oE

oEmbedPy is oEmbed client library for Python 3.x

Hacker News

oEmbedPy is oEmbed client library for Python 3.x

oEmbed is a format for allowing an embedded representation of a URL on third party sites. (ref: https://oembed.com/ ) This is client library for oEmbed written by Python (3.x only) that can fetch data and can handle as python dataclasses from oEmbed API of supported websites. It has adapter for Sphinx and MkDocs. You can render embed content into documents by content url with simply format. See it: https://oembedpy.readthedocs.io/en/stable/

Visit product View on Hacker NewsFeb 15, 2025

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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

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

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

28%28% 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

20%20% 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

8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

Python Client Library for Truverifi50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Python Client Library for Truverifi

pydweet, a python client library for dweet.io66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

pydweet, a python client library for dweet.io

A Python library for Unicode string collation55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A Python library for Unicode string collation

A Python library for accessing Wunderlist67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A Python library for accessing Wunderlist

Ohne I/O, a Python 3.4+ coroutine library without any I/O55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Ohne I/O, a Python 3.4+ coroutine library without any I/O

Combinatorix, yet another combinator library in Python55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Combinatorix, yet another combinator library in Python

Tt Python library67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tt Python library

Python library for GoPro cameras67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Python library for GoPro cameras

B2blaze – A Backblaze B2 library for Python55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

B2blaze – A Backblaze B2 library for Python

Python library for parsing Dockerfile65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Python library for parsing Dockerfile

Browse all products Analyze your launch