St

Stalkmyself.com, parse Gmail exports in the browser thanks to Pyodide

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Stalkmyself.com, parse Gmail exports in the browser thanks to Pyodide

Built using Pyodide [1] (web-assembly-compiled Python), stalkmyself.com lets you convert your GMail inbox into a CSV file summary without relying on any backend service -- everything runs directly in your browser (once you've download an export of your GMail data via Google Takeout [2]). The site also generates some plots of you data automatically, and if you have Amazon.com receipts in your inbox, stalkmyself.com will parse those, too, giving you a separate CSV and a cumulative spending chart. Among friends, this chart has been the crowd favorite to sweat over. Backstory: Stalkmyself.com started originally as a joke with friends about the most terrible startup concept I could come up with. The initial idea was using computer vision to stereotype public Instagram posts, and the first version of stalkmyself.com scraped your Instagram data for you via instagrapi [3] (sans computer vision, all stereotyping was the responsibility of the user). Though I got it working, I didn't feel comfortable releasing a tool that might Instagram accounts banned for bot-like behavior, so I repurposed the site to run on data you can export yourself with first party tools (GMail data exported with Google Takeout). Thoughts on Pyodide: Because this is HN, I figure folks might appreciate thoughts on Pyodide from someone who used it to build a site. Overall, I had a lot of fun with Pyodide. As a data scientist by trade, Python is my bread-and-butter programming language, and being able to run it in the browser feels magical. Even complicated dependencies like numpy and matplotlib run smoothly, allowing for plotting and other complex operations. It's certainly a huge sacrifice of page load time to run the Python interpreter in your website, and developing Python to run in the browser was more of a tightly-coupled experience than I had anticipated (I learned a lot more JavaScript than I wanted to with this project), but for another standalone app I would definitely use it again and recommend it to others! [1] https://pyodide.org [2] https://takeout.google.com [3] https://adw0rd.github.io/instagrapi/

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, para · Missing: supports, reddit linkedin, podcasting
97%97% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: google, user, computer · Missing: mac, agents, macos
81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: google, para · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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