A Python library to bidirectional local drive <> S3 sync and copy

Hacker News

Introducing s3shutil : A python library that copies, syncs, moves files in s3. How does it compare to aws-cli? - aws-cli is amazing and feature complete and supports bulk action in s3. - aws-cli is great to use from the command line and shell scripts. - s3shutil is very easty to install, import and invoke from your python code. How does it compare to s3fs? - s3fs is real fast and mature and has an amazing community. - s3fs has a object oriented API with plenty of different calls. - s3shutil has a simple and symmetric string based API (uploads and downloads are the same. It is just a matter of parameters order). - s3shutil transparently supports s3 to s3 server side copying. And also this: - s3shutil supports syncing (delta copying of new files) while s3fs doesn't. sync is supported equally in all directions (disk to s3, s3 to disk, s3 to s3). Why did I do it? For fun, productive procrastination and to getting packaging and wrapping into a reusable library the experience I gathered working with s3. What do I need from you? Install it, try it, give feedback. Leave me a comment here. Fork and star in github ( https://github.com/andyil/s3shutil ). Will you use it? What missing feature would make it to use it?

Visit product View on Hacker NewsNov 30, 2023

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

78%78% 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, code · Missing: mac, agents, macos

67%67% 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

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.

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

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% 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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