jassinm

[PyHUG] July: Use Python in Org-mode

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import pandas as pd
import numpy as np
from tabulate import tabulate

df = pd.DataFrame(np.random.random((4,3)), columns=['A','B','C'])
print("foo")
return(tabulate(df, headers="keys", tablefmt="orgtbl"))

Dependency Injection in Functional Programming

There exist several DI frameworks / libraries in the Scala ecosystem. But the more functional code you write the more you'll realize there's no need to use any of them.

A few of the most claimed benefits are the following:

Dependency Injection.
Life cycle management.
Dependency graph rewriting.

	# encoding=utf8

	import os

	import cuisine

	from fabric.api import run, sudo, cd, task, local

	from fabtools.vagrant import vagrant

	# Copyright 2012 Erlware, LLC. All Rights Reserved.
	#
	# This file is provided to you under the Apache License,
	# Version 2.0 (the "License"); you may not use this file
	# except in compliance with the License. You may obtain
	# a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing,

	from pyspark import SparkContext
	from pyspark.sql import SQLContext
	from pyspark.sql import Row, StructField, StructType, StringType, IntegerType

	sc = SparkContext('spark://master:7077', 'Spark SQL Intro')
	sqlContext = SQLContext(sc)
	dividends = sc.textFile("hdfs://master:9000/user/hdfs/NYSE_dividends_A.csv")
	dividends_parsed = dividends.filter(lambda r: not r.startswith('exchange')).map(lambda r: r.split(',')).map(
	lambda row: {'exchange': row[0], 'stock_symbol': row[1], 'date': row[2], 'dividends': float(row[3])})

	from flask import Flask
	from flask.ext import restful
	from flask.ext.sqlalchemy import SQLAlchemy

	app = Flask(__name__)
	app.config.from_object('config')

	#flask-sqlalchemy
	db = SQLAlchemy(app)