rbcn25-mastering-robotcode

Mastering RobotCode and robot.toml: Best Practices in Real-Life Robot Framework Projects

How to master RobotCode Extension and Command Line Tools in real-life Robot Framework projects.

This workshop covers installation, setup, project structuring, python project managers, robot.toml configuration, key features, utilizing CLI tools, integrating CI/CD processes, and collaborating with distributed teams.

Workshop Overview

This workshop offers an in-depth introduction to the RobotCode Extension and Command Line Tools, focusing on their practical application in real-life Robot Framework projects.

Participants will gain hands-on experience and learn best practices to enhance their test automation workflows.

Key Topics

1. Installation of RobotCode:
   • Step-by-step guide to installing the RobotCode Extension and CLI tools.
   • Install the VSCode extension and create your python .venv.
2. Project Setup with RobotCode:
   • Creating a new example project.
     • Create virtual python environments to separate system interpreter and development venv.
       • This helps with different projects regarding different dependencies.
       • Separation of projects.
     • Creating a requirements.txt with all project dependencies.
       • Put the project’s dependencies into it.
     • robotframework-tidy helps with linting your project.
     • Developer: Reload Window after installing .venv for RobotCode to get the new environment.
     • Log vs. Log To Console
       • Log is preferred as you have everything in one place (Debug Console).
   • Configuring the project environment and RobotCode settings.
     • Debug Settings:
       • Debug: Group Output helps with more debug information
         • "robotcode.debug.groupOutput": true,
       • Debug: Output Timestamps shows you the execution timestamps
         • "robotcode.debug.outputTimestamps": true
       • Put the Debug Settings in the .vscode/settings.json for local settings.
         • Comment in the settings for overwriting them quickly.
       • "robotcode.run.openOutputAfterRun": "log" if you want to auto open the log/report after each run.
       • Debug Python Code:
         • "robotcode.debug.attachPython": true
   • Devcontainer:
     • Helps with creating a standardized environment with fixed versions for testers/developers to have the same environment.
     • Make ports public if you want to display log.html and it does not work out of the box.
   • Debugging Tips:
     • Use Variable Scopes.
     • Change Variable Values in the debug menu by overwriting them.
     • In the Debug Console, you can use Robot Framework Keywords from Commandline.
     • In Debug watches, you can add expressions.
     • #exprmode enables/disables python expression mode (toggle).
     • Use the breakpoint toggles to enable different breakpoint modes.
   • Features:
     • Find Library Keywords by typing LibraryName + . and scroll the keywords.
     • Variables are sorted by the distance in autocompletion.
       • Local scope is closest, then Suite scope, then global scope.
     • Explorer View:
       • Select Keywords Dropdown.
       • View Keyword-Documentation.
       • Insert Keywords or Drag & Drop them.
       • Search within Library-Keywords (F3).
     • Debug Logs:
       • RobotCode Log: Logging of RobotCode Details.
       • RobotCode Language Server Log: Logging of Language Server Details.
         • Helps with your own debugging or reporting issues with detailed information.
   • Structuring the project for scalability and maintainability.
     • Simple Projects:
       • Create a /resources directory with *.resource files for Robot Framework Keywords.
         • This will add /resources to the PYTHON_PATH.
       • Create a /lib directory with *.py files for python keywords.
         • This will add /lib to the PYTHON_PATH.
       • This way you can add .resource and .py keyword files without using the absolute file path.
       • When using different folder names/structures for your project, you need to add the folder paths to your PYTHON_PATH for usage without the full directory path.
       • TIP: Use settings.json for your personal local changes and do not commit to your Git-Repo!
         • These settings are for your personal preference.
       • Enable/Disable “RobotCode Play Buttons” -> Settings-RobotCode-Test Explorer-Enable/Disable.
   • Using Python project managers for efficient dependency management.
     • Project managers help you with:
       • Managing dependencies.
       • Managing execution and development environments.
       • Creating virtual environments.
       • EXAMPLE: hatch
         • Follows the PEP standard.
         • Gives you the opportunity to create test matrices to e.g. run multiple virtual environments in parallel.
   • Best practices in project setup and organization.
     • Use a python package manager to organize your project and set it up in a standardized way.
     • Integrate Conventional Commits for versioning your project and automatically create a Changelog.md.
3. Exploring RobotCode Features:
   • Overview of general features that enhance productivity.
     • RobotFramework Notebook:
       • File -> New File -> RobotFramework Notebook.
       • First Version included in VSCode supporting *.robot Files and Markdown.
       • Uses the REPL, so there are no *** Settings *** or *** Variables *** sections.
       • Helping with Business Analyst Files such as RPA procedures.
     • Robotcode REPL (Read-Evaluate-Print-Loop):
       • Install (if not yet): pip install robotcode-repl.
       • In CLI: use robotcode repl.
       • Type Keywords and Expressions that are directly evaluated.
   • Introduction to new and advanced features.
4. Using robot.toml Configuration:
   • Understanding general configuration settings.
     • robot.toml supports all possible configurations from toml.io.
     • Helps with interaction towards Robot Framework through its CLI API.
     • Every CLI argument from Robot Framework has a configuration analog in robot.toml.
     • There are different ways of defining values in the toml file.
   • Creating configuration profiles for different environments.
     • robotcode config files shows you all the robot.toml configuration files.
     • robot.toml files exist for the user space and project space.
       • Settings in the project space overwrite user space and local space overwrites project space.
     • All configurations for Python = pyproject.toml.
     • All configurations for Robot Framework = robot.toml.
     • Local Configuration for overwriting robot.toml = .robot.toml.
       • This file is not meant to be pushed to Git.
     • Hierarchy of the files:
       • Default user space.
       • Project space.
       • Local space.
     • robotcode config root gives you the root directory, which is dependent on the position of the robot.toml file.
     • robotcode config info gives you information on the config files.
     • robotcode profiles show shows you the configuration with your selected profiles.
     • Run Robot Framework files with specific profiles: robotcode -p profile_a -p profile_b robot.
     • [variables] at the root level of the robot.toml file are used by all profiles.
       • EXCEPT: using profiles with [profiles.profile_a.variables].
         • All variables in here are specific to the profile and ignore the root-level [variables].
       • When using [profiles.profile_a.extend-variables] the root-level variables are extended, meaning:
         • Root-level existing variables are replaced, if specified again.
         • Root-level existing variables are taken into the profile, if not again specified.
         • Profile-specific variables are included as well.
   • robotcode debug.
   • robotcode analyze is a static code analyzer for your project.
     • Analyzer Errors, Warnings, and Hints can be ignored by commenting # robotcode: ignore[KeywordNotFound].
       • This ignoring is indentation dependent!!
     • Resetting the settings can be done by robotcode: reset[KeywordNotFound].

     • Configure within robot.toml:

       [tool.robotcode-analyze.modifiers]
       ignore=[KeywordNotFound]
       

   • Splitting configuration into multiple files for modularity.
5. Command Line Interface (CLI) Tools:
   • Retrieving valuable information about your project.
     • robotcode will give you all commands with descriptions.
     • robotcode discover will give information about Suites, Test Cases.
       • robotcode discover all . to look for whole project information.
       • Filter test cases with robot options.
         • e.g include/exclude tags etc.
       • --format Option for printing results in a wanted format e.g. json for reuse in different projects.
       • Excludes all files that are ignored within .gitignore.
       • Alternative: create .robotignore for excluding it from robotcode discover and speed up the discovery process or exclude local files for personal usage.
   • Analyzing your project to identify improvements.
     • robotcode analyze.
   • Running tests directly from the command line.
   • Implementing git hooks to streamline your development workflow.
   • Best practices for effective CLI usage.
6. Integrating CI/CD Processes:
   • Executing tests within a CI/CD pipeline.
     • Use robot.toml profiles to run CI settings on a local machine.
     • Ensure the CI process is low in complexity and mimics the steps done on the local machine as closely as possible.
   • Debugging test runs in CI/CD environments.
   • Best practices for continuous integration and deployment.
     • Keep the CI pipeline simple and maintainable.
     • Use the same robot.toml profiles for both local and CI environments to ensure consistency.
     • Automate as much as possible to reduce manual intervention and errors.
7. Collaborating with Distributed Teams:
   • Structuring and packaging Robot Framework projects for team collaboration.
   • Sharing and utilizing resources and libraries across multiple teams and projects.
   • Best practices for working in distributed development environments.
     • Step-by-step guide on building your resource files from src/demo via Hatch to create a .wheel file:

       1. Ensure you have Hatch installed:

          pip install hatch
          

       2. Navigate to your project directory:

          cd /path/to/your/project
          

       3. Create a pyproject.toml file in the root of your project with the following content:

          [build-system]
          requires = ["hatchling"]
          build-backend = "hatchling.build"
          
          [project]
          name = "your_project_name"
          version = "0.1.0"
          description = "Your project description"
          readme = "README.md"
          requires-python = ">=3.7"
          license = {text = "MIT"}
          
          [tool.hatch.build.targets.wheel]
          packages = ["src/demo"]
          

       4. Build the .wheel file:

          hatch build
          

       5. The .wheel file will be created in the dist directory. This file can then be uploaded to any package registry or distributed to other teams in different ways.

     • Integrate this process into the CI pipeline, e.g., with every new release:

       • Add the following steps to your CI configuration:

         jobs:
           build:
             runs-on: ubuntu-latest
             steps:
               - uses: actions/checkout@v2
               - name: Set up Python
                 uses: actions/setup-python@v2
                 with:
                   python-version: '3.x'
               - name: Install Hatch
                 run: pip install hatch
               - name: Build wheel
                 run: hatch build
               - name: Upload wheel to registry
                 run: |
                   twine upload dist/*.whl
         

     • Commands for participants to try the distribution with Hatch themselves:

       1. Navigate to your project directory:

          cd /path/to/your/project
          

       2. Create a pyproject.toml file as described above.

       3. Build the .wheel file:

          hatch build
          

       4. Distribute the .wheel file as needed.

Who Should Attend

• Developers, QA engineers, and test automation professionals using Robot Framework.
• Individuals seeking to enhance their skills with RobotCode.
• Teams interested in improving collaboration and efficiency in test automation.

Methodology

The workshop combines lectures, live demonstrations, and hands-on exercises.

Prerequisites

• Basic understanding of Robot Framework.
• Familiarity with Python is beneficial but not mandatory.
• A Notebook with internet connection and Visual Studio Code (or PyCharm) installed.

Lessons Learned

• Install and configure RobotCode and its CLI tools.
• Set up and structure Robot Framework projects effectively.
• Manage projects and dependencies using Python project managers.
• Leverage RobotCode features to optimize workflows.
• Integrate RobotCode tools into CI/CD pipelines.
• Collaborate efficiently within distributed teams.
• Apply best practices throughout test automation projects.

Authors

• Daniel Biehl
• Fabian Tsirogiannis

Links

• RobotCode
• Hatch

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