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diff --git a/Doc/howto/advocacy.rst b/Doc/howto/advocacy.rst deleted file mode 100644 index 2969d266ad..0000000000 --- a/Doc/howto/advocacy.rst +++ /dev/null @@ -1,355 +0,0 @@ -************************* - Python Advocacy HOWTO -************************* - -:Author: A.M. Kuchling -:Release: 0.03 - - -.. topic:: 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 :mod:`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": - -.. epigraph:: - - 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 :ref:`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://www.fsbassociates.com/books/pythonchpt1.htm - The first chapter of \emph{Internet Programming with Python} also - examines some of the reasons for using Python. The book is well worth - buying, but the publishers have made the first chapter available on - the Web. - -http://www.tcl.tk/doc/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: - - .. epigraph:: - - 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/psa/Commercial.html - Robin Friedrich wrote this document on how to support Python's use in - commercial projects. - -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. - |