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The first statement of __init__.py called pkg_resources.declare_namespace, and setuptools 83 no longer ships pkg_resources, so importing datastore_orm raises ModuleNotFoundError before any of its own modules load. Every consumer dies on `import datastore_orm`; in Insights that is Django app startup, which takes the image build down with it. The declaration was for the `infi` namespace this distribution used to live under — buildout.cfg still names that as the namespace package. The code now ships one plain top-level package, src/datastore_orm, so there is no namespace left to declare and the call could only ever fail. Removing it is what makes the package importable again, not a workaround for the missing module.
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 datastore_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 = 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
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 examples folder.
To learn more please visit the documentation.
Description
Python ORM for defining models and querying data in ClickHouse.
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