Keith Yang keitheis

設定 Python 環境

開始使用 Pyhton 之前，首先要確定電腦上能不能執行 Pyhton 程式。本教學將需要 Python 3.4 或更高的版本，因此請確認電腦上是否有對應版本。若不確定電腦上是否已經安裝 Python，建議直接按照以下步驟設定，以保證教學中的程式皆能夠正常執行。由於各作業系統安裝流程不同，以下請按照作業系統，選擇自己需要的部份閱讀。

Windows

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

在 Windows 上安裝 Miniconda 選 Python 3.5 64bit

這邊用 Miniconda，選擇 Python 3.5 Windows 64-bit。

安裝 Anaconda 一樣沒有問題，兩個裡面是一樣的，只是 Anaconda 預設下載了很多常用套件。

開一個 Command Prompt (Win+R -> cmd + [Enter]) 輸入 conda

	# Copy from http://www.scipy.org/getting-started.html
	import argparse

	import numpy as np
	from scipy import special, optimize
	import matplotlib.pyplot as plt

	def main():
	# Parse command-line arguments
	parser = argparse.ArgumentParser(usage=__doc__)

	"""
	Output all plim to the folder
	e.g.
	python plimcd.py ./templates ../mako
	"""
	import sys
	import os.path
	import subprocess

	________________ TestAssetSpecs.test_asset_spec_no_static_view _________________

	self = <pyramid_webassets.tests.test_webassets.TestAssetSpecs testMethod=test_asset_spec_no_static_view>

	def test_asset_spec_no_static_view(self):
	from webassets import Bundle

	self.create_files({
	'dotted/__init__.py': '',
	'dotted/package/__init__.py': '',

	"""
	Usage:
	1. Enter your plim templates folder
	cd app/templates
	2. Run this Python script
	python bulk_compile_plims.py
	3. Check it out
	tree __plim_output
	"""
	from pathlib import Path

	import time
	import concurrent.futures
	import rx

	num_stream = [1, 2, 3, 4, 5]

	def heavy_work(data):
	time.sleep(1)
	return data

	import alog
	from threading import Thread
	from multiprocessing import Process


	def make_log(x):
	def logging():
	for i in range(5):
	alog.info("loging {}:{}".format(x, i))
	return logging

	import logging
	logging.basicConfig(level=logging.INFO)
	import alog
	from threading import Thread
	from multiprocessing import Process


	def make_log(name, x):
	def logging():
	for i in range(5):