PD

PDF API – Generate, convert, and modify PDF documents

Hacker News

PDF API – Generate, convert, and modify PDF documents

Hi HN, Arek here. We’re super excited to officially launch PSPDFKit API [1]. PSPDFKit API is a collection of HTTP APIs that enable you to convert, generate, and edit documents without running any service on your infrastructure. What differentiates our API from others is that you can chain together multiple “actions” as part of a single API request. For example, you can convert, OCR, watermark, edit, and flatten a document — all in one call. Available actions [2]: - PDF Generator - PDF Converter - Image Converter - OCR - Watermark - Merge - Split - Duplicate - Delete - Flatten Our documentation includes sample code for JavaScript [3], Python [4], Java [5], C# [6], PHP [7], and the command line. We also have a Postman collection [8]. Let us know what you think or if you have any questions. [1] https://pspdfkit.com/api/ [2] https://pspdfkit.com/api/documentation/tools-and-api/ [3] https://pspdfkit.com/api/tools/javascript/ [4] https://pspdfkit.com/api/tools/python/ [5] https://pspdfkit.com/api/tools/java/ [6] https://pspdfkit.com/api/tools/csharp/ [7] https://pspdfkit.com/api/tools/php/ [8] https://pspdfkit.com/api/documentation/getting-started/postm...

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204points
116comments
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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
88%88% 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, io · Missing: https docs, just released, exist
55%55% 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 · Missing: mobile apps, ios, personal
46%46% 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.
Product HuntUnlikely to reach the leaderboard · Strong signals: single, code, apis · Missing: mac, agents, macos
15%15% predicted probability of success on Product Hunt, 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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