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271 Stars 95 Forks BSD 3-Clause "New" or "Revised" License 500 Commits 37 Opened issues


A Python library for working with the ClickHouse database (

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This project is simple ORM for working with the ClickHouse database. It allows you to define model classes whose instances can be written to the database and read from it.

Let's jump right in with a simple example of monitoring CPU usage. First we need to define the model class, connect to the database and create a table for the model:

from infi.clickhouse_orm import Database, Model, DateTimeField, UInt16Field, Float32Field, Memory, F

class CPUStats(Model):

timestamp = DateTimeField()
cpu_id = UInt16Field()
cpu_percent = Float32Field()

engine = Memory()

db = Database('demo') db.create_table(CPUStats)

Now we can collect usage statistics per CPU, and write them to the database:

import psutil, time, datetime

psutil.cpu_percent(percpu=True) # first sample should be discarded while True: time.sleep(1) stats = psutil.cpu_percent(percpu=True) timestamp = db.insert([ CPUStats(timestamp=timestamp, cpu_id=cpu_id, cpu_percent=cpu_percent) for cpu_id, cpu_percent in enumerate(stats) ])

Querying the table is easy, using either the query builder or raw SQL:

# Calculate what percentage of the time CPU 1 was over 95% busy
queryset = CPUStats.objects_in(db)
total = queryset.filter(CPUStats.cpu_id == 1).count()
busy = queryset.filter(CPUStats.cpu_id == 1, CPUStats.cpu_percent > 95).count()
print('CPU 1 was busy {:.2f}% of the time'.format(busy * 100.0 / total))

Calculate the average usage per CPU

for row in queryset.aggregate(CPUStats.cpu_id, average=F.avg(CPUStats.cpu_percent)): print('CPU {row.cpu_id}: {row.average:.2f}%'.format(row=row))

This and other examples can be found in the


To learn more please visit the documentation.

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