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Description:

peaka 1.1.0

Peaka Python client
Client for Peaka, a Zero-ETL data integration platform.
Provides a low-level client and a DBAPI 2.0 implementation and a SQLAlchemy adapter.
It supports Python>=3.8 and PyPy.
Usage
The Python Database API (DBAPI)
Installation
$ pip install peaka

Quick Start
Use the DBAPI interface to query Peaka:
You can call the connect_to_peaka method with your Peaka api_key. catalog, schema, timezone and zone are the optional parameters.
from peaka.dbapi import connect_to_peaka

conn = connect_to_peaka(api_key="<YOUR_API_KEY>", catalog="<CATALOG_NAME>", schema="<SCHEMA_NAME>", timezone="<TIMEZONE>", zone="<'eu' | 'us'>")

cur = conn.cursor()
cur.execute("SELECT * FROM <table_name>")
rows = cur.fetchall()

You can query your table directly, if you enter the catalog and schema when you connect.
SQLAlchemy
Installation
$ pip install peaka[sqlalchemy]

Usage
To connect to Peaka using SQLAlchemy, use a connection string (URL) following this pattern:
peaka://dbc.peaka.studio:4567/<catalog>/<schema>?http_scheme=https&extra_credential=[["peakaKey",<YOUR_API_KEY>]]&access_token=true

NOTE: schema is optional
Examples:
from sqlalchemy import create_engine
from sqlalchemy.schema import Table, MetaData
from sqlalchemy.sql.expression import select, text

engine = create_engine('peaka://dbc.peaka.studio:4567/<CATALOG_NAME>/<SCHEMA_NAME>?http_scheme=https&extra_credential=[["peakaKey",<YOUR_API_KEY>]]&access_token=true')
connection = engine.connect()

rows = connection.execute(text("SELECT * FROM <TABLE_NAME>")).fetchall()

# or using SQLAlchemy schema
nodes = Table(
'<TABLE_NAME>',
MetaData(schema='<SCHEMA_NAME>'),
peaka_autoload=True,
autoload_with=engine
)
rows = connection.execute(select(nodes)).fetchall()

In order to pass additional connection attributes use connect_args method.
Attributes can also be passed in the connection string.