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Snapshot testing library.

Project description

SnappierShot

Add snapshot testing to your testing toolkit.

Installation

$ pip install snappiershot

Configuration

SnappierShot is following the trend of packages in performing project-wide configuration through the pyproject.toml file established by PEP 518.

Within the pyproject.toml file, all SnappierShot configuration can be found under the [tool.snappiershot] heading. While the [tool.snappiershot] heading is optional, the [tool.poetry.plugins.pytest11] heading must also be included.

Example (with default values):

[tool.poetry.plugins.pytest11]
snappiershot = "snappiershot.plugins.pytest"

[tool.snappiershot]
file_format = "json"
float_absolute_tolerance = 1e-6
float_relative_tolerance = 0.001
full_diff = false
json_indentation = 4

Currently, the only allowed file format is JSON.

Usage

SnappierShot allows you to take a "snapshot" of data the first time that a test is run, and stores it nearby in a .snapshots directory as a JSON. Then, for all subsequent times that test is run, the data is asserted to "match" the original data.

SnappierShot uses metadata to find tests stored in each snapshot file. Metadata is defined as the inputs to a test method.

  • If the metadata is not found, a new file is Written.
  • If the metadata is found, the contents of the snapshot are checked and can either Pass or Fail.
  • If a snapshot file is found but the test isn't run, then the test is marked as Unchecked

Best Practices

  • Do not run assert_match within a loop
  • Do not try to snapshot uninstantiated classes/objects or use them as inputs to a test method
  • If an unsupported object type cannot be recorded, see CONTRIBUTING.md for instructions on how to contribute to the project
    • __snapshot__ is a workaround described below

Pytest Examples

from snappiershot import Snapshot

def test_basic(snapshot: Snapshot):
    """ Will do a basic snapshotting of one value with no metadata """
    # Arrange
    x = 1
    y = 2

    # Act
    result = x + y

    # Assert
    snapshot.assert_match(result)

def test_ignore_metadata(snapshot: Snapshot, input_to_ignore: str = "ignore me"):
    """ Test that metadata gets ignored """
    # Arrange
    x = 1
    y = 2
    ignored_input = ["input_to_ignore"]

    # Act
    result = x + y

    # Assert
    snapshot.assert_match(result, ignore=ignored_input)

No Test Runner Example

from snappiershot import Snapshot

def test_no_pytest_runner():
    """ Run test without pytest runner """
    # Arrange
    x = 1
    y = 2

    # Act
    result = x + y

    # Assert
    with Snapshot() as snapshot:
        snapshot.assert_match(result)

Custom Encoding and Override Examples

__snapshot__ overrides serializing behavior for class objects being recorded. Some of its potential use cases:

  • Partially recording class objects with many unnecessary properties
  • Skipping over encoding an object by returning a string
from snappiershot import Snapshot
from pytest import fixture

class TestClass1:
  def __init__(self):
    self.a = 1
    self.b = 2

  def __snapshot__(self) -> dict:
    encoding = {
      "a": self.a,
      "b": self.b,
    }
    return encoding

class TestClass2:
  def __init__(self):
    self.a = 1
    self.b = 2

  def __snapshot__(self) -> str:
    encoding = "ENCODING SKIPPED"
    return encoding

@fixture
def class_input1() -> TestClass1:
  class_input1 = TestClass1()
  return class_input1

@fixture
def class_input2() -> TestClass2:
  class_input2 = TestClass2()
  return class_input2

def test_class1(class_input1: TestClass1, snapshot: Snapshot):
    """ Test encoding snapshot and metadata for a custom class with a dictionary override"""

    # Act
    result = class_input1

    # Assert
    snapshot.assert_match(result)

def test_class2(class_input2: TestClass2, snapshot: Snapshot):
    """ Test encoding snapshot and metadata for a custom class with a string override """

    # Act
    result = class_input2

    # Assert
    snapshot.assert_match(result)

Raises

Snappiershot also allows you to record errors that are raised during the execution of a code block. This allows you to track how and when errors are reported more easily.

def fallible_function():
    """ A function with an error state. """
    raise RuntimeError("An error occurred!")


def test_fallible_function(snapshot):
    """ Test that errors are being reported as expected"""
    # Arrange

    # Act & Assert
    with snapshot.raises(RuntimeError):
        fallible_function()

Support Types:

  • Primitives (bool, int, float, None, str)
  • Numerics (complex)
  • Collections (lists, tuples, sets)
  • Dictionaries
  • Classes (with an underlying __dict__, __slots__, or to_dict)
  • Unit types from the pint package
  • Classes with custom encoding (by defining a __snapshot__ method)

Contributing

See CONTRIBUTING.md

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