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Based on our record, MJML should be more popular than FuzzyWuzzy. It has been mentiond 88 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
We’ll leverage Novu’s code-first workflow (Echo) approach in creating notification workflows within our codebase. Novu empowers you with the ability to integrate email, SMS, and chat template and content generators, such as React Email, and MJML into your app via code. - Source: dev.to / about 1 month ago
What an excellent resource! (And yes Outlook is a pain!) We've tried building email templates for notifications for our apps where I work, and it has typically been a pain. We have since swapped to using mjml (https://mjml.io/) to build the templates, and it's working wonders. The output seems the be the most compatible with all different devices that we've tested on. The other tool we enjoy using is Litmus... - Source: Hacker News / about 1 month ago
I am using MJML and it’s relatively easy to build your described layout with snippets from the docs. https://mjml.io/. - Source: Hacker News / 4 months ago
Last time I had to deal with emails, I've used https://mjml.io/ and was very happy with it. You can version the templates, compile them as part of your build pipeline and it seems to do produce very _adequate_ HTML full of tables that looks good on all clients that we tested. - Source: Hacker News / 10 months ago
I suggest you look at https://mjml.io and see if their code holds better after forwards. Source: 11 months 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
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