Integrating DCM Dashboards

This guide walks you through the complete process of integrating your project with DCM Dashboards from creating a project and choosing an upload strategy, to uploading your analysis results and generating reports.

1. Create Your First Project

A project in the Dashboards is expected to represent a single entrypoint from which the tool is being run. For example, if you run the tool from the root of your repository/package, there needs to be only one project. But if you have multiple packages in your repository and run DCM in each package separately, then you need to create a project for each package.

To create a new project:

1. Click the + Add project button.
2. Enter a project name.
3. Click Add project.

The new project will appear immediately in the list.

Uploading only from a single branch is supported right now, but if you want to upload from multiple branches (e.g. main and feature-branch), consider creating several project in the Dashboards each representing a branch in your repository.

2. Choose Your Uploading Strategy

DCM gives you the flexibility to upload analysis results either from your local machine or from your CI/CD pipelines, depending on your workflow and deployment strategy.

info

If you are already running dcm commands on our CI/CD (e.g. dcm analyze lib or dcm check-unused-code lib), uploading your project data is not a replacement for those checks and should be set up independently.

Branch

Initially you need to decide on which branch should be deploy to a project that you create. For example, you might have staging project for feature-branch and main branch goes to your production projects.

Local

You can run DCM analysis and upload results directly from your local machine. DCM supports running checks and uploading in a single command, so you don’t need to split the workflow:

dcm run lib --all --upload --with-details --project=PROJECT_KEY --email=LICENSE_EMAIL

You can also upload data from a branch as well. We do recommend you to create a project for a branch or staging / testing environment and separate it from your production environment or main branch.

CI/CD (Recommended)

We recommend adding DCM to your CI/CD pipeline. Typically, it can be triggered on merges to your main branch. This keeps your Dashboards up-to-date with every meaningful change.

Here is an example of Github Action:

jobs:
  analyze:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
    ...
      - name: Run DCM and Upload
        run: |
          dcm run lib \
            --all \
            --upload \
            --with-details \
            --project=${{ secrets.DCM_PROJECT_KEY }} \
            --email=${{ secrets.DCM_LICENSE_EMAIL }} \
            --ci-key=${{ secrets.DCM_CI_KEY }}

info

You’re free to upload at any time, daily, weekly, or even multiple times a day. Just keep in mind, only the latest upload per day is kept. If you upload more than once in a day, the newest upload will overwrite the previous one to ensure the dashboard always reflects the most recent data.

3. Upload Your Metadata

DCM lets you upload your analysis results whether you want a lightweight summary or a full report with all details.

Here’s a typical command that runs a full analysis and uploads everything:

dcm run lib --all --upload --with-details --project=PROJECT_KEY --email=LICENSE_EMAIL

Each flag is responsible to handle a task:

• --all - Runs all available code quality checks.
• --upload - to indicate that the results of the command should be uploaded
• --project - to pass the unique key of a project in your DCM Dashboards
• --with-details - to switch to a more detailed mode. By default the command will only upload a summary and configuration. With this flag the command will also upload a list of issues and metrics.

DCM also provides additional flags to control how uploads behave:

• --preview-upload: Performs a dry run and shows what would be uploaded without sending any data. Great for validation before committing changes.

dcm run lib --all --upload  --with-details --project=PROJECT_KEY --email=LICENSE_EMAIL --preview-upload

and here is the result in your console:

~/.../example_app on main ✗  > dcm run lib --all --upload  --with-details --project=PROJECT_KEY --email=LICENSE_EMAIL --preview-upload

{
  "project": "<hidden>",
  "email": "<hidden>",
  "date": "2025-04-25T13:13:15.516343",
  "dateOverride": null,
  "version": "1.29.0",
  "issues": {
    "96f9112a84d1f0e410fcebd0885bc17f": {
      "issues": [
        {
          "id": "duplication-issue",
          "message": "This method has 1 duplicate declaration",
          "line": 168,
          "effort": 20
        },
      ],

  ...
}

• --upload-date="YYYY-MM-DD": Lets you override the upload date.

dcm run lib --all --upload --upload-date="2025-04-15"

Project Key

You’ll find the Project Key at the top of the selected project page in your DCM Dashboards. Copy and use it in all your --project flags to ensure the data is correctly linked.

Available Code Quality Checks

Instead of --all, you can target specific types of analysis based on your goals:

dcm run lib \
  --analyze \
  --metrics \
  --code-duplication \
  --upload \
  --with-details \
  --project=PROJECT_KEY \
  --email=LICENSE_EMAIL

info

If you are passing --analyze or --metrics, don't forget to enable DCM lint rules or metrics in your package's analysis_options.yaml.

Available check flags include:

    --all                                          Run all dcm commands.
    --analyze                                      Run dcm analyze.
    --metrics                                      Run dcm calculate-metrics.
    --analyze-assets                               Run dcm analyze-assets.
    --code-duplication                             Run dcm check-code-duplication.
    --unused-code                                  Run dcm check-unused-code.
    --unused-files                                 Run dcm check-unused-files.
    --dependencies                                 Run dcm check-dependencies.
    --unused-l10n                                  Run dcm check-unused-l10n.

Note that the other flags are not available for Dashboards including:

    --parameters                                   Run dcm check-parameters.
    --analyze-widgets                              Run dcm analyze-widgets.
    --exports-completeness                         Run dcm check-exports-completeness.

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Keep in mind that every time you upload data with specific flag, it will override the entire previous dashboard data to ensure the data is always up-to-date.

4. View the Results

After you uploaded the data successfully, your data is available immediately on the dashboard.

5. (Optional) Generate a Report

If you need to print or generate a report for stakeholders and share it with your customers,managers or teammates, use the browser ctrl+P/cmd+P menu and save the page as PDF.