R: Snapshot testing

expect_snapshot {testthat} | R Documentation

## Snapshot testing

### Description

Snapshot tests (aka golden tests) are similar to unit tests except that the expected result is stored in a separate file that is managed by testthat. Snapshot tests are useful for when the expected value is large, or when the intent of the code is something that can only be verified by a human (e.g. this is a useful error message). Learn more in `vignette("snapshotting")`.

- `expect_snapshot()` captures all messages, warnings, errors, and output from code.

- `expect_snapshot_output()` captures just output printed to the console.

- `expect_snapshot_error()` captures just error messages.

- `expect_snapshot_value()` captures the return value.

(These functions supersede `verify_output()`, `expect_known_output()`, `expect_known_value()`, and `expect_known_hash()`.)

### Usage

    expect_snapshot(x, cran = FALSE)

    expect_snapshot_output(x, cran = FALSE)

    expect_snapshot_error(x, class = "error", cran = FALSE)

    expect_snapshot_value(
      x,
      style = c("json", "json2", "deparse", "serialize"),
      cran = FALSE
    )

### Arguments

`x` | Code to evaluate.
`cran` | Should these expectations be verified on CRAN? By default, they are not, because snapshot tests tend to be fragile because they often rely on minor details of dependencies. Even on CRAN, the expectations will still fail if `x` errors.
`class` | Expected class of condition, e.g. use `error` for errors, `warning` for warnings, `message` for messages. The expectation will always fail (even on CRAN) if a condition of this class isn't seen when executing `x`.
`style` | Serialization style to use: `json` uses `jsonlite::fromJSON()` and `jsonlite::toJSON()`. This produces the simplest output but only works for relatively simple objects. `json2` uses `jsonlite::serializeJSON()` and `jsonlite::unserializeJSON()` which are more verbose but work for a wider range of type. `deparse` uses `deparse()`, which generates a depiction of the object using R code. `serialize()` produces a binary serialization of the object using `serialize()`. This is all but guaranteed to work for any R object, but produces a completely opaque serialization.

### Workflow

The first time that you run a snapshot expectation it will run `x`, capture the results, and record in `tests/testthat/snap/{test}.json`. Each test file gets its own snapshot file, e.g. `test-foo.R` will get `snap/foo.json`.

It's important to review the JSON files and commit them to git. They are designed to be human readable, and you should always review new additions to ensure that the salient information has been capture. They should also be carefully reviewed in pull requests, to make sure that snapshots have updated in the expected way.

On subsequent runs, the result of `x` will be compared to the value stored on disk. If it's different, the expectation will fail, and a new file `snap/{test}.new.json` will be created. If the change was deliberate, you can approve the change with `snapshot_accept()` and then the tests will pass the next time you run them.

[Package testthat version 3.0.0 Index]