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This is our fork, so it should read like it. `import datastore_orm` instead of `from infi.clickhouse_orm import ...`: `infi` was the original vendor's org namespace, and carrying someone else's org name through every import in the consuming codebase is not a fork, it is a vendored copy that never got renamed. The `infi` namespace package is gone entirely (src/infi/__init__.py with it), the distribution is `datastore-orm`, and the metadata points at Hanzo rather than at the upstream repo and author. NOT renamed, deliberately: the migration history tables are still `infi_clickhouse_orm_migrations`. That name is persisted state — 448 rows in production key off it — so changing it is a data migration, not a rename. Doing it carelessly reproduces the exact failure this fork just hit, where a package rename orphaned the history and silently blocked every migration.
1.9 KiB
1.9 KiB
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.