andreacarriero

require 'base64'
require 'digest'
require 'openssl'
require 'fileutils'

module Jekyll
    class ProtectedPage < Page
        def aes256_encrypt(password, cleardata)
            digest = Digest::SHA256.new
            digest.update(password)

danallison

from sshtunnel import SSHTunnelForwarder
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from functools import wraps

# secrets.py contains credentials, etc.
import secrets

def get_engine_for_port(port):
    return create_engine('postgresql://{user}:{password}@{host}:{port}/{db}'.format(

mbednarski

window_size = 2
idx_pairs = []
# for each sentence
for sentence in tokenized_corpus:
    indices = [word2idx[word] for word in sentence]
    # for each word, threated as center word
    for center_word_pos in range(len(indices)):
        # for each window position
        for w in range(-window_size, window_size + 1):
            context_word_pos = center_word_pos + w

gbaman

# An example to get the remaining rate limit using the Github GraphQL API.

import requests

headers = {"Authorization": "Bearer YOUR API KEY"}


def run_query(query): # A simple function to use requests.post to make the API call. Note the json= section.
    request = requests.post('https://api.github.com/graphql', json={'query': query}, headers=headers)
    if request.status_code == 200:

iteufel

# ************************************************************
# Sequel Pro SQL dump
# Version 4541
#
# http://www.sequelpro.com/
# https://github.com/sequelpro/sequelpro
#
# Host: 127.0.0.1 (MySQL 5.7.16-0ubuntu0.16.04.1)
# Generation Time: 2016-12-21 12:35:15 +0000

messefor

"""Example to show how to plot histogram with accumulate ratio.

Plot multiple histogram using seaborn.FacetGrid()
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

% matplotlib inline

pcmasuzzo

# import
import seaborn as sns
import matplotlib.pyplot as plt

# white background in plots
sns.set(style="whitegrid")

# df is a pandas dataframe
# plot by column by variable 'var1', in 3 columns, coloring by variable 'var2'
grid = sns.FacetGrid(df, col='var1', col_wrap=3, hue='var2', size=4, palette='Set2')

jakevdp

deepak365

What is redash?
Redash is database viewer included BI tool inside. Redash has support for querying multiple databases, including: Redshift, Google BigQuery, PostgreSQL, MySQL, Graphite, Presto, Google Spreadsheets, Cloudera Impala, Hive and custom scripts.

Prerequisite :
1. Install docker 
2. Install git

git clone https://github.com/getredash/redash.git
docker-compose -f docker-compose.production.yml run --rm server create_db
docker-compose -f docker-compose.production.yml up

Dreyer

$ cd /usr/local/lib
$ sudo ln -s ../../lib/libSystem.B.dylib libgcc_s.10.5.dylib
$ sudo ln -s ../../lib/libSystem.B.dylib libgcc_s.10.4.dylib