Placeholder package - Reserved by AIH-Infra

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for Baireinhold from gravatar.com Baireinhold

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: AIH-Infra
  • Requires: Python >=3.8
Classifiers
Report project as malware

Project description

scholarly-markdown

⚠️ This is a placeholder package reserved by AIH-Infra.

This package name is reserved for future use by the AIH-Infra project (AI for Humanities Infrastructure).

About AIH-Infra

AIH-Infra is a non-commercial, open-source project dedicated to building AI infrastructure for humanities research.

For more information, visit:

Contact

If you have questions about this package reservation, please open an issue at: https://github.com/AIH-Infra/aih-infra/issues

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for Baireinhold from gravatar.com Baireinhold

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: AIH-Infra
  • Requires: Python >=3.8
Classifiers

Release history Release notifications | RSS feed

This version

0.0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scholarly_markdown-0.0.1.tar.gz (1.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

scholarly_markdown-0.0.1-py3-none-any.whl (1.8 kB view details)

Uploaded Python 3

File details

Details for the file scholarly_markdown-0.0.1.tar.gz.

File metadata

  • Download URL: scholarly_markdown-0.0.1.tar.gz
  • Upload date:
  • Size: 1.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.0

File hashes

Hashes for scholarly_markdown-0.0.1.tar.gz
Algorithm Hash digest
SHA256 9af5723fc1d642f0d78398f2b85699c09749b2ca2ef02736ba835ec084da8f42
MD5 23aa789f1d01978a9a3908794b05eddf
BLAKE2b-256 4a8fcab43a22a94002906c57816226b07750dc1019efee1ab797debbd9a824f4

See more details on using hashes here.

File details

Details for the file scholarly_markdown-0.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for scholarly_markdown-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4de07b16c4d9529964b86d925d353ce21612bdc105f223f22b272183dee8717f
MD5 73593f9236837da33a8ad941f0da7c85
BLAKE2b-256 3036ee9a8498ede8af39ca9d2651bb2191e35cdcc42822ae4f7093eeca81643c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page