Do fuzzy matching (something like fuzzywuzzy maybe) to see if the the words line up (allowing for wrong words). You'll need to work out how to use scoring to work out how well aligned the two lists are. Source: over 1 year ago

Convert the original lines to full furigana and do a fuzzy match. (For reference, the original line is 貴方がこれまでに得てきた力、存分に発揮してくださいね。) You can do a regional search using the initial scene data (E60) first, and if the confidence is low, go for a slower full search. Source: over 1 year ago

It's now known as "thefuzz", see https://github.com/seatgeek/fuzzywuzzy. Source: about 2 years ago

You can have a look at this library to use fuzzy search instead of looking for plaintext muck: https://github.com/seatgeek/fuzzywuzzy. Source: over 2 years ago

To deal with comparing the string, I found FuzzyWuzzy ratio function that is returning a score of how much the strings are similar from 0-100. Source: almost 3 years ago

Access to test/trial systems: there are trial systems on SAP CAL but not everyone can cough up 150$/month idle + 4$ per hour (S/4HANA 2021 trial with Google Cloud, according to the cost estimator). There are somewhat shady companies in India offering remote access but I know some people even in the US use them because it's way cheaper and convenient. (I don't endorse such companies and don't have any details.). Source: over 1 year ago

One point though: C4C is especially bad with regards to access. With other solutions, SAP is much better. You can spin up an entire SAP cloud infrastructure with S4 and cloud integration on https://cal.sap.com/ and the BTP trials. Source: over 2 years ago

You can easily spin up an S4 system to look around at cal.sap.com. Source: about 3 years ago