FUN in S&T: Python

Differences between Python 2 and 3 - This articles explains the subtle and not so subtle differences (print ('...'), input(...) and eval(input(..)) instead of raw_input and input in 3, etc)

Python Style Guide - Readability Counts! And hey this document shows a desire for standardization of coding to aid everyone in the community

PyDev - IDE

Generators Generators in Python:

Tricks, Tips, and Hacks:
Python Tips, Tricks, and Hacks

MIT OpenCourseWare
MIT 6.00 Intro to Computer Science & Program
Under MIT OpenCourseWare, all the lectures are available on MIT youtube channel with handouts and associative study materials. Here is the play list for this course -

some presentation (and code samples) on Generators in Python? Generator Tricks for Systems Programmers

Python E-Books - e-Literature to get you started and free to boot

Dive Into Python – The original but not the best anymore. It taught me Python so I’ve got fond memories and a special place in my heart for it.
How to Think Like a Computer Scientist: Learning With Python – A newly revised edition of this book is due out in Feburary 2009 but its still worth taking a look at the original.
Text Processing in Python – I haven’t read it but I thoguht I’d add it for the sake of completeness.
Start Programming With Python – Its a relatively new project started by an enthusiast. A hell of a lot has already been produced and its due to be finished by Xmas.
PLEAC Python – Its like a rapid-fire Python Cookbook with short, concise examples of how to solve a variety of low-level problems. Form string manipulation to database access.
Non-Programmers Tutorial for Python – Its for non-programmers but its sometimes useful to read form a different point of view. I find the perspective refreshing.
Python 101 – Part of a university course this goes through the fundamentals as well as providing exercises.
Thinking in Python Design Patterns and Problem-Solving Techniques – A mammoth title written by the great Bruce Eckel.
Python Standard Library – This is seriously showing its age as it was originally written for Python 2.0. Although there’s updates they’re incomplete. Its still worth a look though to get a good idea of the Python core.
Python Programming Tutorial – It looks okay, though nothing ground breaking.
Django Book – A book on Pythons greatest web framework.
Pylons Book – A book on Pythons 3rd best web framework.
Sockets Programming in Python – I found this over at Scribd which is fast turning out to be a great little site. I recommend you look at some of the other books on offer once you’ve looked at this.
Python Network Programming – Heavy on theory and light on practice. Still a worthy read when you need to sleep.
Advanced Python Programming – This is actually a 126 slide lecture given by a Chicago University lecturer. Some good stuff in here.

“A Byte of Python”.

http://www.swaroopch.com/notes/Python

Python programming wiki book

http://en.wikipedia.org/wiki/Wikibooks:Python_Programming

Open-Source Book: Python 3 Patterns, Recipes and Idioms

http://www.mindviewinc.com/Books/Python3Patterns/Index.php

http://www.pythonxy.com/

http://www.pycon.org/

Python Links

Core

www.python.org
The Python Tutorial
Python 2.5 reference card
Python Quick Reference ( 2.5 , 2.4)
Building Skills in Python
How to Think Like a (Python) Programmer
Dive Into Python
A Byte of Python
Python-by-example
Useful simple examples from the Python Standard Library
- commands, glob, math, os, random, shutil, stat, sys time
String documentation
Google's Python Class
MIT Introduction to Computer Science and Programming

General Scientific Programming

(Very) Simple (Numerical) Recipes in Python
scipy (docs).
numpy ( Numpy reference, Simple Examples)
Summary of NumPy Commands
Arrays in SciPy/Numpy/Python (attributes, methods, functions)

SciPy Course
Minuit numerical function minimization in Python
PyMC Markov chain Monte Carlo package
Python Scripting for Computational Science
Numerical Methods in Engineering with Python (2nd Edition) by Jaan Kiusalaas ( Examples )
Physical constants in python
Python Imaging Library (PIL)
RPy - R from Python

Calling c functions and fortran subroutines

SWIG
f2py

Plotting

Matplotlib

Pgplot and ppgplot

pgplot
Subroutine Descriptions
pgplot colours, symbols, line types
ppgplot ( local copy of ppgplot-1.3.tar.gz ).
pgplot, ppgplot and gfortran
Using ppgplot on Durham ITS, first star.init, then try the demo programmes
jor_comp.py, (data file)
ex_graph.py
ex_arro.py
ex_panel.py
ex_cont.py
ex_sierp.py

Astronomy

pyfits
Topical Software
Astronomy Tutorial (pdf)
pyraf
PyEphem
VOTable.py
Python version of Ned Wright's Cosmology Calculator by James Schombert.
Scott Ransom's pySLALIB python+numpy wrappers for the SLALIB
Russell Owen's RO Python Package
Russell Owen's AstroPy Links
Matt Hilton's astLib (Python tools for Astronomy)

Example Python Programs and Functions

Find the median of an array (source)
Angular separation of two points on the Celestial Sphere (source)
Bearing (position angle) of one point on a sphere relative to another (source)
To the azimuth and elevation of celestial object (source)
Convert from J2000 equatorial coordinates to galactic coordinates (source)
To find aperture magitudes for a set of x, y position on an image (source)
Incomplete Gamma functions, etc (gammln, gser, gcf, gammp, gammq translated from Numerical Recipes) (source)
plot_prof.py Plots galaxy surface brightness curves, outputs: prof.ps
plot_petro.py Plots petrosian functions for a range of sersic profiles, outputs: petro.ps
make_galfit_gal.py Create bulge and disk images from GALFIT output fit.log file
Average a set of JPEGS with PIL and numpy (source)
Convert the SDSS photo flag hex number into the flag names (source, PhotoFlags.dat)
Make up 2d gaussian fits image (source).
Example of using scipy.signal.convolve2d (source). Input fits files (gal.fits, psf.fits).
How to use the signal timeout (source).
Using astLibs to make up a postage stamp image (source)
Examples of file locking in GCC and python

PyTables is a package for managing hierarchical datasets and designed to efficiently and easily cope with extremely large amounts of data. You can download PyTables and use it for free. You can access documentation, some examples of use and presentations in the HowToUsesection.

--

♥ ¸¸.•*¨*•♫♪♪♫•*¨*•.¸¸♥

Wednesday, February 9, 2011

Paul Harrison

Paul Harrison

Some very good Python packages
one of them is : Robust topological sorting and Tarjan's algorithm in Python

Other Code snippets

A key-value data warehouse
Querying intervals efficiently in SQL + Python revisited
Querying intervals efficiently in SQL + Python
Sketchifier
Robust topological sorting and Tarjan's algorithm in Python
lol.py
Lazy lists in Python
Approximate string matching with regular expressions
Search a large sorted text file in Python
Euclidean Distance Transform in Python
Prototype-based programming in Python
Python VP-tree implementation
Simple fairly robust time and date parsing in Python

Sunday, January 30, 2011

简明 Python 编程规范

本文最初发表于赖勇浩（恋花蝶）的博客：http://blog.csdn.net/lanphaday，
简明 Python 编程规范

标准头部

#!/usr/bin/python

编码
    所有的 Python 脚本文件都应在文件头标上 # -*- coding:utf-8 -*- 。设置编辑器，默认保存为 utf-8 格式。
注释
    业界普遍认同 Python 的注释分为两种的概念，一种是由 # 开头的“真正的”注释，另一种是 docstrings。前者表明为何选择当前实现以及这种实现的原理和难点，后者表明如何使用这个包、模块、类、函数（方法），甚至包括使用示例和单元测试。
    坚持适当注释原则。对不存在技术难点的代码坚持不注释，对存在技术难点的代码必须注释。但与注释不同，推荐对每一个包、模块、类、函数（方法）写 docstrings，除非代码一目了然，非常简单。
缩进
    Python 依赖缩进来确定代码块的层次，行首空白符主要有两种：tab 和空格，但严禁两者混用。如果使用 tab 缩进，设定 tab 为 4 个空格。
    公司内部推荐使用 4 个空格的 tab 进行缩进。
空格
    空格在 Python 代码中是有意义的，因为 Python 的语法依赖于缩进，在行首的空格称为前导空格。在这一节不讨论前导空格相关的内容，只讨论非前导空格。非前导空格在 Python 代码中没有意义，但适当地加入非前导空格可以增进代码的可读性。
1）在二元算术、逻辑运算符前后加空格：如 a = b + c；
2）在一元前缀运算符后不加空格，如 if !flg: pass；
3） “:”用在行尾时前后皆不加空格，如分枝、循环、函数和类定义语言；用在非行尾时两端加空格，如 dict 对象的定义 d = {‘key’ : ’value’}。
4）括号（含圆括号、方括号和花括号）前后不加空格，如 do_something(arg1, arg2)，而不是 do_something( arg1, arg2 )；
5）逗号后面加一个空格，前面不加空格；s
空行
    适当的空行有利于增加代码的可读性，加空行可以参考如下几个准则：
1）在类、函数的定义间加空行；
2）在 import 不同种类的模块间加工行；
3）在函数中的逻辑段落间加空行，即把相关的代码紧凑写在一起，作为一个逻辑段落，段落间以空行分隔；
断行
    尽管现在的宽屏显示器已经可以单屏显示超过 256 列字符，但本规范仍然坚持行的最大长度不得超过 78 个字符的标准。折叠长行的方法有以下几种方法：
1) 为长变量名换一个短名，如：
    this.is.a.very.long.variable_name = this.is.another.long.variable_name
    应改为：
    variable_name1 = this.is.a.very.long.variable_name
    variable_name2 = this.is.another.variable_name
    variable_name1 = variable_name2s
2) 在括号（包括圆括号、方括号和花括号）内换行，如：
    class Edit(CBase):
        def __init__(self, parent, width,
                                font = FONT, color = BLACK, pos = POS, style = 0):
    或：
    very_very_very_long_variable_name = Edit(parent, \
                                                                            width, \
                                                                            font, \
                                                                            color, \
                                                                            pos)
    如果行长到连第一个括号内的参数都放不下，则每个元素都单独占一行：
    very_very_very_long_variable_name = ui.widgets.Edit( \
                                                                                    panrent, \
                                                                                    width, \
                                                                                    font, \
                                                                                    color, \
                                                                                    pos)
3) 在长行加入续行符强行断行，断行的位置应在操作符前，且换行后多一个缩进，以使维护人员看代码的时候看到代码行首即可判定这里存在换行，如：
if color == WHITE or color == BLACK \
or color == BLUE: # 注意 or 操作符在新行的行首而不是旧行的行尾
do_something(color);
命名
    一致的命名可以给开发人员减少许多麻烦，而恰如其分的命名则可以大幅提高代码的可读性，降低维护成本。
常量
常量名所有字母大写，由下划线连接各个单词，如
WHITE = 0XFFFFFF
THIS_IS_A_CONSTANT = 1
变量
    变量名全部小写，由下划线连接各个单词，如
color = WHITE
this_is_a_variable = 1
    不论是类成员变量还是全局变量，均不使用 m 或 g 前缀。私有类成员使用单一下划线前缀标识，多定义公开成员，少定义私有成员。
    变量名不应带有类型信息，因为 Python 是动态类型语言。如 iValue、names_list、dict_obj 等都是不好的命名。
函数
    函数名的命名规则与变量名相同。
类
    类名单词首字母大写，不使用下划线连接单词，也不加入 C、T 等前缀。如：
class ThisIsAClass(object):
    passs
模块
    模块名全部小写，对于包内使用的模块，可以加一个下划线前缀，如
module.py
_internal_module.py
包
    包的命名规范与模块相同。
缩写    命名应当尽量使用全拼写的单词，缩写的情况有如下两种：
1）常用的缩写，如 XML、ID等，在命名时也应只大写首字母，如
class XmlParser(object):pass
2）命名中含有长单词，对某个单词进行缩写。这时应使用约定成俗的缩写方式，如去除元音、包含辅音的首字符等方式，例如：
function 缩写为 fn
text 缩写为 txt
object 缩写为 obj
count 缩写为 cnt
number 缩写为 num，等。
特定命名方式
    主要是指 __xxx__ 形式的系统保留字命名法。项目中也可以使用这种命名，它的意义在于这种形式的变量是只读的，这种形式的类成员函数尽量不要重载。如
class Base(object):
    def __init__(self, id, parent = None):
        self.__id__ = id
        self.__parent__ = parent
    def __message__(self, msgid):
        # …略
其中 __id__、__parent__ 和 __message__ 都采用了系统保留字命名法。
语句
import
    import 语句有以下几个原则需要遵守：
1） import 的次序，先 import Python 内置模块，再 import 第三方模块，最后 import 自己开发的项目中的其它模块；这几种模块中用空行分隔开来。
2）一条 import 语句 import 一个模块。
3）当从模块中 import 多个对象且超过一行时，使用如下断行法（此语法 py2.5 以上版本才支持）：
from module import (obj1, obj2, obj3, obj4,
                                    obj5, obj6)
4）不要使用 from module import *，除非是 import 常量定义模块或其它你确保不会出现命名空间冲突的模块。
赋值
    对于赋值语言，主要是不要做无谓的对齐，如：
a   = 1     # 这是一个行注释
variable  = 2     # 另一个行注释
fn   = callback_function  # 还是行注释
没有必要做这种对齐，原因有两点：一是这种对齐会打乱编程时的注意力，大脑要同时处理两件事（编程和对齐）；二是以后阅读和维护都很困难，因为人眼的横向视野很窄，把三个字段看成一行很困难，而且维护时要增加一个更长的变量名也会破坏对齐。直接这样写为佳：
a = 1 # 这是一个行注释
variable = 2 # 另一个行注释
fn = callback_function # 还是行注释
分枝和循环
    对于分枝和循环，有如下几点需要注意的：
1) 不要写成一行，如：
if !flg: pass 和 for i in xrange(10): print i都不是好代码，应写成
if !flg:
    pass
for i in xrange(10):
    print i
注：本文档中出现写成一行的例子是因为排版的原因，不得作为编码中不断行的依据。
2) 条件表达式的编写应该足够 pythonic，如以下形式的条件表达式是拙劣的：
if len(alist) != 0: do_something()
if alist != []: do_something()
if s != “”: do_something()
if var != None: do_something()
if var != False: do_something()
上面的语句应该写成：
if seq: do_somethin() # 注意，这里命名也更改了
if var: do_something()
3) 用得着的时候多使用循环语句的 else 分句，以简化代码。
已有代码
    对于项目中已有的代码，可能因为历史遗留原因不符合本规范，应当看作可以容忍的特例，允许存在；但不应在新的代码中延续旧的风格。
    对于第三方模块，可能不符合本规范，也应看作可以容忍的特例，允许存在；但不应在新的代码中使用第三方模块的风格。
    tab 与空格混用的缩进是不可容忍的，在运行项目时应使用 –t 或 –tt 选项排查这种可能性存在。出现混用的情况时，如果是公司开发的基础类库代码，应当通知类库维护人员修改；第三方模块则可以通过提交 patch 等方式敦促开发者修正问题。
已有风格
    开发人员往往在加入项目之前已经形成自有的编码风格，加入项目后应以本规范为准编写代码。特别是匈牙利命名法，因为带有类型信息，并不适合 Python 编程，不应在 Python 项目中应用。

Python的可变参数*args与**kwargs

From:http://hi.baidu.com/zengjianyuan/blog/item/6a1cd400f6a6261c728b65b1.html

*args是个tuple，**kwargs是个dict。

[zjy@zjy Code]$ cat aa.py
def foo(*args,**kwargs):
print('args: %s' % str(args)),
print('kwargs: %s' % str(kwargs))
foo(2,3,4)         #print "args: (2,3,4) kwargs: {}"
foo(a=4,b=5)         #print "args: () kwargs: {'a': 4, 'b': 5}
foo(2,3,a=4,b=5)     #print "args: (2,3) kwargs: {'a': 4, 'b': 5}
#foo(a=4,b=5,2,3)     #raise SyntaxError
x = (2,3,4)
foo(7,8,9,x)         #print "args: (7,8,9,(2,3,4)) kwargs: {}"
foo(7,8,9,*x)         #print "args: (7,8,9,2,3,4) kwargs: {}"

*args和**kwargs并用时，*args必须放在**kwargs的前面。

转自：http://dongua81.blog.163.com/blog/static/55795320095298314707/

Sunday, January 16, 2011

Notes about the virtual python

Notes about the virtual python
===============================
Function: double a mirror of the system python to your own,
such that you can further use it to creat your own Lib (especially
for site-pages

Usage: we test it on the coates:

-$module load python
-$ which python
/apps/coates/Python-2.5.2/bin/python # this is the system python

# To install the virtual-python

-$ module load python
-$ python virtual-python.py
-$ which python
-$ /home/ba01/u117/usename/bin/python

# go ahead to download the pages you need: unzip it and find each setup.py
# dirct to the local folder of that page, then lunch::

-$ /home/ba01/u117/usename/bin/python setup.py install

# Now test:
-bash-3.2$ python
Python 2.5.2 (r252:60911, Apr 8 2010, 10:22:54)
[GCC 4.4.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import nltk
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ImportError: No module named nltk
>>> exit()
-bash-3.2$ /home/ba01/u117/usename/bin/python
Python 2.5.2 (r252:60911, Apr 8 2010, 10:22:54)
[GCC 4.4.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import nltk
>>> dir(nltk)

usename: your user login name

Saturday, January 15, 2011

Python Tips, Tricks, and Hacks

FROM: http://www.siafoo.net/article/52#checking-for-property-and-method-existence
By David

Updated 4 months ago (17 Aug 2010 at 10:12 PM) history recent activity

Want to write shorter, cleaner code? Have an unfortunate situation where you need to fit as much as you can in one expression? Prefer a quick dose of hacks to spending the rest of your life reading the docs? You've come to the right place.

Want to write shorter, cleaner code? Have an unfortunate situation where you need to fit as much as you can in one expression? Prefer a quick dose of hacks to spending the rest of your life reading the docs? You've come to the right place. We start out with some quick tricks that you might have figured out if you've spent some time with Python, but I promise there's more crazy stuff towards the bottom.
I've tried to make all of the code snippets executable on their own. If you want, paste them into your Python shell and try them out. You'll notice that many examples contain a 'true example' and a 'false example', with one commented out. Feel free to switch the comment and see what happens.
You'll also see a few blank comments floating around in the code. These are to improve readability by adding line breaks while still allowing the Python interpreter to parse the code. These would not be necessary in a 'real' (non-pasted) program.
A quick distinction about true vs. True in this article: when I say an object is 'true', I mean that the object, if converted to a boolean in an if statement or elsewhere, would be converted to True and not False. I don't mean that the object necessarily is identical to or equal to True. In the same way, if I say an object is 'false', I mean that the object would be converted to False, not that it necessarily is equal to or identical to False.
If you prefer, there is a Russian translation of the first parts of this article.

1 Quick Tricks

1.1 Four Kinds of Quotes

Let's start with something quick that you probably know. If you're coming from a different language, you're probably used to using single quotes for one thing and double quotes for another. Python lets you use both, although not interchangeably (if you start with one, you have to end with the same one). Python also has a two more types of quotes. A triple quote, ''', is created by typing three single quotes. A triple-double quote, """, is created by typing three double quotes. So, you can have several layers of quoting before you need to worry about escaping your quotes. For example, this is valid Python:

1print """I wish that I'd never heard him say, '''She said, "He said, 'Give me five dollars'"'''"""

1.2 Truthfulness of Various Objects

Unlike some programming languages (cough Javascript cough) Python types are false if empty, and true if not. That means you don't have to check, for example, that the length of a string, tuple, list, or dict is 0 or is equal to an empty one. It is enough to just check the truthfulness of the object.
As you would expect, the number zero is also false, while all other numbers are true.
For example, the following expressions are equivalent. Here, 'my_object' is a string, but it could easily be another Python type (with appropriate modifications to the equality test)

 1my_object = 'Test' # True example
 2# my_object = '' # False example
 3
 4if len(my_object) > 0:
 5    print 'my_object is not empty'
 6
 7if len(my_object):  # 0 will evaluate to False
 8    print 'my_object is not empty'
 9
10if my_object != '':
11    print 'my_object is not empty'
12
13if my_object: # an empty string will evaluate to False
14    print 'my_object is not empty'

In conclusion, there's really no need to check lengths or equality if you're only interested in if the object is empty or not.

1.3 Checking if a String Contains a Substring

Here's a quick hint that might be obvious, but it took me about a year of Python programming to figure it out.
You probably know that you can test if a list, tuple, or dict contains an item by testing the expression 'item in list' or 'item not in list'. I never realized that this would work for strings as well. I was always writing code like:

1string = 'Hi there' # True example
2# string = 'Good bye' # False example
3if string.find('Hi') != -1:
4    print 'Success!'

That's some ugly code. It is completely equivalent to do 'if substring in string':

1string = 'Hi there' # True example
2# string = 'Good bye' # False example
3if 'Hi' in string:
4    print 'Success!'

Much cleaner and simpler. Might be obvious to 99% of the population, but I wish I'd known about it sooner.

1.4 Pretty-Printing a List

Lists don't print nicely. It's of course obvious what the list is, but an average user doesn't want to see brackets around everything. There's a trivial solution to this, using a string's 'join' method:

1recent_presidents = ['George Bush', 'Bill Clinton', 'George W. Bush']
2print 'The three most recent presidents were: %s.' % ', '.join(recent_presidents)
3# prints 'The three most recent presidents were: George Bush, Bill Clinton, George W. Bush.

The join method turns the list into a string by casting each item into a string and connecting them with the string that join was called on. It's even smart enough to not put one after the last element.
As an added advantage, this is pretty fast, running in linear time. Don't ever create a string by '+'ing list items together in a for loop: not only is it ugly, but it takes much longer.

1.5 Integer vs. Float Division

By default, if you divide one integer by another, the result will be truncated into an integer. For example, executing 5/2 returns 2.
There are two was to fix this. The first and simplest way is to just turn one of the integers into a float. If the values are static, you can just append a .0 to one to make it a float: 5.0/2 returns 2.5. Alternatively, you can just cast one of the values: float(5) / 2 returns 2.5.
The other way will result in cleaner code, but you must make sure none of your code is relying on this truncation. You can do a from __future__ import division to change Python to always return a float as the result of a division. After such an import, 5/2 will return 2.5. If you still need to use the truncating integer division somewhere, you can then use the // operator: 5//2 will always return 2.

variable(s)	a comma-separated list variable or variables that the function can receive. You can't use keywords, and you don't want these to be in parentheses (a mistake I started making for a couple of months and wondered why my lambdas never worked).
expression	an inline python expression. Scope includes local scope and variable(s). This is what the function returns.

list	anything that can be treated as a list or iterator
variable(s)	variable or variables to assign the current list element to, just like in a regular `for` loop
condition	an inline python expression. Scope again includes local scope and variable(s). If this evaluates to true, item will be included in result.
element	an inline python expression. Scope includes the local scope and variable(s). This is the actual element that will be included in the result.