python中强大的testdata库自动生成测试所需要的数据

testdata是用于生成测试数据的一个安装包，它不仅提供DictFactory类来生成数据，还提供特定的扩展功能。每个Factory实例均可用于生成用户所需要的特定个数的数据，这将使我们更好地统计分析结果

如果你的目的是生成数据并将其存储到数据库或基于数据库的文档，DictFactory将会变得更加快捷

首先安装testdata，我用的是python2.7版本，在用

pip install python-testdata

遇到下面的报错信息

Command "python setup.py egg_info" failed with error code 1 in c:usersadmini~1appdatalocal	emppip-build-k1cjcxfake-factory

如下是解决方法：先安装fake-factory

pip install fake-factory

接着安装

pip install --no-deps python-testdata

然后运行下面的程序，由于我所装的版本统一用name替代了firstName和 lastName，在原文的基础下进行下改动

import testdata
import random

class Users(testdata.DictFactory):
    id = testdata.CountingFactory(10)
    name = testdata.FakeDataFactory('name')
    address = testdata.FakeDataFactory('address')
    age = testdata.RandomInteger(10, 30)
    gender = testdata.RandomSelection(['female', 'male'])

for user in Users().generate(10): # let say we only want 10 users 
    print user

出现如下的错误提醒：

raise ImportError(error)
ImportError: The ``fake-factory`` package is now called ``Faker``.

继续解决报错，原来是fake-factory的安装版本不对，重新安装并指定安装版本

pip install fake-factory==0.7.4

接下来就可以见证生成的数据啦

{'gender': 'male', 'age': 10, 'id': 10, 'address': u'09953 Sweeney Springs
Jenniferside, FM 00653-9018'}
{'gender': 'female', 'age': 14, 'id': 11, 'address': u'59348 Mike Trail Apt. 106
North Scotthaven, DE 04666'}
{'gender': 'male', 'age': 28, 'id': 12, 'address': u'53128 Archer Island Suite 256
South Michaelfurt, MI 83350'}
{'gender': 'male', 'age': 18, 'id': 13, 'address': u'3559 Kimberly Wall Apt. 924
Justinfort, FM 41543-5666'}
{'gender': 'male', 'age': 14, 'id': 14, 'address': u'54451 Fisher Mount
North Michelle, UT 50280-8984'}
{'gender': 'male', 'age': 22, 'id': 15, 'address': u'PSC 4666, Box 4608
APO AE 90517-5117'}
{'gender': 'male', 'age': 12, 'id': 16, 'address': u'6186 Lisa Groves Apt. 593
Stephenberg, TN 15302-7752'}
{'gender': 'female', 'age': 19, 'id': 17, 'address': u'3919 White Drives
North Calvinport, MD 26577-9590'}
{'gender': 'female', 'age': 30, 'id': 18, 'address': u'148 Anthony Mountain
Stevenfort, RI 38933-9947'}
{'gender': 'female', 'age': 27, 'id': 19, 'address': u'2496 Michael Groves Apt. 021
West Kathleenside, PR 42583-3035'}

我们也可以构造一个数据依赖于另一个数据的情况，如下

import testdata

class ExampleFactory(testdata.DictFactory):
    a = testdata.CountingFactory(10)
    b = testdata.ClonedField("a") # b will have the same value as field 'a'

for e in ExampleFactory().generate(5):
    print e

此时生成的数据为

{'a': 10, 'b': 10}
{'a': 11, 'b': 11}
{'a': 12, 'b': 12}
{'a': 13, 'b': 13}
{'a': 14, 'b': 14}

若我们的需求是生成事件数据，比如我们是构造一个事件的开始和结束时间，并且结束时间要在开始时间的20分钟后结束，并且，我们希望各个数据的开始时间间隔12分钟

import testdata
import datetime

EVENT_TYPES = ["USER_DISCONNECT", "USER_CONNECTED", "USER_LOGIN", "USER_LOGOUT"]
class EventsFactory(testdata.DictFactory):
    start_time = testdata.DateIntervalFactory(datetime.datetime.now(), datetime.timedelta(minutes=12))
    end_time = testdata.RelativeToDatetimeField("start_time", datetime.timedelta(minutes=20))
    event_code = testdata.RandomSelection(EVENT_TYPES)

for event in EventsFactory().generate(5):
    print event

若要生成百分比不同的数据，比如我们想要构造工作的数据，包含用户名、状态、描述，其中状态为pending的占90%，剩下的10%的状态为‘error’。除此之外，如果状态为error的用户该为‘support’，状态为pending的用户应为‘admin’

class Job(testdata.DictFactory):
    state = testdata.StatisticalValuesFactory([('pending', 90), ('error', 10)])
    assigned_user = testdata.ConditionalValueField('state', {'error': 'support'}, 'admin')
    description = testdata.RandomLengthStringFactory()

for i in Job().generate(10):
    print i

生成的数据为

{'state': 'pending', 'assigned_user': 'admin', 'description': 'HKCVoGAOJZVKYqGktTakWqewxScyUSSGcMj'}
{'state': 'pending', 'assigned_user': 'admin', 'description': 'dyyLbtxfoqotlaNfWieoVvXFlzRYNOajYFVmwtXDRdVoQItDnjgptpEiBJHBgCuzqOZVwsxyWbByrJvgiTKKNyuiSsKO'}
{'state': 'error', 'assigned_user': 'support', 'description': 'nuvRQyhcvvXWJuXhCbWVUyWAmKoioTcYIBHtcPwvgRytCsPlWEvSHRFjXDUAIgPblhhHFTKzCmmitBErHzpXLBoI'}
{'state': 'pending', 'assigned_user': 'admin', 'description': 'IhrQoAkFNwqfZSxfkwCSmaGRFodFZYVHCegEnAMpTBtqUZMgaFGlAaznzUNbDrdgPDHNrAvJEQZRDUQxdDKsLvXJiMDR'}
{'state': 'pending', 'assigned_user': 'admin', 'description': 'ftINruSFdOeAqOuDyInNgIrQPoegOwlqWSFIHYNVY'}

另外，可以对字段进行重写和新增字段操作，在前面生成用户信息的例子中，我们可以将用户的名称设置为定值，并且新建email字段

for user in Users(name=testdata.Constant('John'), age=testdata.RandomInteger(40, 60), email=testdata.FakeDataFactory('email')).generate(10): # let say we only want 10 users
    print user

生成的数据为

{'name': 'John', 'gender': 'male', 'age': 40, 'email': u'brownamy@yahoo.com', 'address': u'813 Donald Route
South Andrea, SC 99925', 'id': 15}
{'name': 'John', 'gender': 'female', 'age': 58, 'email': u'gloriapatel@may-mitchell.com', 'address': u'73919 Hodges Courts
Tammyside, ME 89926-3945', 'id': 16}
{'name': 'John', 'gender': 'male', 'age': 45, 'email': u'ashley40@cooper.info', 'address': u'95546 Mary Flats
West Codystad, PA 34744', 'id': 17}
{'name': 'John', 'gender': 'female', 'age': 43, 'email': u'xwhite@pierce-sutton.com', 'address': u'4051 Reese Mission Suite 829
New Danny, NE 92155-8318', 'id': 18}
{'name': 'John', 'gender': 'male', 'age': 60, 'email': u'qpoole@rice.com', 'address': u'3584 Bright Ramp
Johnstonmouth, NV 12566-4343', 'id': 19}

上面例子中所用的基类如下

Factory类	简介
Factory	所有的Factory的基类
DictFactory	非常强大的基类，它可让子类创建Factory，具体可参考上面的例子
ListFactory	A factory that returns on each iteration a list of elements_per_list items returned from calls to the given factory.
Callable	Gets a callable object as an argument and returns the result of calling the object on every iteration
DependentCallable	Gets a callable object as an argument and returns the result of calling the object passing the defined fields as arguments on every iteration
ClonedField	A factory that copies the value of another factory.

日期类

Factory类	简介
RandomDateFactory	Generates random dates (python's datetime) between 2 dates
DateIntervalFactory	Generates datetime objects starting from base while adding delta to it each iteration.
RelativeToDatetimeField	Generates datetime object relative to another datetime field, like if you have start_timewhich is a RandomDateFactory field, and want an end_time field that is always 15 minutes later.

本文是对https://github.com/arieb/python-testdata的粗略翻译