Slashdot Mirror
Python in a Nutshell
Written by my favorite author and Pythonista, Alex Martelli, this book manages to fill three roles in extremely pleasing fashion. First and foremost to me, it is a great read, straight through. Mr. Martelli's prose is always sparkling and always keeps the reader interested. No matter how many Python books you have read, you will learn some nuances from this book, and it is about the best review of the whole Pythonic subject matter that I can imagine. While there is absolutely no fluff whatsoever in these 636 pages, it still makes for rather easy reading because the explanations are so clearly thought out and explored as to lead one gently to understanding, without in any way being verbose. It is obvious that Alex Martelli took his time and put in sufficient thought, effort, and intellectual elbow-grease to make this work a classic for all time.
Secondly, this book is the ultimate Pythonic reference book, the best fit to this role I have yet seen. You will keep this book in the most cherished spot on your book shelf, or else right at your side on your computer desk, because you can almost instantly find any topic on which you need to brush up, in the midst of a programming project.
Third, Python in a Nutshell is the most up-to-date book on Python (as of April 2003) and includes the best and most complete expositions yet on the new features introduced in Python 2.2 and 2.3. These topics are not only covered in depth, they are integrated into the text in their proper positions and relationships to the language as a whole. They are explained better here than I have seen anywhere else, so much so as to make them not only understandable to me (a duffer), but indeed so that they appear seamlessly Pythonic, as if they had been a part of the language since version 1.0. Topics explored in depth include new style classes, static methods, class methods, nested scopes, iterators, generators, and new style division. List comprehensions are made not only comprehensible but indeed intuitive.
The book is surprisingly complete. It covers the core language as well as the most popular libraries and extension modules. It is difficult to choose any one portion of the book to highlight for extra praise, as all topics are treated so well. It is a complete book, the new definitive book about Python.
Everything about this book speaks of quality. In addition to the top notch writing and editing, O'Reilly really did the right thing and published this book printed on the highest quality paper, paper so thin that the 636 pages are encompassed in a book much thinner than one would expect for such a size, but strong enough to resist wear and tear. The text is most pleasing to the eye. Holding the book, and turning its pages, gives one a feeling of satisfaction.
Any job worth doing is worth doing well. Alex Martelli and O'Reilly have done justice to a topic dear to our hearts, the Python programming language. Perhaps, in years to come, the passage of time may make this book to be no longer the most up-to-date reference on the newest features added to Python. But time can not erase the quality craftsmanship and the shear joy of reading such a well thought out masterpiece of Pythonic literature.
You can purchase Python in a Nutshell from bn.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page. Ron Stephens would also like you to check out Python City, with "27+ reviews of books about Python. 67+ links to online tutorials about Python and related subjects Daily newsfeed of Pythonic web articles, new sourceforge projects, etc."
That's a pretty goddam big nutshell, if you ask me!
Congratulations! Now we are the Evil Empire
Gentoo Linux is an interesting new distribution with some great features. Unfortunately, it has attracted a large number of clueless wannabes who absolutely MUST advocate Gentoo at every opportunity. Let's look at the language of these zealots, and find out what it really means...
"Gentoo makes me so much more productive."
"Although I can't use the box at the moment because it's compiling something, as it will be for the next five days, it gives me more time to check out the latest USE flags and potentially unstable optimisation settings."
"Gentoo is more in the spirit of open source!"
"Apart from Hello World in Pascal at school, I've never written a single program in my life or contributed to an open source project, yet staring at endless streams of GCC output whizzing by somehow helps me contribute to international freedom."
"I use Gentoo because it's more like the BSDs."
"Last month I tried to install FreeBSD on a well-supported machine, but the text-based installer scared me off. I've never used a BSD, but the guys on Slashdot say that it's l33t though, so surely I must be for using Gentoo."
"Heh, my system is soooo much faster after installing Gentoo." .debs can be rebuilt with a handful of commands,
my box MUST be faster. It's nothing to do with the fact that I've disabled
all startup services and I'm running BlackBox instead of GNOME or KDE."
"I've spent hours recompiling Fetchmail, X-Chat, gEdit and thousands of other programs which spend 99% of their time waiting for user input. Even though only the kernel and glibc make a significant difference with optimisations, and RPMs and
"...my Gentoo Linux workstation..."
"...my overclocked AMD eMachines box from PC World, and apart from the third-grade made-to-break components and dodgy fan..."
"You Red Hat guys must get sick of dependency hell..." .rpms together on the command line, and that problems
hardly ever occur if one uses proper Red Hat packages instead of mixing
SuSE, Mandrake and Joe's Linux packages together (which the system wasn't
designed for)."
"I'm too stupid to understand that circular dependencies can be resolved by specifying BOTH
"All the other distros are soooo out of date."
"Constantly upgrading to the latest bleeding-edge untested software makes me more productive. Never mind the extensive testing and patching that Debian and Red Hat perform on their packages; I've just emerged the latest GNOME beta snapshot and compiled with -09 -fomit-instructions, and it only crashes once every few hours."
"Let's face it, Gentoo is the future."
"OK, so no serious business is going to even consider Gentoo in the near future, and even with proper support and QA in place, it'll still eat up far too much of a company's valuable time. But this guy I met on #animepr0n is now using it, so it must be growing!"
-
Could the author please respond in this thread and give some examples of the new content, rather than just "covers it all"?
You know, when I saw that title, I just knew that there was a joke in there involoving Monty Python, nuts and hell (nutshell, nuts hell).
If I had the time I'd come up with it, and I'm sure it would be the funniest joke in the world, much better than the German joke, "two peanuts were walking down the street and one was assorted".
Unfortunately, I have to go out for a silly walk, and then onto a mouse club, so I'll have to leave it to someone else to inject some much needed hilarity into these proceedings.
"Accept that some days you are the pigeon, and some days you are the statue." - David Brent, Wernham Hogg
Let me start off by saying that I don't usually read this site. I was pointed here by a python programmer who wanted more python people to join this dicussion. However I'm not exactly a "python person." I'm most comfortable in C, with a smattering of Java, Perl, Asm, Lisp and Python (in no particular order). That being clarified, I'd like to say a few words.
First of all, I don't want to offend anyone, but Perl really is an example of the most horrible way to design a language. I say "design" with tongue-in-cheek, because the language wasn't really designed so much as thrown together from pieces of odd scripting languages (many of which should have been put to rest long ago). The implementation itself is rather unfortunete; because of how it's built you can't really implement perl in terms of itself (well I suppose you could, but not with a slight measure of self-respect), the entire system needs to be scrutinized by security experts before any program written in Perl can be considered secure, and it is doubtful that Perl will ever be re-implemented ever again.
That being said, Perl is at least useful for many things ("practical," I believe it's called). People always tell me how they use it for system-administration tasks (for some reason I don't seem to engage in enough adminitration tasks to require perl's help, or if I do they're all suitibly mundane), and it does have an impressive ability to cope with string data (not something I'd base a language on, but at least it stopped people from using SNOBOL).
Now Python on the other hand is almost completely a different story. It's supremely orthagonal and elegant in its design, with support for functions as first-class types, an enforcement of clean coding standards through whitespace sensitivity (most Perl coders object vehemently to this because it infringes on their ability to write really ugly code), etc.
But the problem is that Python suffers from a lot of Perl's problems and adds a few of its own: you can't implement it in itself, it has no strong typing (even Perl's use strict is ridiculously better), an OO system with no support for data hiding, etc. etc. And that brings me to the biggest problem: Python doesn't really have a niche to fill. The CGI space has been seemingly co-opted completely by Perl (at least until people start using PHP), and it's too dog-slow to be used for real CS applications. As a beginner's language it's ideal, but that's not going to help it be taken seriously when it comes to real computing tasks.
If the python developers made some tweaks to the type system and added a real compiler, then I would advocate that most software engineering be moved there. As it stands it's an original language which is a lot of fun to program in, and still has lots of unmapped potential to it.
So where does that leave us, now that I've managed to piss EVERYBODY off? Well, I guess I conclude by saying that if you read this and got a sudden urge to throw a molotov cocktail through my window, then you're really taking one language too seriously. If you blind yourself so much that you can't see the faults in Perl or , then you're really no use to anyone in your community, in particular the users who depend on you to build solid, well-rounded applications. Don't be a Python zealot or a Perl zealot; be a programming zealot, learn as many languages as possible, and which one to use in a given situation. That's all I have to say.
I got 2 big nutshells for ya, and a python to go with em. If you're lucky, I'll even give you a Perl necklace.
what, PHP doesn't suffer from the same problems as perl? whitespace? data hiding? real objects?
people use these languages because the fluidity at which they can be written (albeit crappily). conversley, a good programmer will write good code regardless of the pro-active design constraints imposed by the language.
etc.
excellent troll btw!
The biggest problem with Python, IMHO, is the online documentation. It's the worst I've ever seen, so abstract that it's of no use to anyone except maybe as a reference for someone who wants to write real documentation.
I can only assume that like Python itself, the documentation is the result of an author who wanted to do things "the best" way, without being willing to look outside his own head to determine what that might be. For the language itself, the result was okay - if slightly annoying at times. For the documentation, it's unacceptable. New and different languages can be learned. But with indecipherable and oddly-organized documentation, that's very difficult to even start doing. I had several "false starts" with Python, abandoning it quickly because the documentation (and installation process) were so opaque. If not coerced by my employer into giving it another try, I never would have touched it again. The only reason I stuck with it this last time was because my employer had a stack of Python books for me to use.
In the "heavy scripting" domain, I've put a lot of time into Perl, Python, and PHP. PHP's online documentation is the exact opposite of Python's; entirely focused on the practical, with lots of examples and very little theory or background. Perl's is somewhere in the middle. Overall, as a learner I found Perl's documentation to be the best, and as an advanced developer I find PHP's to be supreme, bar none. Python's is a disgrace, useful to neither beginning nor advanced users.
It's great that people are writing good books about the language. But in this day and age, it shouldn't be necessary to buy a book just to make sense of an open-source tool.
"Patriotism is your conviction that this country is superior to all other countries because you were born in it." -- GBS
Don't be a Python zealot or a Perl zealot; be a programming zealot, learn as many languages as possible, and which one to use in a given situation.
You have a point there, but I'd put it in a slightly different way. I'd not tell people to learn as many languages as possible, but rather learn programming and its basics (knowing the architecture behind the scenes, the CPU, is really a lot of fun).
There isn't much point in knowing every programming language, but a much better deal to know the syntax used in those languages. Also, when learning programming it's important to have a certain sense of logic (especially for object-oriented and/or heavily nested functions) because you need to keep things apart.
Why do you want to learn the syntaxes?
Let's use me as an example (not a very good one as I don't know very many languages, but I cope)... I've started programming using simple QBasic (where one learnt horrible spaghetti programming since one was 8 yrs old at the time) and Pascal (where I learnt about functions and procedures, something very important for any programmer).
I've then moved on to C and asm (PIC16F84) where I've learnt about pointer arithmetics, references and the joys of loose pointers.
I have since then learnt C++ and asp (vbscript/visual basic/com)...
Later on when you need to use another language (in my case PHP) it's very easyto just utilize the knowledge you already have. For PHP it was just for me to learn how they handled arrays and strings. That's it. All I needed then was a list of functions (php.net is most excellent), because I already knew its syntax (being based on among others C). Macromedia Flash and Javascript (ECMAScript) were also very easy to use...
That said I know I have to test Python... I've never actually used it, but since they all say it's very nice I should really try it out... ^^
I hope this was a far too long comment for most people to put up with, but I don't really care.
In general, I've noticed Python makes writing programs very fast and very easy to modify later to add new features. It takes me a little longer to write equivilent programs in Perl, but the Perl programs probably run a little faster although they take a bit more effort to modify later. Finally, if I really need a program to run very fast, I can port it to C where it'll run extremely fast, but that will naturally take the longest to write and modify.
Having said all that, I use Python programs for those day-to-day administration duties where plenty of tweaks are required. Python works great for CGIs too, and should scale up to a reasonable load. But, if speed or extreme scalability are a requirement, porting a Python prototype over to C is often a good idea. Still, I have no shortage of tasks that require quick programming but don't require great speed - and Python fits those quite well.
But if I could compile it to native code, now that would be pretty sweet.
Ita erat quando hic adveni.
But the problem is that Python suffers from a lot of Perl's problems and adds a few of its own: you can't implement it in itself, it has no strong typing (even Perl's use strict is ridiculously better), an OO system with no support for data hiding, etc. etc
Actually, one of these is being worked on: There's an active project to write Python in itself. I believe they're taking the same tack as Squeak.
John Roth
I couldn't agree more w/ both this post and the one before it. I have yet to find a use for Python that isn't already covered by a language I know (PHP for web apps, Java for more complicated server or GUI stuff), and the few times I have tried to learn more about Python, I run up against the online documentation, which does more to talk about how cool Python is than actually explain how to use it (just like you said - the opposite of PHP's online documentation, which is hands-down superb). This isn't meant to be a troll post, just my experience. Glad to hear I'm not the only developer who has run into those 2 issues w/ using Python (the Why and What, so to speak).
I didn't have this experience at all, I found a lot of their documentation very helpful and certainly more helpful than the free documentation on Perl that you can find.
I didn't have any problem with false starts, I went to the python website one day to check it out and the next day I went to one of the online books about python they linked to and I learned a shitload and within a couple hours I began to appreciate and love Python.
Objects are already passed by reference. You can't change strings because they are an immutable type. If you need references, you can use the weakref module, or create your own wrapper class (delegating accesses to the underlying object).
you can define named functions in-line, that work as closures (i. e. using variables from the declaration scope). I've been using Python 2.3, so the change from 2.2->2.3 may have been the change that made this usable. In case I wasn't clear:do/while is missing. That sucks.
- Python has 'break' and 'continue' like C. But these only affect the innermost loop. Is there a way to break out of an enclosing loop? (In Perl you can label a loop and then say 'next LABEL', etc.)
Usually solved by a try/except clause when needed - which it seldom is.
- How can I pass a variable by reference?
EVERYTHING is a reference. You pass nothing but references. If you call foo(bar), foo will have a reference to the exact same object as bar pointed to. The fact that you can not modify a string passed to a function is because strings are immutable.
- Python advertises its support for first-class functions, but I can't seem to get closures to work.
Can't really comment on this I'm afraid. lambdas are very simple, yes. You can define functions within functions - and they will (in 2.2.1) be able to read from, but not write to the name space of the enclosing function, IIRC.
- Is there a do/while statement in Python?
No. The Python philosophy is usually "Have one way to do it." do/while doesn't really solve problems a simple while clause doesn't solve. Keep it simple.
May we live long and die out
But the problem is that Python suffers from a lot of Perl's problems and adds a few of its own: you can't implement it in itself, it has no strong typing (even Perl's use strict is ridiculously better), an OO system with no support for data hiding, etc. etc. And that brings me to the biggest problem: Python doesn't really have a niche to fill. The CGI space has been seemingly co-opted completely by Perl (at least until people start using PHP), and it's too dog-slow to be used for real CS applications. As a beginner's language it's ideal, but that's not going to help it be taken seriously when it comes to real
Uhh.... you are seriously misinformed.
data hiding: trivial to implement by overriding the standard accessors and limiting the set of things that can be accessed externally. Since you have full access to the scope and stack, you can even limit things in a fashion similar to java's private/public/protected. I have used this many times to force attributes to be set only through a particular path that involves certain chunks of business logic.
implement it in itself: Not sure what your point is, but you can certainly implement the Python VM in itself. The Python VM is actually quite portable as is demonstrated by the excellent Java based implementation found in Jython.
strong typing: yes -- python has no strong typing, but it is trivial to check types and constrain APIs to particular types. At times, it would be nice to have strong types, but weak typing also has some extremely powerful uses and patterns.
Too dog slow? Uh, no. See the Twisted project for an example of an "internet event server" whose web server implementation is faster-- and more flexible-- than apache. Not that apache is fast, mind you, but something that is faster than apache while maintaining flexibility can certainly claim to have better performance than the server used by, what, 50+% of the world's web servers?
Python scales well, it is extremely reliable, and has excellent performance for an interpreted language. Python is used in many mission critical situations in both commercially saleable products as well as in embedded markets.
Personally, I have built trading systems in Python. If you have ever been around a Trader when their technology doesn't work, you know that using technology that is fundamentally broken is exceedingly unpleasant (unless you enjoy being yelled at and having heavy things thrown at you). Python proved to be extremely reliable and allowed us to roll out new versions of the software very rapidly.
Note that I am not a Python Zealot -- I program in some random combination of Python, C, Objective-C, Java and Lisp on a daily basis. Of all the languages, I prefer to use Python because I can get things done more quickly and with lower maintenance costs than any of the other languages. However, I'm not going to berate a client simply because they insist on using Java-- and certainly not if they have a good reason for doing so....
Like Java and Lisp -- and unlike Perl -- Python has exception handling. The structured way to get out of an inner loop is the same as the structured way to get out of a deeply nested function call: raise an exception, and trap it at the higher level where you want to "go to".
In Python, everything is a reference, but strings are immutable objects. There's no such thing as "modifying the string passed in" -- all the built-in string functions return a new string. However, for mutable types such as lists and dictionaries, functions can certainly modify their arguments, as in this example:
Especially since I have some Scheme in my programming background, this is a quirk I find annoying about Python: lambda is underpowered. It's comparable to the old BASIC "DEF FN" in that it allows only expressions, not statements, in the lambda-body.
However, you can do what you want by defining a function with a temporary name, using def, and returning it. (In Python it is perfectly valid to have function definitions inside other function definitions, and it does what you expect: defines functions whose names have local scope, but can be returned.) You can also create callable classes, which act like functions instead of object factories. There's an implementation of curry for instance in the Python Cookbook, which does this. Check it out.
There is neither a do/while nor a repeat/until in Python. Again this is something I don't agree with, but the argument is that this keeps the number of redundant keywords down. The convention is to use while loops and escape with break when necessary.
Throw an exception and catch it whereever. Eg:
How can I pass a variable by reference? For example, to take a reference to a string, pass it to a function and have that function modify the string passed in.
Everything is always passed by reference. You can't modify a string because strings are immutable.
The 'lambda' keyword won't accept assignment or even sequencing inside the function body. So anonymous functions you might want to pass around can't do much beyond trivial operations.
lambda is a short-hand for def. Use that if the body isn't a simple expression:
Is there a do/while statement in Python?
Some python tutorials I wrote:
Python for BASIC programmers
Writing GTK applications in python
I'd have to say that more than a few people are using PHP. In fact, of the available Apache modules, guess which one is the most popular? (Hint: it's not PyApache or even mod_perl by a long shot)
My journal has hot
Like Java and Lisp -- and unlike Perl -- Python has exception handling.
Perl has exception handling with die/eval. Here is an article about it.
My own opinion, like yours, is biased by the specific problem domain I applied Python to. For me that has been sys-admin scripts and network/cgi automation scripts.
How is the ability to write a Python compiler in itself practially relevant to most users?
Lack of strong typing and no support for data hiding can be thought of as a feature by those so inclined. This is just analogous to objections against 'whitespace sensitivity'.
I more closely agree with one of the replies: that Python suffers from horrible documentation. I recommend looking at ActiveState Python for a slight improvement from the web manual.
Some _personal_ highlights using python:
- learning curve duration: 1.5 hours to start writing moderate complexity RE file parsing scripts.
- ability to write a cgi enabled http server in approx 3 lines of code
- ability to write a decent cross-platform opengl demo in approx 200 lines of code. using PyGame, PyOpenGL, Numeric etc.
Also, please just ignore the zealots, don't acknowledge them with so much disclaimer.
all the best,
mbaranow
Lifted whole cloth from Daily Python-URL
Python is an excellent rapid prototyping language. Because of its neat syntax and simple philosophy, programmers can quickly create a working protoype in Python. Later, if needed, it can reimplemented in a faster programing language (like C++).
range generates the entire sequence beforehand. xrange, OTOH, will generate them one by one.
HTH
no comment
I really don't see what the problem is. I learned Python TOTALLY from the documentation that is included with the Python package. I went through the tutorial to get the 'flavour' for the language, then browsed the library documentation to see what kinds of libraries there were, and the same with the language documentation. I go back to the library and language documentation when I need more information.
It's, for the most part, fine.
Yes, there ARE some holes here and there, as there are with a lot of the other types of documentation too. but it's hardly 'useless'.
FYI, I used to be a avid Perl programmer until I had to reverse-engineer a Python program to modify it. (Xerox DocuShare)
I too don't think that Python's documentation is bad, in fact I actually think that its excellent. Much like the K&R C book. One thing that I admire about Pythons documentation, is that you could recreate the language from "Language Reference" section.
I find that there are 2 (if not many more) kinds of documentation. Documentation that is meant to be read (more like a book), and documentation that is meant to be used (looked up while using like manpages and msdn). I believe that Python is that of the former, while PHP is that of the latter.
Conceptually, a for loop always iterates over the members of a sequence. range is just an example of generating a sequence. This is actually quite nice, because if you have a sequenence of lines in a file, you can do stuff like "for line in file:" and loop over them easily. You aren't stuck looping only over integers.
As for your actual question: range does generate the entire list. xrange generates an object instead that calculates the items on the fly. Newer versions of python will be changing things (if they haven't already) so that range generates on the fly as well, and gets rid of the xrange object.
Benchmarks have shown over time that xrange is not appreciably faster than range; you have to spend the time generating that number somewhere, either up front or one at a time. The only reason to use xrange is if you have a very large sequence to loop over, and can't afford the storage for the temporary list.
It's a nerd thing (I would say it's a geek thing, but a geek is a nerd that can actually function well in society and I'm not convinced people who do these things have actually graduated to geek). If a language can be used to create an implementation of itself, and that implementation can in turn be run on itself, then it's considered proven that the language is sufficiently useful for "real" usage.
I won't claim to understand it. It certainly doesn't do anything for the general populace. It ought to be enough to say that a language is Turing complete to say it can be used "for real". For some reason, it just gives the CS crowd big warm fuzzies when they do stuff like that.
Please mod this post only if you think others should/n't read this. I have enough ego^H^H^Hkarma. Thanks!
Combines the flexibility of syntax of C with the efficiency of Javascript. Python can't realistically support Lisp-style macros, doesn't support true closures, and many other things of Goodness that make Lisp languages so good for rapid coding. On the other hand, Python's dynamicism makes it very very slow. It's bad enough that the Python zealots apparently don't know how to program Java -- as minor corrections to their broken test code result in Java code that just stomps Python.
So let's be honest here. Python is slow. So we have a slow language. So what? That's okay. I'm all for slow languages as long as they have features which make up for them. But Python's missing many of the goodies that make slow languages great. Macros. Closures. A good, scientifically-oriented numerical facility.
I get this very strong feeling that Python has the worst features of both Lisp and C, while not having the best features of either of them. No wonder it appears, from my reading, that the vast majority of people pushing for Python are ex-Perl programmers. In other words, they're arguing for Python as a replacement scripting language for Perl. Not as a language for large-scale development or maintainability. But Perl is an easy target. It's a grotesque language, only popular because it was first to bat in the full-featured-scripting-language game.
A malformed object oriented system. My other major beef with Python is that it has, to my mind, the single worst-conceived OOP system of any language I can think of at the moment.
There are two basic families of OOP: class-based (C++/Java/CLOS/etc.) and prototype-based (JavaScript/Self/NewtonScript). The advantage of a class-based language is that you can equate classes with types, and the compiler knows exactly where a slot should be in an object, even an inherited slot. So they're fast. A great choice for a performance program on a desktop. The advantage of a prototype-based language is that it only keeps around the diffs: objects don't need to store tons of slots they don't use -- they just point to a superobject and say "go there for anything else". So they're highly memory efficient. Prototype languages are also highly dynamic, elegant, and small. A great choice for a scripting language, or a language for a PDA (like the Newton).
Python is odd: it has both models. Underneath the model is prototype-based. Kludged on top of this is a class model. What the heck? Do not think this is a good thing. Each model has made sacrifices from the ideal -- by using both models, you're making all the sacrifices at the same time. It appears to me that Python has managed to achieve the worst of both features: it's not as dynamic or small and elegant as a prototype OOP language, and it's not nearly as fast as a class-based OOP language. It has no advantages over a prototype-based model at all. In reality, the kludge means that Python programmers have to keep more syntax rules in their brains in order to achieve less than a prototype language would provide.
I get the feeling that what happened was Python started as a procedural Perl-style language, then hacked on a prototype model, then due to, I dunno, misinformed "customer complaints", hacked on another class-based model on top of that. What a mess.
Anyway, this is how I see the current state of the Python world. Why do people use this language? My guess is that it's because they're ex-Perl programmers, and made an incremental jump to the next slightly better language.
I cannot agree with the reviewer that M. Lutz's O'Reilly "Python" book is good. I disliked this book nearly all the way through. It jumped around too much, used too many words, and had insufficient detail on more advanced topics. Given that the book is about three inches thick (from memory -- I gave away my copy), there's enough room for details on everything.
I concur with other posters that the "Essential Reference" (white and red from New Riders, written by D. Beazley who did SWIG) is an awesome book. It is concise, making it a good reference. I wouldn't think it was a good book for those who have never programmed. If you have some programming experience, though, I expect you'll appreciate this book.
The "Quick Python" book from Manning is nice, too. This was my wife's preferred book for learning Python. I've looked through it a bit, and it seems decently concise but with more explanation than "Essential Reference". I used its section on extending Python through C, and found it very useful. That section didn't have everything bit of reference that I needed for conversion specifiers, but their examples were dead-on what I needed to get started.
I recently finished reading through "How to Think Like a Computer Scientist: Learning With Python" from Green Tea Press. This book is not a complete reference or guide for Python, nor will it be particularly 'useful' for people who have taken university-level programming and data structures classes. However, it seems to be an AWESOME book for people who don't yet program, or whose only experience is web programming or VB or Perl programming (I'm not saying those things are bad, but very often they don't encourage reasonable programming discipline and methodology). I write "it seems" only because I'm not a beginner or an instructor for intro to programming courses.
This book ("How to Think...") is aimed at classroom use, so it doesn't include info about installing Python or starting the Python interpreter under Windows, etc. It does preach solid computer science. Parts of their approach seemed a bit unusual to me, compared to my more classical training, but after a few gripes I always was forced to conclude that their approach was valid and as concise and clear as it could be. The authors are aware of the book being used in high schools and community colleges. I expect that mature students, or any adult intrested in learning proper programming, would benefit from starting with this book.
-Paul Komarek
I just don't see the problem.
That being said, Perl is at least useful for many things ("practical," I believe it's called).
Python is useful for many things as well, as evidenced by the number of people who use it, including Boeing, Disney, Hewlett-Packard, Industrial Light & Magic, Intel, JPL, Lawrence Livermore Labs, NASA, and Yahoo. Programmers at places like these are usually allowed to make their own decsions about their tools, and they chose Python. These guys are good. They don't use tools that they don't like. This is not to say that Python is their only scripting language. I know NASA makes good use of TCL, and probably uses Perl as well.
Peter Norvig says "Python has been an important part of Google since the beginning, and remains so as the system grows and evolves. Today dozens of Google engineers use Python, and we're looking for more people with skills in this language." Norvig is director of search quality at Google. Look at his home page (www.norvig.com/. When a guy who writes AI books talks up a language, it means something. I'm not saying it means everything. It's another piece of data to put on the scales.
More details on use of Python:www.python-in-business.org/success/
http://www.python.org/Quotes.html
Finally, I note that the Google jobs page mentions Perl 11 times and Python 15 times, for what it's worth. I didn't read the job descriptions.
If you need more speed than native Python provides, you can always write code in C and wrap it so it is callable from Python. The wrapping is really easy to do, once you have understood the general concepts involved in it. The product I currently work on has about 10000 lines of C code (crypto and networking) which is used this way, and it works perfectly. For more information about extending Python with C, see:
Extending and Embedding the Python Interpreter
Python/C API Reference Manual
But the problem is that Python suffers from a lot of Perl's problems
:)
Other than Performance?
and adds a few of its own: you can't implement it in itself
Hmm? Its quite trivial to parse Python code in Python, and its qutie trivial to interpret it with Python code, so where's the problem?
it has no strong typing (even Perl's use strict is ridiculously better),
You're confusing "strong typing" with "static typing". Python has no Static Typing, but indeed has Strong Typing (try '5 + "Hello"' in your Python interpreter). Perl, on the other hand, has no strong typing at all ("Hello" + 5 is perfectly valid in Perl, albeit senseless).
Not having Static Typing is not a bad thing - its a concious decision by the language designers. The designers of Python wanted the language to be just-explicit. If you want the program code to express an idea, you express it once - Which is more than implicit, and less than redundant. Static typing is redundant - and avoided in Python as a design goal of minimizing programming time of any task.
Another idea behind the lack of static typing is that all lines of code MUST run at least once anyway for any minimal level of reliability, so the compilation-level check adds no value.
an OO system with no support for data hiding, etc. etc.
Python supports data-hiding, but simply does not enforce it. This is because Python is not a BDL (Bondage and discipline langauge). Instead, there are extremely well-established and documented Python conventions. The prefix underscore that denotes private/protected, The double underscore that
denotes private (avoiding namespace clashing by name mangling), etc.
And that brings me to the biggest problem: Python doesn't really have a niche to fill. The CGI space has been seemingly co-opted completely by Perl (at least until people start using PHP), and it's too dog-slow to be used for real CS applications.
Python isn't a niche language. Its a general-purpose language - and no - its far from being too slow for real CS applications. That's why its successfully used in Search engines, 3d engines, system administration, compilers, games, etc.
As a beginner's language it's ideal, but that's not going to help it be taken seriously when it comes to real computing tasks.
Python is taken very seriously in many many places, with increasing seriousness.
If the python developers made some tweaks to the type system
Like what? Static typing conflicts with the Python design goals.
and added a real compiler
Python already has the Jython compiler to Java, psyco compiler to native code, and others.
then I would advocate that most software engineering be moved there.
Many already advocate it for all software engineering except for the inner loops which are exported to Python from C code. This proves for many people to be the most effective way to write fast, reliable maintainable code.
As it stands it's an original language which is a lot of fun to program in, and still has lots of unmapped potential to it.
The unmapped potential is discovered by more people every day