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When debugging is started without a launch.json file, VS Code looks at the active editor and based on the language mode of the editor decides what debug extension to use. However, for some languages, multiple debug extensions are possible, and in that case, VS Code prompts you to choose one of them. To make debugging smoother, VS Code now remembers the chosen debugger per file, so that the next time you start debugging, the session starts without any prompts.

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We have started working on providing a built-in interactive window experience on top of the notebook ecosystem and the Jupyter extension has adopted it behind a setting jupyter.enableNativeInteractiveWindow. If the feature is enabled, the Jupyter extension will open the built-in editor instead of the webview implementation, when running code from Python files or directly launching from the Command Palette. The built-in editor works with your customized keybindings/keymaps or language extensions since it's deeply integrated with the workbench.

Finally, register the terminal profile provider that will return the set of options used to create the terminal. The options can be either the standard process-based TerminalOptions or the custom ExtensionTerminalOptions:

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Note you must make sure the version of the ginkgo cli you install is the same as the version of Ginkgo in your go.mod file. You can do this by running go install from your package.

Ginkgo hooks into Go's existing testing infrastructure. That means that Ginkgo specs live in *_test.go files, just like standard go tests. However, instead of using func TestX(t *testing.T) to write your tests you use the Ginkgo and Gomega DSLs.

First, ginkgo bootstrap generates a new test file and places it in the books_test package. That small detail is actually quite important so let's take a brief detour to discuss how Go organizes code in general, and test packages in particular.

Go code is organized into modules. A module is typically associated with a version controlled repository and is comprised of a series of versioned packages. Each package is typically associated with a single directory within the module's file tree containing a series of source code files. When testing Go code, unit tests for a package typically reside within the same directory as the package and are named *_test.go. Ginkgo follows this convention. It's also possible to construct test-only packages comprised solely of *_test.go files. For example, module-level integration tests typically live in their own test-only package directory and exercise the various packages of the module as a whole. As Ginkgo simply builds on top of Go's existing test infrastructure, this usecase is supported and encouraged as well.

OK back to our bootstrap file. After the package books_test declaration we import the ginkgo and gomega packages into the test's top-level namespace by performing a . dot-import. Since Ginkgo and Gomega are DSLs this makes the tests more natural to read. If you prefer, you can avoid the dot-import via ginkgo bootstrap --nodot. Throughout this documentation we'll assume dot-imports.

While you can add all your specs directly into books_suite_test.go you'll generally prefer to place your specs in separate files. This is particularly true if you have packages with multiple files that need to be tested. Let's say our book package includes a book.go model and we'd like to test its behavior. We can generate a test file like so:

As with the bootstrapped suite file, this test file is in the separate books_test package and dot-imports both ginkgo and gomega. Since we're testing the external interface of books Ginkgo adds an import statement to pull the books package into the test.

By default, Go does not allow you to invoke bare functions at the top-level of a file. Ginkgo gets around this by having its node DSL functions return a value that is intended to be discarded. This allows us to write var _ = Describe(...) at the top-level which satisfies Go's top-level policies.

We're, admittedly, jumping ahead a bit here by introducing a few new concepts that we'll dig into more later. The JustAfterEach closure in this container will always run after the subject closure but before the AfterEach closure. When it runs it will check if the current spec has failed (CurrentSpecReport().Failed()) and, if a failure was detected, it will download a dump of the database dbClient.Dump() and attach it to the spec's report AddReportEntry(). It's important that this runs before the dbClient.Clear() invocation in AfterEach - so we use a JustAfterEach. Of course, we could have inlined this diagnostic behavior into our AfterEach.

Ginkgo supports suite-level setup and cleanup through two specialized suite setup nodes: BeforeSuite and AfterSuite. These suite setup nodes must be called at the top-level of the suite and cannot be nested in containers. Also there can be at most one BeforeSuite node and one AfterSuite node per suite. It is idiomatic to place the suite setup nodes in the Ginkgo bootstrap suite file.

Let's continue to build out our book tests. Books can be stored and retrieved from an external database and we'd like to test this behavior. To do that, we'll need to spin up a database and set up a client to access it. We can do that BeforeEach spec - but doing so would be prohibitively expensive and slow. Instead, it would be more efficient to spin up the database just once when the suite starts. Here's how we'd do it in our books_suite_test.go file:

Ginkgo's default behavior is to only randomize the order of top-level containers -- the specs within those containers continue to run in the order in which they are specified in the test files. This is helpful when developing specs as it mitigates the cognitive overload of having specs within a container continuously change the order in which they run during a debugging session.

It's a common pattern to have setup and cleanup code at the outer-most level of a suite that is intended to ensure that every spec runs from with a clean slate. For example, we may be testing our library service and want to ensure that each spec begins with the same library setup. We might write something like this at the top level of our suite file:

Ginkgo allows you to filter specs based on their source code location from the command line. You do this using the ginkgo --focus-file and ginkgo --skip-file flags. Ginkgo will only run specs that are in files that do match the --focus-file filter and don't match the --skip-file filter. You can provide multiple --focus-file and --skip-file flags. The --focus-files will be ORed together and the --skip-files will be ORed together.

You can specify multiple comma-separated LINE and LINE1-LINE2 arguments in a single --focus-file/--skip-file (e.g. --focus-file=foo:1,2,10-12 will apply filters for line 1, line 2, and the range [10-12)). To specify multiple files, pass in multiple --focus-file or --skip-file flags.

These Progress Reports can also show you a preview of the running source code, but only if Ginkgo can find your source files. If need be you can tell Ginkgo where to look for source files by specifying --source-root.

The previous two chapters covered how Ginkgo specs are written and how Ginkgo specs run. This chapter is all about output. We'll cover how Ginkgo reports on spec suites and how Ginkgo can help you profile your spec suites.

The resulting JSON file encodes an array of types.Report. Each entry in that array lists detailed information about an individual spec suite and includes a list of types.SpecReport that captures detailed information about each spec. These types are documented in godoc.

By default, when any of these command-line report flags are provided Ginkgo will generate a single report file, per format, at the passed-in file name. If Ginkgo is running multiple suites (e.g. ginkgo -r --json-report=report.json) then all the suite reports will be encoded in the single report file.

When generating separate reports with: ginkgo -r --json-report=report.json --output-dir= --keep-separate-reports Ginkgo will create the directory (if necessary), and place a report file per package in the directory. These reports will be namespaced with the name of the package: PACKAGE_NAME_report.json. 041b061a72


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