Package information:
ClickSQL is a python client for ClickHouse database, which may help users to use ClickHouse more easier and pythonic. More information for ClickHouse can be found at here
pip install ClickSQL
to setup a database connection and send a heartbeat-check signal
from ClickSQL import BaseSingleFactorTableNode conn_str = "clickhouse://default:test121231@99.99.9.9:8123/system" Node = BaseSingleFactorTableNode(conn_str) >>> connection test: Ok.from ClickSQL import BaseSingleFactorTableNode conn_str = "clickhouse://default:test121231@99.99.9.9:8123/system" Node = BaseSingleFactorTableNode(conn_str) Node('show tables from system limit 1') >>> connection test: Ok. >>> name >>> 0 aggregate_function_combinatorsfrom ClickSQL import BaseSingleFactorTableNode factor = BaseSingleFactorTableNode( 'clickhouse://default:default@127.0.0.1:8123/sample.sample', cols=['cust_no', 'product_id', 'money'], order_by_cols=['money asc'], money='money >= 100000' ) factor['money'].head(10) >>> connection test: Ok. >>> money >>> 0 1000000.0 >>> 1 1000000.0 >>> 2 1000000.0 >>> 3 1000000.0 >>> 4 1000000.0 >>> 5 1000000.0 >>> 6 1000000.0 >>> 7 1000000.0 >>> 8 1000000.0 >>> 9 1000000.0 insert data into database by various ways
from ClickSQL import BaseSingleFactorTableNode as factortable import numpy as np import pandas as pd factor = factortable( 'clickhouse://default:default@127.0.0.1:8123/sample.sample' ) db = 'sample' table = 'sample' df = pd.DataFrame(np.random.random(size=(10000,3)),columns=['cust_no', 'product_id', 'money']) factor.insert_df(df, db, table, chunksize=100000) from ClickSQL import BaseSingleFactorTableNode as factortable factor = factortable( 'clickhouse://default:default@127.0.0.1:8123/sample.sample' ) factor("insert into sample.sample select * from other_db.other_table") from ClickSQL import BaseSingleFactorTableNode conn_str = "clickhouse://default:test121231@99.99.9.9:8123/system" Node = BaseSingleFactorTableNode(conn_str) Node('create table test.test2 (v1 String, v2 Int64, v3 Float64,v4 DataTime) Engine=MergeTree() order by v4')from ClickSQL import BaseSingleFactorTableNode import numpy as np import pandas as pd conn_str = "clickhouse://default:test121231@99.99.9.9:8123/system" Node = BaseSingleFactorTableNode(conn_str) db = 'test' table = 'test2' df_or_sql_or_dict = pd.DataFrame(np.random.random(size=(10000,2)),columns=['v1', 'v3']) df_or_sql_or_dict['v2'] =1 df_or_sql_or_dict['v4'] =pd.to_datetime('2020-01-01 00:00:00') Node.create( db, table, df_or_sql_or_dict, key_cols=['v4'],)Welcome to improve this package or submit an issue or any others
sn0wfree
- get data from clickhouse
- insert data into clickhouse
- create
- alter
- execute standard SQL and transform into DataFrame(Auto)
- able to execute select query
- able to execute insert query
- no require clickhouse-client
- auto create table sql
- can execute explain query
- Insert Data via DataFrame
- alter function & drop function
- create a pandas_liked executable function, which can compatible with pandas
- distributed query（query+insert）
- ORM
- can execute user role query
- create analysis component
- auto report system
- table register system
- data manager system
- meta data manager