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A practical snapshot testing plugin for pytest.
assert snapshot() == "awesome!"
Snapshot testing makes it easy to monitor and approve changes by comparing the result of an operation against a previous reference value.
This project borrows from a lot of other implementations to provide a pythonic, batteries included snapshot testing solution. It also tries to feel as native to pytest
as possible with its integrated review tool.
insta
(rust)
Armin's work was the initial motivation for this project and inspired the reviewing workflow.
jest
(javascript)
Jest enabled the mass adoption of snapshot testing throughout the JavaScript ecosystem and now basically stands as the reference when it comes to what snapshot testing is supposed to look like.
The package can be installed with pip
.
$ pip install pytest-insta
The snapshot
fixture is a function that returns the current value of a snapshot.
def test_hello_world(snapshot):
assert snapshot() == "hello"
$ pytest
...
CREATE snapshots/<prefix>__hello_world__0.txt
Running this test will create a new text file in the snapshots
directory. The next time pytest runs, the test will load the snapshot and compare it to the actual value.
The return value of the snapshot
function can be assigned to a variable and used multiple times.
def test_hello_world(snapshot):
expected = snapshot()
assert expected == "hello"
assert expected.upper() == "HELLO"
By default, each invocation of the snapshot
function will generate its own snapshot.
def test_hello_world(snapshot):
assert snapshot() == "hello"
assert snapshot() == "world"
$ pytest
...
CREATE snapshots/<prefix>__hello_world__0.txt
CREATE snapshots/<prefix>__hello_world__1.txt
You can also name snapshots explicitly. This makes it possible to load a snapshot multiple times during the same test.
def test_hello_world(snapshot):
assert snapshot("message.txt") == "hello"
assert snapshot("message.txt") == "hello"
$ pytest
...
CREATE snapshots/<prefix>__hello_world__message.txt
By default, the snapshot
fixture will store snapshots as .txt
files. By providing a filename or just a specific file extension, you can create snapshots using various formats supported out-of-the-box.
def test_hello_world(snapshot):
assert snapshot("json") == {"hello": "world"}
assert snapshot("expected.json") == {"hello": "world"}
$ pytest
...
CREATE snapshots/<prefix>__hello_world__0.json
CREATE snapshots/<prefix>__hello_world__expected.json
Note that the plugin doesn't diff the snapshot files themselves but actually loads snapshots back into the interpreter and performs comparisons on live python objects. This makes it possible to use snapshot formats that aren't directly human-readable like pure binary files and pickle.
Built-in Formats | Extension | Supported Types |
---|---|---|
Plain text | .txt | str |
Binary | .bin | bytes |
Hexdump | .hexdump | bytes |
Json | .json | Any object serializable by the json module |
Pickle | .pickle | Any object serializable by the pickle module |
The built-in formats should get you covered most of the time but you can also really easily implement your own snapshot formats.
from dataclasses import dataclass
from pathlib import Path
from pytest_insta import Fmt
@dataclass
class Point:
x: int
y: int
class FmtPoint(Fmt[Point]):
extension = ".pt"
def load(self, path: Path) -> Point:
return Point(*map(int, path.read_text().split()))
def dump(self, path: Path, value: Point):
path.write_text(f"{value.x} {value.y}")
def test_hello_world(snapshot):
assert snapshot("pt") == Point(4, 2)
You can create a custom formatter by inheriting from the Fmt
class and defining custom load
and dump
methods. The extension
attribute associates the custom formatter to the specified file extension.
Custom formatters can be defined anywhere in your test suite but it's recommended to keep them in conftest.py
if they're meant to be used across multiple files.
The plugin extends the pytest
cli with a new --insta
option that accommodates the snapshot-testing workflow. The option can be set to one of the following strategies:
update
- Record and update differing snapshotsupdate-new
- Record and create snapshots that don't already existupdate-none
- Don't record or update anythingrecord
- Record and save differing snapshots to be reviewed laterreview
- Record and save differing snapshots then bring up the review toolreview-only
- Don't run tests and only bring up the review toolclear
- Don't run tests and clear all the snapshots to reviewIf the option is not specified, the strategy will default to update-none
if pytest
is running in a CI environment and update-new
otherwise. This makes sure that your pipeline properly catches any snapshot you might forget to push while keeping the development experience seamless by automatically creating snapshots as you're writing tests.
The record
option is useful if you're in the middle of something and your snapshots keep changing. Differing snapshots won't cause tests to fail and will instead be recorded and saved.
$ pytest --insta record
...
RECORD .pytest_cache/d/insta/<prefix>__hello_world__0.txt
NOTICE 1 snapshot to review
When you're done making changes you can use the review
option to bring up the review tool after running your tests. Each differing snapshot will display a diff and let you inspect the new value and the old value in a python repl.
$ pytest --insta review
...
_____________________________ [1/1] _____________________________
old: snapshots/example_hello_world__0.txt
new: .pytest_cache/d/insta/example_hello_world__0.txt
> assert old == new
E assert 'hello' == 'world'
E - world
E + hello
test_example.py:1: test_hello_world
a: accept, r: reject, s: skip
>>>
Finally, the update
option will let you update any differing snapshot according to the current test run, without going through the review tool.
$ pytest --insta update
...
UPDATE snapshots/<prefix>__hello_world__0.txt
It's worth mentioning that the updating, recording and reviewing strategies take into account any filter you might specify with the -k
or -m
options.
The snapshot
fixture hijacks equality checks to record changes. This keeps assertions expressive and readable but introduces two caveats that you need to be aware of.
Right-sided snapshots ❌
If an object's __eq__
method doesn't return NotImplemented
when its type doesn't match the compared object, the snapshot won't be able to record the updated value if it's placed on the right side of the comparison.
Strings return NotImplemented
when compared to non-string objects so the following test will behave as expected.
def test_bad(snapshot):
assert "hello" == snapshot() # This works
However, dataclasses return False
when compared to objects of different types and won't let the snapshot record any changes when placed on the left-side of the comparison.
from dataclasses import dataclass
from pathlib import Path
from pytest_insta import Fmt
@dataclass
class Point:
x: int
y: int
class FmtPoint(Fmt[Point]):
extension = ".pt"
def load(self, path: Path) -> Point:
return Point(*map(int, path.read_text().split()))
def dump(self, path: Path, value: Point):
path.write_text(f"{value.x} {value.y}")
def test_bad(snapshot):
assert Point(4, 2) == snapshot("pt") # This doesn't work
Recommendation ✅
To avoid confusion and keep things consistent, always put snapshots on the left-side of the comparison.
def test_good(snapshot):
assert snapshot() == "hello"
def test_good(snapshot):
assert snapshot("pt") == Point(4, 2)
Not comparing snapshots ❌
Snapshots should first be compared to their actual value before being used in other expressions and assertions.
The comparison records the current value if the snapshot doesn't exist yet. In the following example, the test will fail before the actual comparison and the snapshot will not be generated.
def test_bad(snapshot):
expected = snapshot()
assert expected.upper() == "HELLO" # This doesn't work
assert expected == "hello"
$ pytest
...
> assert expected.upper() == "HELLO"
E AttributeError: 'SnapshotNotfound' object has no attribute 'upper'
Recommendation ✅
Always compare the snapshot to its actual value first and only perform additional operations afterwards.
def test_good(snapshot):
expected = snapshot()
assert expected == "hello"
assert expected.upper() == "HELLO"
Contributions are welcome. Make sure to first open an issue discussing the problem or the new feature before creating a pull request. The project uses poetry
.
$ poetry install
You can run the tests with poetry run pytest
.
$ poetry run pytest
The project must type-check with pyright
. If you're using VSCode the pylance
extension should report diagnostics automatically. You can also install the type-checker locally with npm install
and run it from the command-line.
$ npm run watch
$ npm run check
The code follows the black
code style. Import statements are sorted with isort
.
$ poetry run isort pytest_insta tests
$ poetry run black pytest_insta tests
$ poetry run black --check pytest_insta tests
License - MIT
FAQs
A practical snapshot testing plugin for pytest
We found that pytest-insta demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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