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JnBrymn / code.py
Created February 9, 2024 15:23
This is CircuitPython for the CircuitPlaygroundExpress that allows you to record music by pushing the A button and then touching the capacitive sensors. And then you can play the song by pushing the B button.
print("STARTED")
import time
from adafruit_circuitplayground import cp
notes = {
"C": {
"frequency": 523.25,
"color": (0, 0, 3)
},
"D": {
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#!/usr/bin/env python3
"""
This processes TiddlyWiki dumps to stick them into a format that Bear can import.
Full steps:
* First in your TiddlyWiki under the Tools menu click "export all>Static HTML".
* Next, run this command `process_tiddly_export --tiddler_dump_file=somewhere/tiddlers.html --output_directory=/tmp/some_empty_folder/ --extra_tags=any,tags,you,want` it will
* process the static HTML file into one file per tiddler
* each file will start with <h1>your tiddler title</h1>
* next it will list any #tags on the original tiddler as well as and extra tags you supplied
package main
import (
"fmt"
"math/rand"
"net/http"
"os"
"strconv"
"time"
)
/* MarkovModel creates a Markov model of text (or tokens) and allow you to generate new
* text from the model. It takes two optional arguments:
*
* tokenizer - a function that takes a string and returns an array of tokens
* defaults to a tokenizer that breaks on whitespace and lowercases everything
* shingle_n - the number of tokens that make up a state in the markov model
* the higher the number the more realistic the generated data, but the more
* training data required
* defaults to 1
* join_str - string used to join text together
package main
import (
"fmt"
"github.com/Shopify/sarama" //GIT hash = b3d9702dd2d2cfe6b85b9d11d6f25689e6ef24b0
"time"
)
var groupName = "trash"
var topicName = "event"
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@JnBrymn
JnBrymn / MarkovModel.py
Last active August 29, 2015 13:57
Simple Markov Model
from collections import defaultdict
import random
class MarkovModel(object):
"""
Takes iterator of tokens and makes a markov model of the tokens. n is the "order" of the model
None is a special token that serves as a sort of delimiter of phrases.
"""
@classmethod
def _tokenizer(cls,text,token_delim):