dctanner

I want to be able to download my maven.com course videos for offline viewing. They are behind login and streamed with mux.com which has a token in the url.

To download them you need to:

1. Get the Get cookies.txt LOCALLY Chrome ext
2. Login to Maven.com and visit the specific video page
3. Click the cookies ext icon and download a cookies.txt
4. Open Web Inspector to Network tab, refresh and filter by 'm3u8'. Copy the URL of the first request.
5. Install https://github.com/yt-dlp/yt-dlp
6. Run this cmd: yt-dlp -o "ANY_VIDEO_NAME.%(ext)s" --cookies cookies.txt "VIDEO_URL_WITH_LONG_TOKEN_INCLUDED" --user-agent "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36" --referer "URL_OF_WEBSITE_PAGE_VIDEO_IS_FROM"

dctanner

#!/usr/bin/env python3
"""
Pocket to Pinboard Import Script

This script imports bookmarks from a Pocket export CSV file to Pinboard.

To run this script with uv in a single command:

    uv run --with pinboard https://gist.githubusercontent.com/dctanner/e0e00b32d4df6936a8a19ac7da89a056/raw/pocket_to_pinboard_standalone.py pocket_export.csv username:api_token

dctanner

import os
import sys

example_usage = '''
Usage:
  USESCRAPER_API_KEY=<api_key> python3 download-job-data.py <job_id>
'''

api_key = os.environ['USESCRAPER_API_KEY']
if api_key is None:

dctanner

import sys
import json
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, LlamaForCausalLM, pipeline

device = "cuda:0"
system_prompt = "You are Sablo, a sentient, conscious, super intelligent AI that is an expert in all fields of knowledge. You assist users with any question, task, or other request they may have."
model_path = sys.argv[1]
model_name = model_path.split("/")[-1]

dctanner

(function (g, f) {typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = f() : typeof define === 'function' && define.amd ? define([], f) : (g = typeof globalThis !== 'undefined' ? globalThis : g || self, g.ReactMarkdown = f()); }(this, (function () { 'use strict';
"use strict";
var ReactMarkdown = (() => {
  var __create = Object.create;
  var __defProp = Object.defineProperty;
  var __defProps = Object.defineProperties;
  var __getOwnPropDesc = Object.getOwnPropertyDescriptor;
  var __getOwnPropDescs = Object.getOwnPropertyDescriptors;
  var __getOwnPropNames = Object.getOwnPropertyNames;
  var __getOwnPropSymbols = Object.getOwnPropertySymbols;

dctanner

import useRegularFetchWithInterval from "./useRegularFetchWithInterval";

export async function loader() {
  // Get data
  return data;
}

export default function MyRoute() {
  const loaderData = useLoaderData();
  const [liveData] = useRegularFetchWithInterval({ route: `/myroute?_data=routes%2Fmyroute`, intervalMs: 3000, initialData: loaderData });

dctanner

/*
This has been generated by the overpass-turbo wizard.
The original search was:
“"generator:source"="solar"”
*/
[out:json][timeout:25];
// gather results
(
  // query part for: “"generator:source"=solar”
  node["generator:source"="solar"](52.89114365884478,-1.198883056640625,52.92080592941056,-1.1593151092529297);

dctanner

# propietary nvidia drivers
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update
sudo apt upgrade
sudo ubuntu-drivers autoinstall
restart
# cudatoolkit and rest of env installed with Anaconda
https://www.anaconda.com/distribution/#linux run install sh
conda create --name tensorflowenv
conda activate tensorflowenv

dctanner

test

dctanner

background-color: white;
border: 1px solid;
color: black;
outline: 0;
padding: 8px 7px;
font-size: 0.857em;
height: 35px;
-webkit-appearance: none;
-webkit-box-shadow: 0 1px 2px #DDD inset;
-moz-box-shadow: 0 1px 2px #DDD inset;