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gro1m / trie.py
Created March 19, 2022 19:24 — forked from rcshubhadeep/trie.py
trie implementation in Python3
from typing import Tuple
class TrieNode(object):
"""
Our trie node implementation. Very basic. but does the job
"""
def __init__(self, char: str):
self.char = char
@gro1m
gro1m / jupyterlab_shortcuts.md
Created September 28, 2021 12:48 — forked from discdiver/jupyterlab_shortcuts.md
Common Jupyter Lab Keyboard Shortcuts

If you are on a Mac, substitute command for control. Don't type the + (it means press both keys at once).

Shortcuts when in either command mode (outside the cells) or edit mode (inside a cell):

  • Shift + Enter run selected cell or cells - if no cells below, insert a code cell below

  • Ctrl + B toggle hide/show left sidebar

  • Ctrl + S save and checkpoint

  • Ctrl + Shift + S save as

@gro1m
gro1m / bash_strict_mode.md
Created July 23, 2021 10:20 — forked from mohanpedala/bash_strict_mode.md
set -e, -u, -o, -x pipefail explanation

set -e, -u, -o, -x pipefail

The set lines

  • These lines deliberately cause your script to fail. Wait, what? Believe me, this is a good thing.
  • With these settings, certain common errors will cause the script to immediately fail, explicitly and loudly. Otherwise, you can get hidden bugs that are discovered only when they blow up in production.
  • set -euxo pipefail is short for:
set -e
set -u
@gro1m
gro1m / export-svg-inkscape.md
Created October 11, 2020 20:51 — forked from brenopolanski/export-svg-inkscape.md
Exporting an object as svg from inkscape
  1. Select the object(s) to export
  2. Open the document properties window (Ctrl+Shift+D)
  3. Select "Resize page to drawing or selection"
  4. File > Save As Copy...
  5. Select Optimized SVG as the format if you want to use it on the web
@gro1m
gro1m / min-char-rnn.py
Created March 22, 2020 18:30 — forked from karpathy/min-char-rnn.py
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)