Python programming tips

一些實用的小技巧，可減少多餘的動作

1. Swap
//C++和Java的寫法:
temp = x
x = y
y = temp

#Python建議使用
x, y= y, x

2. 讀dict時避免判斷key的存在
d = { 'key': 'value' }
#一般寫法
if 'key' in d: print d['key']
else: print 'not find'

#建議寫法
print d.get('key', 'not find')

3. 尋找最小值和對應位置
s = [ 4,1,8,3 ]
#一般寫法
mval, mpos = MAX, 0
for i in xrange(len(s)):
if s[i] < mval: mval, mpos = s[i], i

#建議寫法
mval, mpos = min([ (s[i], i) for i in xrange(len(s)) ])

4. 讀取檔案
#一般寫法
line = ''
fp = open('text.txt', 'r')
for line in fp: text += line

#建議寫法1
text = string.join([ line for line in open('text.txt')], '']

#建議寫法2
text = ''.join([ line for line in open('text.txt')])

#建議寫法3
text = file('text.txt').read()

5. Python使用三元式
#一般寫法，C++會使用?:來處理
if n >= 0: print 'positive'
else: print 'negitive'

#建議寫法1, 但後面式子為None會有問題
print (n >= 0) and 'positive' or 'negitive'

#建議寫法2, 解決了None的問題
print (n >= 0 and ['positive'] or ['negitive])[0]

#建議寫法3
print ('negitive', 'positive')[n >= 0]

6. Dict成員是複雜類別時的初使用
#一般寫法
if not y in d: d[y] = { }
d[y][x] = 3

#建議寫法
d.setdefault(y, { })[x] = 3

#如果為list時
d.setdefault(key, []).append(val)

Python好用的數值計算套件

在別的地方看到的，順便整理一下, Numpy, Scipy, matplotlib是必備套件,三個套件已經有matlab基本的運算功能。

1. xlrd - Library for developers to extract data from Microsoft Excel spreadsheet files 
2. RPy2 - A simple Python interface for R
3. NetworkX -For analyzing network data
4. SymPy - SymPy contains nearly all of the same functionality (algebraic evaluation, differentiation, expansion, complex numbers, etc.) as SimPy, but is contained in a pure Python distribution.
5. SimPy - Short for “Simulation in Python”, an object-oriented, process-based discrete-event simulation language, making it a wholesale agent-based modeling environment written entirely in Python.
6. Boost.Python - This C++ library enables seamless interoperability between C++ and Python
7. PyMC - PyMC implements the Metropolis-Hastings algorithm as a Python class.
8. Pycluster - It contains implementations of hierarchical and k-means clustering
9. NLTK - Natural Language Toolkit is a suite of libraries and programs for symbolic and statistical natural language processing (NLP)