Jackson Palmer ummjackson

## timeline.json
[{
		"id": "1615562828584480769",
		"created_at": "2023-01-18T04:12:48.000Z",
		"in_reply_to_id": 1615554007954587600,
		"in_reply_to_account_id": 75586944,
		"sensitive": false,
		"spoiler_text": "",
		"visibility": "public",
		"language": "en",
		"uri": "https://twitter.com/karl_delo/status/1615562828584480769",

## fedistream.html
<!DOCTYPE html>
<html>
<head>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width, initial-scale=1">
	<title>fedistream</title>
	<style>
	html,
	body {
		font-family: -apple-system, BlinkMacSystemFont, avenir next, avenir,

## mastodon-emojified-content.js
/*
This JavaScript function takes "content" value and "emojis" array from a Mastodon API "status" object and converts custom emoji shortcodes into the corresponding HTML image tags.

Example usage, assuming you have just parsed a JSON "status" object from the Mastodon API into a "status" variable:

emojifiedContent = customEmojis(status.content, status.emojis);

You will then want to use CSS to style the ".emoji" class. Example CSS:

  .emoji {

## MASTO-FTS.MD

      
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                ummjackson
                / MASTO-FTS.MD
            
            
              Last active
              January 4, 2023 01:03
            
              
                Run full-text search SQL on a Mastodon federated stream
              
          
      View MASTO-FTS.MD
  
      
    Mastodon Streaming Full-Text Search
This is a (hacky) implementation of full-text search in Python for Mastodon. Built and tested with Python 3.10
Errors and disconnections are not handled, so you'll need to implement that for something more robust and production ready. If you just want to monitor certain keywords via SQL queries from a real-time stream, however, the simple implementation may suit your needs.
You can change the instance URL on Line 28 (default: mastodon.social) to fetch the federated timeline from somehwere else, if you'd like. Big, well-federated instances will obviously expose the most rich streams.
Running

  
## audio-spectrum.sh
#!/bin/sh
# Make sure you have ffmpeg installed (eg. brew install ffmpeg)
ffmpeg -i "your-audio-file.wav" -filter_complex "asplit[main][tmp]; [tmp]aformat=channel_layouts=mono,aresample=32000 [cut]; [cut]showfreqs=mode=bar:ascale=sqrt:win_size=2048:s=1920x240:colors=White[out]; [out]split[top][bottom]; [bottom]vflip[bottom]; [top][bottom]vstack=inputs=2[combined]" -map "[combined]" -pix_fmt yuv420p -map "[main]" -preset ultrafast output.mp4

## xrpaway.py
# Requirement: pip install tweepy
import tweepy

# Credentials go here (generate at: https://apps.twitter.com)
auth = tweepy.OAuthHandler('consumer_key', 'consumer_secret')
auth.set_access_token('access_token', 'access_token_secret')

# Connect to Twitter
api = tweepy.API(auth)

## awdy-bitcoin.py
import time
import pandas as pd
from selenium import webdriver

# These are the variables which must be calculated by the script.
consensus_distribution = None
wealth_distribution = None
client_codebases = None
public_nodes_source = None

## killabot.py
# Requirements: pip install tweepy fuzzywuzzy python-Levenshtein
import tweepy
import re
from fuzzywuzzy import fuzz

# Credentials go here (generate at: https://apps.twitter.com)
auth = tweepy.OAuthHandler('consumer_key', 'consumer_secret')
auth.set_access_token('access_token', 'access_token_secret')

# Connect to Twitter

## chime-backup.md

      
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                ummjackson
                / chime-backup.md
            
            
              Created
              April 7, 2017 00:58
            
              
                chime.social data backup, prior to closure of instance.
              
          
      View chime-backup.md
  
      
    🔔 chime.social backup

this is a backup of tables containing non-private/sensitive data from chime.social, prior to the closure of the instance.


## social-requirements.md

      
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                ummjackson
                / social-requirements.md
            
            
              Created
              November 8, 2016 05:21
            
              
                Brainstorming about what Twitter could be... 🤔
              
          
      View social-requirements.md
  
      
    This is a WIP
Basics

Implement core feature set of Twitter (users, statuses, followers/friends, lists, blocking)
Do not implement direct messaging initially (there are already any IM clients out there)
Implement 1:1 replica of Twitter v1.1 API

Very generous limits up-front (only what's needed to avoid denial of service / spam attacks)
Clients must register a Client ID prior to making requests (same as Twitter)
	[{
	"id": "1615562828584480769",
	"created_at": "2023-01-18T04:12:48.000Z",
	"in_reply_to_id": 1615554007954587600,
	"in_reply_to_account_id": 75586944,
	"sensitive": false,
	"spoiler_text": "",
	"visibility": "public",
	"language": "en",
	"uri": "https://twitter.com/karl_delo/status/1615562828584480769",
	<!DOCTYPE html>
	<html>
	<head>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width, initial-scale=1">
	<title>fedistream</title>
	<style>
	html,
	body {
	font-family: -apple-system, BlinkMacSystemFont, avenir next, avenir,
	/*
	This JavaScript function takes "content" value and "emojis" array from a Mastodon API "status" object and converts custom emoji shortcodes into the corresponding HTML image tags.

	Example usage, assuming you have just parsed a JSON "status" object from the Mastodon API into a "status" variable:

	emojifiedContent = customEmojis(status.content, status.emojis);

	You will then want to use CSS to style the ".emoji" class. Example CSS:

	.emoji {
	#!/bin/sh
	# Make sure you have ffmpeg installed (eg. brew install ffmpeg)
	ffmpeg -i "your-audio-file.wav" -filter_complex "asplit[main][tmp]; [tmp]aformat=channel_layouts=mono,aresample=32000 [cut]; [cut]showfreqs=mode=bar:ascale=sqrt:win_size=2048:s=1920x240:colors=White[out]; [out]split[top][bottom]; [bottom]vflip[bottom]; [top][bottom]vstack=inputs=2[combined]" -map "[combined]" -pix_fmt yuv420p -map "[main]" -preset ultrafast output.mp4
	# Requirement: pip install tweepy
	import tweepy

	# Credentials go here (generate at: https://apps.twitter.com)
	auth = tweepy.OAuthHandler('consumer_key', 'consumer_secret')
	auth.set_access_token('access_token', 'access_token_secret')

	# Connect to Twitter
	api = tweepy.API(auth)
	import time
	import pandas as pd
	from selenium import webdriver

	# These are the variables which must be calculated by the script.
	consensus_distribution = None
	wealth_distribution = None
	client_codebases = None
	public_nodes_source = None
	# Requirements: pip install tweepy fuzzywuzzy python-Levenshtein
	import tweepy
	import re
	from fuzzywuzzy import fuzz

	# Credentials go here (generate at: https://apps.twitter.com)
	auth = tweepy.OAuthHandler('consumer_key', 'consumer_secret')
	auth.set_access_token('access_token', 'access_token_secret')

	# Connect to Twitter