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jgm
pandoc
Haskell2012–2026
jgm / pandoc

pandoc

Universal markup converter

56Distinct people
63Mentions
1Explicit recommenders
46.9KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Universal markup converter

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

I really hope that they borrow a lot if not everything from pandoc[1]. My only real complaint with pandoc is the table formatting, but I think fiddlosopher is adding org-mode…

dfc used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 8:03:49 PM UTC.

A technical vision for the Haskell ecosystem direct repository linkDebated

Commenters debate whether Haskell's primary bottleneck is technical performance, such as compile time and incremental builds, or its lack of a coherent, polished ecosystem for building diverse applications like web and desktop software. While some argue that foundational libraries and better developer experience are the missing pieces, others contend that the language's utility is constrained by fragmented tooling and unclear positioning compared to more universal alternatives.

17 readable replies · Supporting reply 1 · Supporting reply 2 · Supporting reply 3 · Supporting reply 4

Mentions over time

HN mentions by year63 dated mentions

Observed mentions: 2012-02-25 18:15:18 UTC to 2026-10-01 15:56:48 UTC.

02468102012-01-01 00:00:00 UTC to 2013-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments20122013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 5 mentions; 0 submissions, 5 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 8 mentions; 1 submissions, 7 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 10 mentions; 1 submissions, 9 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 7 mentions; 1 submissions, 6 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20122012-01-01 00:00:00 UTC2013-01-01 00:00:00 UTC404
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC000
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC303
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC505
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC202
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC514
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC303
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC303
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC312
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC817
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC404
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC1019
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC211
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC404
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC716

What Hacker News says

5 sources
This is very similar to Pandoc, which also processes things into its own AST/Internal representation. It then knows how to translate its representation into a many different outputs. Pandoc is really nice and you can script it with a variety of languages, though if you really want to dig in you have to use Haskell. Kramdown using Ruby makes it more accessible and has some cool options like table of contents generation that is more flexible than Pandoc. You can see some discussion of supporting Kramdown in pandoc. https://github.com/jgm/pandoc/issues/2711 Generally I think pandoc is the more mature tool, but I can see places where it might be a better call (especially if your app needs it as a library and you aren't willing to call a command (Pandoc).
In Kramdown – A Ruby library for parsing and converting a superset of Markdown
The article describes Markdown[1], basically. In my opinion, content should be written once and transformed to any format[2], including ConTeXt[3], docx, HTML, EPUB, or plain text. But here's a puzzler. Every software developer defines and uses variables. If variables are so powerful, why do WYSIWYG word processors lack the ability to quickly and easily insert variable definitions?[4] In the screenshot, the left-hand side provides an editable variable definition hierarchy, the middle pane provides a Markdown editor, and the right-hand side provides a real-time HTML preview of the content with variables interpolated and substituted. After variables, programming language integration--such as R[5]--comes naturally. Consider the following syntax (that could be hidden through a UI): `r#csv2md('data.csv',totals=TRUE)` The function imports
Read the rest
data from an external data source and converts it to Markdown. The HTML version can be styled, or piped through pandoc to create beautiful PDF output[6]. In the screenshot, the left-hand side shows the csv2md command (totals are calculated automatically for numeric columns), the middle pane shows an HTML preview (real-time), and the right-hand side shows a PDF produced from the same source document using pandoc and ConTeXt. The CSV file could also be a JSON request over HTTP, or database query, meaning that the document is always up-to-date with the most recent data: a living document. This could be accomplished without having to change the source document, as well: `r#import(v$data$source,totals=TRUE)` Here, v$data$source is a variable that defines a data source. In this case, the value might be 'data.csv', but could be 'protocol://host/app/api/json'. The variables themselves could be sourced from a YAML file, JSON data stream, or remote database. This is what I've been working towards for the last several months.[7] There's more that this editor can do, but it's still in early beta stages, should anyone care to try it. [1]: https://github.com/jgm/pandoc/issues/168 [2]: http://pandoc.org/ [3]: http://wiki.contextgarden.net/ [4]: https://raw.githubusercontent.com/DaveJarvis/scrivenvar/mast... [5]: https://github.com/bedatadriven/renjin/ [6]: http://i.imgur.com/Qe6mTpx.png [7]: https://github.com/DaveJarvis/scrivenvar
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