Pro test fixture configurator
Project description
protestr
Pro test fixture configurator in Python, for Python, tested with Protester itself.
Table of Contents
Rationale
A test fixture is any arrangement necessary for running tests, consisting of dummies, mocks, stubs, fakes, and even concrete implementations. A well-configured fixture leads to a consistent and reliable testing environment in contrast to an ill-configured one, which is a growing maintenance burden. Good fixtures can support multiple tests with modifications, such as a database seeded differently each time to test a different operation like insertion or deletion. They are also responsible for ensuring the proper disposal of resources without a miss, especially across multiple tests and files. Their configuration logic does not hijack focus from acts and assertions, and they are always reusable with all necessary adjustments. That's where Protestr comes in. It offers a declarative syntax for fixture customization to make tests concise, expressive, and reusable like never before.
Getting Started
Installation
Protestr is available as
protestr
on PyPI and can be
installed with:
pip install protestr
Creating Specs
A fixture is technically a set of specifications (specs) "provided" to a
function to resolve into actual data. The specs — usually functions —
describe how different parts of the fixture form. Protestr offers a few
built-in specs in protestr.specs
, but you may need more. So, let's
create an example geo-coordinate spec to start with. A valid
geo-coordinate consists of a latitude between [-90, 90], a longitude
between [-180, 180], and an altitude — something like:
from protestr import provide
from protestr.specs import between
@provide(
lat=between(-90.0, 90.0),
lon=between(-180.0, 180.0),
alt=float
)
def geo_coord(lat, lon, alt):
return lat, lon, alt
Thus, we have our first spec — geo_coord
. Intuitive, isn't it? Now, we
can "resolve" (generate) geo-coordinates whenever we need to in the
following ways:
-
Call without args:
>>> geo_coord() (-28.56218898364334, 74.83481448106508, 103.16808817617861)
Why invent args when Protestr can provide them?
-
Call with overridden specs:
>>> geo_coord( ... lat=single("equator", "north pole", "south pole"), ... alt=int ... ) ('north pole', -107.37336459941672, 581)
Here,
lat
andalt
have been overridden withsingle
(a built-in spec) andint
. Generally, specs created withprovide()
can be passed any spec to override defaults as long as they are passed intact. Consider the following incorrect approach:>>> geo_coord( ... lat=str(single("equator", "north pole", "south pole")) # ❌ ... ) ('<function[TRIMMED]98AF80>', -126.77844430204937, 678.4366330272486)
It didn't work as expected because
single
was consumed bystr
, so it wasn't intact when passed togeo_coord
. Consider another example:>>> geo_coord( ... lat=merged( ... single("equator", "arctic circle", "antarctic circle"), ... between(5, 10), ... func=lambda them: " ± ".join(str(x) for x in them) ... ) ... ) ('antarctic circle ± 7', 93.7335784938644, 388.76826219877256)
Passing specs intact to one another is perfectly okay.
-
Resolve with
resolve
:>>> from protestr import resolve >>> resolve(geo_coord) (-68.79360870922969, 8.200171266070214, 691.5305890425291)
resolve
also works with other types, as mentioned in Documentation. -
Provide with
provide()
:@provide(geo_coords=2*[geo_coord]) def line(geo_coords): start, end = geo_coords return start, end
provide()
is the decorator version ofresolve
that accepts multiple specs as keyword args.
[!NOTE] The
provide()
decorator works seamlessly when used alongside other decorators, such as Python's handypatch()
decorator. Please note, however, that thepatch()
decorators must be next to one another, and in the list of parameters, they must appear in the reverse order as in the list of decorators (bottom-up). That's howpatch()
works (more info in unittest.mock - Quick Guide).>>> from unittest.mock import patch >>> from protestr import provide >>> @provide(intgr=int) ... @patch('module.ClassName2') ... @patch('module.ClassName1') ... def test(MockClass1, MockClass2, intgr): ... module.ClassName1() ... module.ClassName2() ... assert MockClass1 is module.ClassName1 ... assert MockClass2 is module.ClassName2 ... assert MockClass1.called ... assert MockClass2.called ... assert isinstance(intgr, int) ... >>> test()
Tearing Down
Good fixture design demands remembering to dispose of resources at the
end of tests. Protestr takes care of it out of the box with the
__teardown__
function. Whenever a provide()
-applied function returns
or terminates abnormally, it looks for __teardown__
on each (resolved)
object it provided and invokes it on the object if found. Any exceptions
raised during the process are accumulated and reraised together as
Exception(ex1, ex2, ..., exn)
. So, all you need to do is define
__teardown__
once in a class, and it will be called every time you
provide one.
class UsersDB:
def __init__(self, users):
self.users = users
def insert(self, user):
self.users.append(user)
def __teardown__(self):
self.users = []
Documentation
$\huge \color{gray}protestr.\color{black}\textbf{provide(**kwdspecs)}$
Provides specs to a function as keyword args. The names in the keywords may be in any order in the parameters. The function is thus modified to be callable with the provided args omitted or specified to override.
>>> @provide(
... password=merged(
... single(ascii_uppercase),
... single(ascii_lowercase),
... single(digits),
... permutation(str, k=between(5, 100)),
... func="".join
... ),
... username=permutation(ascii_lowercase, k=between(4, 12))
... )
... def credentials(username, password):
... return username, password
...
>>> credentials()
('cgbqkmsehf', 'Pr8LOipCBKCBkAxbbKykppKkALxykKLOiKpiy')
>>> credentials(username="johndoe")
('johndoe', 'En2HivppppimmFaFHpEeEEEExEamp')
$\huge \color{gray}protestr.\color{black}\textbf{resolve(spec)}$
Resolves a spec, which can be an int
, float
, complex
, float
,
str
, tuple, list, set, dictionary, or anything callable without args.
>>> resolve(str)
'jKKbbyNgzj'
>>> resolve({"number": int})
{'number': 925}
>>> resolve({str: str})
{'RRAIvpJLKAqpLQNNVNXmExe': 'raaqSzSdfCIYxbIhuTGdxi'}
>>> from random import random
>>> resolve(random)
0.8177445321472337
>>> class Foo:
... def __init__(self):
... self.message = "Foo instantiated"
...
>>> resolve(Foo).message
'Foo instantiated'
$\huge \color{gray}protestr.specs.\color{black}\textbf{between(x, y)}$
Returns a spec that resolves to a number between x
and y
, where x
and y
are specs that resolve to numbers. If both x
and y
resolve
to integers, the resulting number is also an integer.
>>> between(10, -10)()
>>> int_spec()
3
>>> between(-10, 10.0)()
-4.475185425413375
>>> between(int, int)()
452
$\huge \color{gray}protestr.specs.\color{black}\textbf{single(*elems)}$
Returns a spec that resolves to some member in elems
, where elems
is
a spec that resolves to some iterable.
>>> colors = ["red", "green", "blue"]
>>> single(colors)()
'green'
>>> single(str)() # single char from a generated str
'T'
>>> single(str, str, str)() # single str from three str objects
'NOBuybxrf'
$\huge \color{gray}protestr.specs.\color{black}\textbf{combination(*elems, k)}$
Returns a spec that resolves to a combination of k
members from
elems
without repetition, where k
and elems
are specs that resolve
to some natural number and collection, respectively.
>>> colors = ["red", "green", "blue"]
>>> combination(colors, k=2)()
['blue', 'green']
>>> combination("red", "green", "blue", k=3)()
('red', 'blue', 'green')
>>> combination(ascii_letters, k=10)()
'tkExshCbTi'
>>> combination([int] * 3, k=between(2, 3))() # 2–3 out of 3 integers
[497, 246]
$\huge \color{gray}protestr.specs.\color{black}\textbf{permutation(*elems, k)}$
Returns a spec that resolves to a permutation of k
members from
elems
with repetition, where k
and elems
are specs that resolve to
some natural number and collection, respectively. It's usage is similar
to combination
.
>>> permutation("abc", k=5)()
'baaca'
Working Example
The complete working example available in tests/example/ should be self-explanatory. If not, please refer to Getting Started and Documentation to become familiar with a few concepts. Here's an excerpt:
# tests/examples/test_example.py
import tests.example.specs as specs
...
...
class TestExample(unittest.TestCase):
...
...
@provide(
db=specs.testdb,
user=specs.user,
shortpass=permutation(str, k=7),
longpass=permutation(str, k=16)
)
@patch("tests.example.fakes.getenv")
def test_insert_user_with_invalid_password_lengths_fails(
self, getenv, db, user, shortpass, longpass
):
getenv.side_effect = lambda env: \
8 if env == "MIN_PASSWORD_LEN" else 15
for pw in (shortpass, longpass):
user.password = pw
try:
db.insert(user)
except Exception as e:
message, = e.args
self.assertEqual(
message, "Password size must be between 8 and 15"
)
self.assertEqual(getenv.mock_calls, [
call("MIN_PASSWORD_LEN"),
call("MAX_PASSWORD_LEN"),
call("MIN_PASSWORD_LEN"),
call("MAX_PASSWORD_LEN")
])
...
...
if __name__ == "__main__":
unittest.main()
If you're curious, here are the specs we created for the example:
# tests/examples/specs.py
from tests.example.fakes import User, UsersDB
...
...
@provide(
id=str,
firstname=single("John", "Jane", "Orange"),
lastname=single("Smith", "Doe", "Carrot"),
username=permutation(ascii_letters, k=between(5, 10)),
password=merged(
single(digits), # password to contain a
single(ascii_uppercase), # number, an uppercase and
single(ascii_lowercase), # a lowercase letter and be
permutation(str, k=between(5, 12)), # 8–15 characters long
func="".join
)
)
def user(id, firstname, lastname, username, password):
return User(id, firstname, lastname, username, password)
@provide(users=3*[user])
def testdb(users):
return UsersDB(users)
License
protestr
is distributed under the terms of the MIT license.
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