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Sampledata Generator

Project description

This package tries to do the best to support the development of sample data generators. A sample data generator is a pluggable tool to create data needed for tests.

Detailed Documentation

Pluggable sample data framework

Creating a good testing environment is the most important way to create high quality software.

But most of the time it is a pain !

This package tries to do the best to support the development of sample data generators. A sample data generator is a pluggable tool to create data needed for tests.

There are several goals to this framework:

  • provide the developers with an automatic setup that is close to real-world use.

  • provide the users with an easy setup for evaluation with plausible data

  • provide the user a management interface for different sample generators

The framework is pluggable and allows the creators of generator extensions to provide their own plugins that generate sample data for those extensions.

Generators

A generator generates sample data.

>>> from zope import interface
>>> from zope import component
>>> from z3c.sampledata.interfaces import ISampleDataPlugin
>>> class GeneratePrincipals(object):
...     interface.implements(ISampleDataPlugin)
...     dependencies = []
...     schema = None
...     def generate(self, context, param={}, dataSource=None, seed=None):
...         print self.__class__.__name__
...         if dataSource is not None:
...             for data in dataSource:
...                 print '- %s'%data['login']
>>> principalPlugin = GeneratePrincipals()

For our tests we provide another generator :

>>> class GenerateSite(object):
...     interface.implements(ISampleDataPlugin)
...     dependencies = []
...     schema = None
...     def generate(self, context, param={}, dataSource=None, seed=None):
...         if 'sitename' in param:
...             print 'This is site %r'%param['sitename']
...         else:
...             print self.__class__.__name__
...         return 'I am from the site'
>>> sitePlugin = GenerateSite()

Generator Manager

A generator manager groups a collection of generators. The manager allows to :

  • define dependencies between generators

  • define data connections between dependent generators

  • provide default configuration data

>>> from z3c.sampledata import Manager
>>> manager = Manager('manager', '')
Generator Plugin

For the manager our sample generators must be registered as named utilities.

>>> component.provideUtility(sitePlugin,
...                          ISampleDataPlugin,'z3c.sampledata.site')
>>> component.provideUtility(principalPlugin,
...                          ISampleDataPlugin,'z3c.sampledata.principals')
Generating Sample Data

Now we can add generators to the manager.

>>> manager.add('z3c.sampledata.principals',
...             dependsOn=['z3c.sampledata.site',],
...             contextFrom='z3c.sampledata.site')

In addition to the “hardwired” dependencies defined by the dependencies property in each generator it is possible to add dependencies in the generator manager.

A manager provides it’s generators.

>>> manager.generators.keys()
['z3c.sampledata.principals']

We can tell the manager to generate all samples. There is no need to add the sample generator ‘z3c.sampledata.site’, it is added automatically because of the dependency of ‘z3c.sampledata.principals’.

>>> infos = manager.generate(context=None, param={}, seed='something')
GenerateSite
GeneratePrincipals
>>> [info.name for info in infos]
['z3c.sampledata.site', 'z3c.sampledata.principals']

Parameters for the sample generators

To have more control over the sample generation process it is possible to setup parameters for the generators.

>>> manager = Manager('manager', '')
>>> manager.add('z3c.sampledata.site',
...             param={'sitename':'samplesite'})
>>> manager.add('z3c.sampledata.principals',
...             dependsOn=['z3c.sampledata.site',],
...             contextFrom='z3c.sampledata.site')
>>> infos = manager.generate(context=None, param={}, seed='something')
This is site 'samplesite'
GeneratePrincipals

It is also possible to overwrite the parameters from the configuration.

>>> infos = manager.generate(context=None,
...                          param={'z3c.sampledata.site':
...                                 {'sitename':'managers site'}},
...                          seed='something')
This is site 'managers site'
GeneratePrincipals

Cycles in the generator definition

>>> manager = Manager('manager', '')
>>> manager.add('z3c.sampledata.principals',
...             dependsOn=['z3c.sampledata.site',],
...             contextFrom='z3c.sampledata.site')
>>> manager.add('z3c.sampledata.site',
...             dependsOn=['z3c.sampledata.principals',])
>>> infos = manager.generate(context=None, param={}, seed='something')
Traceback (most recent call last):
...
CyclicDependencyError: cyclic dependency at 'z3c.sampledata.principals'

A test for a complex dependency.

>>> class Generator(object):
...     interface.implements(ISampleDataPlugin)
...     name = 'generator'
...     dependencies = []
...     schema = None
...     def generate(self, context, param={}, dataSource=None, seed=None):
...         return 'I am a generator'
>>> component.provideUtility(Generator(), ISampleDataPlugin,'g.1')
>>> component.provideUtility(Generator(), ISampleDataPlugin,'g.2')
>>> component.provideUtility(Generator(), ISampleDataPlugin,'g.3')
>>> manager = Manager('manager', '')
>>> manager.add('g.1')
>>> manager.add('g.2', contextFrom='g.1')
>>> manager.add('g.3', dependsOn=['g.2', 'g.1'], contextFrom='g.1')
>>> infos = manager.generate(context=None, param={}, seed=None)
>>> [info.name for info in infos]
['g.1', 'g.2', 'g.3']

Sample Data Source

A sample data generator usually gets its sample data from a data source. Mostly it is necessary to have different data sources for different uses.

As an example, it is always a pain if the sample data for the tests use the same data as the UI uses later to provide data for the customer to click around.

>>> manager = Manager('manager', '')
>>> manager.addSource('z3c.datasource.principals',
...                   data=[{'login':'jukart', 'password':'trakuj'},
...                         {'login':'srichter', 'password':'rethcirs'}])
>>> manager.add('z3c.sampledata.principals',
...             dataSource='z3c.datasource.principals',
...             dependsOn=['z3c.sampledata.site',],
...             contextFrom='z3c.sampledata.site')
>>> infos = manager.generate(context=None, param={}, seed='something')
GenerateSite
GeneratePrincipals
- jukart
- srichter

It is also possible to use adapters to act as a data source.

>>> manager = Manager('manager', '')
>>> class IPrincipalDataSource(interface.Interface):
...     pass
>>> def principalDataFactory(object):
...      return [{'login':'jukart', 'password':'trakuj'},
...              {'login':'srichter', 'password':'rethcirs'}]
>>> component.provideAdapter(
...                          factory=principalDataFactory,
...                          adapts=(ISampleDataPlugin,),
...                          provides=IPrincipalDataSource,
...                          name='testprincipals')
>>> manager.addSource('z3c.datasource.principals',
...                   adapterName='testprincipals',
...                   adaptTo=IPrincipalDataSource)
>>> manager.add('z3c.sampledata.principals',
...             dataSource='z3c.datasource.principals',
...             dependsOn=['z3c.sampledata.site',],
...             contextFrom='z3c.sampledata.site')
>>> infos = manager.generate(context=None, param={}, seed='something')
GenerateSite
GeneratePrincipals
- jukart
- srichter

How to setup configuration for the generator manager

Configuration can be done using ZCML:

<configure xmlns="http://namespaces.zope.org/zope">

  <configure
      xmlns:zcml="http://namespaces.zope.org/zcml"
      zcml:condition="have devmode">

    <utility
        factory=".SampleSite"
        provides="z3c.sampledata.interfaces.ISampleDataPlugin"
        name="z3c.site"
        />

    <utility
        factory=".SamplePrincipals"
        provides="z3c.sampledata.interfaces.ISampleDataPlugin"
        name="z3c.principals"
        />

    <SampleManager
      name="Site with principals"
      >
      <generator name="z3c.site" />
      <generator
        name="z3c.principal"
        dependsOn="z3c.site"
        contextFrom="z3c.site" />
    </SampleManager>

  </configure>

</configure>

Data Sources

This package implements the base functionality for data generators. A data generator is used to provide the raw data for a sample generator. Raw data can be read from text files in different ways.

>>> from z3c.sampledata.data import DataGenerator
>>> generator = DataGenerator(55)

The generator can read data lines from files.

>>> generator.readLines('testlines.txt')
[u'Line 1', u'Another line']

The generator can read data from CSV files.

>>> generator.readCSV('testlines.csv')
[['Line 1', 'Col 2'], ['Another line', 'Another Col']]

The generator can read a list of files from a path :

>>> import os
>>> generator.files(os.path.dirname(__file__))
['...README.txt', ...]

CHANGES

0.4.0 (2010-08-30)

  • Use current pacakges.

0.3.1 (2010-08-30)

  • Update dependency meta, Clean imports.

0.3.0 (2010-06-28)

  • Configured test runner to run functional tests.

  • Removed ZPKG and ZCML slugs.

  • Now requires zope.app.pagetemplate >= 3.6.0 as zope.formlib.namedtemplate has been moved there an there is no longer a BBB import zope.formlib >= 4.0

  • Fixed tests to run with zope.app.authentication >= 3.7.0.

  • Fixed tests to run with zope.publisher >= 3.12.0.

  • Using python’s doctest module instead of deprecated zope.testing.doctestunit.

0.2.0 (2010-06-25)

  • adjust zope.app.session to zope.session in ftesting.zcml

  • Adjusted zope.app.securitypolicy to zope.securitpolicy in ftesting.zcml.

  • Fixed tests after zope packages refactoring. Updated imports and dependencies.

0.1.0 (2008-02-14)

  • Initial release.

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