ensure is a set of simple assertion helpers that let you write more expressive, literate, concise, and readable Pythonic code for validating conditions. It’s inspired by should.js, expect.js, and builds on top of the unittest/JUnit assert helpers.
If you use Python 3, you can use ensure to enforce your function signature annotations: see PEP 3107 and the @ensure_annotations decorator below.
Because ensure is fast, is a standalone library (not part of a test framework), doesn’t monkey-patch anything or use DSLs,
and doesn’t use the assert statement (which is liable to be turned off with the -O
flag), it can be used to validate
conditions in production code, not just for testing (though it certainly works as a BDD test utility library).
Aside from better looking code, a big reason to use ensure is that it provides more consistent, readable, and informative error messages when things go wrong. See Motivation and Goals for more.
pip install ensure
from ensure import ensure
ensure(1).is_an(int)
ensure({1: {2: 3}}).equals({1: {2: 3}}).also.contains(1)
ensure({1: "a"}).has_key(1).whose_value.has_length(1)
ensure.each_of([{1: 2}, {3: 4}]).is_a(dict).of(int).to(int)
ensure(int).called_with("1100101", base=2).returns(101)
ensure(dict).called_with(1, 2).raises(TypeError)
check(1).is_a(float).or_raise(Exception, "An error happened: {msg}. See http://example.com for more information.")
In Python 3:
from ensure import ensure_annotations
@ensure_annotations
def f(x: int, y: float) -> float:
return x+y
See More examples below.
The ensure
module exports the Ensure
class and its convenience instance ensure
. Instances of the class are
callable, and the call will reset the contents that the instance is inspecting, so you can reuse it for many checks (as
seen above).
The class raises EnsureError
(a subclass of AssertionError
) by default.
There are several ways to chain clauses, depending on the grammatical context: .also
, .which
, and
.whose_value
are available per examples below.
You can pass a callable or exception class as the error_factory
keyword argument to Ensure()
, or you can use the
Check
class or its convenience instance check()
. This class behaves like Ensure
, but does not raise errors
immediately. It saves them and chains the methods otherwise()
, or_raise()
and or_call()
to the end of the
clauses.
from ensure import check
check("w00t").is_an(int).or_raise(Exception)
check(1).is_a(float).or_raise(Exception, "An error happened: {msg}. See http://example.com for more information.")
check("w00t").is_an(int).or_raise(MyException, 1, 2, x=3, y=4)
def build_fancy_exception(original_exception):
return MyException(original_exception)
check("w00t").is_an(int).otherwise(build_fancy_exception)
check("w00t").is_an(int).or_call(build_fancy_exception, *args, **kwargs)
ensure({1: {2: 3}}).is_not_equal_to({1: {2: 4}})
ensure(True).does_not_equal(False)
ensure(1).is_in(range(10))
ensure(True).is_a(bool)
ensure(True).is_(True)
ensure(True).is_not(False)
ensure(["train", "boat"]).contains_one_of(["train"])
ensure(range(8)).contains(5)
ensure(["spam"]).contains_none_of(["eggs", "ham"])
ensure("abcdef").contains_some_of("abcxyz")
ensure("abcdef").contains_one_or_more_of("abcxyz")
ensure("abcdef").contains_all_of("acf")
ensure("abcd").contains_only("dcba")
ensure("abc").does_not_contain("xyz")
ensure([1, 2, 3]).contains_no(float)
ensure(1).is_in(range(10))
ensure("z").is_not_in("abc")
ensure(None).is_not_in([])
ensure(dict).has_attribute('__contains__').which.is_callable()
ensure({1: "a", 2: "b", 3: "c"}).has_keys([1, 2])
ensure({1: "a", 2: "b"}).has_only_keys([1, 2])
ensure(1).is_true()
ensure(0).is_false()
ensure(None).is_none()
ensure(1).is_not_none()
ensure("").is_empty()
ensure([1, 2]).is_nonempty().also.has_length(2)
ensure(1.1).is_a(float).which.equals(1.10)
ensure(KeyError()).is_an(Exception)
ensure({x: str(x) for x in range(5)}).is_a_nonempty(dict).of(int).to(str)
ensure({}).is_an_empty(dict)
ensure(None).is_not_a(list)
import re
ensure("abc").matches("A", flags=re.IGNORECASE)
ensure([1, 2, 3]).is_an_iterable_of(int)
ensure([1, 2, 3]).is_a_list_of(int)
ensure({1, 2, 3}).is_a_set_of(int)
ensure({1: 2, 3: 4}).is_a_mapping_of(int).to(int)
ensure({1: 2, 3: 4}).is_a_dict_of(int).to(int)
ensure({1: 2, 3: 4}).is_a(dict).of(int).to(int)
ensure(10**100).is_numeric()
ensure(lambda: 1).is_callable()
ensure("abc").has_length(3)
ensure("abc").has_length(min=3, max=8)
ensure(1).is_greater_than(0)
ensure(1).exceeds(0)
ensure(0).is_less_than(1)
ensure(1).is_greater_than_or_equal_to(1)
ensure(0).is_less_than_or_equal_to(0)
ensure(1).is_positive()
ensure(1.1).is_a_positive(float)
ensure(-1).is_negative()
ensure(-1).is_a_negative(int)
ensure(0).is_nonnegative()
ensure(0).is_a_nonnegative(int)
ensure([1,2,3]).is_sorted()
ensure("{x} {y}".format).called_with(x=1, y=2).equals("1 2")
ensure(int).called_with("1100101", base=2).returns(101)
ensure("{x} {y}".format).with_args(x=1, y=2).is_a(str)
with ensure().raises(ZeroDivisionError):
1/0
with ensure().raises_regex(NameError, "'w00t' is not defined"):
w00t
See complete API documentation.
Use the @ensure_annotations
decorator to enforce
function signature annotations:
from ensure import ensure_annotations
@ensure_annotations
def f(x: int, y: float) -> float:
return x+y
f(1, 2.3)
>>> 3.3
f(1, 2)
>>> ensure.EnsureError: Argument y to <function f at 0x109b7c710> does not match annotation type <class 'float'>
Compare this runtime type checking to compile-time checking in Mypy and type hinting in PEP 484/Python 3.5+.
Many BDD assertion libraries suffer from an excess of magic, or end up having to construct statements that don’t parse as English easily. ensure is deliberately kept simple to avoid succumbing to either issue. The source is easy to read and extend.
Work remains to make error messages raised by ensure even more readable, informative, and consistent. Going forward, ability to introspect exceptions to extract structured error information will be a major development focus. You will be in control of how much information is presented in each error, which context it’s thrown from, and what introspection capabilities the exception object will have.
The original use case for ensure is as an I/O validation helper for API endpoints, where the client needs to be sent a very clear message about what went wrong, some structured information (such as an HTTP error code and machine-readable reference to a failing element) may need to be added, and some information may need to be hidden from the client. To further improve on that, we will work on better error translation, marshalling, message formatting, and schema validation helpers.
Please report bugs, issues, feature requests, etc. on GitHub.
Licensed under the terms of the Apache License, Version 2.0.
Like Ensure, but if a check fails, saves the error instead of raising it immediately. The error can then be acted
upon using or_raise()
or or_call()
.
.each_of()
is not supported by the Check inspector; all other methods are supported.
Calls _callable with supplied args and kwargs if a predicate fails.
Raises an exception produced by error_factory if a predicate fails.
error_factory – Class or callable (e.g. Exception
) which will be invoked to produce the resulting exception.
You can define a custom callable here; it will be given the underlying predicate’s exception (AssertError)
as the first argument, followed by any arguments passed to or_raise
.
message – String to be formatted and passed as the first argument to error_factory. If this is given, subsequent
arguments passed to or_raise
will be used to format contents of the string, and will not be passed to
error_factory
. The keyword argument error
will be set to the underlying predicate’s exception.
Raises an exception produced by error_factory if a predicate fails.
error_factory – Class or callable (e.g. Exception
) which will be invoked to produce the resulting exception.
You can define a custom callable here; it will be given the underlying predicate’s exception (AssertError)
as the first argument, followed by any arguments passed to or_raise
.
message – String to be formatted and passed as the first argument to error_factory. If this is given, subsequent
arguments passed to or_raise
will be used to format contents of the string, and will not be passed to
error_factory
. The keyword argument error
will be set to the underlying predicate’s exception.
Constructs a root-level inspector, which can perform a variety of checks (predicates) on subjects passed to
it. If the checks do not pass, by default EnsureError
is raised. This can be configured by passing the
error_factory
keyword to the constructor.
Subjects can be passed to the inspector at construction time or by calling the resulting object (each call resets the subject):
Ensure(1).is_an(int)
e = Ensure()
e(1).is_an(int)
Some predicates return child inspectors which can be chained into a series of predicates, for example:
ensure({1: {2: "a"}}).has_key(1).whose_value.is_a(dict).of(int).to(str)
Before evaluating subsequent predicates, calls subject
with given arguments (but unlike a direct call,
catches and transforms any exceptions that arise during the call).
Ensures subject
contains all of elements, which must be an iterable.
Ensures subject
is a collections.Mapping
and contains key.
Ensures subject
contains none of elements, which must be an iterable.
Ensures subject
contains exactly one of elements, which must be an iterable.
Ensures subject
contains at least one of elements, which must be an iterable.
Ensures subject
contains all of elements, which must be an iterable, and no other items.
Ensures subject
contains at least one of elements, which must be an iterable.
Ensures subject
is not equal to other.
Ensures subject
is greater than other.
Ensures subject
is a collections.Mapping
and contains keys, which must be an iterable.
Ensures subject
has length length (if given), length at least min (if given), and length at most
max (if given).
Ensures subject
is a collections.Mapping
and contains keys, and no other keys.
Ensures subject
has an attribute attr.
Ensures subject
is a dict
containing only objects of class prototype.
Ensures subject
is a list
containing only objects of class prototype.
Ensures subject
is a collections.Mapping
containing only objects of class prototype.
Ensures subject
is less than 0 and is an object of class prototype.
Ensures subject
is an object of class prototype and has non-zero length.
Ensures subject
is greater than or equal to 0 and is an object of class prototype.
Ensures subject
is greater than 0 and is an object of class prototype.
Ensures subject
is a set
containing only objects of class prototype.
Ensures subject
is an object of class prototype.
Ensures subject
is an object of class prototype and has zero length.
Ensures subject
is an object of class prototype.
Ensures subject
is an iterable containing only objects of class prototype.
Ensures subject
is either None
, or satisfies subsequent (chained) conditions:
Ensure(None).is_none_or.is_an(int)
Ensures subject
is not an object of class prototype.
Ensures subject
is not contained in iterable.
Ensures preceding predicates (specifically, called_with()
) result in expected_exception being raised.
Ensures preceding predicates (specifically, called_with()
) result in expected_exception being raised,
and the string representation of expected_exception must match regular expression expected_regexp.
Before evaluating subsequent predicates, calls subject
with given arguments (but unlike a direct call,
catches and transforms any exceptions that arise during the call).
Decorator to be used on functions with annotations. Runs type checks to enforce annotations. Raises
EnsureError
if any argument passed to f is not of the type specified by the annotation. Also raises
EnsureError
if the return value of f is not of the type specified by the annotation. Examples:
from ensure import ensure_annotations
@ensure_annotations
def f(x: int, y: float) -> float:
return x+y
print(f(1, y=2.2))
>>> 3.2
print(f(1, y=2))
>>> ensure.EnsureError: Argument y of type <class 'int'> to
<function f at 0x109b7c710> does not match annotation type <class 'float'>
Warning
The current implementation of the decorator might trigger
a _pickle.PicklingError
when a decorated function is run through
multiprocessing
.
Fail unless an exception of class expected_exception is raised by the callable when invoked with specified positional and keyword arguments. If a different type of exception is raised, it will not be caught, and the test case will be deemed to have suffered an error, exactly as for an unexpected exception.
If called with the callable and arguments omitted, will return a context object used like this:
with self.assertRaises(SomeException):
do_something()
An optional keyword argument ‘msg’ can be provided when assertRaises is used as a context object.
The context manager keeps a reference to the exception as the ‘exception’ attribute. This allows you to inspect the exception after the assertion:
with self.assertRaises(SomeException) as cm:
do_something()
the_exception = cm.exception
self.assertEqual(the_exception.error_code, 3)
Asserts that the message in a raised exception matches a regex.
expected_exception: Exception class expected to be raised. expected_regex: Regex (re.Pattern object or string) expected
to be found in error message.
args: Function to be called and extra positional args. kwargs: Extra kwargs. msg: Optional message used in case of failure. Can only be used
when assertRaisesRegex is used as a context manager.
Decorator to be used on functions with annotations. Runs type checks to enforce annotations. Raises
EnsureError
if any argument passed to f is not of the type specified by the annotation. Also raises
EnsureError
if the return value of f is not of the type specified by the annotation. Examples:
from ensure import ensure_annotations
@ensure_annotations
def f(x: int, y: float) -> float:
return x+y
print(f(1, y=2.2))
>>> 3.2
print(f(1, y=2))
>>> ensure.EnsureError: Argument y of type <class 'int'> to
<function f at 0x109b7c710> does not match annotation type <class 'float'>
Warning
The current implementation of the decorator might trigger
a _pickle.PicklingError
when a decorated function is run through
multiprocessing
.