233 lines
8.5 KiB
Markdown
233 lines
8.5 KiB
Markdown
# Using custom transformers to customize Valet's behavior
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In this lab we will build upon the `dry-run` command to override Valet's default behavior and customize the converted workflow using "custom transformers". Custom transformers can be used to:
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1. Convert items that are not automatically converted.
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2. Convert items that were automatically converted using different actions.
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3. Convert environment variable values differently.
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4. Convert references to runners to use a different runner name in Actions.
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## Prerequisites
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1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your Codespace environment and bootstrap an Azure DevOps project.
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2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
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3. Completed the [audit lab](./2-audit.md).
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4. Completed the [dry-run lab](./3-dry-run.md).
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## Perform a dry run
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We will be performing a dry-run for a pipeline in the bootstrapped Azure DevOps project. We will need to answer the following questions before running this command:
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1. What is the id of the pipeline to convert?
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- __:pipeline_id__. This id can be found by:
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- Navigating to the build pipelines in the bootstrapped Azure DevOps project <https://dev.azure.com/:organization/:project/_build>
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- Selecting the pipeline with the name "valet-custom-transformer-example"
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- Inspecting the URL to locate the pipeline id <https://dev.azure.com/:organization/:project/_build?definitionId=:pipeline_id>
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2. Where do we want to store the result?
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- __./tmp/dry-run-lab__. This can be any path within the working directory that Valet commands are executed from.
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### Steps
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1. Navigate to the codespace terminal
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2. Run the following command from the root directory:
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```bash
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gh valet dry-run azure-devops pipeline --pipeline-id :pipeline_id -o tmp/dry-run-lab
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```
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3. The command will list all the files written to disk when the command succeeds.
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4. View the converted workflow:
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- Find `./tmp/dry-run-lab` in the file explorer pane in codespaces.
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- Click `valet-custom-transformer-example.yml` to open.
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The converted workflow that is generated can be seen below:
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<details>
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<summary><em>Converted workflow 👇</em></summary>
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```yaml
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name: valet-bootstrap/pipelines/valet-custom-transformer-example
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on:
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push:
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branches:
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- "*"
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env:
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BUILDCONFIGURATION: Release
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BuildParameters_RESTOREBUILDPROJECTS: "**/*.csproj"
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jobs:
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Job_1:
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name: Agent job 1
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runs-on: windows-latest
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steps:
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- name: checkout
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uses: actions/checkout@v2
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- uses: actions/checkout@v2
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- name: Use Node 10.16.3
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uses: actions/setup-node@v2
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with:
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node-version: 10.16.3
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- name: Restore
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run: dotnet restore ${{ env.BuildParameters_RESTOREBUILDPROJECTS }}
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- name: Build
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run: dotnet build ${{ env.BuildParameters_RESTOREBUILDPROJECTS }} --configuration ${{ env.BUILDCONFIGURATION }}
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```
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</details>
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_Note_: You can refer to the previous [lab](./3-dry-run.md) to learn about the fundamentals of the `dry-run` command.
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## Custom transformers for build steps
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We can use custom transformers override Valet's default behavior. In this scenario, we may want to override the behavior for converting `DotnetCoreCLI@2` tasks to support parameters that are glob patterns. We will need to answer the following questions before writing a custom transformer:
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1. What is the "identifier" of the step to customize?
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- __DotnetCoreCLI@2__
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2. What is the desired Actions syntax to use instead?
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- After some research, we have determined that the uploading test results as an artifact will be suitable:
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```yaml
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- run: shopt -s globstar; for f in ./**/*.csproj; do dotnet build $f --configuration ${{ env.BUILDCONFIGURATION }} ; done
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shell: bash
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```
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Now we can begin to write the custom transformer. Customer transformers use a DSL built on top of Ruby and should be defined in a file with the `.rb` file extension. You can create this file by running the following command in your codespace terminal:
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```bash
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code transformers.rb
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```
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Next, we will define a `transform` method for the `DotnetCoreCLI@2` identifier by adding the following code to `transformers.rb`:
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```ruby
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transform "DotNetCoreCLI@2" do |item|
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projects = item["projects"]
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command = item["command"]
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run_command = []
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if projects.include?("$")
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command = "build" if command.nil?
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run_command << "shopt -s globstar; for f in ./**/*.csproj; do dotnet #{command} $f #{item['arguments']} ; done"
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else
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run_command << "dotnet #{command} #{item['projects']} #{item['arguments']}"
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end
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{
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run: run_command.join("\n"),
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shell: "bash",
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}
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end
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```
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This method can use any valid ruby syntax and should return a `Hash` that represents the YAML that should be generated for a given step. Valet will use this method to convert a step with the provided identifier and will use the `item` parameter for the original values configured in Azure DevOps.
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Now, we can perform another `dry-run` command and use the `--custom-transformers` CLI option to provide this custom transformer. Run the following command within your codespace terminal:
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```bash
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gh valet dry-run azure-devops pipeline --pipeline-id :pipeline_id -o tmp/dry-run-lab --custom-transformers transformers.rb
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```
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Open the workflow that is generated and inspect the contents. Now, the `DotnetCoreCLI@2` steps are converted using the customized behavior!
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```diff
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- - name: Restore
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- run: dotnet restore ${{ env.BuildParameters_RESTOREBUILDPROJECTS }}
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- - name: Build
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- run: dotnet build ${{ env.BuildParameters_RESTOREBUILDPROJECTS }} --configuration ${{ env.BUILDCONFIGURATION }}
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+ - name: Restore
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+ run: shopt -s globstar; for f in ./**/*.csproj; do dotnet restore $f ; done
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+ shell: bash
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+ - name: Build
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+ run: shopt -s globstar; for f in ./**/*.csproj; do dotnet build $f --configuration ${{ env.BUILDCONFIGURATION }} ; done
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+ shell: bash
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```
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## Custom transformers for environment variables
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We can also use custom transformers to edit the values of environment variables in converted workflows. In our example, we will be updating the `BUILDCONFIGURATION` environment variable to be `Debug` instead of `Release`.
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To do this, add the following code to the `transformers.rb` file.
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```ruby
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env "BUILDCONFIGURATION", "Debug"
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```
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In this example, the first parameter to the `env` method is the environment variable name and the second is the updated value.
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Now, we can perform another `dry-run` command with the `--custom-transformers` CLI option. When you open the converted workflow the `DB_ENGINE` environment variable will be set to `mongodb`:
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```diff
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env:
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- BUILDCONFIGURATION: Release
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+ BUILDCONFIGURATION: Debug
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BuildParameters_RESTOREBUILDPROJECTS: "**/*.csproj"
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```
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## Custom transformers for runners
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Finally, we can use custom transformers to dictate which runners converted workflows should use. To do this we will need to answer the following questions:
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1. What is label of the runner in Azure DevOps to update?
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- __windows-latest__
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2. What is the label of the runner in Actions to use instead?
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- __ubuntu-latest__
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With these questions answered, we can add the following code to the `transformers.rb` file:
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```ruby
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runner "windows-latest", "ubuntu-latest"
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```
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In this example, the first parameter to the `runner` method is the Azure DevOps label and the second is the Actions runner label.
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Now, we can perform another `dry-run` command with the `--custom-transformers` CLI option. When you open the converted workflow the `runs-on` statement will use the customized runner label:
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```diff
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runs-on:
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- - windows-latest
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+ - ubuntu-latest
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```
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At this point of the lab the file contents of `transformers.rb` should match this:
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<details>
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<summary><em>Custom transformers 👇</em></summary>
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```ruby
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transform "DotNetCoreCLI@2" do |item|
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projects = item["projects"]
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command = item["command"]
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run_command = []
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if projects.include?("$")
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command = "build" if command.nil?
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run_command << "shopt -s globstar; for f in ./**/*.csproj; do dotnet #{command} $f #{item['arguments']} ; done"
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else
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run_command << "dotnet #{command} #{item['projects']} #{item['arguments']}"
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end
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{
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shell: "bash",
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run: run_command.join("\n")
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}
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end
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env "BUILDCONFIGURATION", "Debug"
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runner "windows-latest", "ubuntu-latest"
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```
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</details>
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Thats it! At this point you have overridden Valet's default behavior by customizing the conversion of:
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- Build steps
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- Environment variables
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- Runners
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## Next lab
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[Perform a production migration of an Azure DevOps pipeline](5-migrate.md)
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