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Introduction to Python, COM and PythonCOM. Mark Hammond Skippi-Net, Melbourne, Australia [email protected] http://starship.python.net/crew/mhammond. Introduction to Python, COM and PythonCOM. The plan Section I - Intro to Python 30-45 mins Section II - Intro to COM 30-45 mins

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Introduction to python com and pythoncom l.jpg

Introduction to Python, COM and PythonCOM

Mark Hammond

Skippi-Net, Melbourne, Australia

[email protected]

http://starship.python.net/crew/mhammond


Introduction to python com and pythoncom2 l.jpg
Introduction to Python, COM and PythonCOM

The plan

  • Section I - Intro to Python

    • 30-45 mins

  • Section II - Intro to COM

    • 30-45 mins

  • Python and COM

    • The rest!


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Section I

Introduction to Python


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What Is Python?

  • Created in 1990 by Guido van Rossum

    • While at CWI, Amsterdam

    • Now hosted by centre for national research initiatives, Reston, VA, USA

  • Free, open source

    • And with an amazing community

  • Object oriented language

    • “Everything is an object”


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Why Python?

  • Designed to be easy to learn and master

    • Clean, clear syntax

    • Very few keywords

  • Highly portable

    • Runs almost anywhere - high end servers and workstations, down to windows CE

    • Compiled to machine independent byte-codes

  • Extensible

    • Designed to be extensible using C/C++, thereby allowing access to many external libraries


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Most obvious and notorious features

  • Clean syntax plus high-level data types

    • Leads to fast coding

  • Uses white-space to delimit blocks

    • Humans generally do, so why not the language?

    • Try it, you will end up liking it

  • Variables do not need declaration

    • Although not a type-less language


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Pythonwin

  • We are using Pythonwin

    • Only available on Windows

    • GUI toolkit using Tkinter available for most platforms

    • Standard console Python available on all platforms

  • Has interactive mode for quick testing of code

  • Includes debugger and Python editor


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Interactive Python

  • Starting Python.exe, or any of the GUI environments present an interactive mode

    • >>> prompt indicates start of a statement or expression

    • If incomplete, ... prompt indicates second and subsequent lines

    • All expression results printed back to interactive console


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Variables and Types (1 of 3)

  • Variables need no declaration

  • >>> a=1>>>

  • As a variable assignment is a statement, there is no printed result

  • >>> a1

  • Variable name alone is an expression, so the result is printed


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Variables and Types (2 of 3)

  • Variables must be created before they can be used

  • >>> bTraceback (innermost last): File "<interactive input>", line 1, in ?NameError: b>>>

  • Python uses exceptions - more detail later


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Variables and Types (3 of 3)

  • Objects always have a type

  • >>> a = 1>>> type(a)<type 'int'> >>> a = "Hello">>> type(a)<type 'string'>>>> type(1.0)<type 'float'>


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Assignment versus Equality Testing

  • Assignment performed with single =

  • Equality testing done with double = (==)

    • Sensible type promotions are defined

    • Identity tested with is operator.

  • >>> 1==11>>> 1.0==11>>> "1"==10


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Simple Data Types

  • Strings

    • May hold any data, including embedded NULLs

    • Declared using either single, double, or triple quotes

    • >>> s = "Hi there">>> s'Hi there'>>> s = "Embedded 'quote'">>> s"Embedded 'quote'"


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Simple Data Types

  • Triple quotes useful for multi-line strings

  • >>> s = """ a long... string with "quotes" or anything else""">>> s' a long\012string with "quotes" or anything else' >>> len(s)45


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Simple Data Types

  • Integer objects implemented using C longs

    • Like C, integer division returns the floor

    • >>> 5/22

  • Float types implemented using C doubles

  • Long Integers have unlimited size

    • Limited only by available memory

    • >>> long = 1L << 64>>> long ** 52135987035920910082395021706169552114602704522356652769947041607822219725780640550022962086936576L


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High Level Data Types

  • Lists hold a sequence of items

    • May hold any object

    • Declared using square brackets

  • >>> l = []# An empty list>>> l.append(1)>>> l.append("Hi there")>>> len(l)2


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High Level Data Types

  • >>> l[1, 'Hi there']>>>>>> l = ["Hi there", 1, 2]>>> l['Hi there', 1, 2]>>> l.sort()>>> l[1, 2, 'Hi there']


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High Level Data Types

  • Tuples are similar to lists

    • Sequence of items

    • Key difference is they are immutable

    • Often used in place of simple structures

  • Automatic unpacking

  • >>> point = 2,3>>> x, y = point>>> x2


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High Level Data Types

  • Tuples are particularly useful to return multiple values from a function

  • >>> x, y = GetPoint()

  • As Python has no concept of byref parameters, this technique is used widely


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High Level Data Types

  • Dictionaries hold key-value pairs

    • Often called maps or hashes. Implemented using hash-tables

    • Keys may be any immutable object, values may be any object

    • Declared using braces

  • >>> d={}>>> d[0] = "Hi there">>> d["foo"] = 1


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High Level Data Types

  • Dictionaries (cont.)

  • >>> len(d)2>>> d[0]'Hi there'>>> d = {0 : "Hi there", 1 : "Hello"}>>> len(d)2


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Blocks

  • Blocks are delimited by indentation

    • Colon used to start a block

    • Tabs or spaces may be used

    • Maxing tabs and spaces works, but is discouraged

  • >>> if 1:... print "True"... True>>>


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Blocks

  • Many people hate this when they first see it

    • Almost all Python programmers come to love it

  • Humans use indentation when reading code to determine block structure

    • Ever been bitten by the C code?:

  • if (1) printf("True"); CallSomething();


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Looping

  • The for statement loops over sequences

  • >>> for ch in "Hello":... print ch... Hello>>>


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Looping

  • Built-in function range() used to build sequences of integers

  • >>> for i in range(3):... print i... 012>>>


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Looping

  • while statement for more traditional loops

  • >>> i = 0>>> while i < 3:... print i... i = i + 1... 012>>>


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Functions

  • Functions are defined with the def statement:

  • >>> def foo(bar):... return bar>>>

  • This defines a trivial function named foo that takes a single parameter bar


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Functions

  • A function definition simply places a function object in the namespace

  • >>> foo<function foo at fac680>>>>

  • And the function object can obviously be called:

  • >>> foo(3)3>>>


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Classes

  • Classes are defined using the class statement

  • >>> class Foo:... def __init__(self):... self.member = 1... def GetMember(self):... return self.member... >>>


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Classes

  • A few things are worth pointing out in the previous example:

    • The constructor has a special name __init__, while a destructor (not shown) uses __del__

    • The self parameter is the instance (ie, the this in C++). In Python, the self parameter is explicit (c.f. C++, where it is implicit)

    • The name self is not required - simply a convention


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Classes

  • Like functions, a class statement simply adds a class object to the namespace

  • >>> Foo<class __main__.Foo at 1000960>>>>

  • Classes are instantiated using call syntax

  • >>> f=Foo()>>> f.GetMember()1


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Modules

  • Most of Python’s power comes from modules

  • Modules can be implemented either in Python, or in C/C++

  • import statement makes a module available

  • >>> import string>>> string.join( ["Hi", "there"] )'Hi there'>>>


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Exceptions

  • Python uses exceptions for errors

    • try / except block can handle exceptions

  • >>> try:... 1/0... except ZeroDivisionError:... print "Eeek"... Eeek>>>


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Exceptions

  • try / finally block can guarantee execute of code even in the face of exceptions

  • >>> try:... 1/0... finally:... print "Doing this anyway"... Doing this anywayTraceback (innermost last): File "<interactive input>", line 2, in ?ZeroDivisionError: integer division or modulo>>>


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Threads

  • Number of ways to implement threads

  • Highest level interface modelled after Java

  • >>> class DemoThread(threading.Thread):... def run(self):... for i in range(3):... time.sleep(3)... print i... >>> t = DemoThread()>>> t.start()>>> t.join()01 <etc>


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Standard Library

  • Python comes standard with a set of modules, known as the “standard library”

  • Incredibly rich and diverse functionality available from the standard library

    • All common internet protocols, sockets, CGI, OS services, GUI services (via Tcl/Tk), database, Berkeley style databases, calendar, Python parser, file globbing/searching, debugger, profiler, threading and synchronisation, persistency, etc


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External library

  • Many modules are available externally covering almost every piece of functionality you could ever desire

    • Imaging, numerical analysis, OS specific functionality, SQL databases, Fortran interfaces, XML, Corba, COM, Win32 API, etc

  • Way too many to give the list any justice


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Python Programs

  • Python programs and modules are written as text files with traditionally a .py extension

  • Each Python module has its own discrete namespace

  • Python modules and programs are differentiated only by the way they are called

    • .py files executed directly are programs (often referred to as scripts)

    • .py files referenced via the import statement are modules


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Python Programs

  • Thus, the same .py file can be a program/script, or a module

  • This feature is often used to provide regression tests for modules

    • When module is executed as a program, the regression test is executed

    • When module is imported, test functionality is not executed


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Python “Protocols”

  • Objects can support a number of different “protocols”

  • This allows your objects to be treated as:

    • a sequence - ie, indexed or iterated over

    • A mapping - obtain/assign keys or values

    • A number - perform arithmetic

    • A container - perform dynamic attribute fetching and setting

    • Callable - allow your object to be “called”


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Python “Protocols”

  • Sequence and container example

  • >>> class Protocols:... def __getitem__(self, index):... return index ** 2... def __getattr__(self, attr):... return "A big " + attr... >>> p=Protocols()>>> p[3]9>>> p.Foo'A big Foo’>>>


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More Information on Python

  • Can’t do Python justice in this short time frame

    • But hopefully have given you a taste of the language

  • Comes with extensive documentation, including an excellent tutorial and library reference

    • Also a number of Python books available

  • Visit www.python.org for more details


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Section II

Introduction to COM


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What is COM?

  • Acronym for Component Object Model, a technology defined and implemented by Microsoft

  • Allows “objects” to be shared among many applications, without applications knowing the implementation details of the objects

  • A broad and complex technology

  • We can only provide a brief overview here


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What was COM

  • COM can trace its lineage back to DDE

  • DDE was expanded to Object Linking and Embedding (OLE)

  • VBX (Visual Basic Extensions) enhanced OLE technology for visual components

  • COM was finally derived as a general purpose mechanism

    • Initially known as OLE2


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COM Interfaces

  • COM relies heavily on interfaces

  • An interface defines functionality, but not implementation

    • Each object (or more correctly, each class) defines implementation of the interface

    • Each implementation must conform to the interface

  • COM defines many interfaces

    • But often does not provide implementation of these interfaces


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COM Interfaces

  • Interfaces do not support properties

    • We will see how COM properties are typically defined later

  • Interfaces are defined using a vtable scheme similar to how C++ defines virtual methods

  • All interfaces have a unique ID (an IID)

    • Uses a Universally Unique Identifer (UUID)

    • UUIDs used for many COM IDs, including IIDs


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Classes

  • COM defines the concept of a class, used to create objects

    • Conceptually identical to a C++ or Python class

    • To create an object, COM locates the class factory, and asks it to create an instance

  • Classes have two identifiers

    • Class ID (CLSID) is a UUID, so looks similar to an IID

    • ProgID is a friendly string, and therefore not guaranteed unique


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IUnknown interface

  • Base of all COM interfaces

    • By definition, all interfaces also support the IUnknown interface

  • Contains only three methods

    • AddRef() and Release() for managing COM lifetimes

      • COM lifetimes are based on reference counts

    • QueryInterface() for obtaining a new interface from the object


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Creating objects, and obtaining interfaces

  • To create an object, the programmer specifies either the ProgID, or the CLSID

  • This process always returns the requested interface

    • or fails!

  • New interfaces are obtained by using the IUnknown::QueryInterface() method

    • As each interface derives from IUnknown, each interface must support QI


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Other standard interfaces

  • COM defines many interfaces, for example:

  • IStream

    • Defines file like operations

  • IStorage

    • Defines file system like semantics

  • IPropertyPage

    • Defines how a control exposes a property page

  • etc - many many interfaces are defined

    • But not many have implementations


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Custom interfaces

  • COM allows you to define your own interfaces

  • Interfaces are defined using an Interface Definition Language (IDL)

  • Tools available to assign unique IIDs for the interface

  • Any object can then implement or consume these interfaces


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IDispatch - Automation objects

  • IDispatch interface is used to expose dynamic object models

  • Designed explicitly for scripting languages, or for those languages that can not use normal COM interfaces

    • eg, where the interface is not known at compile time, or there is no compile time at all

  • IDispatch is used extensively

    • Microsoft Office, Netscape, Outlook, VB, etc - almost anything designed to be scripted


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IDispatch - Automation objects

  • Methods and properties of the object model can be determined at runtime

    • Concept of Type Libraries, where the object model can be exposed at compile time

  • Methods and properties are used indirectly

    • GetIDsOfNames() method is used to get an ID for a method or property

    • Invoke() is used to make the call


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IDispatch - Automation objects

  • Languages usually hide these implementation details from the programmer

  • Example: object.SomeCall()

    • Behind the scenes, your language will:id = GetIDsOfNames("SomeCall")Invoke(id, DISPATCH_METHOD)

  • Example: object.SomeProp

    • id = GetIDsOfNames("SomeProp")Invoke(id, DISPATCH_PROP_GET)


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VARIANTs

  • The IDispatch interface uses VARIANTs as its primary data type

  • Simply a C union that supports the common data types

    • and many helper functions for conversion etc

  • Allows the single Invoke() call to accept almost any data type

  • Many languages hide these details, performing automatic conversion as necessary


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Implementation models

  • Objects can be implemented in a number of ways

    • InProc objects are implemented as DLLs, and loaded into the calling process

      • Best performance, as no marshalling is required

    • LocalServer/RemoteServer objects are implemented as stand-alone executables

      • Safer due to process isolation, but slower due to remoting

  • Can be both, and caller can decide, or let COM choose the best


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Distributed COM

  • DCOM allows objects to be remote from their caller

  • DCOM handles all marshalling across machines and necessary security

  • Configuration tools allow an administrator to configure objects so that neither the object nor the caller need any changes

    • Although code changes can be used to explicitly control the source of objects


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The Windows Registry

  • Information on objects stored in the Windows registry

    • ProgID to CLSID mapping

    • Name of DLL for InProc objects

    • Name of EXE for LocalServer objects

    • Other misc details such as threading models

  • Lots of other information also maintained in registry

    • Remoting proxies, object security, etc.


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Conclusion for Section II

  • COM is a complex and broad beast

  • Underlying it all is a fairly simple Interface model

    • Although all the bits around the edges combine to make it very complex

  • Hopefully we have given enough framework to put the final section into some context


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Section III

Python and COM


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PythonCOM architecture

  • Underpinning everything is an extension module written in C++ that provides the core COM integration

    • Support for native COM interfaces exist in this module

    • Python reference counting is married with COM reference counting

  • Number of Python implemented modules that provide helpers for this core module


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Interfaces supported by PythonCOM

  • Over 40 standard interfaces supported by the framework

  • Extension architecture where additional modules can add support for their own interfaces

    • Tools supplied to automate this process

    • Number of extension modules supplied, bringing total interfaces to over 100


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Using Automation from Python

  • Automation uses IDispatch to determine object model at runtime

  • Python function win32com.client.Dispatch() provides this run-time facility

  • Allows a native “look and feel” to these objects


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Using Automation - Example

  • We will use Excel for this demonstration

  • Excel ProgId is Excel.Application

  • >>> from win32com.client import Dispatch>>> xl=Dispatch("Excel.Application")>>> xl<COMObject Excel.Application>>>>


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Using Automation - Example

  • Now that we have an Excel object, we can call methods and set properties

  • But we can’t see Excel running?

    • It has a visible property that may explain things

  • >>> xl.Visible0

  • Excel is not visible, let’s make it visible>>> xl.Visible = 1>>>


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Automation - Late vs. Early Bound

  • In the example we just saw, we have been using late bound COM

    • Python has no idea what properties or methods are available

    • As we attempt a method or property access, Python dynamically asks the object

    • Slight performance penalty, as we must resolve the name to an ID (GetIDsOfNames()) before calling Invoke()


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Automation - Late vs. Early Bound

  • If an object provides type information via a Type Library, Python can use early bound COM

  • Implemented by generating a Python source file with all method and property definitions

    • Slight performance increase as all names have been resolved to IDs at generation time, rather than run-time


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Automation - Late vs. Early Bound

  • Key differences between the 2 techniques:

    • Late bound COM often does not know the specific types of the parameters

      • Type of the Python object determines the VARIANT type created

      • Does not know about ByRef parameters, so no parameters are presented as ByRef

    • Early bound COM knows the types of the parameters

      • All Python types are coerced to the correct type

      • ByRef parameters work (returned as tuples)


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Playing with Excel

  • >>> xl.Workbooks.Add()<COMObject <unknown>>>>> xl.Range("A1:C1").Value = "Hi", "From", "Python">>> xl.Range("A1:C1").Value((L'Hi', L'From', L'Python'),)>>> xl.Range("A1:C1").PrintOut()>>>


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How did we know the methods?

  • Indeed, how did we know to use “Excel.Application”?

  • No easy answer - each application/object defines their own object model and ProgID

  • Documentation is the best answer

    • Note that MSOffice does not install the COM documentation by default - must explicitly select it during setup

  • COM browsers can also help


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Native Interfaces from Python

  • Examples so far have been using using IDispatch

    • win32com.client.Dispatch() function hides the gory details from us

  • Now an example of using interfaces natively

    • Need a simple example - Windows Shortcuts fits the bill

  • Develop some code that shows information about a Windows shortcut


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Native Interfaces from Python

  • 4 main steps in this process

    • Import the necessary Python modules

    • Obtain an object that implements the IShellLink interface

    • Obtain an IPersistFile interface from the object, and load the shortcut

    • Use the IShellLink interface to get information about the shortcut


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Native Interfaces from PythonStep 1: Import the necessary Python modules

  • We need the pythoncom module for core COM support

  • We need the win32com.shell.shell module

    • This is a PythonCOM extension that exposes additional interfaces

  • >>> import pythoncom>>> from win32com.shell import shell


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    Native Interfaces from PythonStep 2: Obtain an object that implements the IShellLink interface

    • Use the COM function CoCreateInstance()

    • Use the published CLSID for the shell

    • The shell requires that the object request be for an InProc object.

    • Request the IShellLink interface


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    Native Interfaces from PythonStep 2: Obtain an object that implements the IShellLink interface

    • >>> sh = pythoncom.CoCreateInstance(shell.CLSID_ShellLink, ... None,... pythoncom.CLSCTX_INPROC_SERVER,... shell.IID_IShellLink)>>> sh<PyIShellLink at 0x1630b04 with obj at 0x14c9d8>>>>


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    Native Interfaces from PythonStep 3: Obtain an IPersist interface from the object, and load the shortcut

    • Use QueryInterface to obtain the new interface from the object

    • >>> pe= sh.QueryInterface(pythoncom.IID_IPersistFile)>>> pe.Load("c:/winnt/profiles/skip/desktop/IDLE.lnk")


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    Native Interfaces from PythonStep 4: Use the IShellLink interface to get information about the shortcut

    • >>> sh.GetWorkingDirectory()'L:\\src\\python-cvs\\tools\\idle'>>> sh.GetArguments()'l:\\src\\python-cvs\\tools\\idle\\idle.pyw'>>>


    Implementing com using python l.jpg
    Implementing COM using Python.

    • Final part of our tutorial is implementing COM objects using Python

    • 3 main steps we must perform

      • Implement a Python class that exposes the functionality

      • Annotate the class with special attributes required by the COM framework.

      • Register our COM object


    Implementing com using python step 1 implement a python class that exposes the functionality l.jpg
    Implementing COM using Python.Step 1: Implement a Python class that exposes the functionality

    • We will build on our last example, by providing a COM object that gets information about a Windows shortcut

    • Useful to use from VB, as it does not have direct access to these interfaces.

    • We will design a class that can be initialised to a shortcut, and provides methods for obtaining the info.


    Implementing com using python step 1 implement a python class that exposes the functionality81 l.jpg
    Implementing COM using PythonStep 1: Implement a Python class that exposes the functionality

    • Code is getting to big for the slides

    • Code is basically identical to that presented before, except:

      • The code has moved into a class.

      • We store the IShellInfo interface as an instance attribute


    Implementing com using python step 1 implement a python class that exposes the functionality82 l.jpg
    Implementing COM using PythonStep 1: Implement a Python class that exposes the functionality

    • Provide an Init method that takes the name of the shortcut.

    • Also provide two trivial methods that simply delegate to the IShellInfo interface

      • Note Python would allow us to automate the delegation, but that is beyond the scope of this!


    Implementing com using python step 2 annotate the class with special attributes l.jpg
    Implementing COM using PythonStep 2: Annotate the class with special attributes

    • PythonCOM requires a number of special attributes

      • The CLSID of the object (a UUID)

        • Generate using print pythoncom.CreateGuid()

      • The ProgID of the object (a friendly string)

        • Make one up!

      • The list of public methods

        • All methods not listed as public are not exposed via COM


    Implementing com using python step 2 annotate the class with special attributes84 l.jpg
    Implementing COM using PythonStep 2: Annotate the class with special attributes

    • class PyShellLink: _public_methods_=['Init', 'GetWorkingDirectory', 'GetArguments']_reg_clsid_="{58DE4632-9323-11D3-85F9-00C04FEFD0A7}" _reg_progid_="Python.ShellDemo" ...


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    Implementing COM using PythonStep 3: Register our COM object

    • General technique is that the object is registered when the module implementing the COM object is run as a script.

      • Recall previous discussion on modules versus scripts

    • Code is trivial

      • Call the UseCommandLine() method, passing the class objects we wish to register


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    Implementing COM using PythonStep 3: Register our COM object

    • Code is simple

      • note we are passing the class object, not a class instance.

    • if __name__=='__main__': UseCommandLine(PyShellLink)

    • Running this script yields:

    • Registered: Python.ShellDemo


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    Testing our COM object

    • Our COM object can be used by any automation capable language

      • VB, Delphi, Perl - even VC at a pinch!

    • We will test with a simple VBScript program

      • VBScript is free. Could use full blown VB, or VBA. Syntax is identical in all cases


    Testing our com object88 l.jpg
    Testing our COM object

    • set shdemo = CreateObject("Python.ShellDemo")shdemo.Init("c:\winnt\profiles\skip\desktop\IDLE.lnk")WScript.Echo "Working dir is " + shdemo.GetWorkingDirectory()

    • Yields

    • Working dir is L:\src\python-cvs\tools\idle


    Summary l.jpg
    Summary

    • Python can make COM simple to work with

      • No reference count management

      • Many interfaces supported.

      • Natural use for IDispatch (automation) objects.

    • Simple to use COM objects, or implement COM objects



    More information l.jpg
    More Information

    • Python itself

      • http://www.python.org

      • news:comp.lang.python

    • Python on Windows

      • http://www.python.org/windows

    • Mark Hammond’s Python extensions

      • http://starship.python.net/crew/mhammond

      • http://www.python.org/windows


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