Building a Flask Test Site and Retrieving Data with Excel and Python

The article demonstrates how to create a simple data‑driven web site using Python Flask, expose the data through a RESTful API, and then fetch the data either with Excel’s “From Web” feature or with Python libraries such as requests, BeautifulSoup and pandas.

First, a Flask application (file 5-5-WebTable.py ) is built that returns an HTML table containing sample user information. The script is started with python ./5-5-WebTable.py and can be accessed at http://127.0.0.1:5000/ .

Second, a Flask‑RESTPlus API (file 5-5-WebAPI.py ) is created. The code installs flask-restplus , defines a data model, implements CRUD operations in the TodoDAO class, and maps the routes / and /<int:id> . The service runs on port 8000 and is reachable at http://127.0.0.1:8000/ExcelPythonTest/ .

Third, the article shows how Excel can import the table directly from the Flask site (Data → From Web) and how Python can retrieve the same data. The Python example uses requests.get(url) to obtain the page, parses the table with BeautifulSoup, and extracts rows into a list.

Finally, the article compares the Excel and Python approaches, noting that Excel’s web‑import is limited to static tables while Python offers full control and can handle JSON responses from the API.