An async http(s) ClickHouse client for python 3.6+ supporting type conversion in both directions, streaming, lazy decoding on select queries, and a fully typed interface.

• Installation
• Quick Start
• Documentation
• Type Conversion
• Connection Pool Settings
• Notes on Speed

You can use it with either aiohttp or httpx http connectors.

To use with aiohttp install it with command:

> pip install aiochclient[aiohttp]

Or aiochclient[aiohttp-speedups] to install with extra speedups.

To use with httpx install it with command:

> pip install aiochclient[httpx]

Or aiochclient[httpx-speedups] to install with extra speedups.

Installing with [*-speedups] adds the following:

• cChardet for aiohttp speedup
• aiodns for aiohttp speedup
• ciso8601 for ultra-fast datetime parsing while decoding data from ClickHouse for aiohttp and httpx.

Additionally the installation process attempts to use Cython for a speed boost (roughly 30% faster).

aiochclient needs aiohttp.ClientSession or httpx.AsyncClient to connect to ClickHouse:

from aiochclient import ChClient
from aiohttp import ClientSession


async def main():
    async with ClientSession() as s:
        client = ChClient(s)
        assert await client.is_alive()  # returns True if connection is Ok

await client.execute(
    "CREATE TABLE t (a UInt8, b Tuple(Date, Nullable(Float32))) ENGINE = Memory"
)

For INSERT queries you can pass values as *args. Values should be iterables:

await client.execute(
    "INSERT INTO t VALUES",
    (1, (dt.date(2018, 9, 7), None)),
    (2, (dt.date(2018, 9, 8), 3.14)),
)

For fetching all rows at once use the fetch method:

all_rows = await client.fetch("SELECT * FROM t")

For fetching first row from result use the fetchrow method:

row = await client.fetchrow("SELECT * FROM t WHERE a=1")

assert row[0] == 1
assert row["b"] == (dt.date(2018, 9, 7), None)

You can also use fetchval method, which returns first value of the first row from query result:

val = await client.fetchval("SELECT b FROM t WHERE a=2")

assert val == (dt.date(2018, 9, 8), 3.14)

With async iteration on the query results stream you can fetch multiple rows without loading them all into memory at once:

async for row in client.iterate(
    "SELECT number, number*2 FROM system.numbers LIMIT 10000"
):
    assert row[0] * 2 == row[1]

Use fetch/fetchrow/fetchval/iterate for SELECT queries and execute or any of last for INSERT and all another queries.

All fetch queries return rows as lightweight, memory efficient objects. Before v1.0.0 rows were only returned as tuples. All rows have a full mapping interface, where you can get fields by names or indexes:

row = await client.fetchrow("SELECT a, b FROM t WHERE a=1")

assert row["a"] == 1
assert row[0] == 1
assert row[:] == (1, (dt.date(2018, 9, 8), 3.14))
assert list(row.keys()) == ["a", "b"]
assert list(row.values()) == [1, (dt.date(2018, 9, 8), 3.14)]

To check out the api docs, visit the readthedocs site..

aiochclient automatically converts types from ClickHouse to python types and vice-versa.

aiochclient uses the aiohttp.TCPConnector to determine pool size. By default, the pool limit is 100 open connections.

It's highly recommended using uvloop and installing aiochclient with speedups for the sake of speed. Some recent benchmarks on our machines without parallelization:

• 180k-220k rows/sec on SELECT
• 50k-80k rows/sec on INSERT

Note: these benchmarks are system dependent