Python Client (provisa-client)

Python client for Provisa. Provides four interfaces:

Interface	Use case
ProvisaClient	GraphQL queries, Arrow Flight, DataFrame output
DB-API 2.0 (connect)	Standard Python database interface (PEP 249) (REQ-268)
SQLAlchemy dialect	BI tools, ORM, Pandas read_sql (REQ-270)
ADBC	Arrow-native columnar streaming via Flight (REQ-271)

Install

pip install provisa-client                      # core (ProvisaClient + DB-API)
pip install "provisa-client[pandas]"            # adds pandas
pip install "provisa-client[sqlalchemy]"        # adds SQLAlchemy dialect
pip install "provisa-client[adbc]"              # adds ADBC over Arrow Flight

---

ProvisaClient

Quick Start

from provisa_client import ProvisaClient

client = ProvisaClient(
    "http://localhost:8001",
    username="alice",
    password="secret",
)

GraphQL Queries

# Raw response dict
result = client.query("{ orders { id amount region } }")

# With variables
result = client.query(
    "query Q($region: String!) { orders(region: $region) { id amount } }",
    variables={"region": "west"},
)

# pandas DataFrame (first root field is flattened)
df = client.query_df("{ orders { id amount region } }")

Async

result = await client.aquery("{ orders { id amount } }")

Arrow Flight (high-throughput columnar)

Use Flight for large result sets — data streams as Arrow record batches without materializing on the server. (REQ-143, REQ-145)

import pyarrow as pa

table: pa.Table = client.flight("{ orders { id amount region } }")
df = client.flight_df("{ orders { id amount region } }")

Flight connects to port 8815 by default. (REQ-143) Override with flight_port=:

client = ProvisaClient("http://prod.example.com", flight_port=8815)

Catalog Exploration

tables_df = client.list_tables()

Connection Reference

Parameter	Default	Description
url	http://localhost:8001	Provisa server base URL
token	None	Bearer token; omit for password auth (REQ-606)
role	"admin"	Role sent with every request (REQ-273)
flight_port	8815	Arrow Flight gRPC port (REQ-143)

Error Handling

query() raises httpx.HTTPStatusError on HTTP errors. (REQ-607)
query_df() raises RuntimeError if the response contains GraphQL errors. (REQ-607)

---

DB-API 2.0

Standard PEP 249 interface. (REQ-268) Works with any tool that accepts a DB-API connection.

from provisa_client import connect

conn = connect(
    "http://localhost:8001",
    username="alice",
    password="secret",
    role="admin",       # optional, default "admin"
)

Executing queries

The cursor accepts either GraphQL or SQL — detected automatically. (REQ-268, REQ-274)

cur = conn.cursor()

# GraphQL
cur.execute("{ orders { id amount region } }")
rows = cur.fetchall()           # list of tuples
one  = cur.fetchone()           # single tuple or None
many = cur.fetchmany(size=50)   # up to N tuples

# SQL (routed through Stage 2 governance)
cur.execute("SELECT id, amount FROM orders WHERE region = 'west'")
rows = cur.fetchall()

Column metadata

cur.execute("{ orders { id amount } }")
print(cur.description)
# [('id', None, ...), ('amount', None, ...)]
print(cur.rowcount)

Named parameters

cur.execute(
    "SELECT * FROM orders WHERE region = :region",
    {"region": "west"},
)

Context managers

with connect("http://localhost:8001", username="alice", password="secret") as conn:
    with conn.cursor() as cur:
        cur.execute("{ orders { id amount } }")
        print(cur.fetchall())

---

SQLAlchemy Dialect

pip install "provisa-client[sqlalchemy]"

URL scheme: provisa+http:// or provisa+https:// (REQ-270)

from sqlalchemy import create_engine, text

engine = create_engine("provisa+http://alice:secret@localhost:8001")

with engine.connect() as conn:
    result = conn.execute(text("{ orders { id amount region } }"))
    for row in result:
        print(row)

With pandas

import pandas as pd

df = pd.read_sql("{ orders { id amount } }", engine)

URL parameters

Parameter	Description	Default
role	Provisa role	admin

engine = create_engine(
    "provisa+http://alice:secret@localhost:8001?role=analyst"
)

Schema introspection

The dialect implements get_table_names(), get_columns(), and has_table() — catalog tools (DBeaver, SQLAlchemy automap) can inspect the schema. (REQ-363, REQ-270)

---

ADBC

Arrow Database Connectivity backed by Arrow Flight. (REQ-271) Returns pyarrow.Table directly — no JSON deserialization. (REQ-271)

pip install "provisa-client[adbc]"

from provisa_client.adbc import adbc_connect

conn = adbc_connect(
    "http://localhost:8001",
    user="alice",
    password="secret",
    role="analyst",   # optional; server validates the requested role
    port=8815,        # Arrow Flight port (REQ-711)
)

Fetch as Arrow Table

with conn.cursor() as cur:
    cur.execute("{ orders { id amount region } }")
    table = cur.fetch_arrow_table()   # pyarrow.Table
    df = table.to_pandas()

Fetch as tuples

with conn.cursor() as cur:
    cur.execute("{ orders { id amount } }")
    rows = cur.fetchall()    # list of tuples
    one  = cur.fetchone()    # single tuple or None

Column metadata

cur.execute("{ orders { id amount } }")
print(cur.description)
# [('id', None, ...), ('amount', None, ...)]

Context manager

with adbc_connect("http://localhost:8001", user="alice", password="secret") as conn:
    with conn.cursor() as cur:
        cur.execute("{ orders { id amount } }")
        table = cur.fetch_arrow_table()

ADBC connects to the Flight server on port 8815 by default. (REQ-143) Pass port= to reach a Flight server bound to a non-default port. (REQ-711)