Python driver with native interface for ClickHouse
Project description
ClickHouse Python Driver
ClickHouse Python Driver with native (TCP) interface support.
Asynchronous wrapper is available here: https://github.com/mymarilyn/aioch
Features
Compression support:
Basic types support:
Float32/64
[U]Int8/16/32/64
Date/DateTime
String/FixedString(N)
Enum8/16
Array(T)
Nullable(T)
UUID
External data for query processing.
Query progress information.
Installation
The package can be installed using pip:
pip install clickhouse-driver
You can install extras packages if you need compression support. Example of LZ4 compression requirements installation:
pip install clickhouse-driver[lz4]
You also can specify multiple extras by using comma. Install LZ4 and ZSTD requirements:
pip install clickhouse-driver[lz4,zstd]
Usage example:
from clickhouse_driver import Client client = Client('localhost') print(client.execute('SHOW TABLES')) client.execute('DROP TABLE IF EXISTS test') client.execute('CREATE TABLE test (x Int32) ENGINE = Memory') client.execute( 'INSERT INTO test (x) VALUES', [{'x': 1}, {'x': 2}, {'x': 3}, {'x': 100}] ) client.execute('INSERT INTO test (x) VALUES', [[200]]) print(client.execute('SELECT sum(x) FROM test'))
Arrays:
client.execute('CREATE TABLE test2 (x Array(Int32)) ENGINE = Memory') client.execute( 'INSERT INTO test2 (x) VALUES', [{'x': [10, 20, 30]}, {'x': (11, 21, 31)}] ) print(client.execute('SELECT * FROM test2'))
Enums:
from enum import IntEnum class MyEnum(IntEnum): foo = 1 bar = 2 client.execute(''' CREATE TABLE test3 ( x Enum8('foo' = 1, 'bar' = 2) ) ENGINE = Memory ''') client.execute( 'INSERT INTO test3 (x) VALUES', [{'x': MyEnum.foo}, {'x': 'bar'}, {'x': 1}] ) print(client.execute('SELECT * FROM test3'))
Data compression:
from clickhouse_driver import Client client_with_lz4 = Client('localhost', compression=True) client_with_lz4 = Client('localhost', compression='lz4') client_with_zstd = Client('localhost', compression='zstd')
External data for query processing:
tables = [{ 'name': 'ext', 'structure': [('x', 'Int32'), ('y', 'Array(Int32)')], 'data': [ {'x': 100, 'y': [2, 4, 6, 8]}, {'x': 500, 'y': [1, 3, 5, 7]}, ] }] rv = client.execute( 'SELECT sum(x) FROM ext', external_tables=tables) print(rv)
Query progress information:
from datetime import datetime progress = client.execute_with_progress('LONG AND COMPLICATED QUERY') timeout = 20 started_at = datetime.now() for num_rows, total_rows in progress: done = float(num_rows) / total_rows if total_rows else total_rows now = datetime.now() # Cancel query if it takes more than 20 seconds to process 50% of rows. if (now - started_at).total_seconds() > timeout and done < 0.5: client.cancel() break else: rv = progress.get_result() print(rv)
CityHash algorithm notes
Unfortunately ClickHouse server comes with built-in old version of CityHash hashing algorithm. That’s why we can’t use original CityHash package. Downgraded version of this algorithm is placed at PyPI.
Client Parameters
The first parameter host is required. There are some optional parameters:
port is port ClickHouse server is bound to. Default is 9000.
database is database connect to. Default is 'default'.
user. Default is 'default'.
password. Default is '' (no password).
client_name. This name will appear in server logs. Default is 'python-driver'.
compression. Whether or not use compression. Default is False. Possible choices:
True is equivalent to 'lz4'.
'lz4'.
'lz4hc' high-compression variant of 'lz4'.
'zstd'.
insert_block_size. Chunk size to split rows for INSERT. Default is 1048576.
You can also specify timeouts via:
connect_timeout. Default is 10 seconds.
send_receive_timeout. Default is 300 seconds.
sync_request_timeout. Default is 5 seconds.
Miscellaneous
Specifying query_id:
from uuid import uuid1 query_id = str(uuid1()) print(client.execute('SHOW TABLES', query_id=query_id))
Overriding default query settings:
# Set lower priority to query and limit max number threads to execute the request. settings = {'max_threads': 2, 'priority': 10} print(client.execute('SHOW TABLES', settings=settings))
Retrieving results in columnar form. This is also faster:
print(client.execute('SELECT arrayJoin(range(3))', columnar=True)
Data types check is disabled for performance on INSERT queries. You can turn it on by types_check option:
client.execute('INSERT INTO test (x) VALUES', [('abc', )], types_check=True)
License
ClickHouse Python Driver is distributed under the MIT license.
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