A Python library for working with the ClickHouse database (https://clickhouse.yandex/)
Go to file
2017-06-16 20:37:37 +03:00
docs - Added ne and not_in queryset operators 2017-06-15 12:19:17 +03:00
scripts - Added ne and not_in queryset operators 2017-06-15 12:19:17 +03:00
src/infi Nullable fields support 2017-06-16 20:37:37 +03:00
tests Nullable fields support 2017-06-16 20:37:37 +03:00
.gitignore refactor documentation 2017-04-26 15:47:02 +03:00
buildout.cfg ipython<6: closes #32 2017-05-15 13:11:20 +03:00
CHANGELOG.md Oops, need to rename 0.9.1 to 0.9.2 2017-06-15 14:49:43 +03:00
README.md rename README 2017-04-28 19:45:54 +03:00
setup.in Add Python 3 support 2016-08-01 10:28:10 +03:00

Introduction

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.database import Database
from infi.clickhouse_orm.models import Model
from infi.clickhouse_orm.fields import *
from infi.clickhouse_orm.engines import Memory

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 = datetime.datetime.now()
    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
total = CPUStats.objects_in(db).filter(cpu_id=1).count()
busy = CPUStats.objects_in(db).filter(cpu_id=1, cpu_percent__gt=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 db.select('SELECT cpu_id, avg(cpu_percent) AS average FROM demo.cpustats GROUP BY cpu_id'):
    print 'CPU {row.cpu_id}: {row.average:.2f}%'.format(row=row)

To learn more please visit the documentation.