name	playwright-excel
description	Integrate Excel (.xlsx) data into Playwright codegen scripts by replacing hardcoded values with config-driven lookups, loading data with polars, and validating every step with Playwright MCP (start MCP from the repo if not running). Use for Playwright automation updates that require Excel-backed data, config.yaml centralization, or MCP validation/reporting.

Playwright Excel Integration

Overview

Convert Playwright codegen scripts into Excel-driven automations with centralized config and required MCP validation.

Use the playwright conda environment.
Before running any Python command, run: conda run -n playwright python -c "import sys; print(sys.executable)"
Do not create or activate any venv or .venv.

Playwright codegen script path
Excel .xlsx path
Mapping lines: "hardcoded_value" -> Excel[Sheet][FilterCol==FilterVal][DataCol]
Optional override: PLAYWRIGHT_TARGET_SUBJECT

Analyze the Playwright script and the Excel structure (sheets, columns, sample rows).
Detect hardcoded .fill() values and confirm that each has a mapping; request clarification for mismatches.
Ensure dependencies in the playwright conda env (prefer conda install -n playwright, fall back to conda run -n playwright pip install).
Create or update config.yaml using centralized control (paths, patterns, column definitions, constants, tunables, shared texts).
Modify the Playwright script:
- Add a config loader and an Excel loader (polars; see references/excel-loading.md).
- Replace hardcoded values with data[...].
Always run Playwright MCP validation; if MCP is not running, start it from this repo before continuing (see references/mcp-validation.md).
When refactoring existing pipelines/logic, generate outputs and compare MD5 checksums with reference files (see references/md5-validation.md).
Run the updated script with conda run -n playwright python.