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@0x4D31
0x4D31 / beautiful_idiomatic_python.md
Last active May 22, 2025 08:53 — forked from JeffPaine/beautiful_idiomatic_python.md
[Beautiful Idiomatic Python] Transforming Code into Beautiful, Idiomatic Python #python

Transforming Code into Beautiful, Idiomatic Python

Notes from Raymond Hettinger's talk at pycon US 2013 video, slides.

The code examples and direct quotes are all from Raymond's talk. I've reproduced them here for my own edification and the hopes that others will find them as handy as I have!

Looping over a range of numbers

for i in [0, 1, 2, 3, 4, 5]:
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@brianspiering
brianspiering / .bash_profile
Last active June 16, 2023 18:08
This file holds all my BASH configurations and aliases
# ---------------------------------------------------------------------------
#
# Description: This file holds all my BASH configurations and aliases
#
# Sections:
# 1. Environment Configuration
# 2. Make Terminal Better (remapping defaults and adding functionality)
# 3. File and Folder Management
# 4. Searching
# 5. Process Management
@pierdom
pierdom / plot_precounted_hist.py
Last active August 3, 2023 11:56
[Plot histograms with pre-computed counters] Plot histograms with Marplotlib hist function or Seaborn distplot function using pre-counted values using 'weights' argument. Very useful for plotting distributions of values queried from a very large dataset, where it is impossible to retrieve and load in memory every element of the distribution inde…
#!/usr/bin/env python3
import matplotlib.pyplot as plt
import seaborn as sns
# dictionary with pre-counted bins
test = {1:1,2:1,3:1,4:2,5:3,6:5,7:4,8:2,9:1,10:1}
# with matplotlib
plt.hist(list(test.keys()), weights=list(test.values()))
@kashif
kashif / cifar10_resnet.py
Last active February 3, 2021 09:06
Keras Pre-activation Residual Network for CIFAR-10
from __future__ import print_function
from keras.datasets import cifar10
from keras.layers import merge, Input
from keras.layers.convolutional import Convolution2D, ZeroPadding2D, AveragePooling2D
from keras.layers.core import Dense, Activation, Flatten
from keras.layers.normalization import BatchNormalization
from keras.models import Model
from keras.preprocessing.image import ImageDataGenerator
from keras.utils import np_utils
@RichardBronosky
RichardBronosky / pep8_cheatsheet.py
Created December 27, 2015 06:25
PEP-8 cheatsheet
#! /usr/bin/env python
# -*- coding: utf-8 -*-
"""This module's docstring summary line.
This is a multi-line docstring. Paragraphs are separated with blank lines.
Lines conform to 79-column limit.
Module and packages names should be short, lower_case_with_underscores.
Notice that this in not PEP8-cheatsheet.py
@gtallen1187
gtallen1187 / slope_vs_starting.md
Created November 2, 2015 00:02
A little bit of slope makes up for a lot of y-intercept

"A little bit of slope makes up for a lot of y-intercept"

01/13/2012. From a lecture by Professor John Ousterhout at Stanford, class CS140

Here's today's thought for the weekend. A little bit of slope makes up for a lot of Y-intercept.

[Laughter]

Casual Raiding and Deliberate Learning

Note: I wrote this in 2015 when I was raiding with a casual guild in WoW.

de·lib·er·ate (adj.)

  • done consciously and intentionally: a deliberate attempt to provoke conflict.

  • fully considered; not impulsive: a deliberate decision.

    synonyms: intentional, calculated, conscious, intended, purposeful

@mreid
mreid / huffman.py
Last active September 25, 2021 12:22
Example implementation of Huffman coding in Python
# Example Huffman coding implementation
# Distributions are represented as dictionaries of { 'symbol': probability }
# Codes are dictionaries too: { 'symbol': 'codeword' }
def huffman(p):
'''Return a Huffman code for an ensemble with distribution p.'''
assert(sum(p.values()) == 1.0) # Ensure probabilities sum to 1
# Base case of only two symbols, assign 0 or 1 arbitrarily
if(len(p) == 2):