aldraco

def gcd(m,n):
    while m % n != 0:
        oldm = m
        oldn = n
        m = oldn
        n = oldm % oldn
    return n

class Rational:
    def __init__(self, n, d):

podhmo

[<__main__.Sub object at 0x1f44250>, <__main__.Sub object at 0x1f44390>, <__main__.Sub object at 0x1f44350>]
[u'a', u'b', u'c']



pre commit
------
	ok
after commit
------

thomas-a-neil

from airflow import DAG
from airflow.operators.bash_operator import BashOperator
from airflow.operators.python_operator import PythonOperator

from datetime import datetime, timedelta


# default arguments for each task
default_args = {
    'owner': 'nthomas',

cmslewis

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <time.h>


/* ==========================================================================
 * COMPARATORS
 * ========================================================================== */

uhho

def s3_to_pandas(client, bucket, key, header=None):

    # get key using boto3 client
    obj = client.get_object(Bucket=bucket, Key=key)
    gz = gzip.GzipFile(fileobj=obj['Body'])
    
    # load stream directly to DF
    return pd.read_csv(gz, header=header, dtype=str)

def s3_to_pandas_with_processing(client, bucket, key, header=None):

kdubovikov

import numpy as np
import tensorflow as tf

from tensorflow.contrib import learn
from tensorflow.contrib.learn.python.learn.estimators import model_fn as model_fn_lib

tf.logging.set_verbosity(tf.logging.INFO)


def cnn_model_fn(features, labels, mode):

satwikkansal

/*
This a header file that includes every standard library.
You can use it to save time.
NOTE: This header file may not be recognized by compilers
other than gcc.
*/
#include <bits/stdc++.h>

/*
//Use this if the above header file doesn't work.

tomdean

from collections import OrderedDict
import datetime
from typing import Iterator, List, Sized, Union

import numpy as np
import pandas as pd
from psycopg2.extensions import QuotedString
from sqlalchemy import and_, exists, MetaData, Table, Column as SAColumn

import logging

malexer

# Note: it is a copy of great answer by "mgoldwasser" from Stackoverflow
# Check the original answer here: http://stackoverflow.com/a/26018934/1032439

# Imagine that post1, post5, and post1000 are posts objects with ids 1, 5 and 1000 respectively
# The goal is to "upsert" these posts.
# we initialize a dict which maps id to the post object

my_new_posts = {1: post1, 5: post5, 1000: post1000} 

for each in posts.query.filter(posts.id.in_(my_new_posts.keys())).all():

szs8

#!/usr/bin/env python

import wx
from wx import EVT_CLOSE
import wx.grid as gridlib

EVEN_ROW_COLOUR = '#CCE6FF'
GRID_LINE_COLOUR = '#ccc'

class PandasTable(wx.Frame):