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linpengcheng
PurefunctionPipelineDataflow
OPEN SOURCE2018–2022
linpengcheng / PurefunctionPipelineDataflow

PurefunctionPipelineDataflow

My Blog: The Math-based Grand Unified Programming Theory: The Pure Function Pipeline Data Flow with principle-based Warehouse/Workshop Model

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3Distinct people
73Mentions
0Explicit recommenders
451GitHub stars
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My Blog: The Math-based Grand Unified Programming Theory: The Pure Function Pipeline Data Flow with principle-based Warehouse/Workshop Model

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This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 8:27:21 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year73 dated mentions

Observed mentions: 2018-10-28 07:13:45 UTC to 2022-01-03 14:12:05 UTC.

0102030402018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 37 mentions; 1 submissions, 36 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 27 mentions; 0 submissions, 27 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022

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
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC413
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC37136
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC27027
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC413
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101

What Hacker News says

37 sources
lincpa·Jul 29, 2019
I wrote 100,000 lines of pure Clojure project, but never wrote Java. The understanding of Java only reaches the of understanding the C-like OO language syntax. This level is just enough to understand the Java API, so writing Clojure does not require Java knowledge. Clojure + JVM Ecology best fits your requirements. The ultimate programming methodology, perfect unity and simplicity ---- [The Pure Function Pipeline Data Flow](https://github.com/linpengcheng/PurefunctionPipelineDataflow)
In Ask HN: Best Lisp for software development?
lincpa·Jul 22, 2019
Data dominates. the programming moves toward the data. from initial state to final state, the shortest linear distance between two points. Simplicity is the root of fast, stable and reliable. `The Pure Function Pipeline Data Flow`, based on the philosophy of `Taoism` and `the Great Unification Theory`, In the computer field, for the first time, it was realized that the unification of hardware engineering and software engineering on the logical model. It has been extended from `Lisp language-level code and data unification` to `system engineering-level software and hardware unification`. Whether it is the appearance of the code or the runtime mechanism, it is highly consistent with the integrated circuit system. Using the input and output characteristics of pure functions, pure functions are used as pipelines. Dataflow is formed by a seri
Read the rest
es of pure functions in series. A dataflow code block as a function, equivalent to an integrated circuit element (or board)。 A complete integrated system is formed by serial or parallel dataflow. It has also been widely unified with other disciplines (such as management, large industrial assembly lines, water conservancy projects, power engineering, etc.). It's also very simple and clear, and the support for concurrency, parallelism, and distribution is simple and natural. There are only five basic components: 1. Pipeline (pure function) 2. Branch 3. Reflow (feedback, whirlpool, recursion) 4. Shunt (concurrent, parallel) 5. Confluence. The whole system consists of five basic components. It perfectly achieves unity and simplicity. It must be the ultimate programming methodology. This method has been applied to 100,000 lines of code-level pure Clojure project, which can prove the practicability of this method. [The Pure Function Pipeline Data Flow](https://github.com/linpengcheng/PurefunctionPipelineDataflow)
In It’s time to move on from OOP?
lincpa·Jul 17, 2019
The Clojure language is a better and simpler Cell language. Clojure is a functional programming language based on relational database theory. ``` Clojure -> DBMS, Super Foxpro STM -> Transaction，MVCC Persistent Collections -> db, table, col hash-map -> indexed data Watch -> trigger, log Spec -> constraint Core API -> SQL, Built-in function function -> Stored Procedure Meta Data -> System Table ``` It officially supports jvm, js, .net platform, and third-party implementations such as go, py, erlang and other language platforms. You can use graalvm for native compilation, and mixing with R, python, ruby, js, Java is very simple. [Clojure is a FP based on RMDB.](https://github.com/linpengcheng/PurefunctionPipeli
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neDataflow...) [Everything is RMDB](https://github.com/linpengcheng/PurefunctionPipelineDataflow...) [Implement relational data model and programming based on hash-map (NoSQL)](https://github.com/linpengcheng/PurefunctionPipelineDataflow...) [Clojure Home](https://clojure.org/)
In A comparison of Cell with OOP
lincpa·Jul 10, 2019
The Pure Function Pipeline Data Flow, based on the philosophy of Taoism and the Great Unification Theory, In the computer field, for the first time, it was realized that the unification of hardware engineering and software engineering on the logical model. It has been extended from `Lisp language-level code and data unification` to `system engineering-level software and hardware unification`. Whether it is the appearance of the code or the runtime mechanism, it is highly consistent with the integrated circuit system. It has also been widely unified with other disciplines (such as management, large industrial assembly lines, water conservancy projects, power engineering, etc.). It's also very simple and clear, and the support for concurrency, parallelism, and distribution is simple and natural. There are only five basic components: 1. Pipe
Read the rest
line (pure function) 2. Branch 3. Reflow (feedback, whirlpool, recursion) 4. Shunt (concurrent, parallel) 5. Confluence. The whole system consists of five basic components. It perfectly achieves unity and simplicity.It must be the ultimate programming methodology. This method has been applied to 100,000 lines of code-level pure clojure project, which can prove the practicability of this method. [The Pure Function Pipeline Data Flow](https://github.com/linpengcheng/PurefunctionPipelineDataflow)
In Data Still Dominates
lincpa·Jul 9, 2019
The Pure Function Pipeline Data Flow, based on the philosophy of Taoism and the Great Unification Theory, In the computer field, for the first time, it was realized that the unification of hardware engineering and software engineering on the logical model. It has been extended from `Lisp language-level code and data unification` to `system engineering-level software and hardware unification`. Whether it is the appearance of the code or the runtime mechanism, it is highly consistent with the integrated circuit system. It has also been widely unified with other disciplines (such as management, large industrial assembly lines, water conservancy projects, power engineering, etc.). It's also very simple and clear, and the support for concurrency, parallelism, and distribution is simple and natural. There are only five basic components: 1.
Read the rest
Pipeline (pure function) 2. Branch 3. Reflow (feedback, whirlpool, recursion) 4. Shunt (concurrent, parallel) 5. Confluence. The whole system consists of five basic components. It perfectly achieves unity and simplicity.It must be the ultimate programming methodology. This method has been applied to 100,000 lines of code-level pure clojure project, which can prove the practicability of this method. [The Pure Function Pipeline Data Flow](https://github.com/linpengcheng/PurefunctionPipelineDataflow)
In Data-Oriented Design (2018)
lincpa·May 20, 2019
Comment Area Markup Method Literary Programming, Programming was the first, Literary was the second. the main purpose of the Code comment area markup method is to live Preview directly in the Code Editor Preview panel without exporting or any preprocessing. Just add a line comment character of the programming language before each line of Markdown. In the comments of code, you can draw flowcharts, tasklist, display data visualizations, etc. The method is to add extension instructions in any programming language comment area: markdown manual eval code, live eval code, print result, display data visualization and other directives When previewing or converting a format, you only need to simply preprocess: delete line comment characters with regular expressions, example: sed 's/^;//' x.clj Note: line comment character of Clojure(Lisp) is ; lin
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e comment characters of the current file type can be obtained from the editor's API. when we edit the code, we can preview the effect in real time. Editing literary code has a live preview panel like most markdown editors. [Markdown Literary programming that don't break the syntax of any programming language](https://github.com/linpengcheng/PurefunctionPipelineDataflow...)
In Why Racket? Why Lisp?
lincpa·May 10, 2019
I worked as a Foxpro programmer for 18 years. I later switched to the Clojure language for 8 years. I used the functional programming language Clojure as SuperFoxpro, which is very easy to use and enjoyable. I has formed a new programming idea ---- `Everything is Foxpro (RMDB)`. ;-) I advocate: Building a relational data model on top of hash-map to achieve a combination of NoSQL and RMDB advantages. This is actually a reverse implementation of posgtresql. [Clojure is a functional programming language based on relational database theory](https://github.com/linpengcheng/PurefunctionPipelineDataflow...) [Everything is RMDB](https://github.com/linpengcheng/PurefunctionPipelineDataflow...) [Implement relational data model and programming based on hash-map (NoSQL)](https://github.com/linpengcheng/PurefunctionPipelineDataflow...)
In We Can Do Better Than SQL
lincpa·May 2, 2019
Markdown Literary programming that doesn't break the syntax of any programming language. Literary Programming, Programming was the first, Literary was the second. the main purpose of the Code comment area markup method is to live Preview directly in the Code Editor Preview panel without exporting or any preprocessing. Just add a line comment character of the programming language before each line of Markdown. In the comments of code, you can draw flowcharts, tasklist, display data visualizations, etc. The method is to add extension instructions in any programming language comment area: markdown manual eval code, live eval code, print result, display data visualization and other directives When previewing or converting a format, you only need to simply preprocess: delete line comment characters with regular expressions, example: sed 's/^;//
Read the rest
' x.clj Note: line comment character of Clojure(Lisp) is ; line comment characters of the current file type can be obtained from the editor's API. when we edit the code, we can preview the effect in real time. Editing literary code has a live preview panel like most markdown editors. Advantages fast, live, simple, no interference. It don't break the syntax of any programming language, you can compile directly. comment area markup method can be applied to any programming language and any markup (including Org,rst, asciidoc, etc.), which is the greatest advantage. you only need a single line code to delete line comment characters using regular expressions, then you can use any Markdown parse or converter. Support any code editor that supports Markdwon Live preview, allowing the source code of any programming language to become rich text in real time. In the code's comment area, You can use the markdown to draw flowcharts, tables, task lists, and display images on the live preview panel, enhance the readability of your code. If you extend the Markdwon tag, you can implement the eval code, print result, display data visualization and other instruction tags, to achieve live programming, live test. When writing (reading or refactoring) code files, It can modify and live preview directly in the editor without exporting or any preprocessing. Reliable. Maximum code accuracy is guaranteed, and markup language errors do not affect the code. It hasn't interfere anyone to read the code. Markdown is simple, so if it doesn’t have syntax highlighting, it doesn’t have much effect on writing and reading. And having a gray comment area doesn’t affect reading code, especially for people who don’t understand the markup language. Strict distinction between markdown and code, and gray comment area can reduce the amount of information in the source code file, conducive to reading code. https://github.com/linpengcheng/PurefunctionPipelineDataflow...
In Next-Paradigm Programming Languages: What Will They Look Like?

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