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Based on our record, FuzzyWuzzy should be more popular than Foundation for Emails 2. It has been mentiond 11 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.
Things like Foundation for Emails helped me a lot when I used to make email templates. Source: 12 months ago
I will say that it sucks just as a much from the developer front. I had to build some email templates for a project a few weeks ago and I was shocked how wired it was compared to regular webdev. Using a framework is almost a requirement if you don't want to spend all your time on little differences between email clients. The layout is really wired too, with the recommendation to use a ton of nested tables. Not to... - Source: Hacker News / almost 2 years ago
I use foundation email framework and integrate it into the emails folder and have mix run its build. Source: almost 2 years ago
Https://mjml.io/ Https://get.foundation/emails.html. Source: almost 2 years ago
I've used https://get.foundation/emails.html but email dev is a nightmare. It's like needing to support 20 different versions of IE6 each with their own unique bugs you have to work around. I said this in another comment:. Source: about 2 years 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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