyPI.org.

# [required] Install ncp-dataquery package.
pip install ncp-dataquery
# [optional] If you integrate Data Query in sqlalchemy format, install the relevant package.
pip install sqlalchemy

2. Python Client integration examples

Authentication method

The NCP IAM authentication methods are supported using the NcpIamAuthentication class.
You must enter your AccessKey and SecretKey.

Submit queries and view results

Write the code to submit the query and view the results.

Example:

# DBAPI
from ncp_dataquery.dbapi import connect
from ncp_dataquery.auth import NcpIamAuthentication

conn = connect(
    host="<dataquery_endpoint>",
    port=443,
    auth=NcpIamAuthentication("<access_key>", "<secret_key>"),
    http_scheme="https",
    reuse_query_result=True, # optional, default=False
    reuse_query_max_age=5,   # optional, default=60, range=1~10080 (unit: minute)
)
cur = conn.cursor()
cur.execute("SELECT * FROM public_data.korea_national_railway.subway_seoul_capital_area LIMIT 10")
rows = cur.fetchall()
for row in rows:
    print(" ".join(row))

# SQLAlchemy
from sqlalchemy import create_engine, text
from ncp_dataquery.auth import NcpIamAuthentication

engine = create_engine(
    "trino://<dataquery_endpoint>:443/<catalog>",
    connect_args={
        "auth": NcpIamAuthentication("<access_key>", "<secret_key>"),
        "http_scheme": "https",
        "reuse_query_result": True, # optional, default=False
        "reuse_query_max_age": 5,   # optional, default=60, range=1~10080 (unit: minute)
    }
)

with engine.connect() as conn:
    result = conn.execute(text("SELECT * FROM public_data.korea_national_railway.subway_seoul_capital_area LIMIT 10"))
    for row in result:
        print(f"{row}")

// Result examples
Daehwa, Line 3 operated by Korail 126.747756 37.675883
Daegok, Line 3 operated by Korail 126.811025 37.631629
Hwajeong, Line 3 operated by Korail 126.832503 37.637837
Wonheung, Line 3 operated by Korail 126.873239 37.650709
Juyeop, Line 3 operated by Korail 126.761232 37.670138
Jeongbalsan, Line 3 operated by Korail 126.773254 37.659709
Madu, Line 3 operated by Korail 126.777641 126.777641
Baekseok, Line 3 operated by Korail 126.788109 37.642973
Wondang, Line 3 operated by Korail 126.842891 37.653103
Samsong, Line 3 operated by Korail 126.895559 37.653096

Available options

• DBAPI: enter it as the argument value of connect().
• SQLAlchemy: enter is as the connect_args argument value of create_engine().

Data Query Service Endpoint by Region
Currently, only the KR Region is available, with more Regions to be provided later.