Getting started with Allure Pytest

Generate beautiful HTML reports using Allure Report and your pytest tests.

Allure Report Pytest Example

INFO

Check out the example project at github.com/allure-examples/pytest-pip to see Allure Pytest in action.

Setting up

1. Prepare your project

These instructions depend on whether you have some tests already or you're just starting a project.

Adding Allure Pytest to an existing project

If you have some pytest tests, and you want to be able to use Allure Report with them:

Install the Allure Report command-line tool, if it is not yet installed in your operating system. Note that Allure Report requires Java, see the installation instructions.
Open a terminal and go to the project directory. For example:
bash
```
cd /home/user/myproject
```
If necessary for your system configuration, activate the virtual Python environment for your project. For example, if the project uses a venv environment, the command to activate it may look like this:
bash
```
source .venv/bin/activate
```
This step is not necessary if you are using the system Python environment.
Install the Allure Pytest adapter.
bash
```
pip install allure-pytest
```

Starting a new project with Allure Pytest

If you are starting a new project which will contain pytest tests:

Install the Allure Report command-line tool, if it is not yet installed in your operating system. Note that Allure Report requires Java, see the installation instructions.
Create a directory for the project.
Open a terminal and go to the project directory. For example:
bash
```
cd /home/user/myproject
```
If necessary, create and activate virtual Python environment for your project. For example, the commands to create and activate a venv environment may look like this:
bash
```
python -m venv .venv
source .venv/bin/activate
```
This step is not necessary if you are going to use the system Python environment in the project.
Write your tests, following the official pytest documentation and, optionally, using some extended features provided by Allure Pytest, see Writing tests.

2. Run tests

When running your tests, specify a path for the test results directory in the --alluredir command-line argument. For example:

bash

python -m pytest --alluredir allure-results

This will save necessary data into the test results directory. If the directory already exists, the new files will be added to the existing ones, so that a future report will be based on them all.

3. Generate a report

Finally, run Allure to convert the test results into an HTML report. This will automatically open your browser to view the report.

bash

allure serve allure-results

Replace allure-results with the path to the directory specified in the outputFolder setting of the reporter, see Configuration.

There are some options that can affect how the report is generated. Run allure --help for the full list of options.

Writing tests

The Allure Pytest adapter not only collects the data provided by pytest's standard features, but also provides additional features for writing even better tests. This section lists the most notable ways to improve your tests, using both pytest's and Allure Pytest's features.

With Allure Pytest, you can:

provide description, links and other metadata,
organize tests into hierarchies,
divide the test into smaller, easier-to-read test steps,
describe parameters used when running parametrized tests,
add readable titles to fixtures,
make the test save screenshots and other files during execution,
select which tests to run via a test plan file.

Specify description, links and other metadata

There is a lot of metadata you can add to each test so that it would appear in the report. See the reference for more details.

For each of the metadata fields, there are multiple ways to assign it.

Call an Allure's function inside the test function's body. This way is called “dynamic” because it allows you to construct strings and other values at runtime before passing to the methods.
Use an Allure's function as a decorator on the test function or a test class.
Add an Allure's function as a pytest mark to a module or a package (see the Marking whole classes or modules section in pytest documentation).

TIP

If you set the fields using the decorators or pytest marks, you can then select and run tests by some metadata fields, see Options affecting test selection.

Decorators APIRuntime API

python

import allure

@allure.title("Test Authentication")
@allure.description("This test attempts to log into the website using a login and a password. Fails if any error happens.\n\nNote that this test does not test 2-Factor Authentication.")
@allure.tag("NewUI", "Essentials", "Authentication")
@allure.severity(allure.severity_level.CRITICAL)
@allure.label("owner", "John Doe")
@allure.link("https://dev.example.com/", name="Website")
@allure.issue("AUTH-123")
@allure.testcase("TMS-456")
def test_authentication():
    ...

python

import allure

def test_authentication():
    allure.dynamic.title("Test Authentication")
    allure.dynamic.description("This test attempts to log into the website using a login and a password. Fails if any error happens.\n\nNote that this test does not test 2-Factor Authentication.")
    allure.dynamic.tag("NewUI", "Essentials", "Authentication")
    allure.dynamic.severity(allure.severity_level.CRITICAL)
    allure.dynamic.label("owner", "John Doe")
    allure.dynamic.link("https://dev.example.com/", name="Website")
    allure.dynamic.issue("AUTH-123")
    allure.dynamic.testcase("TMS-456")
    ...

Organize tests

As described in Improving navigation in your test report, Allure supports multiple ways to organize tests into hierarchical structures. Allure Pytest provides functions to assign the relevant fields to tests either by adding decorators or marks or by calling the “dynamic” functions (same as for the metadata fields).

To specify a test's location in the behavior-based hierarchy:

Decorators APIRuntime API

python

import allure

@allure.epic("Web interface")
@allure.feature("Essential features")
@allure.story("Authentication")
def test_authentication():
    ...

python

import allure

def test_authentication():
    allure.dynamic.epic("Web interface")
    allure.dynamic.feature("Essential features")
    allure.dynamic.story("Authentication")
    ...

To specify a test's location in the suite-based hierarchy:

Decorators APIRuntime API

python

import allure

@allure.parent_suite("Tests for web interface")
@allure.suite("Tests for essential features")
@allure.sub_suite("Tests for authentication")
def test_authentication():
    ...

python

import allure

def test_authentication():
    allure.dynamic.parent_suite("Tests for web interface")
    allure.dynamic.suite("Tests for essential features")
    allure.dynamic.sub_suite("Tests for authentication")
    ...

A test's location in the package-based hierarchy is defined by the fully qualified named of the classes and functions they are declared in, with common prefixes shown as parent packages.

Divide a test into steps

Allure Pytest provides two ways of creating steps and sub-steps: “decorated steps” and “context steps”, both implemented by allure.step().

Decorated stepsContext steps

python

import allure

def test_example():
    steps = Steps()
    steps.step1()
    steps.step2()

class Steps:
    @allure.step("Step 1")
    def step1(self):
        ...

    @allure.step("Step 2")
    def step2(self):
        ...

python

import allure

def test_example():
    with allure.step("Step 1"):
        ...

    with allure.step("Step 2"):
        ...

Describe parametrized tests

When using the parametrized tests pattern, Allure Pytest automatically adds the parameter values to the test report. Allure supports all the methods of parametrizing tests supported by pytest, including declaring parameters for fixtures.

Additionally, you can:

incorporate a parameter's value into the test titles, see title();
manually add a pseudo-parameter, see parameter().
override a parameter's value with a more readable representation, see parameter();

python

from os.path import basename, expanduser

import allure
import pytest


@pytest.mark.parametrize("login", [
    "johndoe",
    "[email protected]",
])
def test_authentication(login):
    ...


def test_authentication_with_empty_login():
    allure.dynamic.parameter("login", "(empty)")
    ...


@pytest.mark.parametrize("ssh_key", [
    expanduser("~/.ssh/id_rsa1"),
    expanduser("~/.ssh/id_rsa2"),
    expanduser("~/.ssh/id_rsa3"),
])
def test_authentication_with_ssh_key(ssh_key):
    allure.dynamic.parameter("ssh_key", basename(ssh_key))
    ...

Describe fixtures

The pytest's concept of fixtures provides a way for each test to define features it requires by just specifying function arguments with their names. Some fixtures are provided by pytest itself, others can be provided by additional libraries or your own code. See the pytest documentation for more details.

When displaying a test in a test report, Allure displays operations related to fixtures similarly to how it displays test steps. To make it easier to understand a fixture's purpose, you can specify its title using the @allure.title() decorator.

python

import allure
import pytest

@pytest.fixture()
@allure.title("Prepare for the test")
def my_fixture():
    ...  # set up
    yield
    ...  # tear down

def test_with_my_fixture(my_fixture):
    ...

Allure Report Pytest Fixtures

Attach screenshots and other files

You can attach any sorts of files to your Allure report. For example, a popular way to make a report easier to understand is to attach a screenshot of the user interface at a certain point. To do so, use allure.attach() or allure.attach.file().

python

import allure
from pathlib import Path

def test_attach(page):
    page.goto("https://example.com/")
    png_bytes = page.screenshot()
    allure.attach(
        png_bytes,
        name="full-page",
        attachment_type=allure.attachment_type.PNG
    )

def test_attach_file(page):
    page.goto("https://example.com/")
    png_bytes = page.screenshot()
    Path("full-page.png").write_bytes(png_bytes)
    allure.attach.file(
        "full-page.png",
        name="full-page",
        attachment_type=allure.attachment_type.PNG
    )

By default, Allure Pytest adds the following data as attached pseudo-files:

Attachment name	Contents
`stdout`	All data that was written to `sys.stdout`, e.g., via `print(...)`.
`stderr`	All data that was written to `sys.stderr`, e.g., via `print(..., file=sys.stderr)`.
`log`	All data that was logged to the standard logging mechanism, e.g., via `logging.debug(...)`.

This behavior can be disabled by the --allure-no-capture option.

Select tests via a test plan file

If the ALLURE_TESTPLAN_PATH environment variable is defined and points to an existing file, pytest will only run tests listed in this file.

Here's an example of running tests according to a file named testplan.json:

MacOS/LinuxWindows

bash

export ALLURE_TESTPLAN_PATH=testplan.json
python -m pytest

powershell

$Env:ALLURE_TESTPLAN_PATH = "testplan.json"
python -m pytest

Environment information

For the main page of the report, you can collect various information about the environment in which the tests were executed.

For example, it is a good idea to use this to remember the OS version and Python version. This may help the future reader investigate bugs that are reproducible only in some environments.

Allure Report Environments Widget

To provide environment information, put a file named environment.properties into the allure-results directory after running the tests. See the example in Environment file.

Note that this feature should be used for properties that do not change for all tests in the report. If you have properties that can be different for different tests, consider using Parametrized tests.

Getting started with Allure Pytest

Setting up

1. Prepare your project

Adding Allure Pytest to an existing project

Starting a new project with Allure Pytest

2. Run tests

3. Generate a report

Writing tests

Specify description, links and other metadata

Organize tests

Divide a test into steps

Describe parametrized tests

Describe fixtures

Attach screenshots and other files

Select tests via a test plan file

Environment information

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Allure TestOps

Company

Getting started with Allure Pytest ​

Setting up ​

1. Prepare your project ​

Adding Allure Pytest to an existing project ​

Starting a new project with Allure Pytest ​

2. Run tests ​

3. Generate a report ​

Writing tests ​

Specify description, links and other metadata ​

Organize tests ​

Divide a test into steps ​

Describe parametrized tests ​

Describe fixtures ​

Attach screenshots and other files ​

Select tests via a test plan file ​

Environment information ​

Powered by

Join our newsletter

Allure TestOps

Company

Getting started with Allure Pytest

Setting up

1. Prepare your project

Adding Allure Pytest to an existing project

Starting a new project with Allure Pytest

2. Run tests

3. Generate a report

Writing tests

Specify description, links and other metadata

Organize tests

Divide a test into steps

Describe parametrized tests

Describe fixtures

Attach screenshots and other files

Select tests via a test plan file

Environment information