Python-Node Data Automation Scripts
Budget / SalaryHourly project
TypeFreelance project
LocationRemote
Posted2 hours ago
This project has three connected pieces and I’d like to tackle them in the order that keeps the workflow smooth for everyone.
Phase 1 – Website-to-Excel Scraper
We begin by coding a Python scraper that pulls data directly from a set of websites and drops it into clean, well-structured Excel workbooks. The scraper should cope with pagination, basic authentication when needed, and changing HTML layouts (lxml or BeautifulSoup are both fine). I will provide the target URLs and the exact column layout; you make the script resilient and easy to re-point when sites change. As soon as the data lands in Excel, a short Pandas routine should run simple sanity checks so I can trust the numbers.
Phase 2 – Automated Word Report Formatting
Once the data is in place, a second Python script should transform the analysis output into a polished Word report. Using python-docx and lxml, the script must:
• switch every section to landscape orientation,
• preserve complex table structures, and
• embed any charts or summary text I pass in.
The goal is a single-click command that turns raw numbers into a board-ready .docx file without manual tweaking.
Phase 3 – Node.js Integration Layer
Finally, I need a lightweight Node.js app (Express is fine) where a user can upload new configuration files or even raw data, hit “Run Collection,” and watch the scraper + formatter pipeline execute in the background. Returned status, logs, and finished reports should be delivered as downloadable links and mirrored in a simple JSON API so other services can hook in later.
Acceptance check
• Scraper writes fully populated Excel files with zero empty header cells.
• Formatter outputs a landscape Word report whose style matches the sample template I’ll provide.
• Web app uploads a file
Phase 1 – Website-to-Excel Scraper
We begin by coding a Python scraper that pulls data directly from a set of websites and drops it into clean, well-structured Excel workbooks. The scraper should cope with pagination, basic authentication when needed, and changing HTML layouts (lxml or BeautifulSoup are both fine). I will provide the target URLs and the exact column layout; you make the script resilient and easy to re-point when sites change. As soon as the data lands in Excel, a short Pandas routine should run simple sanity checks so I can trust the numbers.
Phase 2 – Automated Word Report Formatting
Once the data is in place, a second Python script should transform the analysis output into a polished Word report. Using python-docx and lxml, the script must:
• switch every section to landscape orientation,
• preserve complex table structures, and
• embed any charts or summary text I pass in.
The goal is a single-click command that turns raw numbers into a board-ready .docx file without manual tweaking.
Phase 3 – Node.js Integration Layer
Finally, I need a lightweight Node.js app (Express is fine) where a user can upload new configuration files or even raw data, hit “Run Collection,” and watch the scraper + formatter pipeline execute in the background. Returned status, logs, and finished reports should be delivered as downloadable links and mirrored in a simple JSON API so other services can hook in later.
Acceptance check
• Scraper writes fully populated Excel files with zero empty header cells.
• Formatter outputs a landscape Word report whose style matches the sample template I’ll provide.
• Web app uploads a file
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