create a usecase summary page for religious uses

[eleanorkonik]

• Bible Study with Obsidian video
• The Bible Reference Plugin will let you "fetch" a particular passage of the Bible from the ESV.org.
• Chris Wilson has a youtube video about how he takes notes on the Bible.
• This blog post from Mark McElroy is useful: https://markmcelroy.com/spatial-models-for-relating-ideas/

[achamess]

https://forum.obsidian.md/t/bible-study-in-obsidian-kit-including-the-bible-in-markdown/12503 This is impressive

[micwaab]

I have been using Obsidian to collect and organize resources on Tibetan Buddhism for about a year. I don't have anything online, at the moment, but I will likely publish to a blog in the next two months.

[thecookiemomma]

I keep track of when I remember to listen to my Bible in a Year podcast using dataview and Tracker. I also use the Bible plugin to connect thoughts to Bible verses. Joschua's Bible in Vault project is also useful, though I don't find myself using it as much as I thought I would. I also built a MOC for Faith, using that to pull in ideas and concepts that I'm thinking about.

Obsidian has been great for my faith.

[mitten]

I use Obsidian for my morning prayer ritual - there is a different prayer for each day of the week. I keep each little part of the ritual (the greeting, the specific day prayer, the license to depart, etc) in a separate note and then use the Dynamic Embed plugin to pull them into a master day note for each particular day. That way, if I decide to edit/change the text of one little part, I don't have to change it in 7 different places. (Kind of like an old school mail merge!) I also use a custom CSS class to make the font size huge in preview, so that I can more easily read from the note out loud.

[lguenth]

I have been using Obsidian to collect and organize resources on Tibetan Buddhism for about a year. I don't have anything online, at the moment, but I will likely publish to a blog in the next two months.

If you do, you can drop the link in here (though at that point the issue has probably been closed), send it to me directly or put in the hub channel on Discord.

Edit: Forgot the tag. @micwaab

[kzhovn]

I don't use it, but there's a Daf Yomi plugin for preparing a page with resources for the day's Talmud reading.

[lguenth]

I don't use it, but there's a Daf Yomi plugin for preparing a page with resources for the day's Talmud reading.

@kzhovn, awesome, thank you! I will take a look and add it to the note.

[lguenth]

Just a note to everyone that we are looking for external references like plugins, snippets, blog posts, videos, podcasts or full write-ups such as guides on how to use the Bible Kit etc etc. @mitten @thecookiemomma @achamess

If you want to take a look at what the note currently looks like, it's under review here: https://github.com/obsidian-community/obsidian-hub/blob/6035cb064e7e9e767d73b2854eb2069e3453e99b/04%20-%20Guides%2C%20Workflows%2C%20%26%20Courses/for%20Religious%20Uses.md

[pmbauer]

KJV corpus formatted for obsidian. Unique features and usage in Readme

It uses Obsidian markdown and LaTeX features to approximate the original print as much as possible.

https://github.com/pmbauer/av-obsidian

[cassidoo]

I should probably optimize what I do, but I tend to paste in verses from my Bible app (YouVersion), and then put a link around the book names, like so:

And then the link goes to a dataview note of notes about the book:

[erileff]

I don't use it, but there's a Daf Yomi plugin for preparing a page with resources for the day's Talmud reading.

Thank you! I was hoping to find something related to Judaism here.

[lyonsquark]

Hi! I'm the author of the Daf Yomi plugin. Thanks @kzhovn for mentioning it! Just to give some more information here... Daf Yomi, called "The World's Largest Book Club", is the practice of learning a page of the Talmud every day on a set schedule. It takes 7.5 years (a "cycle") to read all 2,711 pages. We're a bit into the third year of the current cycle. The plugin prepares an Obsidian note with PDF of the day's page as well as links to commentary about it.

[birrellwalsh]

I have a line labeled "SIP for ..." + the date in my daily note. In it I keep what comes to me in Suzanne Giesemann's "Sit in Peace" meditation. The comma-separated 'messages' I keep in a tuple surrounded by double quotes, such as "Hope, rejoice, ask if it's true". I wanted to find out what words come up repeatedly (excluding those on a stopwords list I borrowed from Kaggle). It is a crude sort of quantitative theme analysis.

Since Obsidian has "unfenced" data in its markdown files, I am able to use my favorite language to access and write them without waiting for someone to write me a plug-in.

This is the Python code that first creates a "siplog.md" and then gives those words that have a frequency greater than 2%, ordered by frequency.

# Word Frequency 
''' Edit as needed, please:
    - where to put the siplog.md file,
    - where to find the daily notes in Obsidian vault, 
    - and where to find the stopwords list.  
    Output is a printed list of words that meet the criteria (not being on the stopwords list and being more frequent than the cutoff), with the count of each word.'''

# original much-modified code is from
# https://code.tutsplus.com/tutorials/counting-word-frequency-in-a-file-using-python--cms-25965

siplog_location = "C:/Users/Administrator/OneDrive/ProgrammingLanguages/Python files/Obsidian helpers/siplog.md"
notes_location = "C:/Users/Administrator/OneDrive/Obsidian Vaults/First Obsidian Vault/Daily Notes"
stopword_list_location = "C:/Users/Administrator/OneDrive/ProgrammingLanguages/Python files/Obsidian helpers/stopwords.txt"

import os
from  datetime import date
import re
import string
from operator import itemgetter

def removeLinks (t): # to strip [ and ]
    cleaned = t.replace('[[','')   
    cleaned = cleaned.replace(']]','')
    return(cleaned)

#  =================== MAKE THE SIPLOG ==========================

with open(siplog_location, "w",encoding='utf8') as log:
    log.write("                      Log of SIP's as of " + str(date.today())  )

    os.chdir(notes_location)                          # Change directory to where the notes are
    for eachfile in os.listdir():                     # eachfile is a string - the file name.
        with open(eachfile, "r", encoding='utf8') as f:# "with" will handle closing the file for file object f
            lines = f.readlines()                     # get a list of all lines in f
            for eachline in lines:  # for each of those lines                
                if re.search("SIP", eachline):        # if it contains "SIP"
                    siplist = re.findall(r'\"(.+?)\"', eachline)  #this search returns a list of sips
                    if siplist == []:
                        siptext = "None"
                    else:
                        siptext = siplist[0]  #Use just the first SIP.
                        siptext = removeLinks(siptext) #getting rid of [[ and ]]
                    log.write("\n\n"+ eachfile[0:10] +  " - " +  siptext)  # write filename = date and the sip-line to log

#  =================== PROCESS THE SIPLOG ==========================

document_text = open('C:/Users/Administrator/OneDrive/ProgrammingLanguages/Python files/Obsidian helpers/siplog.md', 'r')
text_string = document_text.read().lower()  # make all lowercase
match_pattern = re.findall(r'\b[a-z]{3,15}\b', text_string) # find alphabetic words 2 - 15 long

 # Now remove all words that are on the stopword list
 # First, make a list of stopped words using https://www.kaggle.com/rowhitswami/stopwords/version/1
with open (stopword_list_location,"r", encoding='utf8') as stopwords_file:
    stopped_words = stopwords_file.readlines()        # read in stopped words
    stopped_words =[sw[:-1] for sw in stopped_words]  # remove newlines at the end of each stopword

frequency = {}  # Make an empty frequency dictionary

for word in match_pattern:
    if not word in stopped_words:  # Do not use stopped words
     count = frequency.get(word,0) # Get the current count for word - or if none, use 0
     frequency[word] = count + 1   # Make the count = count + 1

 # Now choose those words whose frequency is greater than cutoff. 

cutoff = 2*int(len(frequency)/100)        # That is 2 percent

common_enough = []                         #create a blank list for those common words
for word_and_freq in frequency.items():    # For each word
    if word_and_freq[1] > cutoff:          # If it is common enough
     common_enough.append(word_and_freq)   # append it to the list

# Now sort those two-tuples by the second (=[1]) member
sorted_common_enough = sorted(common_enough, key = itemgetter(1), reverse = True)

 # -----------------------  Give results  -----------------------------

output_string = ""

output_string += f"\n\nThere are {len(frequency)} words in the siplog dictionary.\n\n"

output_string += f"\nThere are {len(common_enough)} words whose frequency is greater than {cutoff}, the cutoff:\n\n"

for one_result in sorted_common_enough:
    output_string += str(one_result) +"\n"

# Print results 

print(output_string)

[adueck11]

The user "BibleStudy" describes quite detailed his setup and workflow in his study of the bible: https://forum.obsidian.md/t/my-bible-study-workflow/39044

[lguenth]

Thank you, @adueck11. I had seen the guide and it's already part of the note. See #460

[lguenth]

Closing since #460 got merged. :)