JavaScript Office Library: View and Convert Word, Excel, PowerPoint

Hacker News

Hi HN, Igor here. We’re super excited to officially launch PSPDFKit for Web Standalone’s Office-to-PDF functionality ( try the demo [0] ). PSPDFKit for Web Standalone is a JavaScript document library that runs entirely in the browser - no external dependencies or MS Office licenses required. It’s compatible with any JavaScript framework. What differentiates our Office-to-PDF from others is that it’s built from the ground up with no reliance on open source. When converting to the PDF format, it enables additional document capabilities, like page manipulation, redaction, or editing content. Office document capabilities [1]: - View and open Word, Excel, and PowerPoint files - Convert to PDF, PDF/A, or PNG - Print - Preview Office-to-PDF capabilities [1]: - Edit content - Annotate - Assemble multiple documents - Manipulate pages - Create and fill forms - Add signatures - Redact content Our documentation includes sample code [2] and quickstarts for JavaScript [3], React [4], Vue.js [5], Angular [6], SharePoint [7], and others. Let us know what you think or if you have any questions. [0] https://pspdfkit.com/demo/office-viewer [1] https://pspdfkit.com/guides/web/office [2] https://pspdfkit.com/guides/web/samples [3] https://pspdfkit.com/getting-started/web/?frontend=vanillajs&project=new-project [4] https://pspdfkit.com/getting-started/web/?frontend=react&project=new-project [5] https://pspdfkit.com/getting-started/web/?frontend=vuejs&project=new-project [6] https://pspdfkit.com/getting-started/web/?frontend=angular&project=new-project [7] https://pspdfkit.com/getting-started/web-integrations/?product=sharepoint&deployment=online&project=new-project&integration=web-part

Visit product View on Hacker NewsMay 23, 2023

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

95%95% 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.

Hacker NewsStrong engagement from HN community · Strong signals: excited, open source, ide · Missing: https docs, just released, exist

70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: new, code, open · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

48%48% 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

38%38% 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

12%12% 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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