Python Testing with pytest: Fixtures and Coverage

Python Testing with pytest: Fixtures and Coverage

Improve your Python checking out much more.

In my remaining two articles, I offered pytest, a library for
checking out Python code (see “Testing Your Code with Python’s pytest” Part
and Part
). pytest has grow to be reasonably common, in no small section
as a result of it is so simple to write down exams and combine the ones exams into
your device construction procedure. I have grow to be a large fan, most commonly as a result of
after years of claiming I must recuperate about
checking out my device, pytest in any case has made it conceivable.

So on this article, I evaluate two options of pytest that I have not had a
likelihood to hide but: fixtures and code protection, which is able to (I
hope) persuade you that pytest is value exploring and incorporating into
your paintings.


When you are writing exams, you are hardly going to write down only one or two.
Rather, you’ll write a complete “test suite”, with every check
aiming to test a unique trail thru your code. In many circumstances, this
method you can have a couple of exams with identical traits,
one thing that pytest handles with “parametrized tests”.

But in different circumstances, issues are somewhat extra advanced. You’ll wish to have
some items to be had to your entire exams. Those items may comprise
knowledge you need to proportion throughout exams, or they may contain the community or
filesystem. These are regularly referred to as “fixtures” within the checking out global,
and they take numerous other paperwork.

In pytest, you outline fixtures the usage of a mix of the pytest.fixture
decorator, alongside with a serve as definition. For instance, say
you could have a dossier that returns an inventory of strains from a dossier, wherein every
line is reversed:

def reverse_lines(f):
   go back [one_line.rstrip()[::-1] + 'n'
           for one_line in f]

Note that so as to steer clear of the newline persona from being positioned at
the beginning of the road, you take away it from the string earlier than reversing and
then upload a 'n' in every returned string. Also notice that even if it
most definitely could be a good suggestion to make use of a generator expression moderately than an inventory
comprehension, I am looking to stay issues quite easy right here.

If you’ll check this serve as, you can want to go it a
file-like object. In my remaining article, I confirmed how it’s essential use a StringIO object
for this kind of factor, and that is still the case. But moderately than defining
world variables for your check dossier, you’ll be able to create a fixture that’ll supply
your check with the suitable object on the proper time.

Here’s how that appears in pytest:

def simple_file():
   go back StringIO('n'.sign up for(['abc', 'def', 'ghi', 'jkl']))

On the face of it, this looks as if a easy serve as—one who returns
the price it would be best to use later. And in some ways, it is
very similar to what you’ll get in the event you had been to outline an international variable by means of the
title of “simple_file”.

At the similar time, fixtures are used otherwise from world variables. For
instance, shall we say you need to incorporate this fixture in considered one of your
exams. You then can point out it within the check’s parameter listing. Then,
throughout the check, you’ll be able to get entry to the fixture by means of title. For instance:

def test_reverse_lines(simple_file):
   assert reverse_lines(simple_file) == ['cban', 'fedn',
 ↪'ihgn', 'lkjn']

But it will get even higher. Your fixture may act like knowledge, in that you do not
invoke it with parentheses. But it is if truth be told a serve as below the hood,
because of this it executes each and every time you invoke a check the usage of that
fixture. This signifies that the fixture, against this with regular-old
knowledge, could make calculations and choices.

You may also make a decision how regularly a fixture is administered. For instance, as it is
written now, this fixture will run as soon as in step with check that mentions it.
That’s nice on this case, when you need to check with an inventory or
file-like construction. But what if you wish to arrange an object and then
use it a couple of occasions with out developing it once more? You can do this by means of
surroundings the fixture’s “scope”. For instance, in the event you set the scope of the
fixture to be “module”, it will be to be had all over your exams however
will execute just a unmarried time. You can do that by means of passing the scope
parameter to the @pytest.fixture decorator:

def simple_file():
   go back StringIO('n'.sign up for(['abc', 'def', 'ghi', 'jkl']))

I must notice that giving this actual fixture “module” scope is a
dangerous thought, since the second one check will finally end up having a StringIO whose
location pointer (checked with dossier.inform) is already on the finish.

These fixtures paintings reasonably otherwise from the standard
setup/teardown gadget that many different check programs use. However, the
pytest folks without a doubt have satisfied me that this can be a higher means.

But wait—in all probability you’ll be able to see the place the “setup” capability exists in
those fixtures. And, the place’s the “teardown” capability? The resolution is
each easy and chic. If your fixture makes use of “yield” as a substitute of
“return”, pytest understands that the post-yield code is for
tearing down items and connections. And sure, in case your fixture has
“module” scope, pytest will wait till all the purposes within the
scope have completed executing earlier than tearing it down.


This is all nice, however in the event you’ve ever executed any checking out, you already know there may be
at all times the query of ways completely you could have examined your code. After
all, shall we say you have got written 5 purposes, and that you have written
exams for they all. Can you you should definitely’ve if truth be told examined all of
the conceivable paths thru the ones purposes?

For instance, shall we embrace you could have an excessively unusual serve as, only_odd_mul,
which multiplies simplest bizarre numbers:

def only_odd_mul(x, y):
   if xpercent2 and ypercent2:
       go back x * y
       carry NoEvenNumbersHereException(f' and/or 
 ↪now not bizarre')

Here’s a check you’ll be able to run on it:

def test_odd_numbers():
   assert only_odd_mul(three, five) == 15

Sure sufficient, the check handed. It works nice! The device is terrific!

Oh, however wait—as you have got most definitely spotted, that wasn’t an excellent activity
of checking out it. There are tactics wherein the serve as may just give a unconditionally
other end result (as an example, carry an exception) that the check did not test.

Perhaps it is simple to peer it on this instance, but if device will get
greater and extra advanced, it isn’t going to be really easy to eyeball it.
That the place you need to have “code coverage”, checking that your exams
have run all the code.

Now, 100% code protection doesn’t suggest that your code is absolute best or that
it lacks insects. But it does come up with a better level of self belief in
the code and the truth that it’s been run at least one time.

So, how are you able to come with code protection with pytest? It seems that
there is a bundle referred to as pytest-cov on PyPI that you’ll be able to obtain and
set up. Once that is executed, you’ll be able to invoke pytest with the --cov
choice. If you do not say anything else greater than that, you can get a
protection file for each and every a part of the Python library that your program
used, so I strongly recommend you supply an issue to --cov,
specifying which program(s) you need to check. And, you must point out
the listing into which the file must be written. So on this case, you might

pytest --cov=mymul .

Once you have got executed this, you can want to flip the protection file into
one thing human-readable. I recommend the usage of HTML, even if different output
codecs are to be had:

protection html

This creates a listing referred to as htmlcov. Open the index.html
dossier on this listing the usage of your browser, and you can get an online
file appearing (in crimson) the place your program nonetheless lacks protection. Sure
sufficient, on this case, it confirmed that the even-number
trail wasn’t lined. Let’s upload a check to do that:

def test_even_numbers():
   with pytest.raises(NoEvenNumbersHereException):

And as anticipated, protection has now long gone as much as 100%! That’s without a doubt
one thing to realize and have a good time, but it surely doesn’t suggest you have got
reached optimum checking out. You can and must duvet other combos of
arguments and what’s going to occur whilst you go them.


If you have not guessed from my three-part focal point on pytest, I have been
shocked by means of the best way this checking out gadget has been designed.
After years of striking my head in disgrace when speaking about checking out, I have
began to include it into my code, together with in my on-line “Weekly
Python Exercise” path. If I can get into checking out, so are you able to.
And even if I have not lined the entirety pytest gives, you
now must have a just right sense of what it’s and easy methods to get started the usage of it.


  • The pytest website online is at
  • An very good guide at the matter is Brian Okken’s Python checking out with
    , printed by means of Pragmatic Programmers. He additionally has many different
    sources, about pytest and code checking out normally, at
  • Brian’s weblog posts about pytest’s fixtures are informative and helpful to
    any individual in need of to get began with them.


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