InstabotJS, an Instagram shitposting automation tool

Hacker News

Hi Hacker News, I built a cli based Instagram automation tool for crossposting content from Reddit and submitting it as OC on Instagram. It works by parsing the Reddit API for fresh image content from target subreddits, and then it uses Puppeteer to simulate DOM traversal and post that content on Instagram from your user account. It also automates tasks such as following and refollowing users. I built this out of a desire to practice using Puppeteer and conducting end to end tests. I'm really happy with the result of this project because it not only works as intended, but it also happens to be a very effective stress reliever to be able to post memes with the stroke of a cli command! Check it out on NPM: https://www.npmjs.com/package/instabotjs and on Github: https://github.com/fermidirak/instabotjs Currently the project is licensed under WTFPL so feel free to go wild with it :) Stack and important Technologies Used used: Node, Typescript, Puppeteer, CommanderJS, InquirerJS, Axios, Sharp I hope somebody finds this project educational, or at the very least entertaining. Cheers! -Dirak

Visit product View on Hacker NewsAug 23, 2018

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

87%87% 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: user, new, tasks · Missing: mac, agents, macos

69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, users, education · Missing: mobile apps, personal, entrepreneurs

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: hacker news, io · Missing: https docs, excited, just released

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

43%43% 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

16%16% 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.

Incorrect prediction on native model

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