looper-dashboard 0.1.3

Generate daily CI dashboards for any QE repo on LooperPro (Karate, Playwright, Monocart)

looper-dashboard

Generate daily CI dashboards for any QE repository on the LooperPro CI platform.

Supports three test suite types:

Suite	Report format	Default history
karate	karate-summary-json.txt + per-feature detail	14 days
playwright	pw-summary-report.json	14 days
playwright-monocart	monocart-report/index.html (zlib-compressed)	30 days

---

Requirements

Requirement	Why
Python 3.11+	Runtime
mcp-cli (optional)	Auto-refreshes LooperPro auth tokens
code-puppy (optional)	Powers the AI failure analysis step

Authentication is read from ~/.mcp-cli/tokens.json or ~/.code_puppy/puppy.cfg automatically — no extra config needed.

---

Installation

pip install looper-dashboard

Or from the repo:

pip install ./looper-dashboard

---

Quick Start

1. Scaffold a config

# Creates daily_flows.yml in the current directory
looper-dashboard --init karate
looper-dashboard --init playwright
looper-dashboard --init playwright-monocart

Edit the generated file to add your LooperPro job names and flow names.

2. Generate the dashboard

looper-dashboard --suite karate --config daily_flows.yml --open
looper-dashboard --suite playwright --config daily_flows.yml --open
looper-dashboard --suite playwright-monocart --config daily_flows.yml --open

3. Override the repo SCM URL

looper-dashboard --suite karate \
  --config daily_flows.yml \
  --scm-url https://gecgithub01.walmart.com/my-org/my-repo.git \
  --open

---

daily_flows.yml format

Karate / Playwright

# SCM URL of the repository being monitored
scm_url: https://gecgithub01.walmart.com/my-org/my-repo.git

jobs:

  # LooperPro job name → list of flow names to monitor
  my-org/my-repo-tests:
    - my-flow-dev
    - my-flow-stage
    - my-flow-prod

  my-org/my-repo-health-checks:
    - health-dev
    - health-stage

Playwright-Monocart (with explicit job_ids)

Some repos' jobs cannot be discovered by SCM URL in LooperPro. Add a job_ids section with the UUIDs from the LooperPro UI:

scm_url: https://gecgithub01.walmart.com/my-org/my-repo.git

# Explicit job IDs (look these up in the LooperPro UI)
job_ids:
  my-monocart-job: "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"

jobs:

  my-monocart-job:
    - e2e-flow-dev
    - e2e-flow-stage

---

CLI Reference

looper-dashboard [OPTIONS]

Options:
  --suite SUITE           Test suite type: karate, playwright, playwright-monocart  [required]
  --config PATH           Path to daily_flows.yml  [required]
  --scm-url URL           Override scm_url from daily_flows.yml
  --output PATH           Output HTML file path (default varies by suite)
  --days N                Days of build history to fetch (default: 14 or 30)
  --open                  Auto-open dashboard in browser when done
  --no-ai                 Skip the AI failure analysis step
  --no-details            Skip fetching test summary details (faster, status only)
  --save-failures PATH    Path to save failures JSON
  --analysis-json PATH    Use a pre-computed AI analysis JSON instead of running live AI
  --init SUITE            Scaffold a starter daily_flows.yml and exit

  -h, --help              Show help and exit

---

AI Analysis

When --no-ai is not set, the orchestrator:

1. Saves a *-failures.json summary of all failing flows
2. Invokes code-puppy to classify each failure as one of:
   • service_regression — likely a code regression in the app
   • environment_issue — infra/network/auth failure
   • test_issue — stale selector or bad test data
   • flaky — intermittent, no clear pattern
3. Regenerates the dashboard HTML with an AI analysis panel embedded

If code-puppy is not installed, the AI step is skipped gracefully.

---

Publishing a new version

1. Bump the version

Edit pyproject.toml:

[project]
version = "0.1.2"   # increment as needed

2. Build the wheel

cd looper-dashboard

# Clean any previous build artifacts
rm -rf dist/ build/ looper_dashboard.egg-info/

# Build (requires setuptools + wheel in the active Python env)
pip install setuptools wheel build   # one-time setup
python -m build --wheel --no-isolation

This produces dist/looper_dashboard-<version>-py3-none-any.whl.

3. Upload to PyPI

Prerequisite: You must be off the corporate VPN (or on a personal hotspot) for upload.pypi.org to be reachable.

pip install twine

# Upload only the new version's wheel (never re-upload an existing filename)
twine upload dist/looper_dashboard-<version>-py3-none-any.whl

When prompted:

• Username: __token__
• Password: your PyPI API token from pypi.org/manage/account/token/

Or pass credentials inline to skip the prompt entirely:

.venv/bin/twine upload \
  -u __token__ \
  -p pypi-<your-token-here> \
  dist/looper_dashboard-<version>-py3-none-any.whl \
  --verbose

Skip the prompt with ~/.pypirc

[pypi]
username = __token__
password = pypi-xxxxxxxxxxxxxxxxxxxx

Then just run:

twine upload dist/looper_dashboard-<version>-py3-none-any.whl

4. Verify

pip install --upgrade looper-dashboard
looper-dashboard --version

Or check pypi.org/project/looper-dashboard/ directly.

5. Reinstall locally from the new wheel

# In the project venv
.venv/bin/pip install --force-reinstall dist/looper_dashboard-<version>-py3-none-any.whl

---

Note: PyPI does not allow re-uploading a file with the same name as an existing release. Always increment the version in pyproject.toml before building.

---

Onboarding a new repo

1. Create a daily_flows.yml for the target repo (use --init to scaffold)
2. Add job and flow names (find them in LooperPro or via mcp-cli)
3. Run looper-dashboard --suite <type> --config daily_flows.yml --open

No code changes required — the package is entirely configuration-driven.