Test Coverage¶
Writing unit tests for your application lets you check that the code you wrote works the way you expect. Flask provides a test client that simulates requests to the application and returns the response data.
You should test as much of your code as possible. Code in functions only
runs when the function is called, and code in branches, such as if
blocks, only runs when the condition is met. You want to make sure that
each function is tested with data that covers each branch.
The closer you get to 100% coverage, the more comfortable you can be that making a change won’t unexpectedly change other behavior. However, 100% coverage doesn’t guarantee that your application doesn’t have bugs. In particular, it doesn’t test how the user interacts with the application in the browser. Despite this, test coverage is an important tool to use during development.
Note
This is being introduced late in the tutorial, but in your future projects you should test as you develop.
You’ll use pytest and coverage to test and measure your code. Install them both:
$ pip install pytest coverage
Setup and Fixtures¶
The test code is located in the tests
directory. This directory is
next to the flaskr
package, not inside it. The
tests/conftest.py
file contains setup functions called fixtures
that each test will use. Tests are in Python modules that start with
test_
, and each test function in those modules also starts with
test_
.
Each test will create a new temporary database file and populate some data that will be used in the tests. Write a SQL file to insert that data.
INSERT INTO user (username, password)
VALUES
('test', 'pbkdf2:sha256:50000$TCI4GzcX$0de171a4f4dac32e3364c7ddc7c14f3e2fa61f2d17574483f7ffbb431b4acb2f'),
('other', 'pbkdf2:sha256:50000$kJPKsz6N$d2d4784f1b030a9761f5ccaeeaca413f27f2ecb76d6168407af962ddce849f79');
INSERT INTO post (title, body, author_id, created)
VALUES
('test title', 'test' || x'0a' || 'body', 1, '2018-01-01 00:00:00');
The app
fixture will call the factory and pass test_config
to
configure the application and database for testing instead of using your
local development configuration.
import os
import tempfile
import pytest
from flaskr import create_app
from flaskr.db import get_db, init_db
with open(os.path.join(os.path.dirname(__file__), 'data.sql'), 'rb') as f:
_data_sql = f.read().decode('utf8')
@pytest.fixture
def app():
db_fd, db_path = tempfile.mkstemp()
app = create_app({
'TESTING': True,
'DATABASE': db_path,
})
with app.app_context():
init_db()
get_db().executescript(_data_sql)
yield app
os.close(db_fd)
os.unlink(db_path)
@pytest.fixture
def client(app):
return app.test_client()
@pytest.fixture
def runner(app):
return app.test_cli_runner()
tempfile.mkstemp()
creates and opens a temporary file, returning
the file descriptor and the path to it. The DATABASE
path is
overridden so it points to this temporary path instead of the instance
folder. After setting the path, the database tables are created and the
test data is inserted. After the test is over, the temporary file is
closed and removed.
TESTING
tells Flask that the app is in test mode. Flask changes
some internal behavior so it’s easier to test, and other extensions can
also use the flag to make testing them easier.
The client
fixture calls
app.test_client()
with the application
object created by the app
fixture. Tests will use the client to make
requests to the application without running the server.
The runner
fixture is similar to client
.
app.test_cli_runner()
creates a runner
that can call the Click commands registered with the application.
Pytest uses fixtures by matching their function names with the names
of arguments in the test functions. For example, the test_hello
function you’ll write next takes a client
argument. Pytest matches
that with the client
fixture function, calls it, and passes the
returned value to the test function.
Factory¶
There’s not much to test about the factory itself. Most of the code will be executed for each test already, so if something fails the other tests will notice.
The only behavior that can change is passing test config. If config is not passed, there should be some default configuration, otherwise the configuration should be overridden.
from flaskr import create_app
def test_config():
assert not create_app().testing
assert create_app({'TESTING': True}).testing
def test_hello(client):
response = client.get('/hello')
assert response.data == b'Hello, World!'
You added the hello
route as an example when writing the factory at
the beginning of the tutorial. It returns “Hello, World!”, so the test
checks that the response data matches.
Database¶
Within an application context, get_db
should return the same
connection each time it’s called. After the context, the connection
should be closed.
import sqlite3
import pytest
from flaskr.db import get_db
def test_get_close_db(app):
with app.app_context():
db = get_db()
assert db is get_db()
with pytest.raises(sqlite3.ProgrammingError) as e:
db.execute('SELECT 1')
assert 'closed' in str(e.value)
The init-db
command should call the init_db
function and output
a message.
def test_init_db_command(runner, monkeypatch):
class Recorder(object):
called = False
def fake_init_db():
Recorder.called = True
monkeypatch.setattr('flaskr.db.init_db', fake_init_db)
result = runner.invoke(args=['init-db'])
assert 'Initialized' in result.output
assert Recorder.called
This test uses Pytest’s monkeypatch
fixture to replace the
init_db
function with one that records that it’s been called. The
runner
fixture you wrote above is used to call the init-db
command by name.
Authentication¶
For most of the views, a user needs to be logged in. The easiest way to
do this in tests is to make a POST
request to the login
view
with the client. Rather than writing that out every time, you can write
a class with methods to do that, and use a fixture to pass it the client
for each test.
class AuthActions(object):
def __init__(self, client):
self._client = client
def login(self, username='test', password='test'):
return self._client.post(
'/auth/login',
data={'username': username, 'password': password}
)
def logout(self):
return self._client.get('/auth/logout')
@pytest.fixture
def auth(client):
return AuthActions(client)
With the auth
fixture, you can call auth.login()
in a test to
log in as the test
user, which was inserted as part of the test
data in the app
fixture.
The register
view should render successfully on GET
. On POST
with valid form data, it should redirect to the login URL and the user’s
data should be in the database. Invalid data should display error
messages.
import pytest
from flask import g, session
from flaskr.db import get_db
def test_register(client, app):
assert client.get('/auth/register').status_code == 200
response = client.post(
'/auth/register', data={'username': 'a', 'password': 'a'}
)
assert response.headers["Location"] == "/auth/login"
with app.app_context():
assert get_db().execute(
"SELECT * FROM user WHERE username = 'a'",
).fetchone() is not None
@pytest.mark.parametrize(('username', 'password', 'message'), (
('', '', b'Username is required.'),
('a', '', b'Password is required.'),
('test', 'test', b'already registered'),
))
def test_register_validate_input(client, username, password, message):
response = client.post(
'/auth/register',
data={'username': username, 'password': password}
)
assert message in response.data
client.get()
makes a GET
request
and returns the Response
object returned by Flask. Similarly,
client.post()
makes a POST
request, converting the data
dict into form data.
To test that the page renders successfully, a simple request is made and
checked for a 200 OK
status_code
. If
rendering failed, Flask would return a 500 Internal Server Error
code.
headers
will have a Location
header with the login
URL when the register view redirects to the login view.
data
contains the body of the response as bytes. If
you expect a certain value to render on the page, check that it’s in
data
. Bytes must be compared to bytes. If you want to compare text,
use get_data(as_text=True)
instead.
pytest.mark.parametrize
tells Pytest to run the same test function
with different arguments. You use it here to test different invalid
input and error messages without writing the same code three times.
The tests for the login
view are very similar to those for
register
. Rather than testing the data in the database,
session
should have user_id
set after logging in.
def test_login(client, auth):
assert client.get('/auth/login').status_code == 200
response = auth.login()
assert response.headers["Location"] == "/"
with client:
client.get('/')
assert session['user_id'] == 1
assert g.user['username'] == 'test'
@pytest.mark.parametrize(('username', 'password', 'message'), (
('a', 'test', b'Incorrect username.'),
('test', 'a', b'Incorrect password.'),
))
def test_login_validate_input(auth, username, password, message):
response = auth.login(username, password)
assert message in response.data
Using client
in a with
block allows accessing context variables
such as session
after the response is returned. Normally,
accessing session
outside of a request would raise an error.
Testing logout
is the opposite of login
. session
should
not contain user_id
after logging out.
def test_logout(client, auth):
auth.login()
with client:
auth.logout()
assert 'user_id' not in session
Blog¶
All the blog views use the auth
fixture you wrote earlier. Call
auth.login()
and subsequent requests from the client will be logged
in as the test
user.
The index
view should display information about the post that was
added with the test data. When logged in as the author, there should be
a link to edit the post.
You can also test some more authentication behavior while testing the
index
view. When not logged in, each page shows links to log in or
register. When logged in, there’s a link to log out.
import pytest
from flaskr.db import get_db
def test_index(client, auth):
response = client.get('/')
assert b"Log In" in response.data
assert b"Register" in response.data
auth.login()
response = client.get('/')
assert b'Log Out' in response.data
assert b'test title' in response.data
assert b'by test on 2018-01-01' in response.data
assert b'test\nbody' in response.data
assert b'href="/1/update"' in response.data
A user must be logged in to access the create
, update
, and
delete
views. The logged in user must be the author of the post to
access update
and delete
, otherwise a 403 Forbidden
status
is returned. If a post
with the given id
doesn’t exist,
update
and delete
should return 404 Not Found
.
@pytest.mark.parametrize('path', (
'/create',
'/1/update',
'/1/delete',
))
def test_login_required(client, path):
response = client.post(path)
assert response.headers["Location"] == "/auth/login"
def test_author_required(app, client, auth):
# change the post author to another user
with app.app_context():
db = get_db()
db.execute('UPDATE post SET author_id = 2 WHERE id = 1')
db.commit()
auth.login()
# current user can't modify other user's post
assert client.post('/1/update').status_code == 403
assert client.post('/1/delete').status_code == 403
# current user doesn't see edit link
assert b'href="/1/update"' not in client.get('/').data
@pytest.mark.parametrize('path', (
'/2/update',
'/2/delete',
))
def test_exists_required(client, auth, path):
auth.login()
assert client.post(path).status_code == 404
The create
and update
views should render and return a
200 OK
status for a GET
request. When valid data is sent in a
POST
request, create
should insert the new post data into the
database, and update
should modify the existing data. Both pages
should show an error message on invalid data.
def test_create(client, auth, app):
auth.login()
assert client.get('/create').status_code == 200
client.post('/create', data={'title': 'created', 'body': ''})
with app.app_context():
db = get_db()
count = db.execute('SELECT COUNT(id) FROM post').fetchone()[0]
assert count == 2
def test_update(client, auth, app):
auth.login()
assert client.get('/1/update').status_code == 200
client.post('/1/update', data={'title': 'updated', 'body': ''})
with app.app_context():
db = get_db()
post = db.execute('SELECT * FROM post WHERE id = 1').fetchone()
assert post['title'] == 'updated'
@pytest.mark.parametrize('path', (
'/create',
'/1/update',
))
def test_create_update_validate(client, auth, path):
auth.login()
response = client.post(path, data={'title': '', 'body': ''})
assert b'Title is required.' in response.data
The delete
view should redirect to the index URL and the post should
no longer exist in the database.
def test_delete(client, auth, app):
auth.login()
response = client.post('/1/delete')
assert response.headers["Location"] == "/"
with app.app_context():
db = get_db()
post = db.execute('SELECT * FROM post WHERE id = 1').fetchone()
assert post is None
Running the Tests¶
Some extra configuration, which is not required but makes running
tests with coverage less verbose, can be added to the project’s
setup.cfg
file.
[tool:pytest]
testpaths = tests
[coverage:run]
branch = True
source =
flaskr
To run the tests, use the pytest
command. It will find and run all
the test functions you’ve written.
$ pytest
========================= test session starts ==========================
platform linux -- Python 3.6.4, pytest-3.5.0, py-1.5.3, pluggy-0.6.0
rootdir: /home/user/Projects/flask-tutorial, inifile: setup.cfg
collected 23 items
tests/test_auth.py ........ [ 34%]
tests/test_blog.py ............ [ 86%]
tests/test_db.py .. [ 95%]
tests/test_factory.py .. [100%]
====================== 24 passed in 0.64 seconds =======================
If any tests fail, pytest will show the error that was raised. You can
run pytest -v
to get a list of each test function rather than dots.
To measure the code coverage of your tests, use the coverage
command
to run pytest instead of running it directly.
$ coverage run -m pytest
You can either view a simple coverage report in the terminal:
$ coverage report
Name Stmts Miss Branch BrPart Cover
------------------------------------------------------
flaskr/__init__.py 21 0 2 0 100%
flaskr/auth.py 54 0 22 0 100%
flaskr/blog.py 54 0 16 0 100%
flaskr/db.py 24 0 4 0 100%
------------------------------------------------------
TOTAL 153 0 44 0 100%
An HTML report allows you to see which lines were covered in each file:
$ coverage html
This generates files in the htmlcov
directory. Open
htmlcov/index.html
in your browser to see the report.
Continue to Deploy to Production.