plain text workflow

Files for the publication & poster for Data Workers, an exhibition by Algolit at the Mundaneum in Mons from 28 March until 28 April 2019. http://www.algolit.net/index.php/Data_Workers

_ _ __ ___ | |_ ___ ___ | '_ \ / _ \| __/ _ \/ __| | | | | (_) | || __/\__ \ |_| |_|\___/ \__\___||___/

line width: 110 char lines per page: 70

70 140 210 280 350 420 490 560 630 700

--- txt to pdf ---

options ...

weasyprint

(stretched the page size, font size, etc, in order to place everything)

enscript

(using postscript to create pdf) $ enscript --word-wrap --margins=40:10:10:20 --fancy-header writers.intro.txt -o - | ps2pdf - test.pdf $ cat writers.intro.txt | iconv -c -f utf-8 -t ISO-8859-1 | enscript --word-wrap --margins=40:10:10:20 --fancy-header -o - | ps2pdf - test.pdf

txt2pdf

(uses reportlab) https://github.com/baruchel/txt2pdf $ python3 txt2pdf/txt2pdf.py -T 1 -B 2 -L 2 -R 1 writers.intro.txt -o test.pdf $ python3 txt2pdf/txt2pdf.py -m A4 -f fonts/fantasque/TTF/FantasqueSansMono-Regular.ttf -s 10 -v 0 -T 1 -B 1 -L 1.5 -R 1.5 data-workers.txt -o test.pdf

currently using: $ python3 txt2pdf/txt2pdf.py -m A4 -f fonts/fantasque/TTF/FantasqueSansMono-Regular.ttf -s 9 -v 0.05 -T 1 -B 0.9 -L 1.5 -R 1.5 data-workers.txt -o test.pdf

PDF2txt miner

The inverted tool of this process https://www.unixuser.org/~euske/python/pdfminer/ "What's It? PDFMiner is a tool for extracting information from PDF documents. Unlike other PDF-related tools, it focuses entirely on getting and analyzing text data. PDFMiner allows one to obtain the exact location of text in a page, as well as other information such as fonts or lines."

--- hyphenation ---

Hyphenator

https://pypi.org/project/hyphenator/

textwrap2

https://pypi.org/project/textwrap3/

--- commands ---

Generate the publication to PDF: $ python3 create_all.py && python3 txt2pdf/txt2pdf.py -m A4 -f fonts/unifont-11.0.03.ttf -s 9 -v 0.05 -T 1 -B 0.9 -L 1.6 -R 1.4 data-workers.en.txt -o data-workers.en.pdf

Add logos.pdf on last page with PDFTK $ pdftk data-workers.en.pdf A=data-workers.en.pdf cat A52 output data-workers.en.backcover.pdf $ pdftk data-workers.en.backcover.pdf multistamp logos.pdf output data-workers.en.logos.pdf $ pdftk A=data-workers.en.pdf B=data-workers.en.backcover.logos.pdf cat A1-51 B output data-workers.en.logos.pdf

PDFTK in one command: $ pdftk data-workers.en.pdf A=data-workers.en.pdf cat A52 output data-workers.en.backcover.pdf && pdftk data-workers.en.backcover.pdf multistamp logos.pdf output data-workers.en.logos.pdf && pdftk A=data-workers.en.pdf B=data-workers.en.backcover.logos.pdf cat A1-51 B output data-workers.en.logos.pdf

--- ASCII/UNICODE fonts ---

Unicode art :) http://xahlee.info/comp/unicode_ascii_art.html http://qaz.wtf/u/convert.cgi?text=This+is+pretty+fun+too.+Do+something+for+your+group+tag https://coolsymbol.com/cool-fancy-text-generator.html http://www.alanwood.net/unicode/

--- unifont ---

http://unifoundry.com/unifont/index.html

--- DUMP ---

[/]<?')([\"\w] ░

                                work
    many authors                
                                write
    every human being 
    who has access 
    to the internet 
                                interacts
    we
                                chat, 
                                write, 
                                click, 
                                like 
                                and share
    we 
                                leave our data
    we
                                find ourselves writing in Python
    some neural networks
                                write
    human editors
                                assist
    poets, 
    playwrights 
    or novelists
                                assist

---

Writers write ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ ▒▒▒▒▒▒▒▒▒▒▒▒▒▒

Data workers ░░░░░░░░░░░░ need data to ▒▒▒▒ with. work The data that is used in the context
of Algolit, is written language. Machine learning relies on many types Many authors of writing. ░░░░░░░░░░░░ ▒▒▒▒▒ in the write form of publications, like books or
articles. These are part of organised archives and are sometimes digitized. But there are other kinds of writing every human too. We could say that ░░░░░░░░░░░░
being who has access to the internet ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ is a writer each time they ▒▒▒▒▒▒▒▒▒ interact with algorithms.

We ░░ ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒. chat, write, click, like and share

                         we         In return for free services, ░░ ▒▒▒▒▒       leave 
                                    ▒▒▒▒▒▒▒▒ that is compiled into profiles     our data
                                    and sold for advertisement and research.    
                                                                                
                                    Machine learning algorithms are not 
                                    critics: they take whatever they're 
                                    given, no matter the writing style, 
                                    no matter the CV of the author, no 
                                    matter their spelling mistakes. In 
                                    fact, mistakes make it better: the 
                                    more variety, the better they learn 
                                    to anticipate unexpected text. But 
                                    often, human authors are not aware 
                                    of what happens to their work.

                                    Most of the writing we use is in 
                                    English, some is in French, some in 
                                    Dutch. Most often we find ourselves 
                                    writing in Python, the programming 
                                    language we use.

                                    Algorithms can be writers too. Some 
                                    neural networks write their own rules 
                                    and generate their own texts. And for 
                                    the models that are still wrestling with 
                                    the ambiguities of natural language, 
                                    there are human editors to assist them. 
                                    Poets, playwrights or novelists start 
                                    their new careers as assistants of AI.

---

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