{"version":"1.0","type":"rich","title":"Gist 6c1ae0e4fff5fb8d4704","description":"This example shows a text-parsing utility that cleans and tokenizes a raw string into lowercase words. It first replaces common punctuation sequences like dashes and double quotes with spaces, then uses a regular expression with Unicode flags to extract word tokens, allowing characters such as `@`, `#`, `&`, and hyphens. The code relies on Python’s standard `re` module and basic string methods, with no external visualization libraries or rendering pipeline. The output is a list of normalized words, illustrating a preprocessing step rather than a visual chart or graph.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-6c1ae0e4fff5fb8d4704?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}