Peach is hot right now so I poked around their API using https://mitmproxy.org/
As of the last update, this seems to be a fairly extensive/complete list of v1 endpoints, but feel free to submit revisions to this gist with any others you find!
| <!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, |
| [{ | |
| "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", |
| /* | |
| 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 { |
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.
| # 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 |
| # 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) |
| #!/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 |
| 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 |