HarshTrivedi

import torch
from torch import LongTensor
from torch.nn import Embedding, LSTM
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence

## We want to run LSTM on a batch of 3 character sequences ['long_str', 'tiny', 'medium']
#
#     Step 1: Construct Vocabulary
#     Step 2: Load indexed data (list of instances, where each instance is list of character indices)

ihsgnef

import numpy as np
import matplotlib
import matplotlib.pyplot as plt

def colorize(words, color_array):
    # words is a list of words
    # color_array is an array of numbers between 0 and 1 of length equal to words
    cmap = matplotlib.cm.get_cmap('RdBu')
    template = '<span class="barcode"; style="color: black; background-color: {}">{}</span>'
    colored_string = ''

cameronmaske

"""
base64's `urlsafe_b64encode` uses '=' as padding.
These are not URL safe when used in URL paramaters.
Functions below work around this to strip/add back in padding.

See:
https://docs.python.org/2/library/base64.html
https://mail.python.org/pipermail/python-bugs-list/2007-February/037195.html
"""

hest

def get_count(q):
    count_q = q.statement.with_only_columns([func.count()]).order_by(None)
    count = q.session.execute(count_q).scalar()
    return count

q = session.query(TestModel).filter(...).order_by(...)

# Slow: SELECT COUNT(*) FROM (SELECT ... FROM TestModel WHERE ...) ...
print q.count()

shawnbutts

def bytesto(bytes, to, bsize=1024):
    """convert bytes to megabytes, etc.
       sample code:
           print('mb= ' + str(bytesto(314575262000000, 'm')))

       sample output: 
           mb= 300002347.946
    """

    a = {'k' : 1, 'm': 2, 'g' : 3, 't' : 4, 'p' : 5, 'e' : 6 }

diosmosis

import os
from log_exceptions import log_exceptions

def throw_something(a1, a2):
  raise Exception('Whoops!')

@log_exceptions(log_if = os.getenv('MYAPP_DEBUG') is not None)
def my_function(arg1, arg2):
  throw_something(arg1 + 24, arg2 - 24)