parmentf

Inspired by dannyfritz/commit-message-emoji

See also gitmoji.

Commit type	Emoji
Initial commit	🎉 :tada:
Version tag	🔖 :bookmark:
New feature	✨ :sparkles:
Bugfix	🐛 :bug:

zhengjia

=Navigating=
    visit('/projects')
    visit(post_comments_path(post))

=Clicking links and buttons=
    click_link('id-of-link')
    click_link('Link Text')
    click_button('Save')
    click('Link Text') # Click either a link or a button
    click('Button Value')

bwhite

"""Information Retrieval metrics

Useful Resources:
http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt
http://www.nii.ac.jp/TechReports/05-014E.pdf
http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf
http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf
Learning to Rank for Information Retrieval (Tie-Yan Liu)
"""
import numpy as np

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

duhaime

import warnings
from skimage.measure import compare_ssim
from skimage.transform import resize
from scipy.stats import wasserstein_distance
from scipy.misc import imsave
from scipy.ndimage import imread
import numpy as np
import cv2

##

crmccreary

from Crypto.Cipher import AES
from Crypto import Random

BS = 16
pad = lambda s: s + (BS - len(s) % BS) * chr(BS - len(s) % BS) 
unpad = lambda s : s[0:-ord(s[-1])]

class AESCipher:
    def __init__( self, key ):
        """

aronwc

""" Example using GenSim's LDA and sklearn. """

import numpy as np

from gensim import matutils
from gensim.models.ldamodel import LdaModel
from sklearn import linear_model
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import CountVectorizer

kylehounslow

from __future__ import print_function
import requests
import json
import cv2

addr = 'http://localhost:5000'
test_url = addr + '/api/test'

# prepare headers for http request
content_type = 'image/jpeg'

ghandic

import boto3
from PIL import Image
from io import BytesIO
import os

class S3ImagesInvalidExtension(Exception):
    pass

class S3ImagesUploadFailed(Exception):
    pass

turadg

# Support for Rspec / Capybara subdomain integration testing
# Make sure this file is required by spec_helper.rb
# (e.g. save as spec/support/subdomains.rb)
 
def switch_to_subdomain(subdomain)
  # lvh.me always resolves to 127.0.0.1
  hostname = subdomain ? "#{subdomain}.lvh.me" : "lvh.me"
  Capybara.app_host = "http://#{hostname}"
end