Interactive HTML dashboard for tracking airport VIP lounge partner performance, paired with the Python pipeline that builds the input workbook, collects exchange rates, and generates the report.
This project automates the reporting workflow for VIP lounge partnership performance across multiple airports:
- Input generation:
criar_planilha_input.pybuilds a structured input workbook from the raw partner access base, one sheet per lounge, preserving manually entered fields (paying passengers, currency overrides) across regenerations. - Exchange rate collection:
fx_collector.pyfetches daily EUR/USD rates from investing.com (with the European Central Bank as fallback), audits the data for invalid or duplicate dates, and outputs both the legacy and corrected monthly averages. - Report generation:
gerar_relatorio.pyreads the input workbook and renders the standalone HTML dashboard.
Open VIP_Lounges_Performance (In).html directly in any browser, no server or build step required. All data and rendering logic are self-contained in the file.
Highlights
- Revenue and passenger volume by lounge and partner airline
- Paying passenger percentage
- Published vs. corrected EUR/USD rate comparison, with data quality alerts
- Year-over-year and month-over-month breakdowns
- Responsive layout, print-friendly
| criar_planilha_input.py | Rebuilds the VIP lounge input workbook from the latest partner access base, keeping manual entries intact |
| fx_collector.py | Collects and audits daily EUR/USD rates, flagging invalid dates, duplicates, and text-formatted values that Excel's AVERAGE silently ignores |
| gerar_relatorio.py | Generates the final HTML dashboard from the input workbook |
Built with openpyxl for spreadsheet generation and parsing, and plain urllib for the exchange rate collection, no external HTTPS dependencies.
Paths for the source and output folders are read from environment variables (VIP_LOUNGE_SOURCE_PATH, VIP_LOUNGE_OUTPUT_PATH) rather than hardcoded, so the scripts can run against any equivalent folder structure.
Python · openpyxl · urllib · HTML · CSS · JavaScript
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The dataset shown in the dashboard is illustrative and does not represent real financial figures or actual partner agreements