I built an email cleaner. CSV parsing took longer than the actual validators.
Damian Forzani has developed an email list cleaner called databridge.so that provides detailed explanations for flagged emails. Unlike typical cleaners that only offer a confidence score, this tool includes specific reasons for each flag in the cleaned CSV. The project faced challenges, particularly with CSV parsing, which took longer than expected due to various formatting issues.
- ▪The email cleaner provides a detailed explanation for each flagged email, enhancing transparency.
- ▪CSV parsing was a significant challenge due to various formatting issues such as mixed line endings and improper escaping.
- ▪The tool aims to improve user understanding by providing context for flagged emails rather than just a confidence score.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3944115) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Damian Forzani Posted on May 21 I built an email cleaner. CSV parsing took longer than the actual validators. #webdev #api #typescript #showdev I've been building databridge.so by myself for a while. It's an email list cleaner that explains every decision. Most cleaners give you back "74/100, risky" and that's all you get. You cannot audit it. So I built one where every row in the cleaned CSV carries the actual reason it was flagged. A few things I expected to be quick that weren't.
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