
Python Advocacy HOWTO
*********************

Author:
   A.M. Kuchling

Release:
   0.03


Abstract
^^^^^^^^

It's usually difficult to get your management to accept open source
software, and Python is no exception to this rule.  This document
discusses reasons to use Python, strategies for winning acceptance,
facts and arguments you can use, and cases where you *shouldn't* try
to use Python.


Reasons to Use Python
=====================

There are several reasons to incorporate a scripting language into
your development process, and this section will discuss them, and why
Python has some properties that make it a particularly good choice.


Programmability
---------------

Programs are often organized in a modular fashion.  Lower-level
operations are grouped together, and called by higher-level functions,
which may in turn be used as basic operations by still further upper
levels.

For example, the lowest level might define a very low-level set of
functions for accessing a hash table.  The next level might use hash
tables to store the headers of a mail message, mapping a header name
like ``Date`` to a value such as ``Tue, 13 May 1997 20:00:54 -0400``.
A yet higher level may operate on message objects, without knowing or
caring that message headers are stored in a hash table, and so forth.

Often, the lowest levels do very simple things; they implement a data
structure such as a binary tree or hash table, or they perform some
simple computation, such as converting a date string to a number.  The
higher levels then contain logic connecting these primitive
operations.  Using the approach, the primitives can be seen as basic
building blocks which are then glued together to produce the complete
product.

Why is this design approach relevant to Python?  Because Python is
well suited to functioning as such a glue language.  A common approach
is to write a Python module that implements the lower level
operations; for the sake of speed, the implementation might be in C,
Java, or even Fortran.  Once the primitives are available to Python
programs, the logic underlying higher level operations is written in
the form of Python code.  The high-level logic is then more
understandable, and easier to modify.

John Ousterhout wrote a paper that explains this idea at greater
length, entitled "Scripting: Higher Level Programming for the 21st
Century".  I recommend that you read this paper; see the references
for the URL.  Ousterhout is the inventor of the Tcl language, and
therefore argues that Tcl should be used for this purpose; he only
briefly refers to other languages such as Python, Perl, and
Lisp/Scheme, but in reality, Ousterhout's argument applies to
scripting languages in general, since you could equally write
extensions for any of the languages mentioned above.


Prototyping
-----------

In *The Mythical Man-Month*, Fredrick Brooks suggests the following
rule when planning software projects: "Plan to throw one away; you
will anyway."  Brooks is saying that the first attempt at a software
design often turns out to be wrong; unless the problem is very simple
or you're an extremely good designer, you'll find that new
requirements and features become apparent once development has
actually started.  If these new requirements can't be cleanly
incorporated into the program's structure, you're presented with two
unpleasant choices: hammer the new features into the program somehow,
or scrap everything and write a new version of the program, taking the
new features into account from the beginning.

Python provides you with a good environment for quickly developing an
initial prototype.  That lets you get the overall program structure
and logic right, and you can fine-tune small details in the fast
development cycle that Python provides.  Once you're satisfied with
the GUI interface or program output, you can translate the Python code
into C++, Fortran, Java, or some other compiled language.

Prototyping means you have to be careful not to use too many Python
features that are hard to implement in your other language.  Using
``eval()``, or regular expressions, or the ``pickle`` module, means
that you're going to need C or Java libraries for formula evaluation,
regular expressions, and serialization, for example.  But it's not
hard to avoid such tricky code, and in the end the translation usually
isn't very difficult.  The resulting code can be rapidly debugged,
because any serious logical errors will have been removed from the
prototype, leaving only more minor slip-ups in the translation to
track down.

This strategy builds on the earlier discussion of programmability.
Using Python as glue to connect lower-level components has obvious
relevance for constructing prototype systems.  In this way Python can
help you with development, even if end users never come in contact
with Python code at all.  If the performance of the Python version is
adequate and corporate politics allow it, you may not need to do a
translation into C or Java, but it can still be faster to develop a
prototype and then translate it, instead of attempting to produce the
final version immediately.

One example of this development strategy is Microsoft Merchant Server.
Version 1.0 was written in pure Python, by a company that subsequently
was purchased by Microsoft.  Version 2.0 began to translate the code
into C++, shipping with some C++code and some Python code.  Version
3.0 didn't contain any Python at all; all the code had been translated
into C++.  Even though the product doesn't contain a Python
interpreter, the Python language has still served a useful purpose by
speeding up development.

This is a very common use for Python.  Past conference papers have
also described this approach for developing high-level numerical
algorithms; see David M. Beazley and Peter S. Lomdahl's paper "Feeding
a Large-scale Physics Application to Python" in the references for a
good example.  If an algorithm's basic operations are things like
"Take the inverse of this 4000x4000 matrix", and are implemented in
some lower-level language, then Python has almost no additional
performance cost; the extra time required for Python to evaluate an
expression like ``m.invert()`` is dwarfed by the cost of the actual
computation. It's particularly good for applications where seemingly
endless tweaking is required to get things right. GUI interfaces and
Web sites are prime examples.

The Python code is also shorter and faster to write (once you're
familiar with Python), so it's easier to throw it away if you decide
your approach was wrong; if you'd spent two weeks working on it
instead of just two hours, you might waste time trying to patch up
what you've got out of a natural reluctance to admit that those two
weeks were wasted.  Truthfully, those two weeks haven't been wasted,
since you've learnt something about the problem and the technology
you're using to solve it, but it's human nature to view this as a
failure of some sort.


Simplicity and Ease of Understanding
------------------------------------

Python is definitely *not* a toy language that's only usable for small
tasks. The language features are general and powerful enough to enable
it to be used for many different purposes.  It's useful at the small
end, for 10- or 20-line scripts, but it also scales up to larger
systems that contain thousands of lines of code.

However, this expressiveness doesn't come at the cost of an obscure or
tricky syntax.  While Python has some dark corners that can lead to
obscure code, there are relatively few such corners, and proper design
can isolate their use to only a few classes or modules.  It's
certainly possible to write confusing code by using too many features
with too little concern for clarity, but most Python code can look a
lot like a slightly-formalized version of human-understandable
pseudocode.

In *The New Hacker's Dictionary*, Eric S. Raymond gives the following
definition for "compact":

   Compact *adj.*  Of a design, describes the valuable property that
   it can all be apprehended at once in one's head. This generally
   means the thing created from the design can be used with greater
   facility and fewer errors than an equivalent tool that is not
   compact. Compactness does not imply triviality or lack of power;
   for example, C is compact and FORTRAN is not, but C is more
   powerful than FORTRAN. Designs become non-compact through accreting
   features and cruft that don't merge cleanly into the overall design
   scheme (thus, some fans of Classic C maintain that ANSI C is no
   longer compact).

   (From http://www.catb.org/~esr/jargon/html/C/compact.html)

In this sense of the word, Python is quite compact, because the
language has just a few ideas, which are used in lots of places.  Take
namespaces, for example.  Import a module with ``import math``, and
you create a new namespace called ``math``.  Classes are also
namespaces that share many of the properties of modules, and have a
few of their own; for example, you can create instances of a class.
Instances?  They're yet another namespace.  Namespaces are currently
implemented as Python dictionaries, so they have the same methods as
the standard dictionary data type: .keys() returns all the keys, and
so forth.

This simplicity arises from Python's development history.  The
language syntax derives from different sources; ABC, a relatively
obscure teaching language, is one primary influence, and Modula-3 is
another.  (For more information about ABC and Modula-3, consult their
respective Web sites at http://www.cwi.nl/~steven/abc/ and
http://www.m3.org.)  Other features have come from C, Icon, Algol-68,
and even Perl.  Python hasn't really innovated very much, but instead
has tried to keep the language small and easy to learn, building on
ideas that have been tried in other languages and found useful.

Simplicity is a virtue that should not be underestimated.  It lets you
learn the language more quickly, and then rapidly write code -- code
that often works the first time you run it.


Java Integration
----------------

If you're working with Java, Jython (http://www.jython.org/) is
definitely worth your attention.  Jython is a re-implementation of
Python in Java that compiles Python code into Java bytecodes.  The
resulting environment has very tight, almost seamless, integration
with Java.  It's trivial to access Java classes from Python, and you
can write Python classes that subclass Java classes. Jython can be
used for prototyping Java applications in much the same way CPython is
used, and it can also be used for test suites for Java code, or
embedded in a Java application to add scripting capabilities.


Arguments and Rebuttals
=======================

Let's say that you've decided upon Python as the best choice for your
application.  How can you convince your management, or your fellow
developers, to use Python?  This section lists some common arguments
against using Python, and provides some possible rebuttals.

**Python is freely available software that doesn't cost anything. How
good can it be?**

Very good, indeed.  These days Linux and Apache, two other pieces of
open source software, are becoming more respected as alternatives to
commercial software, but Python hasn't had all the publicity.

Python has been around for several years, with many users and
developers. Accordingly, the interpreter has been used by many people,
and has gotten most of the bugs shaken out of it.  While bugs are
still discovered at intervals, they're usually either quite obscure
(they'd have to be, for no one to have run into them before) or they
involve interfaces to external libraries.  The internals of the
language itself are quite stable.

Having the source code should be viewed as making the software
available for peer review; people can examine the code, suggest (and
implement) improvements, and track down bugs.  To find out more about
the idea of open source code, along with arguments and case studies
supporting it, go to http://www.opensource.org.

**Who's going to support it?**

Python has a sizable community of developers, and the number is still
growing. The Internet community surrounding the language is an active
one, and is worth being considered another one of Python's advantages.
Most questions posted to the comp.lang.python newsgroup are quickly
answered by someone.

Should you need to dig into the source code, you'll find it's clear
and well-organized, so it's not very difficult to write extensions and
track down bugs yourself.  If you'd prefer to pay for support, there
are companies and individuals who offer commercial support for Python.

**Who uses Python for serious work?**

Lots of people; one interesting thing about Python is the surprising
diversity of applications that it's been used for.  People are using
Python to:

* Run Web sites

* Write GUI interfaces

* Control number-crunching code on supercomputers

* Make a commercial application scriptable by embedding the Python
  interpreter inside it

* Process large XML data sets

* Build test suites for C or Java code

Whatever your application domain is, there's probably someone who's
used Python for something similar.  Yet, despite being useable for
such high-end applications, Python's still simple enough to use for
little jobs.

See http://wiki.python.org/moin/OrganizationsUsingPython for a list of
some of the  organizations that use Python.

**What are the restrictions on Python's use?**

They're practically nonexistent.  Consult the ``Misc/COPYRIGHT`` file
in the source distribution, or the section *History and License* for
the full language, but it boils down to three conditions:

* You have to leave the copyright notice on the software; if you don't
  include the source code in a product, you have to put the copyright
  notice in the supporting documentation.

* Don't claim that the institutions that have developed Python endorse
  your product in any way.

* If something goes wrong, you can't sue for damages.  Practically all
  software licenses contain this condition.

Notice that you don't have to provide source code for anything that
contains Python or is built with it.  Also, the Python interpreter and
accompanying documentation can be modified and redistributed in any
way you like, and you don't have to pay anyone any licensing fees at
all.

**Why should we use an obscure language like Python instead of well-
known language X?**

I hope this HOWTO, and the documents listed in the final section, will
help convince you that Python isn't obscure, and has a healthily
growing user base. One word of advice: always present Python's
positive advantages, instead of concentrating on language X's
failings.  People want to know why a solution is good, rather than why
all the other solutions are bad.  So instead of attacking a competing
solution on various grounds, simply show how Python's virtues can
help.


Useful Resources
================

http://www.pythonology.com/success
   The Python Success Stories are a collection of stories from
   successful users of Python, with the emphasis on business and
   corporate users.

http://home.pacbell.net/ouster/scripting.html
   John Ousterhout's white paper on scripting is a good argument for
   the utility of scripting languages, though naturally enough, he
   emphasizes Tcl, the language he developed.  Most of the arguments
   would apply to any scripting language.

http://www.python.org/workshops/1997-10/proceedings/beazley.html
   The authors, David M. Beazley and Peter S. Lomdahl,  describe their
   use of Python at Los Alamos National Laboratory. It's another good
   example of how Python can help get real work done. This quotation
   from the paper has been echoed by many people:

      Originally developed as a large monolithic application for
      massively parallel processing systems, we have used Python to
      transform our application into a flexible, highly modular, and
      extremely powerful system for performing simulation, data
      analysis, and visualization. In addition, we describe how Python
      has solved a number of important problems related to the
      development, debugging, deployment, and maintenance of
      scientific software.

http://pythonjournal.cognizor.com/pyj1/Everitt-
Feit_interview98-V1.html
   This interview with Andy Feit, discussing Infoseek's use of Python,
   can be used to show that choosing Python didn't introduce any
   difficulties into a company's development process, and provided
   some substantial benefits.

http://www.python.org/workshops/1997-10/proceedings/stein.ps
   For the 6th Python conference, Greg Stein presented a paper that
   traced Python's adoption and usage at a startup called eShop, and
   later at Microsoft.

http://www.opensource.org
   Management may be doubtful of the reliability and usefulness of
   software that wasn't written commercially.  This site presents
   arguments that show how open source software can have considerable
   advantages over closed-source software.

http://www.faqs.org/docs/Linux-mini/Advocacy.html
   The Linux Advocacy mini-HOWTO was the inspiration for this
   document, and is also well worth reading for general suggestions on
   winning acceptance for a new technology, such as Linux or Python.
   In general, you won't make much progress by simply attacking
   existing systems and complaining about their inadequacies; this
   often ends up looking like unfocused whining.  It's much better to
   point out some of the many areas where Python is an improvement
   over other systems.
