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>>> @interface.implementer(ISampleDataPlugin) ... class GeneratePrincipals(object): ... 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 :
>>> @interface.implementer(ISampleDataPlugin) ... class GenerateSite(object): ... 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.
>>> list(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.
>>> @interface.implementer(ISampleDataPlugin) ... class Generator(object): ... 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
2.0.0 (2015-11-09)
Standardize namespace __init__
2.0.0a1 (2013-03-04)
Added support for Python 3.3.
Dropped browser support completely, since it relied on really old o-wrap techniques. Also, it contained Lovely-specif project language from about 7 years ago. ;-)
Replaced deprecated zope.interface.implements usage with equivalent zope.interface.implementer decorator.
Dropped support for Python 2.4 and 2.5.
1.0.0 (2013-02-26)
Moved depndencies for the special SampleDataLayer setup to the “testing” extra.
Added MANIFEST.in and tox.ini.
Fixed file headers.
Browser views are only available using the “browser” extra.
Change zope.app.pagetemplate dependency to zope.browserpage.
0.4.0 (2010-08-30)
Use current packages.
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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