Download Python - 4D Solutions

Python:
Overview and Advanced Topics
Kirby Urner
4D Solutions
Python World
3rd Party
Add-Ons
Standard
Library
Core
Applications
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Topics to Cover
Overview
 Core Python
 “Batteries Included” (adding
power)
 Python as Glue Language
(talking to other apps)

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Part 1: Overview
What is Python?
 Community
 On Ramps
 Development Environments
 Design Philosophy
 Evolution

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By the way, the language is named after the BBC show
“Monty Python's Flying Circus” and has nothing to do with
nasty reptiles. Making references to Monty Python skits in
documentation is not only allowed, it is encouraged!
Guido van Rossum
Python Tutorial
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What is Python?
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Interpreted:
Interactive:
OO:
Modular:
Extensible:
Portable:
High Level:
Free:
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compiles to byte codes
shell mode
“everything is an object”
Standard Library & 3rd party
code new modules in C/C++
Windows, Unix, Linux, Mac
built-in dynamic data types
including for commercial use
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Python - why settle for snake oil when you can have
the whole snake?
— From Usenet posting by Mark Jackson, June 1998
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Interpreted
Not much compile time checking
 No type declarations
 Lots of freedom at runtime
 “Compiling” to byte codes: .pyc, .pyo
 Python VM required (a .dll in Windows)
 No compile/link loop – reload instead
 Rapid development, relatively
slow execution (but frequently “plenty
fast”)

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Interactive
Many GUI shell options (plus
non-GUI shell)
 Shell mode as work bench
 Jython: interactive access
to Java classes
 Learning / testing time is
drastically reduced

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Object Oriented
Ideas from C++, Modula-3, SmallTalk
etc.
 Variable names = aliases or references
to objects; assignment results in
multiple aliases to the same object

>>> a = [1,2,3]; b = a; b[1]=0
>>> a
[1, 0, 3]
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Modular
Users save code in modules
 Standard Library consists of modules
 Modules may be grouped in packages
 Scripts are modules (.py files)
 Problem of namespace collisions is
handled with module prefixes
(like in Java)

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Extensible
Wrap existing C/C++ libraries to
make them importable as Python
modules (e.g. wxPython, win32all)
 Prototype in Python then rewrite
speed-critical parts in C/C++ and
import
 Create Python bindings for your
applications i.e. export an API

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Portable
Language accommodates many
platform difference (e.g. path name
separators
 .pyc byte codes run on any CPython
VM
 The language may be stripped down
to run on cell phones, PDAs
 Python VMs may be written in other
languages besides C

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High Level
Powerful built-in types:
list, tuple, dictionary (also set)
string, unicode
 Native long integers (i.e. multiprecision), complex numbers, fixed
precision decimals (new in 2.4)
 Built-in and user-defined Exceptions
with try… except… raise… finally
 Canned parsers, protocol servers etc.

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Free and Open Source
license is a built-in function.
Call it, i.e. enter license() for some
fascinating reading
 Some older versions are more
restricted
 Although current Pythons are GPL
compatible, you are not required to
release the source of derivative works,
only to provide a summary of changes
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Community
Guido van Rossum is BDFL
 Language evolves via PEPs
 Mail Lists: technical, tutorial, sigs
 Web sites: add ons, tutorials
 Documentation: python.org, HTML
 comp.lang.python (very active)
 Subcultures: Numeric, Zope/Plone,
wxPython etc.

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On Ramps
O’Reilly:
Learning Python
Programming in Python
Python in a Nutshell
 Apress:
Dive Into Python (on-line edition!)
 Guido’s Tutorial in Python docs
 Python Programming: An Intro to CS

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Development Environments
Free and Open Source
 Commercial
 Experimental
 Graphical
 A lot of developers use a text editor
of choice (vi, emacs, eclipse)
 Platform specific or more generic

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Design Philosophy
>>> import this
The Zen of Python, by Tim Peters
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!
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Evolution
Change to division operator:
/ vs. //
 Addition of new types:
set, Decimal
 Type / Class unification:
newstyle vs. classic classes
 List comprehensions, generators
 from __future__ import …

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Part 2: Nuts and Bolts
Invoking the interpreter
 Statements and Expressions
 Scoping
 Control Structures
 Functions and Generators
 Classes
 Modules
 Packages

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D:\Python24>python -m test2 < inputs.txt
['D:\\Python24\\test2.py']
Enter text:
"Hello world"
D:\Python24>type test2.py
import sys
print sys.argv
a = raw_input("Enter text: ")
print
print a
D:\Python24>type inputs.txt
"Hello world"
Scoping
A namespace is a mapping from names to
objects...
Examples of namespaces are:
• the set of built-in names (functions such as
abs(), and built-in exception names);
• the global names in a module;
• and the local names in a function invocation.
from the Python Tutorial by GVR
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Scoping
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Locals: lexically defined
Globals: per module
Built-ins: always available
>>> import math
>>> math.pi
3.1415926535897931
>>> from math import pi
>>> pi
3.1415926535897931
>>> from math import atan as arctan
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>>>
>>>
>>>
4
>>>
a = 2
def f():
f()
return a + 2
def f():
a = a + 2
return a
# try to bind local variable
>>> f()
Traceback (most recent call last):
File "<pyshell#8>", line 1, in -toplevelf()
File "<pyshell#7>", line 2, in f
a = a + 2
UnboundLocalError: local variable 'a'
referenced before assignment
>>> def f():
global a # explicit binding to a global
a = a + 2
return a
>>> a = 2
>>> f()
4
>>> f()
6
>>> a
6
>>> globals() # built-in function
{'a': 6, 'f': <function f at 0x00C96F30>,
'__builtins__': <module '__builtin__' (builtin)>, '__name__': '__main__', '__doc__': None}
Control Structures
The usual things but…
no case or switch – other ways to
get the same effect
 break and continue
 no “GO TO” or labels
 for, while, if/elif
 Exception handling
try: except: else: finally: raise:

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>>> pb = {'guido': 4127, 'kirby': 4127,
'jack': 4098}
>>> pb['marla'] = 4147 # add an entry
def invert(table):
index = {} # empty dictionary
for key in table.keys():
value = table[key]
if not index.has_key(value):
index[value] = [] # empty list
index[value].append(key)
return index
>>> inverted_pb = invert(pb)
>>> print inverted_pb
{4098: ['jack'], 4127: ['guido','kirby'],
4147: ['marla']}
>>> pb.get('jason',[]); pb.get('guido',[])
[]
4127
def invert(table):
"""Alternative invert function"""
index = {} # empty dictionary
for key,value in table.items():
index[value] = index.get(value,[])
index[value].append(key)
return index
>>> from tutor1 import invert
>>> help(invert)
Help on function invert in module tutor1:
invert(table)
Alternative invert function
>>> faces = [('A','H','C','F'),
('A','H','B','G'), ('B','E','C','H'),
('B','E','D','G'), ('D','G','A','F'),
('C','E','D','F')]
>>> getedges(faces)
[('A','F'),('A','G'),('A','H'),('B','E'),
('B','G'),('B','H'),('C','E'),('C','F'),
('C','H'),('D','E'),('D','F'),('D','G')]
def getedges(faces):
"""Extract edges from the faces list"""
edges = set()
for f in faces:
pairs = zip( f , f[1:] + (f[0],) )
for p in pairs:
edges.add(tuple(sorted(p)))
return sorted(list(edges))
Functions and Generators
Functions are top level, meaning
you may pass them as arguments
to other functions
 Generators save state between
function calls. Write as a function
but with keyword ‘yield’ instead
of ‘return’
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Classes

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Classes support multiple inheritance
New-style classes inherit from
object, are of type ‘type’
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Classic classes are of type Classtype
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Static and class methods supported
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Late binding means lots of flexibility

“Duck typing”
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Modules

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A module may double as a script
Sometimes the script does selftesting
A module is the logical unit of a
small solution space
Multiple modules organize in
packages
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Packages

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Packages = directories with
subdirectories
__init__ defines what’s imported or
importable
__all__ governs the behavior of
‘from xxx import *’
Packages may have subpackages
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Part 3: GUI Programming
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Cross-platform: wxPython, Tk,
GTK, Qt
Platform specific: MFC, .NET (?)
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Python as Glue Language
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win32all available for all versions
from python.org
ActiveState Python incorporates
Win32 features
Cross-platform GUI solutions
Future: Python .NET (IronPython) –
also somewhat cross-platform
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Windows Integration
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Using win32all extensions, Python
may operate as a COM client (e.g.
control MSFT Office applications)
Python may also operate as a COM
(or DCOM) server (e.g. callable from
VBA)
Other COM objects: DAO and ADO
for database access
MSF: Microsoft Foundation Classes
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