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Helium - Simple web automation

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Helium - Simple web automation

Hi everyone, I'm working for a startup called BugFree Software and would love to hear your feedback on a new product we are launching today. Helium is a library that wraps around Selenium to simplify web automation. It does away with many of the technicalities involved with web scripting. For example: Here is a Selenium script. Can you guess what it does? >>> ff = Firefox() ... >>> text_area = ff.find_element_by_id("u_0_1q") >>> text_area.send_keys("Hello World!") >>> button = ff.find_element_by_class_name("_42g-") >>> button.click() Here is the same script rewritten using Helium: >>> start_firefox() ... >>> write("Hello World!", into="Update Status") >>> click("Post") Can you now guess what it does? That's right; It updates your Facebook status. In an extended comparison that we were invited to write for the December issue of Professional Tester (professionaltester.com), we found that an example script automating Gmail took 66% fewer lines of code and 75% less effort using Helium than with Selenium alone. You can find more information and download Helium from http://heliumhq.com. Any feedback would be highly appreciated. Hoping to hear your thoughts and comments, Michael Herrmann heliumhq.com

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
77%77% 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: new, using, code · Missing: mac, agents, macos
64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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