I need a clean, well-commented Python 3 script that connects to the SEC EDGAR API, pulls the latest annual 10-K filings for a list of tickers I will supply, and extracts all of the data. After normalising the figures, the script should write them into an Excel workbook following a custom layout I will share once the project begins. The SEC data is notoriously bad for having multiple tags accross different tickers for the same financial data. What I need is a way to normalise the differing tags to output the same data, if i run this on 10 company tickers they might have different tags to show the value of revenue, I need a script that will handle the difference and give me accurate data. Core expectations • Use standard libraries such as requests for API calls, pandas for data handling, and either openpyxl or xlsxwriter for the Excel output so the workbook remains fully editable. • Respect SEC rate-limits and include basic error-handling for timeouts, missing XBRL tags, or amended filings. • Code should be clearly structured, with functions or classes that make future feature additions straightforward. To move forward, send me a detailed project proposal outlining your planned workflow, timeline, and any assumptions you need clarified. I’ll review the proposal, share the Excel template, and we can refine the layout together before you begin coding.