eebmagic

with open('homeworks.txt') as file:
    content = file.read().strip()
    homeworks = [int(x) for x in content.split('\n')]

with open('tests.txt') as file:
    content = file.read().strip()
    tests = [int(x) for x in content.split('\n')]

# Fill 100s for remaining grades

eebmagic

set tabstop=4 shiftwidth=4 expandtab
syntax on

nnoremap ; : 

" Use tab key for indenting visual blocks
vnoremap <Tab> >gv
vnoremap <S-Tab> <gv

" duplicate highlighted selection under itself

eebmagic

############################################################################################################################
#### MY ALIASES ####
alias youtube-dl-mp3='youtube-dl -x --audio-format mp3 '
alias l='ls -1'
alias md5='md5 -r'
alias usg='du -chd 1 |sort -h'
alias count='ls . | wc -l'
alias counttypes='python3 ~/pythonTools/type_counts/counttypes'
alias typecounts='counttypes '
alias typecount='counttypes '

eebmagic

if [ $UID -eq 0 ]; then NCOLOR="red"; else NCOLOR="yellow"; fi

username() {
    echo "%F{cyan}%n%{$reset_color%}"
}

directory() {
    echo "%~"
}

eebmagic

#!/usr/bin/env python3
import os

remote = os.popen('git remote show').read()
if not remote:
    quit()

response = os.popen(f'git remote show {remote}').read()

for line in response.split('\n'):

eebmagic

• Sample Portrait of Tracy - Live by: Weather Report
  • Starting around 3:30
  • Add dramatic fast crashing drums (like drum&bass type thing, but more jazzy)
  • https://open.spotify.com/track/3sQKRCB0psj3786dD5MmrI?si=4ce0427e179046a5
  • https://www.youtube.com/watch?v=W6iH3JYvJWg
  • Live video:
• https://www.youtube.com/watch?v=25DXcFg1TFo

eebmagic

set tabstop=4 shiftwidth=4 expandtab
syntax on
set clipboard=unnamed
set hlsearch incsearch
set number relativenumber
set ruler
set splitright
set splitbelow
set showcmd

eebmagic

import hashlib
import json
import threading
import math
import time

class SafeInterface():
    def __init__(self, collection, batchSize=200, threaded=True):
        self.col = collection
        self.batchSize = batchSize

eebmagic

Reduce and Plot

Reduce data from a collection to 3D datapoints with PCA reduction.

Then use plotly to plot to a 3d scatter plot.

import plotly.express as px
from sklearn.decomposition import PCA

eebmagic

import chromadb

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.metrics.pairwise import euclidean_distances
from sklearn.metrics import silhouette_score as sil_score
from sklearn.decomposition import PCA
from sklearn.cluster import DBSCAN