CodeGuru is a machine learning service by Amazon Web Services that provides automated code reviews and performance recommendations. Amazon CodeGuru leverages machine learning to enhance code quality by providing automated code reviews and performance recommendations. - Source: dev.to / 2 months ago

There are security scans available in JetBrains for Python, Java, JavaScript, TypeScript, and VS code as well. AWS CodeGuru Security is another amazing security tool that takes the assistance from detection engine. Detector Library is an important component of detection engine which is responsible in making you understand why your code was highlighted by CodeWhisperer and whether an action is to be taken or not.... - Source: dev.to / 4 months ago

The final hint that something will probably happen soon was the announcement of the CodeGuru Security service, and the modification of the main CodeGuru page to point instead towards this new service. CodeGuru Security at first glance seems to be a modified version of the Reviewer, with a focus on security. This is pure speculation at this point, but I suspect that CodeGuru Reviewer will soon be either dropped or... - Source: dev.to / 10 months ago

The security of your applications is critical in the world of software development. Amazon CodeGuru Security is an AI-powered tool that helps developers identify potential security flaws in their code. CodeGuru Security analyses codebases, makes intelligent recommendations, and flags potential security risks using machine learning algorithms. This powerful tool enables developers to proactively improve their... - Source: dev.to / 12 months ago

As AI technology advances, it will likely profoundly impact code reviews. This is already starting to happen with the development of tools such as Amazon CodeGuru and GitLab's ModelOps. These tools automate certain aspects of the code review process, such as identifying potential errors and suggesting improvements, saving developers time and effort while also helping to improve code quality. - Source: dev.to / over 1 year ago

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