Python code to scrape lichess.org coach listing metadata and generate a .csv for subsequent analysis. Lichess has a strong community of title-verified coaches with a variety of ratings, rates, and locations, but does not expose structured data or search tools allowing a prospective student to sort and filter on these criteria, which makes it challenging to find a suitable coach in a mutually convenient timezone.
It uses Selenium for browser automation and generates a file containing selected metadata, currently
coach['Name']
coach['Country']
coach['Rate']
coach['Rating']
coach['Link']
Modification to add additional fields via Selenium selectors is trivial. Unfortunately, some of the key fields are unstructured (e.g. Rate, which is a free text input and includes various currencies and human-readable notes such as "package discounts available") and others are not validated (e.g. Country)
The output of this script is a .csv which is suitable for analysis by a tool of your choice or for import into Google Sheets, where you can create pivot tables, slicers, or other views to find good candidate coaches.
Infinite scroll of the page is automated, data is scraped and coach Name written to stdout. The scraped data fields (including Name) are written to coaches.csv
Breakdown of number of coaches available in each country; countries coded white have zero coaches. This analysis was created in Google Sheets using an import of the generated .csv, a pivot table, and the map chart type. It is provided as an example.
