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src/infi/clickhouse_orm/__version__.py
bootstrap.py
htmldocs/

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Change Log
==========
v0.9.0
------
- Major new feature: building model queries using QuerySets
- Refactor and expand the documentation
- Add support for FixedString fields
- Add support for more engine types: TinyLog, Log, Memory
- Bug fix: Do not send readonly=1 when connection is already in readonly mode
v0.8.2
------
- Fix broken Python 3 support (M1hacka)

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Introduction
============
This project is simple ORM for working with the [ClickHouse database](https://clickhouse.yandex/).
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:
```python
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:
```python
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:
```python
# 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](docs/toc.md).

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Overview
========
This project is simple ORM for working with the `ClickHouse database <https://clickhouse.yandex/>`_.
It allows you to define model classes whose instances can be written to the database and read from it.
Installation
============
To install infi.clickhouse_orm::
pip install infi.clickhouse_orm
Usage
=====
Defining Models
---------------
Models are defined in a way reminiscent of Django's ORM::
from infi.clickhouse_orm import models, fields, engines
class Person(models.Model):
first_name = fields.StringField()
last_name = fields.StringField()
birthday = fields.DateField()
height = fields.Float32Field()
engine = engines.MergeTree('birthday', ('first_name', 'last_name', 'birthday'))
It is possible to provide a default value for a field, instead of its "natural" default (empty string for string fields, zero for numeric fields etc.).
Alternatively it is possible to pass alias or materialized parameters (see below for usage examples).
Only one of ``default``, ``alias`` and ``materialized`` parameters can be provided.
See below for the supported field types and table engines.
Table Names
***********
The table name used for the model is its class name, converted to lowercase. To override the default name,
implement the ``table_name`` method::
class Person(models.Model):
...
@classmethod
def table_name(cls):
return 'people'
Using Models
------------
Once you have a model, you can create model instances::
>>> dan = Person(first_name='Dan', last_name='Schwartz')
>>> suzy = Person(first_name='Suzy', last_name='Jones')
>>> dan.first_name
u'Dan'
When values are assigned to model fields, they are immediately converted to their Pythonic data type.
In case the value is invalid, a ``ValueError`` is raised::
>>> suzy.birthday = '1980-01-17'
>>> suzy.birthday
datetime.date(1980, 1, 17)
>>> suzy.birthday = 0.5
ValueError: Invalid value for DateField - 0.5
>>> suzy.birthday = '1922-05-31'
ValueError: DateField out of range - 1922-05-31 is not between 1970-01-01 and 2038-01-19
Inserting to the Database
-------------------------
To write your instances to ClickHouse, you need a ``Database`` instance::
from infi.clickhouse_orm.database import Database
db = Database('my_test_db')
This automatically connects to http://localhost:8123 and creates a database called my_test_db, unless it already exists.
If necessary, you can specify a different database URL and optional credentials::
db = Database('my_test_db', db_url='http://192.168.1.1:8050', username='scott', password='tiger')
Using the ``Database`` instance you can create a table for your model, and insert instances to it::
db.create_table(Person)
db.insert([dan, suzy])
The ``insert`` method can take any iterable of model instances, but they all must belong to the same model class.
Creating a read-only database is also supported. Such a ``Database`` instance can only read data, and cannot
modify data or schemas::
db = Database('my_test_db', readonly=True)
Reading from the Database
-------------------------
Loading model instances from the database is simple::
for person in db.select("SELECT * FROM my_test_db.person", model_class=Person):
print person.first_name, person.last_name
Do not include a ``FORMAT`` clause in the query, since the ORM automatically sets the format to ``TabSeparatedWithNamesAndTypes``.
It is possible to select only a subset of the columns, and the rest will receive their default values::
for person in db.select("SELECT first_name FROM my_test_db.person WHERE last_name='Smith'", model_class=Person):
print person.first_name
SQL Placeholders
****************
There are a couple of special placeholders that you can use inside the SQL to make it easier to write:
``$db`` and ``$table``. The first one is replaced by the database name, and the second is replaced by
the database name plus table name (but is available only when the model is specified).
So instead of this::
db.select("SELECT * FROM my_test_db.person", model_class=Person)
you can use::
db.select("SELECT * FROM $db.person", model_class=Person)
or even::
db.select("SELECT * FROM $table", model_class=Person)
Ad-Hoc Models
*************
Specifying a model class is not required. In case you do not provide a model class, an ad-hoc class will
be defined based on the column names and types returned by the query::
for row in db.select("SELECT max(height) as max_height FROM my_test_db.person"):
print row.max_height
This is a very convenient feature that saves you the need to define a model for each query, while still letting
you work with Pythonic column values and an elegant syntax.
Counting
--------
The ``Database`` class also supports counting records easily::
>>> db.count(Person)
117
>>> db.count(Person, conditions="height > 1.90")
6
Pagination
----------
It is possible to paginate through model instances::
>>> order_by = 'first_name, last_name'
>>> page = db.paginate(Person, order_by, page_num=1, page_size=10)
>>> print page.number_of_objects
2507
>>> print page.pages_total
251
>>> for person in page.objects:
>>> # do something
The ``paginate`` method returns a ``namedtuple`` containing the following fields:
- ``objects`` - the list of objects in this page
- ``number_of_objects`` - total number of objects in all pages
- ``pages_total`` - total number of pages
- ``number`` - the page number, starting from 1; the special value -1 may be used to retrieve the last page
- ``page_size`` - the number of objects per page
You can optionally pass conditions to the query::
>>> page = db.paginate(Person, order_by, page_num=1, page_size=100, conditions='height > 1.90')
Note that ``order_by`` must be chosen so that the ordering is unique, otherwise there might be
inconsistencies in the pagination (such as an instance that appears on two different pages).
System models
-------------
`Clickhouse docs <https://clickhouse.yandex/reference_en.html#System tables>`_.
System models are read only models for implementing part of the system's functionality,
and for providing access to information about how the system is working.
Currently the following system models are supported:
=================== ============ ===================================================
Class DB Table Comments
=================== ============ ===================================================
SystemPart system.parts Gives methods to work with partitions. See below.
=================== ============ ===================================================
Partitions and parts
--------------------
`ClickHouse docs <https://clickhouse.yandex/reference_en.html#Manipulations with partitions and parts>`_.
A partition in a table is data for a single calendar month. Table "system.parts" contains information about each part.
=================== ======================= =============================================================================================
Method Parameters Comments
=================== ======================= =============================================================================================
get(static) database, conditions="" Gets database partitions, filtered by conditions
get_active(static) database, conditions="" Gets only active (not detached or dropped) partitions, filtered by conditions
detach settings=None Detaches the partition. Settings is a dict of params to pass to http request
drop settings=None Drops the partition. Settings is a dict of params to pass to http request
attach settings=None Attaches already detached partition. Settings is a dict of params to pass to http request
freeze settings=None Freezes (makes backup) of the partition. Settings is a dict of params to pass to http request
fetch settings=None Fetches partition. Settings is a dict of params to pass to http request
=================== ======================= =============================================================================================
Usage example::
from infi.clickhouse_orm.database import Database
from infi.clickhouse_orm.system_models import SystemPart
db = Database('my_test_db', db_url='http://192.168.1.1:8050', username='scott', password='tiger')
partitions = SystemPart.get_active(db, conditions='') # Getting all active partitions of the database
if len(partitions) > 0:
partitions = sorted(partitions, key=lambda obj: obj.name) # Partition name is YYYYMM, so we can sort so
partitions[0].freeze() # Make a backup in /opt/clickhouse/shadow directory
partitions[0].drop() # Dropped partition
``Note``: system.parts stores information for all databases. To be correct,
SystemPart model was designed to receive only given database parts.
Schema Migrations
-----------------
Over time, your models may change and the database will have to be modified accordingly.
Migrations allow you to describe these changes succinctly using Python, and to apply them
to the database. A migrations table automatically keeps track of which migrations were already applied.
For details please refer to the MIGRATIONS.rst document.
Field Types
-----------
Currently the following field types are supported:
=================== ======== ================= ===================================================
Class DB Type Pythonic Type Comments
=================== ======== ================= ===================================================
StringField String unicode Encoded as UTF-8 when written to ClickHouse
DateField Date datetime.date Range 1970-01-01 to 2038-01-19
DateTimeField DateTime datetime.datetime Minimal value is 1970-01-01 00:00:00; Always in UTC
Int8Field Int8 int Range -128 to 127
Int16Field Int16 int Range -32768 to 32767
Int32Field Int32 int Range -2147483648 to 2147483647
Int64Field Int64 int/long Range -9223372036854775808 to 9223372036854775807
UInt8Field UInt8 int Range 0 to 255
UInt16Field UInt16 int Range 0 to 65535
UInt32Field UInt32 int Range 0 to 4294967295
UInt64Field UInt64 int/long Range 0 to 18446744073709551615
Float32Field Float32 float
Float64Field Float64 float
Enum8Field Enum8 Enum See below
Enum16Field Enum16 Enum See below
ArrayField Array list See below
=================== ======== ================= ===================================================
DateTimeField and Time Zones
****************************
A ``DateTimeField`` can be assigned values from one of the following types:
- datetime
- date
- integer - number of seconds since the Unix epoch
- string in ``YYYY-MM-DD HH:MM:SS`` format
The assigned value always gets converted to a timezone-aware ``datetime`` in UTC. If the assigned
value is a timezone-aware ``datetime`` in another timezone, it will be converted to UTC. Otherwise, the assigned value is assumed to already be in UTC.
DateTime values that are read from the database are also converted to UTC. ClickHouse formats them according to the
timezone of the server, and the ORM makes the necessary conversions. This requires a ClickHouse version which is new
enough to support the ``timezone()`` function, otherwise it is assumed to be using UTC. In any case, we recommend
settings the server timezone to UTC in order to prevent confusion.
Working with enum fields
************************
``Enum8Field`` and ``Enum16Field`` provide support for working with ClickHouse enum columns. They accept
strings or integers as values, and convert them to the matching Pythonic Enum member.
Python 3.4 and higher supports Enums natively. When using previous Python versions you
need to install the `enum34` library.
Example of a model with an enum field::
Gender = Enum('Gender', 'male female unspecified')
class Person(models.Model):
first_name = fields.StringField()
last_name = fields.StringField()
birthday = fields.DateField()
gender = fields.Enum32Field(Gender)
engine = engines.MergeTree('birthday', ('first_name', 'last_name', 'birthday'))
suzy = Person(first_name='Suzy', last_name='Jones', gender=Gender.female)
Working with array fields
*************************
You can create array fields containing any data type, for example::
class SensorData(models.Model):
date = fields.DateField()
temperatures = fields.ArrayField(fields.Float32Field())
humidity_levels = fields.ArrayField(fields.UInt8Field())
engine = engines.MergeTree('date', ('date',))
data = SensorData(date=date.today(), temperatures=[25.5, 31.2, 28.7], humidity_levels=[41, 39, 66])
Working with materialized and alias fields
******************************************
ClickHouse provides an opportunity to create MATERIALIZED and ALIAS Fields.
See documentation `here <https://clickhouse.yandex/reference_en.html#Default values>`_.
Both field types can't be inserted into the database directly, so they are ignored when using the ``Database.insert()`` method.
ClickHouse does not return the field values if you use ``"SELECT * FROM ..."`` - you have to list these field
names explicitly in the query.
Usage::
class Event(models.Model):
created = fields.DateTimeField()
created_date = fields.DateTimeField(materialized='toDate(created)')
name = fields.StringField()
username = fields.StringField(alias='name')
engine = engines.MergeTree('created_date', ('created_date', 'created'))
obj = Event(created=datetime.now(), name='MyEvent')
db = Database('my_test_db')
db.insert([obj])
# All values will be retrieved from database
db.select('SELECT created, created_date, username, name FROM $db.event', model_class=Event)
# created_date and username will contain a default value
db.select('SELECT * FROM $db.event', model_class=Event)
Table Engines
-------------
Each model must have an engine instance, used when creating the table in ClickHouse.
To define a ``MergeTree`` engine, supply the date column name and the names (or expressions) for the key columns::
engine = engines.MergeTree('EventDate', ('CounterID', 'EventDate'))
You may also provide a sampling expression::
engine = engines.MergeTree('EventDate', ('CounterID', 'EventDate'), sampling_expr='intHash32(UserID)')
A ``CollapsingMergeTree`` engine is defined in a similar manner, but requires also a sign column::
engine = engines.CollapsingMergeTree('EventDate', ('CounterID', 'EventDate'), 'Sign')
For a ``SummingMergeTree`` you can optionally specify the summing columns::
engine = engines.SummingMergeTree('EventDate', ('OrderID', 'EventDate', 'BannerID'),
summing_cols=('Shows', 'Clicks', 'Cost'))
For a ``ReplacingMergeTree`` you can optionally specify the version column::
engine = engines.ReplacingMergeTree('EventDate', ('OrderID', 'EventDate', 'BannerID'), ver_col='Version')
A ``Buffer`` engine is available for BufferModels. (See below how to use BufferModel). You can specify following parameters::
engine = engines.Buffer(Person) # you need to initialize engine with main Model. Other default parameters will be used
# or:
engine = engines.Buffer(Person, num_layers=16, min_time=10,
max_time=100, min_rows=10000, max_rows=1000000,
min_bytes=10000000, max_bytes=100000000)
Buffer Models
-------------
Here's how you can define Model for Buffer Engine. The Buffer Model should be inherited from models.BufferModel and main Model::
class PersonBuffer(models.BufferModel, Person):
engine = engines.Buffer(Person)
Then you can insert objects into Buffer model and they will be handled by Clickhouse properly::
db.create_table(PersonBuffer)
suzy = PersonBuffer(first_name='Suzy', last_name='Jones')
dan = PersonBuffer(first_name='Dan', last_name='Schwartz')
db.insert([dan, suzy])
Data Replication
****************
Any of the above engines can be converted to a replicated engine (e.g. ``ReplicatedMergeTree``) by adding two parameters, ``replica_table_path`` and ``replica_name``::
engine = engines.MergeTree('EventDate', ('CounterID', 'EventDate'),
replica_table_path='/clickhouse/tables/{layer}-{shard}/hits',
replica_name='{replica}')
Development
===========
After cloning the project, run the following commands::
easy_install -U infi.projector
cd infi.clickhouse_orm
projector devenv build
To run the tests, ensure that the ClickHouse server is running on http://localhost:8123/ (this is the default), and run::
bin/nosetests
To see test coverage information run::
bin/nosetests --with-coverage --cover-package=infi.clickhouse_orm

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[isolated-python]
recipe = infi.recipe.python
version = v2.7.8.4
version = v2.7.9.4
[setup.py]
recipe = infi.recipe.template.version

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Class Reference
===============
infi.clickhouse_orm.database
----------------------------
### Database
Database instances connect to a specific ClickHouse database for running queries,
inserting data and other operations.
#### Database(db_name, db_url="http://localhost:8123/", username=None, password=None, readonly=False)
Initializes a database instance. Unless it's readonly, the database will be
created on the ClickHouse server if it does not already exist.
- `db_name`: name of the database to connect to.
- `db_url`: URL of the ClickHouse server.
- `username`: optional connection credentials.
- `password`: optional connection credentials.
- `readonly`: use a read-only connection.
#### count(model_class, conditions=None)
Counts the number of records in the model's table.
- `model_class`: the model to count.
- `conditions`: optional SQL conditions (contents of the WHERE clause).
#### create_database()
Creates the database on the ClickHouse server if it does not already exist.
#### create_table(model_class)
Creates a table for the given model class, if it does not exist already.
#### drop_database()
Deletes the database on the ClickHouse server.
#### drop_table(model_class)
Drops the database table of the given model class, if it exists.
#### insert(model_instances, batch_size=1000)
Insert records into the database.
- `model_instances`: any iterable containing instances of a single model class.
- `batch_size`: number of records to send per chunk (use a lower number if your records are very large).
#### migrate(migrations_package_name, up_to=9999)
Executes schema migrations.
- `migrations_package_name` - fully qualified name of the Python package
containing the migrations.
- `up_to` - number of the last migration to apply.
#### paginate(model_class, order_by, page_num=1, page_size=100, conditions=None, settings=None)
Selects records and returns a single page of model instances.
- `model_class`: the model class matching the query's table,
or `None` for getting back instances of an ad-hoc model.
- `order_by`: columns to use for sorting the query (contents of the ORDER BY clause).
- `page_num`: the page number (1-based), or -1 to get the last page.
- `page_size`: number of records to return per page.
- `conditions`: optional SQL conditions (contents of the WHERE clause).
- `settings`: query settings to send as HTTP GET parameters
The result is a namedtuple containing `objects` (list), `number_of_objects`,
`pages_total`, `number` (of the current page), and `page_size`.
#### raw(query, settings=None, stream=False)
Performs a query and returns its output as text.
- `query`: the SQL query to execute.
- `settings`: query settings to send as HTTP GET parameters
- `stream`: if true, the HTTP response from ClickHouse will be streamed.
#### select(query, model_class=None, settings=None)
Performs a query and returns a generator of model instances.
- `query`: the SQL query to execute.
- `model_class`: the model class matching the query's table,
or `None` for getting back instances of an ad-hoc model.
- `settings`: query settings to send as HTTP GET parameters
### DatabaseException
Extends Exception
Raised when a database operation fails.
infi.clickhouse_orm.models
--------------------------
### Model
A base class for ORM models. Each model class represent a ClickHouse table. For example:
class CPUStats(Model):
timestamp = DateTimeField()
cpu_id = UInt16Field()
cpu_percent = Float32Field()
engine = Memory()
#### Model(**kwargs)
Creates a model instance, using keyword arguments as field values.
Since values are immediately converted to their Pythonic type,
invalid values will cause a `ValueError` to be raised.
Unrecognized field names will cause an `AttributeError`.
#### Model.create_table_sql(db_name)
Returns the SQL command for creating a table for this model.
#### Model.drop_table_sql(db_name)
Returns the SQL command for deleting this model's table.
#### Model.from_tsv(line, field_names=None, timezone_in_use=UTC, database=None)
Create a model instance from a tab-separated line. The line may or may not include a newline.
The `field_names` list must match the fields defined in the model, but does not have to include all of them.
If omitted, it is assumed to be the names of all fields in the model, in order of definition.
- `line`: the TSV-formatted data.
- `field_names`: names of the model fields in the data.
- `timezone_in_use`: the timezone to use when parsing dates and datetimes.
- `database`: if given, sets the database that this instance belongs to.
#### get_database()
Gets the `Database` that this model instance belongs to.
Returns `None` unless the instance was read from the database or written to it.
#### get_field(name)
Gets a `Field` instance given its name, or `None` if not found.
#### Model.objects_in(database)
Returns a `QuerySet` for selecting instances of this model class.
#### set_database(db)
Sets the `Database` that this model instance belongs to.
This is done automatically when the instance is read from the database or written to it.
#### Model.table_name()
Returns the model's database table name. By default this is the
class name converted to lowercase. Override this if you want to use
a different table name.
#### to_dict(include_readonly=True, field_names=None)
Returns the instance's column values as a dict.
- `include_readonly`: if false, returns only fields that can be inserted into database.
- `field_names`: an iterable of field names to return (optional)
#### to_tsv(include_readonly=True)
Returns the instance's column values as a tab-separated line. A newline is not included.
- `include_readonly`: if false, returns only fields that can be inserted into database.
### BufferModel
Extends Model
#### BufferModel(**kwargs)
Creates a model instance, using keyword arguments as field values.
Since values are immediately converted to their Pythonic type,
invalid values will cause a `ValueError` to be raised.
Unrecognized field names will cause an `AttributeError`.
#### BufferModel.create_table_sql(db_name)
Returns the SQL command for creating a table for this model.
#### BufferModel.drop_table_sql(db_name)
Returns the SQL command for deleting this model's table.
#### BufferModel.from_tsv(line, field_names=None, timezone_in_use=UTC, database=None)
Create a model instance from a tab-separated line. The line may or may not include a newline.
The `field_names` list must match the fields defined in the model, but does not have to include all of them.
If omitted, it is assumed to be the names of all fields in the model, in order of definition.
- `line`: the TSV-formatted data.
- `field_names`: names of the model fields in the data.
- `timezone_in_use`: the timezone to use when parsing dates and datetimes.
- `database`: if given, sets the database that this instance belongs to.
#### get_database()
Gets the `Database` that this model instance belongs to.
Returns `None` unless the instance was read from the database or written to it.
#### get_field(name)
Gets a `Field` instance given its name, or `None` if not found.
#### BufferModel.objects_in(database)
Returns a `QuerySet` for selecting instances of this model class.
#### set_database(db)
Sets the `Database` that this model instance belongs to.
This is done automatically when the instance is read from the database or written to it.
#### BufferModel.table_name()
Returns the model's database table name. By default this is the
class name converted to lowercase. Override this if you want to use
a different table name.
#### to_dict(include_readonly=True, field_names=None)
Returns the instance's column values as a dict.
- `include_readonly`: if false, returns only fields that can be inserted into database.
- `field_names`: an iterable of field names to return (optional)
#### to_tsv(include_readonly=True)
Returns the instance's column values as a tab-separated line. A newline is not included.
- `include_readonly`: if false, returns only fields that can be inserted into database.
infi.clickhouse_orm.fields
--------------------------
### Field
Abstract base class for all field types.
#### Field(default=None, alias=None, materialized=None)
### StringField
Extends Field
#### StringField(default=None, alias=None, materialized=None)
### DateField
Extends Field
#### DateField(default=None, alias=None, materialized=None)
### DateTimeField
Extends Field
#### DateTimeField(default=None, alias=None, materialized=None)
### BaseIntField
Extends Field
Abstract base class for all integer-type fields.
#### BaseIntField(default=None, alias=None, materialized=None)
### BaseFloatField
Extends Field
Abstract base class for all float-type fields.
#### BaseFloatField(default=None, alias=None, materialized=None)
### BaseEnumField
Extends Field
Abstract base class for all enum-type fields.
#### BaseEnumField(enum_cls, default=None, alias=None, materialized=None)
### ArrayField
Extends Field
#### ArrayField(inner_field, default=None, alias=None, materialized=None)
### FixedStringField
Extends StringField
#### FixedStringField(length, default=None, alias=None, materialized=None)
### UInt8Field
Extends BaseIntField
#### UInt8Field(default=None, alias=None, materialized=None)
### UInt16Field
Extends BaseIntField
#### UInt16Field(default=None, alias=None, materialized=None)
### UInt32Field
Extends BaseIntField
#### UInt32Field(default=None, alias=None, materialized=None)
### UInt64Field
Extends BaseIntField
#### UInt64Field(default=None, alias=None, materialized=None)
### Int8Field
Extends BaseIntField
#### Int8Field(default=None, alias=None, materialized=None)
### Int16Field
Extends BaseIntField
#### Int16Field(default=None, alias=None, materialized=None)
### Int32Field
Extends BaseIntField
#### Int32Field(default=None, alias=None, materialized=None)
### Int64Field
Extends BaseIntField
#### Int64Field(default=None, alias=None, materialized=None)
### Float32Field
Extends BaseFloatField
#### Float32Field(default=None, alias=None, materialized=None)
### Float64Field
Extends BaseFloatField
#### Float64Field(default=None, alias=None, materialized=None)
### Enum8Field
Extends BaseEnumField
#### Enum8Field(enum_cls, default=None, alias=None, materialized=None)
### Enum16Field
Extends BaseEnumField
#### Enum16Field(enum_cls, default=None, alias=None, materialized=None)
infi.clickhouse_orm.engines
---------------------------
### Engine
### TinyLog
Extends Engine
### Log
Extends Engine
### Memory
Extends Engine
### MergeTree
Extends Engine
#### MergeTree(date_col, key_cols, sampling_expr=None, index_granularity=8192, replica_table_path=None, replica_name=None)
### Buffer
Extends Engine
Buffers the data to write in RAM, periodically flushing it to another table.
Must be used in conjuction with a `BufferModel`.
Read more [here](https://clickhouse.yandex/reference_en.html#Buffer).
#### Buffer(main_model, num_layers=16, min_time=10, max_time=100, min_rows=10000, max_rows=1000000, min_bytes=10000000, max_bytes=100000000)
### CollapsingMergeTree
Extends MergeTree
#### CollapsingMergeTree(date_col, key_cols, sign_col, sampling_expr=None, index_granularity=8192, replica_table_path=None, replica_name=None)
### SummingMergeTree
Extends MergeTree
#### SummingMergeTree(date_col, key_cols, summing_cols=None, sampling_expr=None, index_granularity=8192, replica_table_path=None, replica_name=None)
### ReplacingMergeTree
Extends MergeTree
#### ReplacingMergeTree(date_col, key_cols, ver_col=None, sampling_expr=None, index_granularity=8192, replica_table_path=None, replica_name=None)
infi.clickhouse_orm.query
-------------------------
### QuerySet
A queryset is an object that represents a database query using a specific `Model`.
It is lazy, meaning that it does not hit the database until you iterate over its
matching rows (model instances).
#### QuerySet(model_cls, database)
Initializer. It is possible to create a queryset like this, but the standard
way is to use `MyModel.objects_in(database)`.
#### as_sql()
Returns the whole query as a SQL string.
#### conditions_as_sql()
Returns the contents of the query's `WHERE` clause as a string.
#### count()
Returns the number of matching model instances.
#### exclude(**kwargs)
Returns a new `QuerySet` instance that excludes all rows matching the conditions.
#### filter(**kwargs)
Returns a new `QuerySet` instance that includes only rows matching the conditions.
#### only(*field_names)
Returns a new `QuerySet` instance limited to the specified field names.
Useful when there are large fields that are not needed,
or for creating a subquery to use with an IN operator.
#### order_by(*field_names)
Returns a new `QuerySet` instance with the ordering changed.
#### order_by_as_sql()
Returns the contents of the query's `ORDER BY` clause as a string.

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Contributing
============
This project is hosted on GitHub - [https://github.com/Infinidat/infi.clickhouse_orm/](https://github.com/Infinidat/infi.clickhouse_orm/).
Please open an issue there if you encounter a bug or want to request a feature.
Pull requests are also welcome.
Building
--------
After cloning the project, run the following commands:
easy_install -U infi.projector
cd infi.clickhouse_orm
projector devenv build
A `setup.py` file will be generated, which you can use to install the development version of the package:
python setup.py install
Tests
-----
To run the tests, ensure that the ClickHouse server is running on <http://localhost:8123/> (this is the default), and run:
bin/nosetests
To see test coverage information run:
bin/nosetests --with-coverage --cover-package=infi.clickhouse_orm
---
[<< System Models](system_models.md) | [Table of Contents](toc.md) | [Class Reference >>](class_reference.md)

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Field Types
===========
Currently the following field types are supported:
| Class | DB Type | Pythonic Type | Comments
| ------------------ | ---------- | ------------------- | -----------------------------------------------------
| StringField | String | unicode | Encoded as UTF-8 when written to ClickHouse
| FixedStringField | String | unicode | Encoded as UTF-8 when written to ClickHouse
| DateField | Date | datetime.date | Range 1970-01-01 to 2038-01-19
| DateTimeField | DateTime | datetime.datetime | Minimal value is 1970-01-01 00:00:00; Always in UTC
| Int8Field | Int8 | int | Range -128 to 127
| Int16Field | Int16 | int | Range -32768 to 32767
| Int32Field | Int32 | int | Range -2147483648 to 2147483647
| Int64Field | Int64 | int/long | Range -9223372036854775808 to 9223372036854775807
| UInt8Field | UInt8 | int | Range 0 to 255
| UInt16Field | UInt16 | int | Range 0 to 65535
| UInt32Field | UInt32 | int | Range 0 to 4294967295
| UInt64Field | UInt64 | int/long | Range 0 to 18446744073709551615
| Float32Field | Float32 | float |
| Float64Field | Float64 | float |
| Enum8Field | Enum8 | Enum | See below
| Enum16Field | Enum16 | Enum | See below
| ArrayField | Array | list | See below
DateTimeField and Time Zones
----------------------------
A `DateTimeField` can be assigned values from one of the following types:
- datetime
- date
- integer - number of seconds since the Unix epoch
- string in `YYYY-MM-DD HH:MM:SS` format
The assigned value always gets converted to a timezone-aware `datetime` in UTC. If the assigned value is a timezone-aware `datetime` in another timezone, it will be converted to UTC. Otherwise, the assigned value is assumed to already be in UTC.
DateTime values that are read from the database are also converted to UTC. ClickHouse formats them according to the timezone of the server, and the ORM makes the necessary conversions. This requires a ClickHouse
version which is new enough to support the `timezone()` function, otherwise it is assumed to be using UTC. In any case, we recommend settings the server timezone to UTC in order to prevent confusion.
Working with enum fields
------------------------
`Enum8Field` and `Enum16Field` provide support for working with ClickHouse enum columns. They accept strings or integers as values, and convert them to the matching Pythonic Enum member.
Python 3.4 and higher supports Enums natively. When using previous Python versions you need to install the enum34 library.
Example of a model with an enum field:
Gender = Enum('Gender', 'male female unspecified')
class Person(models.Model):
first_name = fields.StringField()
last_name = fields.StringField()
birthday = fields.DateField()
gender = fields.Enum32Field(Gender)
engine = engines.MergeTree('birthday', ('first_name', 'last_name', 'birthday'))
suzy = Person(first_name='Suzy', last_name='Jones', gender=Gender.female)
Working with array fields
-------------------------
You can create array fields containing any data type, for example:
class SensorData(models.Model):
date = fields.DateField()
temperatures = fields.ArrayField(fields.Float32Field())
humidity_levels = fields.ArrayField(fields.UInt8Field())
engine = engines.MergeTree('date', ('date',))
data = SensorData(date=date.today(), temperatures=[25.5, 31.2, 28.7], humidity_levels=[41, 39, 66])
Working with materialized and alias fields
------------------------------------------
ClickHouse provides an opportunity to create MATERIALIZED and ALIAS Fields.
See documentation [here](https://clickhouse.yandex/reference_en.html#Default%20values).
Both field types can't be inserted into the database directly, so they are ignored when using the `Database.insert()` method. ClickHouse does not return the field values if you use `"SELECT * FROM ..."` - you have to list these field names explicitly in the query.
Usage:
class Event(models.Model):
created = fields.DateTimeField()
created_date = fields.DateTimeField(materialized='toDate(created)')
name = fields.StringField()
username = fields.StringField(alias='name')
engine = engines.MergeTree('created_date', ('created_date', 'created'))
obj = Event(created=datetime.now(), name='MyEvent')
db = Database('my_test_db')
db.insert([obj])
# All values will be retrieved from database
db.select('SELECT created, created_date, username, name FROM $db.event', model_class=Event)
# created_date and username will contain a default value
db.select('SELECT * FROM $db.event', model_class=Event)
---
[<< Querysets](querysets.md) | [Table of Contents](toc.md) | [Table Engines >>](table_engines.md)

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Overview
========
This project is simple ORM for working with the [ClickHouse database](https://clickhouse.yandex/). It allows you to define model classes whose instances can be written to the database and read from it.
It was tested on Python 2.7 and 3.5.
Installation
------------
To install infi.clickhouse_orm:
pip install infi.clickhouse_orm
---
[Table of Contents](toc.md) | [Models and Databases >>](models_and_databases.md)

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Models and Databases
====================
Models represent ClickHouse tables, allowing you to work with them using familiar pythonic syntax.
Database instances connect to a specific ClickHouse database for running queries, inserting data and other operations.
Defining Models
---------------
Models are defined in a way reminiscent of Django's ORM:
from infi.clickhouse_orm import models, fields, engines
class Person(models.Model):
first_name = fields.StringField()
last_name = fields.StringField()
birthday = fields.DateField()
height = fields.Float32Field()
engine = engines.MergeTree('birthday', ('first_name', 'last_name', 'birthday'))
It is possible to provide a default value for a field, instead of its "natural" default (empty string for string fields, zero for numeric fields etc.). Alternatively it is possible to pass alias or materialized parameters (see below for usage examples). Only one of `default`, `alias` and `materialized` parameters can be provided.
For more details see [Field Types](field_types.md) and [Table Engines](table_engines.md).
### Table Names
The table name used for the model is its class name, converted to lowercase. To override the default name, implement the `table_name` method:
class Person(models.Model):
...
@classmethod
def table_name(cls):
return 'people'
Using Models
------------
Once you have a model, you can create model instances:
>>> dan = Person(first_name='Dan', last_name='Schwartz')
>>> suzy = Person(first_name='Suzy', last_name='Jones')
>>> dan.first_name
u'Dan'
When values are assigned to model fields, they are immediately converted to their Pythonic data type. In case the value is invalid, a `ValueError` is raised:
>>> suzy.birthday = '1980-01-17'
>>> suzy.birthday
datetime.date(1980, 1, 17)
>>> suzy.birthday = 0.5
ValueError: Invalid value for DateField - 0.5
>>> suzy.birthday = '1922-05-31'
ValueError: DateField out of range - 1922-05-31 is not between 1970-01-01 and 2038-01-19
Inserting to the Database
-------------------------
To write your instances to ClickHouse, you need a `Database` instance:
from infi.clickhouse_orm.database import Database
db = Database('my_test_db')
This automatically connects to <http://localhost:8123> and creates a database called my_test_db, unless it already exists. If necessary, you can specify a different database URL and optional credentials:
db = Database('my_test_db', db_url='http://192.168.1.1:8050', username='scott', password='tiger')
Using the `Database` instance you can create a table for your model, and insert instances to it:
db.create_table(Person)
db.insert([dan, suzy])
The `insert` method can take any iterable of model instances, but they all must belong to the same model class.
Creating a read-only database is also supported. Such a `Database` instance can only read data, and cannot modify data or schemas:
db = Database('my_test_db', readonly=True)
Reading from the Database
-------------------------
Loading model instances from the database is simple:
for person in db.select("SELECT * FROM my_test_db.person", model_class=Person):
print person.first_name, person.last_name
Do not include a `FORMAT` clause in the query, since the ORM automatically sets the format to `TabSeparatedWithNamesAndTypes`.
It is possible to select only a subset of the columns, and the rest will receive their default values:
for person in db.select("SELECT first_name FROM my_test_db.person WHERE last_name='Smith'", model_class=Person):
print person.first_name
The ORM provides a way to build simple queries without writing SQL by hand. The previous snippet can be written like this:
for person in Person.objects_in(db).filter(last_name='Smith').only('first_name'):
print person.first_name
See [Querysets](querysets.md) for more information.
Reading without a Model
-----------------------
When running a query, specifying a model class is not required. In case you do not provide a model class, an ad-hoc class will be defined based on the column names and types returned by the query:
for row in db.select("SELECT max(height) as max_height FROM my_test_db.person"):
print row.max_height
This is a very convenient feature that saves you the need to define a model for each query, while still letting you work with Pythonic column values and an elegant syntax.
SQL Placeholders
----------------
There are a couple of special placeholders that you can use inside the SQL to make it easier to write: `$db` and `$table`. The first one is replaced by the database name, and the second is replaced by the database name plus table name (but is available only when the model is specified).
So instead of this:
db.select("SELECT * FROM my_test_db.person", model_class=Person)
you can use:
db.select("SELECT * FROM $db.person", model_class=Person)
or even:
db.select("SELECT * FROM $table", model_class=Person)
Counting
--------
The `Database` class also supports counting records easily:
>>> db.count(Person)
117
>>> db.count(Person, conditions="height > 1.90")
6
Pagination
----------
It is possible to paginate through model instances:
>>> order_by = 'first_name, last_name'
>>> page = db.paginate(Person, order_by, page_num=1, page_size=10)
>>> print page.number_of_objects
2507
>>> print page.pages_total
251
>>> for person in page.objects:
>>> # do something
The `paginate` method returns a `namedtuple` containing the following fields:
- `objects` - the list of objects in this page
- `number_of_objects` - total number of objects in all pages
- `pages_total` - total number of pages
- `number` - the page number, starting from 1; the special value -1
may be used to retrieve the last page
- `page_size` - the number of objects per page
You can optionally pass conditions to the query:
>>> page = db.paginate(Person, order_by, page_num=1, page_size=100, conditions='height > 1.90')
Note that `order_by` must be chosen so that the ordering is unique, otherwise there might be inconsistencies in the pagination (such as an instance that appears on two different pages).
---
[<< Overview](index.md) | [Table of Contents](toc.md) | [Querysets >>](querysets.md)

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Querysets
=========
A queryset is an object that represents a database query using a specific Model. It is lazy, meaning that it does not hit the database until you iterate over its matching rows (model instances). To create a base queryset for a model class, use:
qs = Person.objects_in(database)
This queryset matches all Person instances in the database. You can get these instances using iteration:
for person in qs:
print person.first_name, person.last_name
Filtering
---------
The `filter` and `exclude` methods are used for filtering the matching instances. Calling these methods returns a new queryset instance, with the added conditions. For example:
>>> qs = Person.objects_in(database)
>>> qs = qs.filter(first_name__startswith='V').exclude(birthday__lt='2000-01-01')
>>> qs.conditions_as_sql()
u"first_name LIKE 'V%' AND NOT (birthday < '2000-01-01')"
It is possible to specify several fields to filter or exclude by:
>>> qs = Person.objects_in(database).filter(last_name='Smith', height__gt=1.75)
>>> qs.conditions_as_sql()
u"last_name = 'Smith' AND height > 1.75"
There are different operators that can be used, by passing `<fieldname>__<operator>=<value>` (two underscores separate the field name from the operator). In case no operator is given, `eq` is used by default. Below are all the supported operators.
| Operator | Equivalent SQL | Comments |
| -------- | -------------------------------------------- | ---------------------------------- |
| `eq` | `field = value` | |
| `gt` | `field > value` | |
| `gte` | `field >= value` | |
| `lt` | `field < value` | |
| `lte` | `field <= value` | |
| `in` | `field IN (values)` | See below |
| `contains` | `field LIKE '%value%'` | For string fields only |
| `startswith` | `field LIKE 'value%'` | For string fields only |
| `endswith` | `field LIKE '%value'` | For string fields only |
| `icontains` | `lowerUTF8(field) LIKE lowerUTF8('%value%')` | For string fields only |
| `istartswith` | `lowerUTF8(field) LIKE lowerUTF8('value%')` | For string fields only |
| `iendswith` | `lowerUTF8(field) LIKE lowerUTF8('%value')` | For string fields only |
| `iexact` | `lowerUTF8(field) = lowerUTF8(value)` | For string fields only |
### Using the `in` Operator
The `in` operator expects one of three types of values:
* A list or tuple of simple values
* A string, which is used verbatim as the contents of the parentheses
* Another queryset (subquery)
For example if we want to select only people with Irish last names:
# A list of simple values
qs = Person.objects_in(database).filter(last_name__in=["Murphy", "O'Sullivan"])
# A string
subquery = "SELECT name from $db.irishlastname"
qs = Person.objects_in(database).filter(last_name__in=subquery)
# A queryset
subquery = IrishLastName.objects_in(database).only("name")
qs = Person.objects_in(database).filter(last_name__in=subquery)
Counting and Checking Existence
-------------------------------
Use the `count` method to get the number of matches:
Person.objects_in(database).count()
To check if there are any matches at all, you can use any of the following equivalent options:
if qs.count(): ...
if bool(qs): ...
if qs: ...
Ordering
--------
The sorting order of the results can be controlled using the `order_by` method:
qs = Person.objects_in(database).order_by('last_name', 'first_name')
The default order is ascending. To use descending order, add a minus sign before the field name:
qs = Person.objects_in(database).order_by('-height')
Omitting Fields
---------------
When some of the model fields aren't needed, it is more efficient to omit them from the query. This is especially true when there are large fields that may slow the query down. Use the `only` method to specify which fields to retrieve:
qs = Person.objects_in(database).only('first_name', 'birthday')
---
[<< Models and Databases](models_and_databases.md) | [Table of Contents](toc.md) | [Field Types >>](field_types.md)

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Class Reference
===============
infi.clickhouse_orm.database
----------------------------
### Database
#### Database(db_name, db_url="http://localhost:8123/", username=None, password=None, readonly=False)
Initializes a database instance. Unless it's readonly, the database will be
created on the ClickHouse server if it does not already exist.
- `db_name`: name of the database to connect to.
- `db_url`: URL of the ClickHouse server.
- `username`: optional connection credentials.
- `password`: optional connection credentials.
- `readonly`: use a read-only connection.
#### count(model_class, conditions=None)
Counts the number of records in the model's table.
- `model_class`: the model to count.
- `conditions`: optional SQL conditions (contents of the WHERE clause).
#### create_database()
Creates the database on the ClickHouse server if it does not already exist.
#### create_table(model_class)
Creates a table for the given model class, if it does not exist already.
#### drop_database()
Deletes the database on the ClickHouse server.
#### drop_table(model_class)
Drops the database table of the given model class, if it exists.
#### insert(model_instances, batch_size=1000)
Insert records into the database.
- `model_instances`: any iterable containing instances of a single model class.
- `batch_size`: number of records to send per chunk (use a lower number if your records are very large).
#### migrate(migrations_package_name, up_to=9999)
Executes schema migrations.
- `migrations_package_name` - fully qualified name of the Python package
containing the migrations.
- `up_to` - number of the last migration to apply.
#### paginate(model_class, order_by, page_num=1, page_size=100, conditions=None, settings=None)
Selects records and returns a single page of model instances.
- `model_class`: the model class matching the query's table,
or `None` for getting back instances of an ad-hoc model.
- `order_by`: columns to use for sorting the query (contents of the ORDER BY clause).
- `page_num`: the page number (1-based), or -1 to get the last page.
- `page_size`: number of records to return per page.
- `conditions`: optional SQL conditions (contents of the WHERE clause).
- `settings`: query settings to send as HTTP GET parameters
The result is a namedtuple containing `objects` (list), `number_of_objects`,
`pages_total`, `number` (of the current page), and `page_size`.
#### raw(query, settings=None, stream=False)
Performs a query and returns its output as text.
- `query`: the SQL query to execute.
- `settings`: query settings to send as HTTP GET parameters
- `stream`: if true, the HTTP response from ClickHouse will be streamed.
#### select(query, model_class=None, settings=None)
Performs a query and returns a generator of model instances.
- `query`: the SQL query to execute.
- `model_class`: the model class matching the query's table,
or `None` for getting back instances of an ad-hoc model.
- `settings`: query settings to send as HTTP GET parameters
### DatabaseException
Extends Exception
Raised when a database operation fails.
infi.clickhouse_orm.models
--------------------------
### Model
A base class for ORM models.
#### Model(**kwargs)
Creates a model instance, using keyword arguments as field values.
Since values are immediately converted to their Pythonic type,
invalid values will cause a `ValueError` to be raised.
Unrecognized field names will cause an `AttributeError`.
#### Model.create_table_sql(db_name)
Returns the SQL command for creating a table for this model.
#### Model.drop_table_sql(db_name)
Returns the SQL command for deleting this model's table.
#### Model.from_tsv(line, field_names=None, timezone_in_use=UTC, database=None)
Create a model instance from a tab-separated line. The line may or may not include a newline.
The `field_names` list must match the fields defined in the model, but does not have to include all of them.
If omitted, it is assumed to be the names of all fields in the model, in order of definition.
- `line`: the TSV-formatted data.
- `field_names`: names of the model fields in the data.
- `timezone_in_use`: the timezone to use when parsing dates and datetimes.
- `database`: if given, sets the database that this instance belongs to.
#### get_database()
Gets the `Database` that this model instance belongs to.
Returns `None` unless the instance was read from the database or written to it.
#### get_field(name)
Gets a `Field` instance given its name, or `None` if not found.
#### Model.objects_in(database)
Returns a `QuerySet` for selecting instances of this model class.
#### set_database(db)
Sets the `Database` that this model instance belongs to.
This is done automatically when the instance is read from the database or written to it.
#### Model.table_name()
Returns the model's database table name. By default this is the
class name converted to lowercase. Override this if you want to use
a different table name.
#### to_dict(include_readonly=True, field_names=None)
Returns the instance's column values as a dict.
- `include_readonly`: if false, returns only fields that can be inserted into database.
- `field_names`: an iterable of field names to return (optional)
#### to_tsv(include_readonly=True)
Returns the instance's column values as a tab-separated line. A newline is not included.
- `include_readonly`: if false, returns only fields that can be inserted into database.
### BufferModel
Extends Model
#### BufferModel(**kwargs)
Creates a model instance, using keyword arguments as field values.
Since values are immediately converted to their Pythonic type,
invalid values will cause a `ValueError` to be raised.
Unrecognized field names will cause an `AttributeError`.
#### BufferModel.create_table_sql(db_name)
Returns the SQL command for creating a table for this model.
#### BufferModel.drop_table_sql(db_name)
Returns the SQL command for deleting this model's table.
#### BufferModel.from_tsv(line, field_names=None, timezone_in_use=UTC, database=None)
Create a model instance from a tab-separated line. The line may or may not include a newline.
The `field_names` list must match the fields defined in the model, but does not have to include all of them.
If omitted, it is assumed to be the names of all fields in the model, in order of definition.
- `line`: the TSV-formatted data.
- `field_names`: names of the model fields in the data.
- `timezone_in_use`: the timezone to use when parsing dates and datetimes.
- `database`: if given, sets the database that this instance belongs to.
#### get_database()
Gets the `Database` that this model instance belongs to.
Returns `None` unless the instance was read from the database or written to it.
#### get_field(name)
Gets a `Field` instance given its name, or `None` if not found.
#### BufferModel.objects_in(database)
Returns a `QuerySet` for selecting instances of this model class.
#### set_database(db)
Sets the `Database` that this model instance belongs to.
This is done automatically when the instance is read from the database or written to it.
#### BufferModel.table_name()
Returns the model's database table name. By default this is the
class name converted to lowercase. Override this if you want to use
a different table name.
#### to_dict(include_readonly=True, field_names=None)
Returns the instance's column values as a dict.
- `include_readonly`: if false, returns only fields that can be inserted into database.
- `field_names`: an iterable of field names to return (optional)
#### to_tsv(include_readonly=True)
Returns the instance's column values as a tab-separated line. A newline is not included.
- `include_readonly`: if false, returns only fields that can be inserted into database.
infi.clickhouse_orm.fields
--------------------------
### Field
Abstract base class for all field types.
#### Field(default=None, alias=None, materialized=None)
### StringField
Extends Field
#### StringField(default=None, alias=None, materialized=None)
### DateField
Extends Field
#### DateField(default=None, alias=None, materialized=None)
### DateTimeField
Extends Field
#### DateTimeField(default=None, alias=None, materialized=None)
### BaseIntField
Extends Field
Abstract base class for all integer-type fields.
#### BaseIntField(default=None, alias=None, materialized=None)
### BaseFloatField
Extends Field
Abstract base class for all float-type fields.
#### BaseFloatField(default=None, alias=None, materialized=None)
### BaseEnumField
Extends Field
Abstract base class for all enum-type fields.
#### BaseEnumField(enum_cls, default=None, alias=None, materialized=None)
### ArrayField
Extends Field
#### ArrayField(inner_field, default=None, alias=None, materialized=None)
### FixedStringField
Extends StringField
#### FixedStringField(length, default=None, alias=None, materialized=None)
### UInt8Field
Extends BaseIntField
#### UInt8Field(default=None, alias=None, materialized=None)
### UInt16Field
Extends BaseIntField
#### UInt16Field(default=None, alias=None, materialized=None)
### UInt32Field
Extends BaseIntField
#### UInt32Field(default=None, alias=None, materialized=None)
### UInt64Field
Extends BaseIntField
#### UInt64Field(default=None, alias=None, materialized=None)
### Int8Field
Extends BaseIntField
#### Int8Field(default=None, alias=None, materialized=None)
### Int16Field
Extends BaseIntField
#### Int16Field(default=None, alias=None, materialized=None)
### Int32Field
Extends BaseIntField
#### Int32Field(default=None, alias=None, materialized=None)
### Int64Field
Extends BaseIntField
#### Int64Field(default=None, alias=None, materialized=None)
### Float32Field
Extends BaseFloatField
#### Float32Field(default=None, alias=None, materialized=None)
### Float64Field
Extends BaseFloatField
#### Float64Field(default=None, alias=None, materialized=None)
### Enum8Field
Extends BaseEnumField
#### Enum8Field(enum_cls, default=None, alias=None, materialized=None)
### Enum16Field
Extends BaseEnumField
#### Enum16Field(enum_cls, default=None, alias=None, materialized=None)
infi.clickhouse_orm.engines
---------------------------
### Engine
### TinyLog
Extends Engine
### Log
Extends Engine
### Memory
Extends Engine
### MergeTree
Extends Engine
#### MergeTree(date_col, key_cols, sampling_expr=None, index_granularity=8192, replica_table_path=None, replica_name=None)
### Buffer
Extends Engine
Here we define Buffer engine
Read more here https://clickhouse.yandex/reference_en.html#Buffer
#### Buffer(main_model, num_layers=16, min_time=10, max_time=100, min_rows=10000, max_rows=1000000, min_bytes=10000000, max_bytes=100000000)
### CollapsingMergeTree
Extends MergeTree
#### CollapsingMergeTree(date_col, key_cols, sign_col, sampling_expr=None, index_granularity=8192, replica_table_path=None, replica_name=None)
### SummingMergeTree
Extends MergeTree
#### SummingMergeTree(date_col, key_cols, summing_cols=None, sampling_expr=None, index_granularity=8192, replica_table_path=None, replica_name=None)
### ReplacingMergeTree
Extends MergeTree
#### ReplacingMergeTree(date_col, key_cols, ver_col=None, sampling_expr=None, index_granularity=8192, replica_table_path=None, replica_name=None)
infi.clickhouse_orm.query
-------------------------
### QuerySet
#### QuerySet(model_cls, database)
#### conditions_as_sql()
Return the contents of the queryset's WHERE clause.
#### count()
Returns the number of matching model instances.
#### exclude(**kwargs)
Returns a new QuerySet instance that excludes all rows matching the conditions.
#### filter(**kwargs)
Returns a new QuerySet instance that includes only rows matching the conditions.
#### only(*field_names)
Limit the query to return only the specified field names.
Useful when there are large fields that are not needed,
or for creating a subquery to use with an IN operator.
#### order_by(*field_names)
Returns a new QuerySet instance with the ordering changed.
#### order_by_as_sql()
Return the contents of the queryset's ORDER BY clause.
#### query()
Return the the queryset as SQL.

34
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@ -1,17 +1,14 @@
Migrations
==========
Schema Migrations
=================
Over time, the ORM models in your application may change. Migrations provide a way to modify the database
tables according to the changes in your models, without writing raw SQL.
Over time, the ORM models in your application may change. Migrations provide a way to modify the database tables according to the changes in your models, without writing raw SQL.
The migrations that were applied to the database are recorded in the ``infi_clickhouse_orm_migrations`` table,
so migrating the database will only apply any missing migrations.
The migrations that were applied to the database are recorded in the `infi_clickhouse_orm_migrations` table, so migrating the database will only apply any missing migrations.
Writing Migrations
------------------
To write migrations, create a Python package. Then create a python file for the initial migration. The migration
files must begin with a four-digit number, and will be applied in sequence. For example::
To write migrations, create a Python package. Then create a python file for the initial migration. The migration files must begin with a four-digit number, and will be applied in sequence. For example:
analytics
|
@ -23,7 +20,7 @@ files must begin with a four-digit number, and will be applied in sequence. For
|
+-- 0002_add_user_agents_table.py
Each migration file is expected to contain a list of ``operations``, for example::
Each migration file is expected to contain a list of `operations`, for example:
from infi.clickhouse_orm import migrations
from analytics import models
@ -45,21 +42,24 @@ A migration operation that drops the table of a given model class.
**AlterTable**
A migration operation that compares the table of a given model class to
the model's fields, and alters the table to match the model. The operation can:
A migration operation that compares the table of a given model class to the model’s fields, and alters the table to match the model. The operation can:
- add new columns
- drop obsolete columns
- modify column types
- add new columns
- drop obsolete columns
- modify column types
Default values are not altered by this operation.
Running Migrations
------------------
To migrate a database, create a ``Database`` instance and call its ``migrate`` method with the package
name containing your migrations::
To migrate a database, create a `Database` instance and call its `migrate` method with the package name containing your migrations:
Database('analytics_db').migrate('analytics.analytics_migrations')
Note that you may have more than one migrations package.
Note that you may have more than one migrations package.
---
[<< Table Engines](table_engines.md) | [Table of Contents](toc.md) | [System Models >>](system_models.md)

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System Models
=============
[Clickhouse docs](https://clickhouse.yandex/reference_en.html#System%20tables).
System models are read only models for implementing part of the system's functionality, and for providing access to information about how the system is working.
Currently the following system models are supported:
| Class | DB Table | Comments
| ------------ | -------------- | ---------------------------------------------------
| SystemPart | system.parts | Gives methods to work with partitions. See below.
Partitions and Parts
--------------------
[ClickHouse docs](https://clickhouse.yandex/reference_en.html#Manipulations%20with%20partitions%20and%20parts).
A partition in a table is data for a single calendar month. Table "system.parts" contains information about each part.
| Method | Parameters | Comments
| --------------------- | ------------------------- | -----------------------------------------------------------------------------------------------
| get(static) | database, conditions="" | Gets database partitions, filtered by conditions
| get_active(static) | database, conditions="" | Gets only active (not detached or dropped) partitions, filtered by conditions
| detach | settings=None | Detaches the partition. Settings is a dict of params to pass to http request
| drop | settings=None | Drops the partition. Settings is a dict of params to pass to http request
| attach | settings=None | Attaches already detached partition. Settings is a dict of params to pass to http request
| freeze | settings=None | Freezes (makes backup) of the partition. Settings is a dict of params to pass to http request
| fetch | settings=None | Fetches partition. Settings is a dict of params to pass to http request
Usage example:
from infi.clickhouse_orm.database import Database
from infi.clickhouse_orm.system_models import SystemPart
db = Database('my_test_db', db_url='http://192.168.1.1:8050', username='scott', password='tiger')
partitions = SystemPart.get_active(db, conditions='') # Getting all active partitions of the database
if len(partitions) > 0:
partitions = sorted(partitions, key=lambda obj: obj.name) # Partition name is YYYYMM, so we can sort so
partitions[0].freeze() # Make a backup in /opt/clickhouse/shadow directory
partitions[0].drop() # Dropped partition
`Note`: system.parts stores information for all databases. To be correct, SystemPart model was designed to receive only parts belonging to the given database instance.
---
[<< Schema Migrations](schema_migrations.md) | [Table of Contents](toc.md) | [Contributing >>](contributing.md)

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Table Engines
=============
See: [ClickHouse Documentation](https://clickhouse.yandex/reference_en.html#Table+engines)
Each model must have an engine instance, used when creating the table in ClickHouse.
The following engines are supported by the ORM:
- TinyLog
- Log
- Memory
- MergeTree / ReplicatedMergeTree
- CollapsingMergeTree / ReplicatedCollapsingMergeTree
- SummingMergeTree / ReplicatedSummingMergeTree
- ReplacingMergeTree / ReplicatedReplacingMergeTree
- Buffer
Simple Engines
--------------
`TinyLog`, `Log` and `Memory` engines do not require any parameters:
engine = engines.TinyLog()
engine = engines.Log()
engine = engines.Memory()
Engines in the MergeTree Family
-------------------------------
To define a `MergeTree` engine, supply the date column name and the names (or expressions) for the key columns:
engine = engines.MergeTree('EventDate', ('CounterID', 'EventDate'))
You may also provide a sampling expression:
engine = engines.MergeTree('EventDate', ('CounterID', 'EventDate'), sampling_expr='intHash32(UserID)')
A `CollapsingMergeTree` engine is defined in a similar manner, but requires also a sign column:
engine = engines.CollapsingMergeTree('EventDate', ('CounterID', 'EventDate'), 'Sign')
For a `SummingMergeTree` you can optionally specify the summing columns:
engine = engines.SummingMergeTree('EventDate', ('OrderID', 'EventDate', 'BannerID'),
summing_cols=('Shows', 'Clicks', 'Cost'))
For a `ReplacingMergeTree` you can optionally specify the version column:
engine = engines.ReplacingMergeTree('EventDate', ('OrderID', 'EventDate', 'BannerID'), ver_col='Version')
### Data Replication
Any of the above engines can be converted to a replicated engine (e.g. `ReplicatedMergeTree`) by adding two parameters, `replica_table_path` and `replica_name`:
engine = engines.MergeTree('EventDate', ('CounterID', 'EventDate'),
replica_table_path='/clickhouse/tables/{layer}-{shard}/hits',
replica_name='{replica}')
Buffer Engine
-------------
A `Buffer` engine is only used in conjunction with a `BufferModel`.
The model should be a subclass of both `models.BufferModel` and the main model.
The main model is also passed to the engine:
class PersonBuffer(models.BufferModel, Person):
engine = engines.Buffer(Person)
Additional buffer parameters can optionally be specified:
engine = engines.Buffer(Person, num_layers=16, min_time=10,
max_time=100, min_rows=10000, max_rows=1000000,
min_bytes=10000000, max_bytes=100000000)
Then you can insert objects into Buffer model and they will be handled by ClickHouse properly:
db.create_table(PersonBuffer)
suzy = PersonBuffer(first_name='Suzy', last_name='Jones')
dan = PersonBuffer(first_name='Dan', last_name='Schwartz')
db.insert([dan, suzy])
---
[<< Field Types](field_types.md) | [Table of Contents](toc.md) | [Schema Migrations >>](schema_migrations.md)

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# Table of Contents
* [Overview](index.md#overview)
* [Installation](index.md#installation)
* [Models and Databases](models_and_databases.md#models-and-databases)
* [Defining Models](models_and_databases.md#defining-models)
* [Table Names](models_and_databases.md#table-names)
* [Using Models](models_and_databases.md#using-models)
* [Inserting to the Database](models_and_databases.md#inserting-to-the-database)
* [Reading from the Database](models_and_databases.md#reading-from-the-database)
* [Reading without a Model](models_and_databases.md#reading-without-a-model)
* [SQL Placeholders](models_and_databases.md#sql-placeholders)
* [Counting](models_and_databases.md#counting)
* [Pagination](models_and_databases.md#pagination)
* [Querysets](querysets.md#querysets)
* [Filtering](querysets.md#filtering)
* [Using the in Operator](querysets.md#using-the-in-operator)
* [Counting and Checking Existence](querysets.md#counting-and-checking-existence)
* [Ordering](querysets.md#ordering)
* [Omitting Fields](querysets.md#omitting-fields)
* [Field Types](field_types.md#field-types)
* [DateTimeField and Time Zones](field_types.md#datetimefield-and-time-zones)
* [Working with enum fields](field_types.md#working-with-enum-fields)
* [Working with array fields](field_types.md#working-with-array-fields)
* [Working with materialized and alias fields](field_types.md#working-with-materialized-and-alias-fields)
* [Table Engines](table_engines.md#table-engines)
* [Simple Engines](table_engines.md#simple-engines)
* [Engines in the MergeTree Family](table_engines.md#engines-in-the-mergetree-family)
* [Data Replication](table_engines.md#data-replication)
* [Buffer Engine](table_engines.md#buffer-engine)
* [Schema Migrations](schema_migrations.md#schema-migrations)
* [Writing Migrations](schema_migrations.md#writing-migrations)
* [Running Migrations](schema_migrations.md#running-migrations)
* [System Models](system_models.md#system-models)
* [Partitions and Parts](system_models.md#partitions-and-parts)
* [Contributing](contributing.md#contributing)
* [Building](contributing.md#building)
* [Tests](contributing.md#tests)
* [Class Reference](class_reference.md#class-reference)
* [infi.clickhouse_orm.database](class_reference.md#infi.clickhouse_orm.database)
* [Database](class_reference.md#database)
* [DatabaseException](class_reference.md#databaseexception)
* [infi.clickhouse_orm.models](class_reference.md#infi.clickhouse_orm.models)
* [Model](class_reference.md#model)
* [BufferModel](class_reference.md#buffermodel)
* [infi.clickhouse_orm.fields](class_reference.md#infi.clickhouse_orm.fields)
* [Field](class_reference.md#field)
* [StringField](class_reference.md#stringfield)
* [DateField](class_reference.md#datefield)
* [DateTimeField](class_reference.md#datetimefield)
* [BaseIntField](class_reference.md#baseintfield)
* [BaseFloatField](class_reference.md#basefloatfield)
* [BaseEnumField](class_reference.md#baseenumfield)
* [ArrayField](class_reference.md#arrayfield)
* [FixedStringField](class_reference.md#fixedstringfield)
* [UInt8Field](class_reference.md#uint8field)
* [UInt16Field](class_reference.md#uint16field)
* [UInt32Field](class_reference.md#uint32field)
* [UInt64Field](class_reference.md#uint64field)
* [Int8Field](class_reference.md#int8field)
* [Int16Field](class_reference.md#int16field)
* [Int32Field](class_reference.md#int32field)
* [Int64Field](class_reference.md#int64field)
* [Float32Field](class_reference.md#float32field)
* [Float64Field](class_reference.md#float64field)
* [Enum8Field](class_reference.md#enum8field)
* [Enum16Field](class_reference.md#enum16field)
* [infi.clickhouse_orm.engines](class_reference.md#infi.clickhouse_orm.engines)
* [Engine](class_reference.md#engine)
* [TinyLog](class_reference.md#tinylog)
* [Log](class_reference.md#log)
* [Memory](class_reference.md#memory)
* [MergeTree](class_reference.md#mergetree)
* [Buffer](class_reference.md#buffer)
* [CollapsingMergeTree](class_reference.md#collapsingmergetree)
* [SummingMergeTree](class_reference.md#summingmergetree)
* [ReplacingMergeTree](class_reference.md#replacingmergetree)
* [infi.clickhouse_orm.query](class_reference.md#infi.clickhouse_orm.query)
* [QuerySet](class_reference.md#queryset)

54
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@ -0,0 +1,54 @@
This directory contains various scripts for use while developing.
generate_toc
------------
Generates the table of contents (toc.md). Requires Pandoc.
Usage:
cd docs
../scripts/generate_toc.sh
html_to_markdown_toc.py
-----------------------
Used by generate_toc.
docs2html
---------
Converts markdown docs to html for preview. Requires Pandoc.
Usage:
cd docs
../scripts/docs2html.sh
generate_ref
------------
Generates a class reference.
Usage:
cd docs
../bin/python ../scripts/generate_ref.py > class_reference.md
generate_all
------------
Does everything:
- Generates the class reference using generate_ref
- Generates the table of contents using generate_toc
- Converts to HTML for visual inspection using docs2html
Usage:
cd docs
../scripts/generate_all.sh
test_python3
------------
Creates a Python 3 virtualenv, clones the project into it, and runs the tests.
Usage:
./test_python3.sh

10
scripts/docs2html.sh Executable file
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@ -0,0 +1,10 @@
mkdir -p ../htmldocs
find ./ -iname "*.md" -type f -exec sh -c 'echo "Converting ${0}"; pandoc "${0}" -s -o "../htmldocs/${0%.md}.html"' {} \;
echo "Converting README.md"
pandoc ../README.md -s -o "../htmldocs/README.html"
echo "Fixing links"
sed -i 's/\.md/\.html/g' ../htmldocs/*.html

8
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@ -0,0 +1,8 @@
# Class reference
../bin/python ../scripts/generate_ref.py > class_reference.md
# Table of contents
../scripts/generate_toc.sh
# Convert to HTML for visual inspection
../scripts/docs2html.sh

135
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@ -0,0 +1,135 @@
import inspect
from collections import namedtuple
DefaultArgSpec = namedtuple('DefaultArgSpec', 'has_default default_value')
def _get_default_arg(args, defaults, arg_index):
""" Method that determines if an argument has default value or not,
and if yes what is the default value for the argument
:param args: array of arguments, eg: ['first_arg', 'second_arg', 'third_arg']
:param defaults: array of default values, eg: (42, 'something')
:param arg_index: index of the argument in the argument array for which,
this function checks if a default value exists or not. And if default value
exists it would return the default value. Example argument: 1
:return: Tuple of whether there is a default or not, and if yes the default
value, eg: for index 2 i.e. for "second_arg" this function returns (True, 42)
"""
if not defaults:
return DefaultArgSpec(False, None)
args_with_no_defaults = len(args) - len(defaults)
if arg_index < args_with_no_defaults:
return DefaultArgSpec(False, None)
else:
value = defaults[arg_index - args_with_no_defaults]
if (type(value) is str):
value = '"%s"' % value
return DefaultArgSpec(True, value)
def get_method_sig(method):
""" Given a function, it returns a string that pretty much looks how the
function signature would be written in python.
:param method: a python method
:return: A string similar describing the pythong method signature.
eg: "my_method(first_argArg, second_arg=42, third_arg='something')"
"""
# The return value of ArgSpec is a bit weird, as the list of arguments and
# list of defaults are returned in separate array.
# eg: ArgSpec(args=['first_arg', 'second_arg', 'third_arg'],
# varargs=None, keywords=None, defaults=(42, 'something'))
argspec = inspect.getargspec(method)
arg_index=0
args = []
# Use the args and defaults array returned by argspec and find out
# which arguments has default
for arg in argspec.args:
default_arg = _get_default_arg(argspec.args, argspec.defaults, arg_index)
if default_arg.has_default:
args.append("%s=%s" % (arg, default_arg.default_value))
else:
args.append(arg)
arg_index += 1
if argspec.varargs:
args.append('*' + argspec.varargs)
if argspec.keywords:
args.append('**' + argspec.keywords)
return "%s(%s)" % (method.__name__, ", ".join(args[1:]))
def docstring(obj):
doc = (obj.__doc__ or '').rstrip()
if doc:
lines = doc.split('\n')
# Find the length of the whitespace prefix common to all non-empty lines
indentation = min(len(line) - len(line.lstrip()) for line in lines if line.strip())
# Output the lines without the indentation
for line in lines:
print line[indentation:]
print
def class_doc(cls, list_methods=True):
bases = ', '.join([b.__name__ for b in cls.__bases__])
print '###', cls.__name__
print
if bases != 'object':
print 'Extends', bases
print
docstring(cls)
for name, method in inspect.getmembers(cls, inspect.ismethod):
if name == '__init__':
# Initializer
print '####', get_method_sig(method).replace(name, cls.__name__)
elif name[0] == '_':
# Private method
continue
elif method.__self__ == cls:
# Class method
if not list_methods:
continue
print '#### %s.%s' % (cls.__name__, get_method_sig(method))
else:
# Regular method
if not list_methods:
continue
print '####', get_method_sig(method)
print
docstring(method)
print
def module_doc(classes, list_methods=True):
mdl = classes[0].__module__
print mdl
print '-' * len(mdl)
print
for cls in classes:
class_doc(cls, list_methods)
def all_subclasses(cls):
return cls.__subclasses__() + [g for s in cls.__subclasses__() for g in all_subclasses(s)]
if __name__ == '__main__':
from infi.clickhouse_orm import database
from infi.clickhouse_orm import fields
from infi.clickhouse_orm import engines
from infi.clickhouse_orm import models
from infi.clickhouse_orm import query
print 'Class Reference'
print '==============='
print
module_doc([database.Database, database.DatabaseException])
module_doc([models.Model, models.BufferModel])
module_doc([fields.Field] + all_subclasses(fields.Field), False)
module_doc([engines.Engine] + all_subclasses(engines.Engine), False)
module_doc([query.QuerySet])

17
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@ -0,0 +1,17 @@
generate_one() {
# Converts Markdown to HTML using Pandoc, and then extracts the header tags
pandoc "$1" | python "../scripts/html_to_markdown_toc.py" "$1" >> toc.md
}
printf "# Table of Contents\n\n" > toc.md
generate_one "index.md"
generate_one "models_and_databases.md"
generate_one "querysets.md"
generate_one "field_types.md"
generate_one "table_engines.md"
generate_one "schema_migrations.md"
generate_one "system_models.md"
generate_one "contributing.md"
generate_one "class_reference.md"

31
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@ -0,0 +1,31 @@
from HTMLParser import HTMLParser
import sys
HEADER_TAGS = ('h1', 'h2', 'h3')
class HeadersToMarkdownParser(HTMLParser):
inside = None
text = ''
def handle_starttag(self, tag, attrs):
if tag.lower() in HEADER_TAGS:
self.inside = tag
def handle_endtag(self, tag):
if tag.lower() in HEADER_TAGS:
indent = ' ' * int(self.inside[1])
fragment = self.text.lower().replace(' ', '-')
print '%s* [%s](%s#%s)' % (indent, self.text, sys.argv[1], fragment)
self.inside = None
self.text = ''
def handle_data(self, data):
if self.inside:
self.text += data
HeadersToMarkdownParser().feed(sys.stdin.read())
print

11
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@ -0,0 +1,11 @@
#!/bin/bash
cd /tmp
rm -rf /tmp/orm_env*
virtualenv -p python3 /tmp/orm_env
cd /tmp/orm_env
source bin/activate
pip install infi.projector
git clone https://github.com/Infinidat/infi.clickhouse_orm.git
cd infi.clickhouse_orm
projector devenv build
bin/nosetests

100
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View File

@ -16,39 +16,77 @@ Page = namedtuple('Page', 'objects number_of_objects pages_total number page_siz
class DatabaseException(Exception):
'''
Raised when a database operation fails.
'''
pass
class Database(object):
'''
Database instances connect to a specific ClickHouse database for running queries,
inserting data and other operations.
'''
def __init__(self, db_name, db_url='http://localhost:8123/', username=None, password=None, readonly=False):
'''
Initializes a database instance. Unless it's readonly, the database will be
created on the ClickHouse server if it does not already exist.
- `db_name`: name of the database to connect to.
- `db_url`: URL of the ClickHouse server.
- `username`: optional connection credentials.
- `password`: optional connection credentials.
- `readonly`: use a read-only connection.
'''
self.db_name = db_name
self.db_url = db_url
self.username = username
self.password = password
self.readonly = readonly
if not self.readonly:
self.readonly = False
if readonly:
self.connection_readonly = self._is_connection_readonly()
self.readonly = True
else:
self.create_database()
self.server_timezone = self._get_server_timezone()
def create_database(self):
'''
Creates the database on the ClickHouse server if it does not already exist.
'''
self._send('CREATE DATABASE IF NOT EXISTS `%s`' % self.db_name)
def drop_database(self):
'''
Deletes the database on the ClickHouse server.
'''
self._send('DROP DATABASE `%s`' % self.db_name)
def create_table(self, model_class):
'''
Creates a table for the given model class, if it does not exist already.
'''
# TODO check that model has an engine
if model_class.readonly:
raise DatabaseException("You can't create read only table")
self._send(model_class.create_table_sql(self.db_name))
def drop_table(self, model_class):
'''
Drops the database table of the given model class, if it exists.
'''
if model_class.readonly:
raise DatabaseException("You can't drop read only table")
self._send(model_class.drop_table_sql(self.db_name))
def insert(self, model_instances, batch_size=1000):
'''
Insert records into the database.
- `model_instances`: any iterable containing instances of a single model class.
- `batch_size`: number of records to send per chunk (use a lower number if your records are very large).
'''
from six import next
from io import BytesIO
i = iter(model_instances)
@ -86,6 +124,12 @@ class Database(object):
self._send(gen())
def count(self, model_class, conditions=None):
'''
Counts the number of records in the model's table.
- `model_class`: the model to count.
- `conditions`: optional SQL conditions (contents of the WHERE clause).
'''
query = 'SELECT count() FROM $table'
if conditions:
query += ' WHERE ' + conditions
@ -94,6 +138,14 @@ class Database(object):
return int(r.text) if r.text else 0
def select(self, query, model_class=None, settings=None):
'''
Performs a query and returns a generator of model instances.
- `query`: the SQL query to execute.
- `model_class`: the model class matching the query's table,
or `None` for getting back instances of an ad-hoc model.
- `settings`: query settings to send as HTTP GET parameters
'''
query += ' FORMAT TabSeparatedWithNamesAndTypes'
query = self._substitute(query, model_class)
r = self._send(query, settings, True)
@ -107,17 +159,31 @@ class Database(object):
yield model_class.from_tsv(line, field_names, self.server_timezone, self)
def raw(self, query, settings=None, stream=False):
"""
Performs raw query to database. Returns its output
:param query: Query to execute
:param settings: Query settings to send as query GET parameters
:param stream: If flag is true, Http response from ClickHouse will be streamed.
:return: Query execution result
"""
'''
Performs a query and returns its output as text.
- `query`: the SQL query to execute.
- `settings`: query settings to send as HTTP GET parameters
- `stream`: if true, the HTTP response from ClickHouse will be streamed.
'''
query = self._substitute(query, None)
return self._send(query, settings=settings, stream=stream).text
def paginate(self, model_class, order_by, page_num=1, page_size=100, conditions=None, settings=None):
'''
Selects records and returns a single page of model instances.
- `model_class`: the model class matching the query's table,
or `None` for getting back instances of an ad-hoc model.
- `order_by`: columns to use for sorting the query (contents of the ORDER BY clause).
- `page_num`: the page number (1-based), or -1 to get the last page.
- `page_size`: number of records to return per page.
- `conditions`: optional SQL conditions (contents of the WHERE clause).
- `settings`: query settings to send as HTTP GET parameters
The result is a namedtuple containing `objects` (list), `number_of_objects`,
`pages_total`, `number` (of the current page), and `page_size`.
'''
count = self.count(model_class, conditions)
pages_total = int(ceil(count / float(page_size)))
if page_num == -1:
@ -140,6 +206,13 @@ class Database(object):
)
def migrate(self, migrations_package_name, up_to=9999):
'''
Executes schema migrations.
- `migrations_package_name` - fully qualified name of the Python package
containing the migrations.
- `up_to` - number of the last migration to apply.
'''
from .migrations import MigrationHistory
logger = logging.getLogger('migrations')
applied_migrations = self._get_applied_migrations(migrations_package_name)
@ -161,7 +234,7 @@ class Database(object):
return set(obj.module_name for obj in self.select(query))
def _send(self, data, settings=None, stream=False):
if PY3 and isinstance(data, string_types):
if isinstance(data, string_types):
data = data.encode('utf-8')
params = self._build_params(settings)
r = requests.post(self.db_url, params=params, data=data, stream=stream)
@ -175,7 +248,8 @@ class Database(object):
params['user'] = self.username
if self.password:
params['password'] = self.password
if self.readonly:
# Send the readonly flag, unless the connection is already readonly (to prevent db error)
if self.readonly and not self.connection_readonly:
params['readonly'] = '1'
return params
@ -197,3 +271,7 @@ class Database(object):
except DatabaseException:
logger.exception('Cannot determine server timezone, assuming UTC')
return pytz.utc
def _is_connection_readonly(self):
r = self._send("SELECT value FROM system.settings WHERE name = 'readonly'")
return r.text.strip() != '0'

24
src/infi/clickhouse_orm/engines.py
View File

@ -5,6 +5,24 @@ class Engine(object):
raise NotImplementedError()
class TinyLog(Engine):
def create_table_sql(self):
return 'TinyLog'
class Log(Engine):
def create_table_sql(self):
return 'Log'
class Memory(Engine):
def create_table_sql(self):
return 'Memory'
class MergeTree(Engine):
def __init__(self, date_col, key_cols, sampling_expr=None,
@ -80,8 +98,10 @@ class ReplacingMergeTree(MergeTree):
class Buffer(Engine):
"""Here we define Buffer engine
Read more here https://clickhouse.yandex/reference_en.html#Buffer
"""
Buffers the data to write in RAM, periodically flushing it to another table.
Must be used in conjuction with a `BufferModel`.
Read more [here](https://clickhouse.yandex/reference_en.html#Buffer).
"""
#Buffer(database, table, num_layers, min_time, max_time, min_rows, max_rows, min_bytes, max_bytes)

32
src/infi/clickhouse_orm/fields.py
View File

@ -8,7 +8,9 @@ from .utils import escape, parse_array
class Field(object):
'''
Abstract base class for all field types.
'''
creation_counter = 0
class_default = 0
db_type = None
@ -90,6 +92,24 @@ class StringField(Field):
raise ValueError('Invalid value for %s: %r' % (self.__class__.__name__, value))
class FixedStringField(StringField):
def __init__(self, length, default=None, alias=None, materialized=None):
self._length = length
self.db_type = 'FixedString(%d)' % length
super(FixedStringField, self).__init__(default, alias, materialized)
def to_python(self, value, timezone_in_use):
value = super(FixedStringField, self).to_python(value, timezone_in_use)
return value.rstrip('\0')
def validate(self, value):
if isinstance(value, text_type):
value = value.encode('UTF-8')
if len(value) > self._length:
raise ValueError('Value of %d bytes is too long for FixedStringField(%d)' % (len(value), self._length))
class DateField(Field):
min_value = datetime.date(1970, 1, 1)
@ -147,7 +167,9 @@ class DateTimeField(Field):
class BaseIntField(Field):
'''
Abstract base class for all integer-type fields.
'''
def to_python(self, value, timezone_in_use):
try:
return int(value)
@ -220,6 +242,9 @@ class Int64Field(BaseIntField):
class BaseFloatField(Field):
'''
Abstract base class for all float-type fields.
'''
def to_python(self, value, timezone_in_use):
try:
@ -244,6 +269,9 @@ class Float64Field(BaseFloatField):
class BaseEnumField(Field):
'''
Abstract base class for all enum-type fields.
'''
def __init__(self, enum_cls, default=None, alias=None, materialized=None):
self.enum_cls = enum_cls

65
src/infi/clickhouse_orm/models.py
View File

@ -5,6 +5,7 @@ import pytz
from .fields import Field
from .utils import parse_tsv
from .query import QuerySet
logger = getLogger('clickhouse_orm')
@ -57,6 +58,10 @@ class ModelBase(type):
if db_type.startswith('Array'):
inner_field = cls.create_ad_hoc_field(db_type[6 : -1])
return orm_fields.ArrayField(inner_field)
# FixedString
if db_type.startswith('FixedString'):
length = int(db_type[12 : -1])
return orm_fields.FixedStringField(length)
# Simple fields
name = db_type + 'Field'
if not hasattr(orm_fields, name):
@ -66,7 +71,13 @@ class ModelBase(type):
class Model(with_metaclass(ModelBase)):
'''
A base class for ORM models.
A base class for ORM models. Each model class represent a ClickHouse table. For example:
class CPUStats(Model):
timestamp = DateTimeField()
cpu_id = UInt16Field()
cpu_percent = Float32Field()
engine = Memory()
'''
engine = None
@ -76,8 +87,8 @@ class Model(with_metaclass(ModelBase)):
'''
Creates a model instance, using keyword arguments as field values.
Since values are immediately converted to their Pythonic type,
invalid values will cause a ValueError to be raised.
Unrecognized field names will cause an AttributeError.
invalid values will cause a `ValueError` to be raised.
Unrecognized field names will cause an `AttributeError`.
'''
super(Model, self).__init__()
@ -98,7 +109,7 @@ class Model(with_metaclass(ModelBase)):
def __setattr__(self, name, value):
'''
When setting a field value, converts the value to its Pythonic type and validates it.
This may raise a ValueError.
This may raise a `ValueError`.
'''
field = self.get_field(name)
if field:
@ -107,26 +118,25 @@ class Model(with_metaclass(ModelBase)):
super(Model, self).__setattr__(name, value)
def set_database(self, db):
"""
Sets _database attribute for current model instance
:param db: Database instance
:return: None
"""
'''
Sets the `Database` that this model instance belongs to.
This is done automatically when the instance is read from the database or written to it.
'''
# This can not be imported globally due to circular import
from .database import Database
assert isinstance(db, Database), "database must be database.Database instance"
self._database = db
def get_database(self):
"""
Gets _database attribute for current model instance
:return: database.Database instance, model was inserted or selected from or None
"""
'''
Gets the `Database` that this model instance belongs to.
Returns `None` unless the instance was read from the database or written to it.
'''
return self._database
def get_field(self, name):
'''
Get a Field instance given its name, or None if not found.
Gets a `Field` instance given its name, or `None` if not found.
'''
field = getattr(self.__class__, name, None)
return field if isinstance(field, Field) else None
@ -134,7 +144,9 @@ class Model(with_metaclass(ModelBase)):
@classmethod
def table_name(cls):
'''
Returns the model's database table name.
Returns the model's database table name. By default this is the
class name converted to lowercase. Override this if you want to use
a different table name.
'''
return cls.__name__.lower()
@ -163,9 +175,13 @@ class Model(with_metaclass(ModelBase)):
def from_tsv(cls, line, field_names=None, timezone_in_use=pytz.utc, database=None):
'''
Create a model instance from a tab-separated line. The line may or may not include a newline.
The field_names list must match the fields defined in the model, but does not have to include all of them.
The `field_names` list must match the fields defined in the model, but does not have to include all of them.
If omitted, it is assumed to be the names of all fields in the model, in order of definition.
:param database: if given, model receives database
- `line`: the TSV-formatted data.
- `field_names`: names of the model fields in the data.
- `timezone_in_use`: the timezone to use when parsing dates and datetimes.
- `database`: if given, sets the database that this instance belongs to.
'''
from six import next
field_names = field_names or [name for name, field in cls._fields]
@ -184,7 +200,8 @@ class Model(with_metaclass(ModelBase)):
def to_tsv(self, include_readonly=True):
'''
Returns the instance's column values as a tab-separated line. A newline is not included.
:param bool include_readonly: If False, returns only fields, that can be inserted into database
- `include_readonly`: if false, returns only fields that can be inserted into database.
'''
data = self.__dict__
fields = self._fields if include_readonly else self._writable_fields
@ -193,8 +210,9 @@ class Model(with_metaclass(ModelBase)):
def to_dict(self, include_readonly=True, field_names=None):
'''
Returns the instance's column values as a dict.
:param bool include_readonly: If False, returns only fields, that can be inserted into database
:param field_names: An iterable of field names to return
- `include_readonly`: if false, returns only fields that can be inserted into database.
- `field_names`: an iterable of field names to return (optional)
'''
fields = self._fields if include_readonly else self._writable_fields
@ -204,6 +222,13 @@ class Model(with_metaclass(ModelBase)):
data = self.__dict__
return {name: data[name] for name, field in fields}
@classmethod
def objects_in(cls, database):
'''
Returns a `QuerySet` for selecting instances of this model class.
'''
return QuerySet(cls, database)
class BufferModel(Model):

256
src/infi/clickhouse_orm/query.py Normal file
View File

@ -0,0 +1,256 @@
import six
import pytz
from copy import copy
# TODO
# - and/or between Q objects
# - check that field names are valid
# - qs slicing
# - operators for arrays: length, has, empty
class Operator(object):
"""
Base class for filtering operators.
"""
def to_sql(self, model_cls, field_name, value):
"""
Subclasses should implement this method. It returns an SQL string
that applies this operator on the given field and value.
"""
raise NotImplementedError
class SimpleOperator(Operator):
"""
A simple binary operator such as a=b, a<b, a>b etc.
"""
def __init__(self, sql_operator):
self._sql_operator = sql_operator
def to_sql(self, model_cls, field_name, value):
field = getattr(model_cls, field_name)
value = field.to_db_string(field.to_python(value, pytz.utc))
return ' '.join([field_name, self._sql_operator, value])
class InOperator(Operator):
"""
An operator that implements IN.
Accepts 3 different types of values:
- a list or tuple of simple values
- a string (used verbatim as the contents of the parenthesis)
- a queryset (subquery)
"""
def to_sql(self, model_cls, field_name, value):
field = getattr(model_cls, field_name)
if isinstance(value, QuerySet):
value = value.as_sql()
elif isinstance(value, six.string_types):
pass
else:
value = ', '.join([field.to_db_string(field.to_python(v, pytz.utc)) for v in value])
return '%s IN (%s)' % (field_name, value)
class LikeOperator(Operator):
"""
A LIKE operator that matches the field to a given pattern. Can be
case sensitive or insensitive.
"""
def __init__(self, pattern, case_sensitive=True):
self._pattern = pattern
self._case_sensitive = case_sensitive
def to_sql(self, model_cls, field_name, value):
field = getattr(model_cls, field_name)
value = field.to_db_string(field.to_python(value, pytz.utc), quote=False)
value = value.replace('\\', '\\\\').replace('%', '\\\\%').replace('_', '\\\\_')
pattern = self._pattern.format(value)
if self._case_sensitive:
return '%s LIKE \'%s\'' % (field_name, pattern)
else:
return 'lowerUTF8(%s) LIKE lowerUTF8(\'%s\')' % (field_name, pattern)
class IExactOperator(Operator):
"""
An operator for case insensitive string comparison.
"""
def to_sql(self, model_cls, field_name, value):
field = getattr(model_cls, field_name)
value = field.to_db_string(field.to_python(value, pytz.utc))
return 'lowerUTF8(%s) = lowerUTF8(%s)' % (field_name, value)
# Define the set of builtin operators
_operators = {}
def register_operator(name, sql):
_operators[name] = sql
register_operator('eq', SimpleOperator('='))
register_operator('gt', SimpleOperator('>'))
register_operator('gte', SimpleOperator('>='))
register_operator('lt', SimpleOperator('<'))
register_operator('lte', SimpleOperator('<='))
register_operator('in', InOperator())
register_operator('contains', LikeOperator('%{}%'))
register_operator('startswith', LikeOperator('{}%'))
register_operator('endswith', LikeOperator('%{}'))
register_operator('icontains', LikeOperator('%{}%', False))
register_operator('istartswith', LikeOperator('{}%', False))
register_operator('iendswith', LikeOperator('%{}', False))
register_operator('iexact', IExactOperator())
class FOV(object):
"""
An object for storing Field + Operator + Value.
"""
def __init__(self, field_name, operator, value):
self._field_name = field_name
self._operator = _operators[operator]
self._value = value
def to_sql(self, model_cls):
return self._operator.to_sql(model_cls, self._field_name, self._value)
class Q(object):
def __init__(self, **kwargs):
self._fovs = [self._build_fov(k, v) for k, v in six.iteritems(kwargs)]
self._negate = False
def _build_fov(self, key, value):
if '__' in key:
field_name, operator = key.rsplit('__', 1)
else:
field_name, operator = key, 'eq'
return FOV(field_name, operator, value)
def to_sql(self, model_cls):
if not self._fovs:
return '1'
sql = ' AND '.join(fov.to_sql(model_cls) for fov in self._fovs)
if self._negate:
sql = 'NOT (%s)' % sql
return sql
def __invert__(self):
q = copy(self)
q._negate = True
return q
class QuerySet(object):
"""
A queryset is an object that represents a database query using a specific `Model`.
It is lazy, meaning that it does not hit the database until you iterate over its
matching rows (model instances).
"""
def __init__(self, model_cls, database):
"""
Initializer. It is possible to create a queryset like this, but the standard
way is to use `MyModel.objects_in(database)`.
"""
self._model_cls = model_cls
self._database = database
self._order_by = [f[0] for f in model_cls._fields]
self._q = []
self._fields = []
def __iter__(self):
"""
Iterates over the model instances matching this queryset
"""
return self._database.select(self.as_sql(), self._model_cls)
def __bool__(self):
"""
Returns true if this queryset matches any rows.
"""
return bool(self.count())
def __nonzero__(self): # Python 2 compatibility
return type(self).__bool__(self)
def __unicode__(self):
return self.as_sql()
def as_sql(self):
"""
Returns the whole query as a SQL string.
"""
fields = '*'
if self._fields:
fields = ', '.join('`%s`' % field for field in self._fields)
params = (fields, self._database.db_name, self._model_cls.table_name(), self.conditions_as_sql(), self.order_by_as_sql())
return u'SELECT %s\nFROM `%s`.`%s`\nWHERE %s\nORDER BY %s' % params
def order_by_as_sql(self):
"""
Returns the contents of the query's `ORDER BY` clause as a string.
"""
return u', '.join([
'%s DESC' % field[1:] if field[0] == '-' else field
for field in self._order_by
])
def conditions_as_sql(self):
"""
Returns the contents of the query's `WHERE` clause as a string.
"""
if self._q:
return u' AND '.join([q.to_sql(self._model_cls) for q in self._q])
else:
return u'1'
def count(self):
"""
Returns the number of matching model instances.
"""
return self._database.count(self._model_cls, self.conditions_as_sql())
def order_by(self, *field_names):
"""
Returns a new `QuerySet` instance with the ordering changed.
"""
qs = copy(self)
qs._order_by = field_names
return qs
def only(self, *field_names):
"""
Returns a new `QuerySet` instance limited to the specified field names.
Useful when there are large fields that are not needed,
or for creating a subquery to use with an IN operator.
"""
qs = copy(self)
qs._fields = field_names
return qs
def filter(self, **kwargs):
"""
Returns a new `QuerySet` instance that includes only rows matching the conditions.
"""
qs = copy(self)
qs._q = list(self._q) + [Q(**kwargs)]
return qs
def exclude(self, **kwargs):
"""
Returns a new `QuerySet` instance that excludes all rows matching the conditions.
"""
qs = copy(self)
qs._q = list(self._q) + [~Q(**kwargs)]
return qs

146
tests/base_test_with_data.py Normal file
View File

@ -0,0 +1,146 @@
# -*- coding: utf-8 -*-
import unittest
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 *
import logging
logging.getLogger("requests").setLevel(logging.WARNING)
class TestCaseWithData(unittest.TestCase):
def setUp(self):
self.database = Database('test-db')
self.database.create_table(Person)
def tearDown(self):
self.database.drop_table(Person)
self.database.drop_database()
def _insert_and_check(self, data, count):
self.database.insert(data)
self.assertEquals(count, self.database.count(Person))
for instance in data:
self.assertEquals(self.database, instance.get_database())
def _sample_data(self):
for entry in data:
yield Person(**entry)
class Person(Model):
first_name = StringField()
last_name = StringField()
birthday = DateField()
height = Float32Field()
engine = MergeTree('birthday', ('first_name', 'last_name', 'birthday'))
data = [
{"first_name": "Abdul", "last_name": "Hester", "birthday": "1970-12-02", "height": "1.63"},
{"first_name": "Adam", "last_name": "Goodman", "birthday": "1986-01-07", "height": "1.74"},
{"first_name": "Adena", "last_name": "Norman", "birthday": "1979-05-14", "height": "1.66"},
{"first_name": "Aline", "last_name": "Crane", "birthday": "1988-05-01", "height": "1.62"},
{"first_name": "Althea", "last_name": "Barrett", "birthday": "2004-07-28", "height": "1.71"},
{"first_name": "Amanda", "last_name": "Vang", "birthday": "1973-02-23", "height": "1.68"},
{"first_name": "Angela", "last_name": "Sanders", "birthday": "2016-01-08", "height": "1.66"},
{"first_name": "Anne", "last_name": "Rasmussen", "birthday": "1995-04-03", "height": "1.77"},
{"first_name": "Ariana", "last_name": "Cole", "birthday": "1977-12-20", "height": "1.72"},
{"first_name": "Ashton", "last_name": "Fuller", "birthday": "1995-11-17", "height": "1.75"},
{"first_name": "Ava", "last_name": "Sanders", "birthday": "1997-08-10", "height": "1.60"},
{"first_name": "Barrett", "last_name": "Clemons", "birthday": "1985-07-03", "height": "1.71"},
{"first_name": "Beatrice", "last_name": "Gregory", "birthday": "1992-01-19", "height": "1.80"},
{"first_name": "Buffy", "last_name": "Webb", "birthday": "1990-03-06", "height": "1.68"},
{"first_name": "Callie", "last_name": "Wiley", "birthday": "1987-11-24", "height": "1.69"},
{"first_name": "Cara", "last_name": "Fox", "birthday": "2004-05-15", "height": "1.71"},
{"first_name": "Caryn", "last_name": "Sears", "birthday": "1999-02-17", "height": "1.71"},
{"first_name": "Cassady", "last_name": "Knapp", "birthday": "1977-12-15", "height": "1.72"},
{"first_name": "Cassady", "last_name": "Rogers", "birthday": "2013-11-04", "height": "1.71"},
{"first_name": "Catherine", "last_name": "Hicks", "birthday": "1989-05-23", "height": "1.80"},
{"first_name": "Cathleen", "last_name": "Frank", "birthday": "1977-09-04", "height": "1.61"},
{"first_name": "Celeste", "last_name": "James", "birthday": "1990-03-08", "height": "1.67"},
{"first_name": "Chelsea", "last_name": "Castro", "birthday": "2001-08-10", "height": "1.71"},
{"first_name": "Ciaran", "last_name": "Carver", "birthday": "2016-12-25", "height": "1.76"},
{"first_name": "Ciaran", "last_name": "Hurley", "birthday": "1995-10-25", "height": "1.65"},
{"first_name": "Clementine", "last_name": "Moon", "birthday": "1994-03-29", "height": "1.73"},
{"first_name": "Connor", "last_name": "Jenkins", "birthday": "1999-07-23", "height": "1.67"},
{"first_name": "Courtney", "last_name": "Cannon", "birthday": "1997-10-26", "height": "1.76"},
{"first_name": "Courtney", "last_name": "Hoffman", "birthday": "1994-11-07", "height": "1.65"},
{"first_name": "Denton", "last_name": "Sanchez", "birthday": "1971-10-16", "height": "1.72"},
{"first_name": "Dominique", "last_name": "Sandoval", "birthday": "1972-02-01", "height": "1.72"},
{"first_name": "Dora", "last_name": "Cabrera", "birthday": "2016-04-26", "height": "1.68"},
{"first_name": "Eagan", "last_name": "Dodson", "birthday": "2015-10-22", "height": "1.67"},
{"first_name": "Edan", "last_name": "Dennis", "birthday": "1989-09-18", "height": "1.73"},
{"first_name": "Ella", "last_name": "Castillo", "birthday": "1973-03-28", "height": "1.73"},
{"first_name": "Elton", "last_name": "Ayers", "birthday": "1994-06-20", "height": "1.68"},
{"first_name": "Elton", "last_name": "Smith", "birthday": "1982-06-20", "height": "1.66"},
{"first_name": "Emma", "last_name": "Clements", "birthday": "1996-08-07", "height": "1.75"},
{"first_name": "Evangeline", "last_name": "Weber", "birthday": "1984-06-03", "height": "1.70"},
{"first_name": "Faith", "last_name": "Emerson", "birthday": "1989-12-30", "height": "1.62"},
{"first_name": "Fritz", "last_name": "Atkinson", "birthday": "2011-06-15", "height": "1.73"},
{"first_name": "Galvin", "last_name": "Phillips", "birthday": "2004-01-17", "height": "1.74"},
{"first_name": "Georgia", "last_name": "Kennedy", "birthday": "1974-12-29", "height": "1.66"},
{"first_name": "Griffith", "last_name": "Henry", "birthday": "1985-04-02", "height": "1.66"},
{"first_name": "Hedy", "last_name": "Strong", "birthday": "2001-10-04", "height": "1.60"},
{"first_name": "Hu", "last_name": "May", "birthday": "1976-10-01", "height": "1.76"},
{"first_name": "Hyacinth", "last_name": "Kent", "birthday": "1971-07-18", "height": "1.72"},
{"first_name": "Idola", "last_name": "Fulton", "birthday": "1974-11-27", "height": "1.66"},
{"first_name": "Jarrod", "last_name": "Gibbs", "birthday": "1987-06-13", "height": "1.62"},
{"first_name": "Jesse", "last_name": "Gomez", "birthday": "2011-01-28", "height": "1.71"},
{"first_name": "Josiah", "last_name": "Hodges", "birthday": "2011-09-04", "height": "1.68"},
{"first_name": "Karleigh", "last_name": "Bartlett", "birthday": "1991-10-24", "height": "1.69"},
{"first_name": "Keelie", "last_name": "Mathis", "birthday": "1993-10-26", "height": "1.69"},
{"first_name": "Kieran", "last_name": "Solomon", "birthday": "1993-10-30", "height": "1.69"},
{"first_name": "Laith", "last_name": "Howell", "birthday": "1991-07-07", "height": "1.70"},
{"first_name": "Leroy", "last_name": "Pacheco", "birthday": "1998-12-30", "height": "1.70"},
{"first_name": "Lesley", "last_name": "Stephenson", "birthday": "2010-04-10", "height": "1.64"},
{"first_name": "Macaulay", "last_name": "Rowe", "birthday": "1982-03-02", "height": "1.68"},
{"first_name": "Macey", "last_name": "Griffin", "birthday": "1971-09-18", "height": "1.63"},
{"first_name": "Madeline", "last_name": "Kidd", "birthday": "1984-12-09", "height": "1.69"},
{"first_name": "Maia", "last_name": "Hyde", "birthday": "1972-06-09", "height": "1.74"},
{"first_name": "Mary", "last_name": "Kirkland", "birthday": "1987-10-09", "height": "1.73"},
{"first_name": "Molly", "last_name": "Salas", "birthday": "1994-04-23", "height": "1.70"},
{"first_name": "Montana", "last_name": "Bruce", "birthday": "1982-06-28", "height": "1.66"},
{"first_name": "Naomi", "last_name": "Hays", "birthday": "2004-11-27", "height": "1.70"},
{"first_name": "Norman", "last_name": "Santos", "birthday": "1989-01-10", "height": "1.68"},
{"first_name": "Octavius", "last_name": "Floyd", "birthday": "1985-02-22", "height": "1.68"},
{"first_name": "Odette", "last_name": "Mcneil", "birthday": "1978-05-21", "height": "1.76"},
{"first_name": "Oliver", "last_name": "Ashley", "birthday": "2004-08-13", "height": "1.68"},
{"first_name": "Quon", "last_name": "Wiggins", "birthday": "1992-05-06", "height": "1.74"},
{"first_name": "Rafael", "last_name": "Parker", "birthday": "2016-01-24", "height": "1.76"},
{"first_name": "Reese", "last_name": "Noel", "birthday": "1996-11-04", "height": "1.77"},
{"first_name": "Rhona", "last_name": "Camacho", "birthday": "1976-12-17", "height": "1.59"},
{"first_name": "Rigel", "last_name": "Oneal", "birthday": "1993-11-05", "height": "1.63"},
{"first_name": "Roary", "last_name": "Simmons", "birthday": "1986-07-23", "height": "1.63"},
{"first_name": "Russell", "last_name": "Pruitt", "birthday": "1979-05-04", "height": "1.63"},
{"first_name": "Sawyer", "last_name": "Fischer", "birthday": "1995-04-01", "height": "1.78"},
{"first_name": "Scarlett", "last_name": "Durham", "birthday": "2005-09-29", "height": "1.65"},
{"first_name": "Seth", "last_name": "Serrano", "birthday": "2017-06-02", "height": "1.71"},
{"first_name": "Shad", "last_name": "Bradshaw", "birthday": "1998-08-25", "height": "1.72"},
{"first_name": "Shana", "last_name": "Jarvis", "birthday": "1997-05-21", "height": "1.72"},
{"first_name": "Sharon", "last_name": "Shelton", "birthday": "1970-05-02", "height": "1.65"},
{"first_name": "Shoshana", "last_name": "Solis", "birthday": "1998-07-18", "height": "1.65"},
{"first_name": "Stephen", "last_name": "Baxter", "birthday": "2004-09-24", "height": "1.74"},
{"first_name": "Sydney", "last_name": "Stevens", "birthday": "1989-07-11", "height": "1.70"},
{"first_name": "Tasha", "last_name": "Campos", "birthday": "1984-02-11", "height": "1.72"},
{"first_name": "Ulla", "last_name": "Arnold", "birthday": "1990-06-04", "height": "1.63"},
{"first_name": "Vaughan", "last_name": "Schmidt", "birthday": "1985-06-19", "height": "1.61"},
{"first_name": "Velma", "last_name": "English", "birthday": "1999-01-18", "height": "1.65"},
{"first_name": "Venus", "last_name": "Hurst", "birthday": "1993-10-22", "height": "1.72"},
{"first_name": "Victor", "last_name": "Woods", "birthday": "1989-06-23", "height": "1.67"},
{"first_name": "Victoria", "last_name": "Slater", "birthday": "2009-07-19", "height": "1.72"},
{"first_name": "Wang", "last_name": "Goodwin", "birthday": "1983-05-15", "height": "1.66"},
{"first_name": "Warren", "last_name": "Bowen", "birthday": "2000-07-20", "height": "1.76"},
{"first_name": "Warren", "last_name": "Dudley", "birthday": "1995-10-23", "height": "1.59"},
{"first_name": "Whilemina", "last_name": "Blankenship", "birthday": "1970-07-14", "height": "1.66"},
{"first_name": "Whitney", "last_name": "Durham", "birthday": "1977-09-15", "height": "1.72"},
{"first_name": "Whitney", "last_name": "Scott", "birthday": "1971-07-04", "height": "1.70"},
{"first_name": "Wynter", "last_name": "Garcia", "birthday": "1975-01-10", "height": "1.69"},
{"first_name": "Yolanda", "last_name": "Duke", "birthday": "1997-02-25", "height": "1.74"}
];

29
tests/test_buffer.py Normal file
View File

@ -0,0 +1,29 @@
# -*- coding: utf-8 -*-
import unittest
from infi.clickhouse_orm.models import BufferModel
from infi.clickhouse_orm.engines import *
from .base_test_with_data import *
class BufferTestCase(TestCaseWithData):
def _insert_and_check_buffer(self, data, count):
self.database.insert(data)
self.assertEquals(count, self.database.count(PersonBuffer))
def _sample_buffer_data(self):
for entry in data:
yield PersonBuffer(**entry)
def test_insert_buffer(self):
self.database.create_table(PersonBuffer)
self._insert_and_check_buffer(self._sample_buffer_data(), len(data))
class PersonBuffer(BufferModel, Person):
engine = Buffer(Person)

197
tests/test_database.py
View File

@ -3,35 +3,10 @@
import unittest
from infi.clickhouse_orm.database import Database, DatabaseException
from infi.clickhouse_orm.models import Model, BufferModel
from infi.clickhouse_orm.fields import *
from infi.clickhouse_orm.engines import *
import logging
logging.getLogger("requests").setLevel(logging.WARNING)
from .base_test_with_data import *
class DatabaseTestCase(unittest.TestCase):
def setUp(self):
self.database = Database('test-db')
self.database.create_table(Person)
self.database.create_table(PersonBuffer)
def tearDown(self):
self.database.drop_table(PersonBuffer)
self.database.drop_table(Person)
self.database.drop_database()
def _insert_and_check(self, data, count):
self.database.insert(data)
self.assertEquals(count, self.database.count(Person))
for instance in data:
self.assertEquals(self.database, instance.get_database())
def _insert_and_check_buffer(self, data, count):
self.database.insert(data)
self.assertEquals(count, self.database.count(PersonBuffer))
class DatabaseTestCase(TestCaseWithData):
def test_insert__generator(self):
self._insert_and_check(self._sample_data(), len(data))
@ -133,6 +108,11 @@ class DatabaseTestCase(unittest.TestCase):
with self.assertRaises(ValueError):
self.database.paginate(Person, 'first_name, last_name', page_num, 100)
def test_pagination_with_conditions(self):
self._insert_and_check(self._sample_data(), len(data))
page = self.database.paginate(Person, 'first_name, last_name', 1, 100, conditions="first_name < 'Ava'")
self.assertEquals(page.number_of_objects, 10)
def test_special_chars(self):
s = u'אבגד \\\'"`,.;éåäöšž\n\t\0\b\r'
p = Person(first_name=s)
@ -140,171 +120,12 @@ class DatabaseTestCase(unittest.TestCase):
p = list(self.database.select("SELECT * from $table", Person))[0]
self.assertEquals(p.first_name, s)
def test_readonly(self):
orig_database = self.database
self.database = Database(orig_database.db_name, readonly=True)
with self.assertRaises(DatabaseException):
self._insert_and_check(self._sample_data(), len(data))
self.assertEquals(self.database.count(Person), 0)
with self.assertRaises(DatabaseException):
self.database.drop_table(Person)
with self.assertRaises(DatabaseException):
self.database.drop_database()
self.database = orig_database
def test_insert_buffer(self):
self._insert_and_check_buffer(self._sample_buffer_data(), len(data))
def _sample_data(self):
for entry in data:
yield Person(**entry)
def test_raw(self):
self._insert_and_check(self._sample_data(), len(data))
query = "SELECT * FROM `test-db`.person WHERE first_name = 'Whitney' ORDER BY last_name"
results = self.database.raw(query)
self.assertEqual(results, "Whitney\tDurham\t1977-09-15\t1.72\nWhitney\tScott\t1971-07-04\t1.7\n")
def test_insert_readonly(self):
m = ReadOnlyModel(name='readonly')
def test_invalid_user(self):
with self.assertRaises(DatabaseException):
self.database.insert([m])
def test_create_readonly_table(self):
with self.assertRaises(DatabaseException):
self.database.create_table(ReadOnlyModel)
def test_drop_readonly_table(self):
with self.assertRaises(DatabaseException):
self.database.drop_table(ReadOnlyModel)
def _sample_buffer_data(self):
for entry in data:
yield PersonBuffer(**entry)
class Person(Model):
first_name = StringField()
last_name = StringField()
birthday = DateField()
height = Float32Field()
engine = MergeTree('birthday', ('first_name', 'last_name', 'birthday'))
class ReadOnlyModel(Model):
readonly = True
name = StringField()
class PersonBuffer(BufferModel, Person):
engine = Buffer(Person)
data = [
{"first_name": "Abdul", "last_name": "Hester", "birthday": "1970-12-02", "height": "1.63"},
{"first_name": "Adam", "last_name": "Goodman", "birthday": "1986-01-07", "height": "1.74"},
{"first_name": "Adena", "last_name": "Norman", "birthday": "1979-05-14", "height": "1.66"},
{"first_name": "Aline", "last_name": "Crane", "birthday": "1988-05-01", "height": "1.62"},
{"first_name": "Althea", "last_name": "Barrett", "birthday": "2004-07-28", "height": "1.71"},
{"first_name": "Amanda", "last_name": "Vang", "birthday": "1973-02-23", "height": "1.68"},
{"first_name": "Angela", "last_name": "Sanders", "birthday": "2016-01-08", "height": "1.66"},
{"first_name": "Anne", "last_name": "Rasmussen", "birthday": "1995-04-03", "height": "1.77"},
{"first_name": "Ariana", "last_name": "Cole", "birthday": "1977-12-20", "height": "1.72"},
{"first_name": "Ashton", "last_name": "Fuller", "birthday": "1995-11-17", "height": "1.75"},
{"first_name": "Ava", "last_name": "Sanders", "birthday": "1997-08-10", "height": "1.60"},
{"first_name": "Barrett", "last_name": "Clemons", "birthday": "1985-07-03", "height": "1.71"},
{"first_name": "Beatrice", "last_name": "Gregory", "birthday": "1992-01-19", "height": "1.80"},
{"first_name": "Buffy", "last_name": "Webb", "birthday": "1990-03-06", "height": "1.68"},
{"first_name": "Callie", "last_name": "Wiley", "birthday": "1987-11-24", "height": "1.69"},
{"first_name": "Cara", "last_name": "Fox", "birthday": "2004-05-15", "height": "1.71"},
{"first_name": "Caryn", "last_name": "Sears", "birthday": "1999-02-17", "height": "1.71"},
{"first_name": "Cassady", "last_name": "Knapp", "birthday": "1977-12-15", "height": "1.72"},
{"first_name": "Cassady", "last_name": "Rogers", "birthday": "2013-11-04", "height": "1.71"},
{"first_name": "Catherine", "last_name": "Hicks", "birthday": "1989-05-23", "height": "1.80"},
{"first_name": "Cathleen", "last_name": "Frank", "birthday": "1977-09-04", "height": "1.61"},
{"first_name": "Celeste", "last_name": "James", "birthday": "1990-03-08", "height": "1.67"},
{"first_name": "Chelsea", "last_name": "Castro", "birthday": "2001-08-10", "height": "1.71"},
{"first_name": "Ciaran", "last_name": "Carver", "birthday": "2016-12-25", "height": "1.76"},
{"first_name": "Ciaran", "last_name": "Hurley", "birthday": "1995-10-25", "height": "1.65"},
{"first_name": "Clementine", "last_name": "Moon", "birthday": "1994-03-29", "height": "1.73"},
{"first_name": "Connor", "last_name": "Jenkins", "birthday": "1999-07-23", "height": "1.67"},
{"first_name": "Courtney", "last_name": "Cannon", "birthday": "1997-10-26", "height": "1.76"},
{"first_name": "Courtney", "last_name": "Hoffman", "birthday": "1994-11-07", "height": "1.65"},
{"first_name": "Denton", "last_name": "Sanchez", "birthday": "1971-10-16", "height": "1.72"},
{"first_name": "Dominique", "last_name": "Sandoval", "birthday": "1972-02-01", "height": "1.72"},
{"first_name": "Dora", "last_name": "Cabrera", "birthday": "2016-04-26", "height": "1.68"},
{"first_name": "Eagan", "last_name": "Dodson", "birthday": "2015-10-22", "height": "1.67"},
{"first_name": "Edan", "last_name": "Dennis", "birthday": "1989-09-18", "height": "1.73"},
{"first_name": "Ella", "last_name": "Castillo", "birthday": "1973-03-28", "height": "1.73"},
{"first_name": "Elton", "last_name": "Ayers", "birthday": "1994-06-20", "height": "1.68"},
{"first_name": "Elton", "last_name": "Smith", "birthday": "1982-06-20", "height": "1.66"},
{"first_name": "Emma", "last_name": "Clements", "birthday": "1996-08-07", "height": "1.75"},
{"first_name": "Evangeline", "last_name": "Weber", "birthday": "1984-06-03", "height": "1.70"},
{"first_name": "Faith", "last_name": "Emerson", "birthday": "1989-12-30", "height": "1.62"},
{"first_name": "Fritz", "last_name": "Atkinson", "birthday": "2011-06-15", "height": "1.73"},
{"first_name": "Galvin", "last_name": "Phillips", "birthday": "2004-01-17", "height": "1.74"},
{"first_name": "Georgia", "last_name": "Kennedy", "birthday": "1974-12-29", "height": "1.66"},
{"first_name": "Griffith", "last_name": "Henry", "birthday": "1985-04-02", "height": "1.66"},
{"first_name": "Hedy", "last_name": "Strong", "birthday": "2001-10-04", "height": "1.60"},
{"first_name": "Hu", "last_name": "May", "birthday": "1976-10-01", "height": "1.76"},
{"first_name": "Hyacinth", "last_name": "Kent", "birthday": "1971-07-18", "height": "1.72"},
{"first_name": "Idola", "last_name": "Fulton", "birthday": "1974-11-27", "height": "1.66"},
{"first_name": "Jarrod", "last_name": "Gibbs", "birthday": "1987-06-13", "height": "1.62"},
{"first_name": "Jesse", "last_name": "Gomez", "birthday": "2011-01-28", "height": "1.71"},
{"first_name": "Josiah", "last_name": "Hodges", "birthday": "2011-09-04", "height": "1.68"},
{"first_name": "Karleigh", "last_name": "Bartlett", "birthday": "1991-10-24", "height": "1.69"},
{"first_name": "Keelie", "last_name": "Mathis", "birthday": "1993-10-26", "height": "1.69"},
{"first_name": "Kieran", "last_name": "Solomon", "birthday": "1993-10-30", "height": "1.69"},
{"first_name": "Laith", "last_name": "Howell", "birthday": "1991-07-07", "height": "1.70"},
{"first_name": "Leroy", "last_name": "Pacheco", "birthday": "1998-12-30", "height": "1.70"},
{"first_name": "Lesley", "last_name": "Stephenson", "birthday": "2010-04-10", "height": "1.64"},
{"first_name": "Macaulay", "last_name": "Rowe", "birthday": "1982-03-02", "height": "1.68"},
{"first_name": "Macey", "last_name": "Griffin", "birthday": "1971-09-18", "height": "1.63"},
{"first_name": "Madeline", "last_name": "Kidd", "birthday": "1984-12-09", "height": "1.69"},
{"first_name": "Maia", "last_name": "Hyde", "birthday": "1972-06-09", "height": "1.74"},
{"first_name": "Mary", "last_name": "Kirkland", "birthday": "1987-10-09", "height": "1.73"},
{"first_name": "Molly", "last_name": "Salas", "birthday": "1994-04-23", "height": "1.70"},
{"first_name": "Montana", "last_name": "Bruce", "birthday": "1982-06-28", "height": "1.66"},
{"first_name": "Naomi", "last_name": "Hays", "birthday": "2004-11-27", "height": "1.70"},
{"first_name": "Norman", "last_name": "Santos", "birthday": "1989-01-10", "height": "1.68"},
{"first_name": "Octavius", "last_name": "Floyd", "birthday": "1985-02-22", "height": "1.68"},
{"first_name": "Odette", "last_name": "Mcneil", "birthday": "1978-05-21", "height": "1.76"},
{"first_name": "Oliver", "last_name": "Ashley", "birthday": "2004-08-13", "height": "1.68"},
{"first_name": "Quon", "last_name": "Wiggins", "birthday": "1992-05-06", "height": "1.74"},
{"first_name": "Rafael", "last_name": "Parker", "birthday": "2016-01-24", "height": "1.76"},
{"first_name": "Reese", "last_name": "Noel", "birthday": "1996-11-04", "height": "1.77"},
{"first_name": "Rhona", "last_name": "Camacho", "birthday": "1976-12-17", "height": "1.59"},
{"first_name": "Rigel", "last_name": "Oneal", "birthday": "1993-11-05", "height": "1.63"},
{"first_name": "Roary", "last_name": "Simmons", "birthday": "1986-07-23", "height": "1.63"},
{"first_name": "Russell", "last_name": "Pruitt", "birthday": "1979-05-04", "height": "1.63"},
{"first_name": "Sawyer", "last_name": "Fischer", "birthday": "1995-04-01", "height": "1.78"},
{"first_name": "Scarlett", "last_name": "Durham", "birthday": "2005-09-29", "height": "1.65"},
{"first_name": "Seth", "last_name": "Serrano", "birthday": "2017-06-02", "height": "1.71"},
{"first_name": "Shad", "last_name": "Bradshaw", "birthday": "1998-08-25", "height": "1.72"},
{"first_name": "Shana", "last_name": "Jarvis", "birthday": "1997-05-21", "height": "1.72"},
{"first_name": "Sharon", "last_name": "Shelton", "birthday": "1970-05-02", "height": "1.65"},
{"first_name": "Shoshana", "last_name": "Solis", "birthday": "1998-07-18", "height": "1.65"},
{"first_name": "Stephen", "last_name": "Baxter", "birthday": "2004-09-24", "height": "1.74"},
{"first_name": "Sydney", "last_name": "Stevens", "birthday": "1989-07-11", "height": "1.70"},
{"first_name": "Tasha", "last_name": "Campos", "birthday": "1984-02-11", "height": "1.72"},
{"first_name": "Ulla", "last_name": "Arnold", "birthday": "1990-06-04", "height": "1.63"},
{"first_name": "Vaughan", "last_name": "Schmidt", "birthday": "1985-06-19", "height": "1.61"},
{"first_name": "Velma", "last_name": "English", "birthday": "1999-01-18", "height": "1.65"},
{"first_name": "Venus", "last_name": "Hurst", "birthday": "1993-10-22", "height": "1.72"},
{"first_name": "Victor", "last_name": "Woods", "birthday": "1989-06-23", "height": "1.67"},
{"first_name": "Victoria", "last_name": "Slater", "birthday": "2009-07-19", "height": "1.72"},
{"first_name": "Wang", "last_name": "Goodwin", "birthday": "1983-05-15", "height": "1.66"},
{"first_name": "Warren", "last_name": "Bowen", "birthday": "2000-07-20", "height": "1.76"},
{"first_name": "Warren", "last_name": "Dudley", "birthday": "1995-10-23", "height": "1.59"},
{"first_name": "Whilemina", "last_name": "Blankenship", "birthday": "1970-07-14", "height": "1.66"},
{"first_name": "Whitney", "last_name": "Durham", "birthday": "1977-09-15", "height": "1.72"},
{"first_name": "Whitney", "last_name": "Scott", "birthday": "1971-07-04", "height": "1.70"},
{"first_name": "Wynter", "last_name": "Garcia", "birthday": "1975-01-10", "height": "1.69"},
{"first_name": "Yolanda", "last_name": "Duke", "birthday": "1997-02-25", "height": "1.74"}
];
Database(self.database.db_name, username='default', password='wrong')

20
tests/test_engines.py
View File

@ -38,6 +38,11 @@ class EnginesTestCase(unittest.TestCase):
engine = MergeTree('date', ('date', 'event_id', 'event_group'), index_granularity=4096)
self._create_and_insert(TestModel)
def test_replicated_merge_tree(self):
engine = MergeTree('date', ('date', 'event_id', 'event_group'), replica_table_path='/clickhouse/tables/{layer}-{shard}/hits', replica_name='{replica}')
expected = "ReplicatedMergeTree('/clickhouse/tables/{layer}-{shard}/hits', '{replica}', date, (date, event_id, event_group), 8192)"
self.assertEquals(engine.create_table_sql(), expected)
def test_collapsing_merge_tree(self):
class TestModel(SampleModel):
engine = CollapsingMergeTree('date', ('date', 'event_id', 'event_group'), 'event_version')
@ -53,6 +58,21 @@ class EnginesTestCase(unittest.TestCase):
engine = ReplacingMergeTree('date', ('date', 'event_id', 'event_group'), 'event_uversion')
self._create_and_insert(TestModel)
def test_tiny_log(self):
class TestModel(SampleModel):
engine = TinyLog()
self._create_and_insert(TestModel)
def test_log(self):
class TestModel(SampleModel):
engine = Log()
self._create_and_insert(TestModel)
def test_memory(self):
class TestModel(SampleModel):
engine = Memory()
self._create_and_insert(TestModel)
class SampleModel(Model):

58
tests/test_fixed_string_fields.py Normal file
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@ -0,0 +1,58 @@
# -*- coding: utf-8 -*-
import unittest
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 *
class FixedStringFieldsTest(unittest.TestCase):
def setUp(self):
self.database = Database('test-db')
self.database.create_table(FixedStringModel)
def tearDown(self):
self.database.drop_database()
def _insert_sample_data(self):
self.database.insert([
FixedStringModel(date_field='2016-08-30', fstr_field=''),
FixedStringModel(date_field='2016-08-30'),
FixedStringModel(date_field='2016-08-31', fstr_field='foo'),
FixedStringModel(date_field='2016-08-31', fstr_field=u'לילה')
])
def _assert_sample_data(self, results):
self.assertEquals(len(results), 4)
self.assertEquals(results[0].fstr_field, '')
self.assertEquals(results[1].fstr_field, 'ABCDEFGHIJK')
self.assertEquals(results[2].fstr_field, 'foo')
self.assertEquals(results[3].fstr_field, u'לילה')
def test_insert_and_select(self):
self._insert_sample_data()
query = 'SELECT * from $table ORDER BY date_field'
results = list(self.database.select(query, FixedStringModel))
self._assert_sample_data(results)
def test_ad_hoc_model(self):
self._insert_sample_data()
query = 'SELECT * from $db.fixedstringmodel ORDER BY date_field'
results = list(self.database.select(query))
self._assert_sample_data(results)
def test_assignment_error(self):
for value in (17, 'this is too long', u'זה ארוך', None, 99.9):
with self.assertRaises(ValueError):
FixedStringModel(fstr_field=value)
class FixedStringModel(Model):
date_field = DateField()
fstr_field = FixedStringField(12, default='ABCDEFGHIJK')
engine = MergeTree('date_field', ('date_field',))

144
tests/test_querysets.py Normal file
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# -*- coding: utf-8 -*-
import unittest
from infi.clickhouse_orm.database import Database
from .base_test_with_data import *
import logging
from datetime import date, datetime
try:
Enum # exists in Python 3.4+
except NameError:
from enum import Enum # use the enum34 library instead
class QuerySetTestCase(TestCaseWithData):
def setUp(self):
super(QuerySetTestCase, self).setUp()
self.database.insert(self._sample_data())
def _test_qs(self, qs, expected_count):
logging.info(qs.as_sql())
for instance in qs:
logging.info('\t%s' % instance.to_dict())
self.assertEquals(qs.count(), expected_count)
def test_no_filtering(self):
qs = Person.objects_in(self.database)
self._test_qs(qs, len(data))
def test_truthiness(self):
qs = Person.objects_in(self.database)
self.assertTrue(qs.filter(first_name='Connor'))
self.assertFalse(qs.filter(first_name='Willy'))
def test_filter_string_field(self):
qs = Person.objects_in(self.database)
self._test_qs(qs.filter(first_name='Ciaran'), 2)
self._test_qs(qs.filter(first_name='ciaran'), 0) # case sensitive
self._test_qs(qs.filter(first_name__iexact='ciaran'), 2) # case insensitive
self._test_qs(qs.filter(first_name__gt='Whilemina'), 4)
self._test_qs(qs.filter(first_name__gte='Whilemina'), 5)
self._test_qs(qs.filter(first_name__lt='Adam'), 1)
self._test_qs(qs.filter(first_name__lte='Adam'), 2)
self._test_qs(qs.filter(first_name__in=('Connor', 'Courtney')), 3) # in tuple
self._test_qs(qs.filter(first_name__in=['Connor', 'Courtney']), 3) # in list
self._test_qs(qs.filter(first_name__in="'Connor', 'Courtney'"), 3) # in string
self._test_qs(qs.filter(first_name__contains='sh'), 3) # case sensitive
self._test_qs(qs.filter(first_name__icontains='sh'), 6) # case insensitive
self._test_qs(qs.filter(first_name__startswith='le'), 0) # case sensitive
self._test_qs(qs.filter(first_name__istartswith='Le'), 2) # case insensitive
self._test_qs(qs.filter(first_name__istartswith=''), 100) # empty prefix
self._test_qs(qs.filter(first_name__endswith='IA'), 0) # case sensitive
self._test_qs(qs.filter(first_name__iendswith='ia'), 3) # case insensitive
self._test_qs(qs.filter(first_name__iendswith=''), 100) # empty suffix
def test_filter_unicode_string(self):
self.database.insert([
Person(first_name=u'דונלד', last_name=u'דאק')
])
qs = Person.objects_in(self.database)
self._test_qs(qs.filter(first_name=u'דונלד'), 1)
def test_filter_float_field(self):
qs = Person.objects_in(self.database)
self._test_qs(qs.filter(height__gt=2), 0)
self._test_qs(qs.filter(height__lt=1.61), 4)
self._test_qs(qs.filter(height__lt='1.61'), 4)
self._test_qs(qs.exclude(height__lt='1.61'), 96)
self._test_qs(qs.filter(height__gt=0), 100)
self._test_qs(qs.exclude(height__gt=0), 0)
def test_filter_date_field(self):
qs = Person.objects_in(self.database)
self._test_qs(qs.filter(birthday='1970-12-02'), 1)
self._test_qs(qs.filter(birthday=date(1970, 12, 2)), 1)
self._test_qs(qs.filter(birthday__lte=date(1970, 12, 2)), 3)
def test_only(self):
qs = Person.objects_in(self.database).only('first_name', 'last_name')
for person in qs:
self.assertTrue(person.first_name)
self.assertTrue(person.last_name)
self.assertFalse(person.height)
self.assertEquals(person.birthday, date(1970, 1, 1))
def test_order_by(self):
qs = Person.objects_in(self.database)
person = list(qs.order_by('first_name', 'last_name'))[0]
self.assertEquals(person.first_name, 'Abdul')
person = list(qs.order_by('-first_name', '-last_name'))[0]
self.assertEquals(person.first_name, 'Yolanda')
person = list(qs.order_by('height'))[0]
self.assertEquals(person.height, 1.59)
person = list(qs.order_by('-height'))[0]
self.assertEquals(person.height, 1.8)
def test_in_subquery(self):
qs = Person.objects_in(self.database)
self._test_qs(qs.filter(height__in='SELECT max(height) FROM $table'), 2)
self._test_qs(qs.filter(first_name__in=qs.only('last_name')), 2)
def _insert_sample_model(self):
self.database.create_table(SampleModel)
now = datetime.now()
self.database.insert([
SampleModel(timestamp=now, num=1, color=Color.red),
SampleModel(timestamp=now, num=2, color=Color.red),
SampleModel(timestamp=now, num=3, color=Color.blue),
SampleModel(timestamp=now, num=4, color=Color.white),
])
def test_filter_enum_field(self):
self._insert_sample_model()
qs = SampleModel.objects_in(self.database)
self._test_qs(qs.filter(color=Color.red), 2)
self._test_qs(qs.exclude(color=Color.white), 3)
# Different ways to specify blue
self._test_qs(qs.filter(color__gt=Color.blue), 1)
self._test_qs(qs.filter(color__gt='blue'), 1)
self._test_qs(qs.filter(color__gt=2), 1)
def test_filter_int_field(self):
self._insert_sample_model()
qs = SampleModel.objects_in(self.database)
self._test_qs(qs.filter(num=1), 1)
self._test_qs(qs.filter(num__gt=1), 3)
self._test_qs(qs.filter(num__gte=1), 4)
self._test_qs(qs.filter(num__in=(1, 2, 3)), 3)
self._test_qs(qs.filter(num__in=range(1, 4)), 3)
Color = Enum('Color', u'red blue green yellow brown white black')
class SampleModel(Model):
timestamp = DateTimeField()
materialized_date = DateField(materialized='toDate(timestamp)')
num = Int32Field()
color = Enum8Field(Color)
engine = MergeTree('materialized_date', ('materialized_date',))

59
tests/test_readonly.py Normal file
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@ -0,0 +1,59 @@
# -*- coding: utf-8 -*-
import unittest
from infi.clickhouse_orm.database import Database, DatabaseException
from infi.clickhouse_orm.models import Model
from infi.clickhouse_orm.fields import *
from infi.clickhouse_orm.engines import *
from .base_test_with_data import *
class ReadonlyTestCase(TestCaseWithData):
def _test_readonly_db(self, username):
self._insert_and_check(self._sample_data(), len(data))
orig_database = self.database
try:
self.database = Database(orig_database.db_name, username=username, readonly=True)
with self.assertRaises(DatabaseException):
self._insert_and_check(self._sample_data(), len(data))
self.assertEquals(self.database.count(Person), 100)
list(self.database.select('SELECT * from $table', Person))
with self.assertRaises(DatabaseException):
self.database.drop_table(Person)
with self.assertRaises(DatabaseException):
self.database.drop_database()
except DatabaseException as e:
if 'Unknown user' in unicode(e):
raise unittest.SkipTest('Database user "%s" is not defined' % username)
else:
raise
finally:
self.database = orig_database
def test_readonly_db_with_default_user(self):
self._test_readonly_db('default')
def test_readonly_db_with_readonly_user(self):
self._test_readonly_db('readonly')
def test_insert_readonly(self):
m = ReadOnlyModel(name='readonly')
with self.assertRaises(DatabaseException):
self.database.insert([m])
def test_create_readonly_table(self):
with self.assertRaises(DatabaseException):
self.database.create_table(ReadOnlyModel)
def test_drop_readonly_table(self):
with self.assertRaises(DatabaseException):
self.database.drop_table(ReadOnlyModel)
class ReadOnlyModel(Model):
readonly = True
name = StringField()