This is a tough question to word and I'm not sure what the proper term for it would be (if any). I'm curious what languages allow you to "build up" a string during program execution, and then execute it as part of the program. The only language that I know of that allows you to do this is Snobol.
Reading the wikipedia entry for Tcl however, it sounds like it may be able to do this also?
I always thought this was a nifty feature even if it may not be used much. Thanks.
PS: Would tag this with Snobol, Spitbol, but don't have the reputation to create new tags.
I'm curious what languages allow you to "build up" a string during program execution, and then execute it as part of the program.
Look for languages that support eval, or, more generally, runtime meta-programming. Pretty much every language supports an eval (even strongly, statically typed languages like Haskell). Many runtimes built for languages that are primarily implemented via bytecode
interpretation (such as Lisp-like languages, Erlang or Java) support the ability to
insert new (byte)code at runtime. Once you can insert new code dynamically, you can write eval, or do "monkey patching".
Even in language implementations without specific support for full meta-programming, or even dynamic linking, there are often ways to dynamically generate code under programmer control, either via reflection mechanisms or code generation support libraries (such as LLVM).
Beyond just a simple one-stage eval, more generally, languages that support multi-stage computation allow for generation of programs from one stage to the next, for arbitrary numbers of stages, making it possible to safely, arbitrarily nest evals.
To quote Taha, who's thesis on multi-stage programming models introduces much of the theory.
Program generation is a powerful and pervasive technique for the development of software. It has been used to improve code reuse, product reliability and maintainability, performance and resource utilization, and developer productivity
The languages you're looking for usually provide three primitives, in some form or another:
delay
splice
run
for delaying computation by one stage (e.g. quoting a fragment as a string), splicing it into a running program, and executing that fragment (in Lisp, back-quote, comma, and eval).
Lisp and eval
McCarthy, John, History of LISP, SIGPLAN Not. 1978. -- introduces eval
Generalizing eval to multi-stage programming
On multi-stage programming:
Taha, Multi-Stage Programming: Its Theory and Applications
Nielson, Flemming and Nielson, Hanne Riis, Two-level functional languages, -- introduced 2-level languages.
Taha, Walid and Sheard, Tim, Multi-stage programming with explicit annotations -- simple operators to support all runtime metaprogramming techniques.
Giving types to multi-stage programming
Formal descriptions of multi-stage computation are quite tricky, and involve unusual techniques (for programming languages) like modal logic.
Giving types to meta-programs:
Wickline, Philip and Lee, Peter and Pfenning, Frank and Davies, Rowan, Modal types as staging specifications for run-time code generation.
Security issues
The trickiness of formalzing the semantics of multi-stage programming explains why they're often confusing systems to work with, and why eval can open up so many security concerns: it becomes unclear what code is executing when, and exactly what data is being turned into code. Getting name capture from one stage to the next is tricky, leading to code injection attacks. Such complexity doesn't help security.
Definitely can be done in a lot of interpreted scripting languages. And some languages are specifically designed for this. It can be done, to my knowledge, in:
Perl
PHP
Lisp (and dialects, like CL, Clojure, Scheme, etc.)
JavaScript
It can be done in all Lisp dialects, where this feature originated under the name eval, as well as in Prolog (call/1) and any number of other languages. Most keep the name eval and most are dynamic languages.
That being said, this is hardly a nifty feature. I'd call it a major security issue, given how easy it is to abuse this feature. If you want dynamic code execution, then writing your own, restricted, micro-interpreter (or using something like Lua) is almost always a better idea.
Related
What qualifies a programming language to be called dynamic language? What sort of problems should I use a dynamic programming language to solve? What is the main difference between static programming languages and dynamic programming languages?
I don't think there is black and white here - there is a whole spectrum between dynamic and static.
Let's take two extreme examples for each side of the spectrum, and see where that takes us.
Haskell is an extreme in the static direction.
It has a powerful type system that is checked at compile time: If your program compiles it is free from common and not so common errors.
The compiled form is very different from the haskell program (it is a binary). Consequently runtime reflection and modification is hard, unless you have foreseen it. In comparison to interpreting the original, the result is potentially more efficient, as the compiler is free to do funky optimizations.
So for static languages I usually think: fairly lengthy compile-time analysis needed, type system will prevent me from making silly mistakes but also from doing some things that are actually valid, and if I want to do any manipulation of a program at runtime, it's going to be somewhat of a pain because the runtime representation of a program (i.e. its compiled form) is different from the actual language itself. Also it could be a pain to modify things later on if I have not foreseen it.
Clojure is an extreme in the dynamic direction.
It too has a type system, but at compile time there is no type checking. Many common errors can only be discovered by running the program.
Clojure programs are essentially just Clojure lists (the data structure) and can be manipulated as such. So when doing runtime reflection, you are actually processing a Clojure program more or less as you would type it - the runtime form is very close to the programming language itself. So you can basically do the same things at runtime as you could at "type time". Consequently, runtime performance may suffer because the compiler can't do many up-front optimizations.
For dynamic languages I usually think: short compilation step (basically just reading syntax), so fast and incremental development, practically no limits to what it will allow me to do, but won't prevent me from silly mistakes.
As other posts have indicated, other languages try to take more of a middle ground - e.g. static languages like F# and C# offer reflection capabilities through a separate API, and of course can offer incremental development by using clever tools like F#'s REPL. Dynamic languages sometimes offer optional typing (like Racket, Strongtalk), and generally, it seems, have more advanced testing frameworks to offset the lack of any sanity checking at compile time. Also type hints, while not checked at compile time, are useful hints to generate more efficient code (e.g. Clojure).
If you are looking to find the right tool for a given problem, then this is certainly one of the dimensions you can look at - but by itself is not likely to force a decision either way. Have a think about the other properties of the languages you are considering - is it a functional or OO or logic or ... language? Does it have a good framework for the things I need? Do I need stability and binary backwards compatibility, or can I live with some churn in the compiler? Do I need extensive tooling?Etc.
Dynamic language does many tasks at runtime where a static language would do them at compile-time.
The tasks in question are usually one or more of: type system, method dispatch and code generation.
Which also pretty much answers the questions about their usage.
There are a lot of different definitions in use, but one possible difference is:
A dynamic language typically uses dynamic typing.
A static language typically uses static typing.
Some languages are difficult to classify as either static or dynamically typed. For example, C# is traditionally regarded as a statically typed language, but C# 4.0 introduced a static type called dynamic which behaves in some ways more like a dynamic type than a static type.
What qualifies a programming language to be called dynamic language.
Dynamic languages are generally considered to be those that offer flexibility at run-time. Note that this does not necessarily conflict with static type systems. For example, F# was recently voted "favorite dynamic language on .NET" at a conference even though it is statically typed. Many people consider F# to be a dynamic language because it offers run-time features like meta-circular evaluation, a Read-Evaluate-Print-Loop (REPL) and dynamic typing (of sorts). Also, type inference means that F# code is not littered with type declarations like most statically typed languages (e.g. C, C++, Java, C# 2, Scala).
What are the problems for which I should go for dynamic language to solve.
In general, provided time and space are not of critical importance you probably always want to use languages with run-time flexibility and capabilities like run-time compilation.
This thread covers the issue pretty well:
Static/Dynamic vs Strong/Weak
The question is asked during Dynamic Languages Wizards Series - Panel on Language Design (at 24m 04s).
Answer from Jonathan Rees:
You know one when you see one
Answer from Guy Steele:
A dynamic language is one that defers as many decisions as possible to run time.
For example about array size, the number of data objects to allocate, decisions like that.
The concept is deferring until runtime, that's what I understand to be dynamic.
A lot of languages (perhaps all of them) are designed to make writing programs easier. They all have different domains, and aim to simplify developing programs in these domains (C makes developing low-level programs easier, Java makes developing complex business logic easier, et al.). Perhaps other purposes are sacrificed in sake of writing and maintaining programs in an easier, more natural, less error-prone way.
Are there any languages specifically designed to make verification of source code--i.e. static analysis--easier? Of course, capability to write common programs for modern machines should also persist.
One of the design goals of Ada was to support a certian amount of formal verification. It was moderately successful, but verification didn't exactly take off like they were hoping. Luckily Ada is good for far more than that. Sadly, that hasn't helped it much either...
There's an Ada subset called Spark that keeps this alive today. Praxis sells a development suite built around it.
Are there any languages specifically designed to make verification of source code easier?
This was a vague goal of both the CLU and ML languages, but the only language design I know that takes static verification really seriously is Spark Ada.
Dijkstra's language of guarded commands (as described in Discipline of Programming) was designed to support static verification, but it was explicitly not supposed to be implemented.
Gerard Holzmann's Promela language was also designed for static analysis by the model checker SPIN, but again it's not executable.
Auditors in the E language provide a built-in means of writing code analyses within the language itself and requiring that some section of code pass some static check. You might also be interested in the related-work part of the paper.
I haven’t used it myself, so I can’t speak with any authority, but I understand that the Eiffel programming language was designed to use Code by Contracts, which would make static analysis much easier. I don’t know if that counts or not.
There is SAIL, the Static Analysis Intermediate Language or Flexibo
One has two problems in "making verification of source code easier". One is languages in which you don't do gross things such as arbitrary cases (such as C).
Another is specifying what you want to verify, for that you need a good assertions languages.
While many languages have proposed such assertions languages,
I think the EDA community has been pushing the envelope most effectively with temporal specifications. The "Property Specification Language" is a standard; you can learn more from P1850 Standard for PSL: Property Specification Language (IEEE-1850). One idea behind PSL is that you can add it to existing EDA languages; I think the EDA community has been incorporating into the EDA langauges as time goes by.
I've often wished for something like PSL to embed in conventional computer software.
Static verification is a bad start for this task. It's based on an assumption that it's possible to verify correctness of the program automatically. It's not feasible in real world, and expecting the program to check arbitrarily complex code without any hints is just plain dumb. Usually software for static verification ends up requiring hints all over source code, and in the end generates lots of false positives and false negatives. It has some niche, but that's it. (See introduction to "Types and programming languages" by Pierce)
While these kind of tools were developed by engineers for their own simple purposes, real solution have been baking in an academy. It was found that types in statically typed programming languages are equivalent to logic statements given everything goes smooth and language doesn't have some kind of bad behaviour. This is called "Curry-Howard correspondence", and the embedding of logic into types is "Brouwer-Heyting-Kolmogorov logic". The most powerful proofs are possible only in the languages with powerful types: dependent types. If we forget all this terminology for a while, this means that we can write programs that carry proofs of its own correctness, and these proofs are checked while the program gets compiled, with no executable file given in case of failure.
The positive side of this approach is that you never get any false negatives, i.e. compiled program is guaranteed to work properly according to the specification. Even without extra proofs about specification, programs in dependently-typed languages are less prone to mistakes, because divisions by zero, unhandled exceptions and overflows just never end up in an executable program.
Always writing such proofs by hand is tedious. For that there are "tactics", i.e. programs that generate proofs of correctness. These are almost equivalent to programs for static verification, but, unlike them, are required to generate formal proof.
There is a range of dependently-typed languages for different purposes: Coq, Agda, Idris, Epigram, Cayenne etc.
Tactics are implemented in Coq and probably several more languages. Also Coq is the most mature of them all, with infrastructure including libraries like Bedrock.
In case C code extraction from Coq is not enough for your requirements, you can use ATS, which is on par in performance with C.
Haskell employs weak form of Curry-Howard correspondence: it works fine, unless you start writing failing or forever-looping programs. In case your requirements are not that hard to write formal proofs, consider using Haskell.
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There is a lot of hype around Haskell, however, it is hard to get information on how it is used in the real world applications. What are the most popular projects / usages of Haskell and why it excels at solving these problems?
What are some common uses for this
language?
Rapid application development.
If you want to know "why Haskell?", then you need to consider advantages of functional programming languages (taken from https://c2.com/cgi/wiki?AdvantagesOfFunctionalProgramming):
Functional programs tend to be much more terse than their ImperativeLanguage counterparts. Often this leads to enhanced
programmer productivity
FP encourages quick prototyping. As such, I think it is the best software design paradigm for ExtremeProgrammers... but what do I know?
FP is modular in the dimension of functionality, where ObjectOrientedProgramming is modular in the dimension of different
components.
The ability to have your cake and eat it. Imagine you have a complex OO system processing messages - every component might make state
changes depending on the message and then forward the message to some
objects it has links to. Wouldn't it be just too cool to be able to
easily roll back every change if some object deep in the call
hierarchy decided the message is flawed? How about having a history of
different states?
Many housekeeping tasks made for you: deconstructing data structures (PatternMatching), storing variable bindings (LexicalScope with
closures), strong typing (TypeInference), GarbageCollection, storage
allocation, whether to use boxed (pointer-to-value) or unboxed (value
directly) representation...
Safe multithreading! Immutable data structures are not subject to data race conditions, and consequently don't have to be protected by
locks. If you are always allocating new objects, rather than
destructively manipulating existing ones, the locking can be hidden in
the allocation and GarbageCollection system.
Apart from this Haskell has its own advantages such as:
Clear, intuitive syntax inspired by mathematical notation.
List comprehensions to create a list based on existing lists.
Lambda expressions: create functions without giving them explicit names. So it's easier to handle big formulas.
Haskell is completely referentially transparent. Any code that uses I/O must be marked as such. This way, it encourages you to separate code with side effects (e.g. putting text on the screen) from code without (calculations).
Lazy evaluation is a really nice feature:
Even if something would usually cause an error, it will still work as long as you don't use the result. For example, you could put 1 / 0 as the first item of a list and it will still work if you only used the second item.
It is easier to write search programs such as this sudoku solver because it doesn't load every combination at once—it just generates them as it goes along. You can do this in other languages, but only Haskell does this by default.
You can check out following links:
https://c2.com/cgi/wiki?AdvantagesOfFunctionalProgramming
https://learn.microsoft.com/archive/blogs/wesdyer/why-functional-programming-is-important-in-a-mixed-environment
https://web.archive.org/web/20160626145828/http://blog.kickino.org/archives/2007/05/22/T22_34_16/
https://useless-factor.blogspot.com/2007/05/advantage-of-functional-programming.html
I think people in this post are missing the most important point for anyone who has never used a functional programming language: expanding your mind. If you are new to functional programming then Haskell will make you think in ways you've never thought before. As a result your programming in other areas and other languages will improve. How much? Hard to quantify.
There is one good answer for what a general purpose language like Haskell is good for: writing programs in general.
For what it is used for in practice, I've three approaches to establishing that:
A tag cloud of Haskell library and app areas, weighted by frequency on Hackage.
Indicates that it is good for graphics, networking, systems programming, data structures, databases, development, text processing ...
Areas it is used in industry - a lot of DSLs, web apps, compiler design, networking, analysis, systems programming , ...
And finally, my opinion on what it is really strong at:
Problems where correctness matters, domain specific languages, and parallel and concurrent programming
I hope that gives you a sense on how broad your question is, if it is to be answered with any specificity.
One example of Haskell in action is xmonad, a "featureful window manager in less than 1200 lines of code".
From the Haskell Wiki:
Haskell has a diverse range of use
commercially, from aerospace and
defense, to finance, to web startups,
hardware design firms and lawnmower
manufacturers. This page collects
resources on the industrial use of
Haskell.
According to Wikipedia, the Haskell language was created out of the need to consolidate existing functional languages into a common one which could be used for future research in functional-language design.
It is apparent based on the information available that it has outgrown it's original purpose and is used for much more than research. It is now considered a general purpose functional programming language.
If you're still asking yourself, "Why should I use it?", then read the Why use it? section of the Haskell Wiki Introduction.
Haskell is a general purpose programming language. It can be used for anything you use any other language to do. You aren't limited by anything but your own imagination. As for what it's suited for? Well, pretty much everything. There are few tasks in which a functional language does not excel.
And yes, I'm the Rayne from Dreamincode. :)
I would also like to mention that, in case you haven't read the Wikipedia page, functional programming is a paradigm like Object Oriented programming is a paradigm. Just in case you didn't know. Haskell is also functional in the sense that it works; it works quite well at that.
Just because a language isn't an Object Oriented language doesn't mean the language is limited by anything. Haskell is a general-purpose programming language, and is just as general purpose as Java.
I have a cool one, facebook created a automated tool for rewriting PHP code. They parse the source into an abstract syntax tree, do some transformations:
if ($f == false) -> if (false == $f)
I don't know why, but that seems to be their particular style and then they pretty print it.
https://github.com/facebook/lex-pass
We use haskell for making small domain specific languages. Huge amounts of data processing. Web development. Web spiders. Testing applications. Writing system administration scripts. Backend scripts, which communicate with other parties. Monitoring scripts (we have a DSL which works nicely together with munin, makes it much easier to write correct monitor code for your applications.)
All kind of stuff actually. It is just a everyday general purpose language with some very powerful and useful features, if you are somewhat mathematically inclined.
From Haskell:
Haskell is a standardized, general-purpose purely functional
programming language, with
non-strict semantics and strong static
typing. It is named after logician
Haskell Curry.
Basically Haskell can be used to create pretty much anything you would normally create using other general-purpose languages (e.g. C#, Java, C, C++, etc.).
For example, for developing interactive, realtime HTML5 web applications. See Elm, the compiler of which is implemented in Haskell and the syntax of which borrows a lot from Haskell's.
This is a pretty good source for info about Haskell and its uses:
Open Source Haskell Releases and Growth
I know of several functional languages - F#, Lisp and its dialects, R, and more. However, as I've never used any of them (although the three I mentioned are on my "to-learn" list), I was wondering about the pros/cons of the various functional languages out there. Are there significant pros/cons, both in learning the language and in any real-world applications of said language?
Haskell is "extreme" (lazy, pure), has active users, lots of documentation, and makes runnable applications.
SML is "less extreme" (strict, impure), has active users, formal specification, many implementations (SML/NJ, Mlton, Moscow ML, etc.). Implementations vary on how applications are deployed wrt the runtimes.
OCaml is ML with attitude. It has an object orientation, active users, documentation, add ons, and makes runnable applications.
Erlang is concurrent, strict, pure (mostly), and supports distributed apps. It needs a runtime installed separately, so deployment is different from the languages that make runnable binaries.
F# is similar to OCaml with Microsoft backing and .NET libraries.
Scala runs on the JVM and can be used as a functional language with advanced features, or as simply a souped-up Java, or both. The flexibility is cited as a drawback for learning a functional language because it's easy to slip back into imperative Java ways. Of course it is also an advantage if you want to use existing JVM libraries.
I'm not sure if your question is to functional languages in general, or differences between them. For general info on why functional:
http://paulspontifications.blogspot.com/2007/08/no-silver-bullet-and-functional.html
Why Functional Programming Matters
As far as differences between functional languages:
Distinctive traits of the functional languages
The awesome thing about functional languages is that base themselves off of the lambda calculus and other math. This results in being able to use similar algorithms and thoughts across languages more easily.
As far as which one you should learn: Pick one that will have a comfortable environment for you. For example, if you're using .NET and Visual Studio, F# is an excellent fit. (Actually, the VS integration makes F# a strong contender, period.) The book "How to Design Programs" (full text, free, online) with PLT Scheme is also a good choice.
I'm biased, but F# looks to have the biggest "real-world" potential. This is mainly because of the nice IDE/.NET integration, allowing you to fully tap .NET and OO, while keeping a lot of functional power (and extending it in ways too). Scala might be possible contender, but it's more of an OO language that has some functional features; hence Scala won't be as big a productivity gain.
Edit: Just to note JavaScript and Ruby, before someone comments on that :). Ruby is something else you could take a look at if you're doing that type of web dev, as it has a lot of functional concepts in, although not as polished as other languages.
The biggest downside is that once you see the power you can have, you won't be happy using lesser languages. This becomes a problem if you're forced to deal with people who haven't yet understood.
One final note, the only "con" is that "it's so complicated". This isn't actually true -- functional languages are often simpler -- but if you have years of C or whatnot in your brain, it can be a significant hurdle to "get" the functional concept. After it clicks, it should be relatively smooth sailing.
Lisp has a gentle learning curve. You can learn the basics in an hour, though of course it takes longer to learn idioms etc. On the down side, there are many dialects of Lisp, and it's difficult to interact with mainstream environments like Java or .NET.
I would not recommend R unless you need to do statistics. It's a strange language, and not exactly functional. You can do functional programming in R, but most people don't.
If you're familiar with the Microsoft tool stack, F# might be easy to get into. And it has a huge, well-tested library behind it, i.e. the CLR.
You can use a functional programming style in any language, though some make it easier than others. As far as that goes, you might try Python.
ML family (SML/OCaml/F#):
Pros:
Fairly simple
Have effective implementations (on the level with Java/C#)
Easily predictable resource consumption (compared to lazy languages)
Readable syntax
Strong module system
(For F#): large .Net library available
Has mutable variables
Cons:
Sometimes too simple (no typeclasses => problems with overloading)
(Except F#): standard libraries are missing some useful things
Has mutable variables :)
Cannot have infinite data structures (not lazy language)
I haven't mentioned features common to most static-typed functional languages: type inference, parametric polymorphism, higher-order functions, algrebraic data types & pattern matching.
I have learnt Haskell at the university like a pure functional languaje and I can say that's really powerful, but also I couldn't find a practical use.
However, i found this: Haskell in practice . Check it, is amazing.
The characteristics of functional paradigms sometimes are pros, and sometimes cons, depending on the situation / context.
Some of them are:
high level
lambda functions
lazy evaluation
Higher-order functions
recursion
type inference
Cite from wikipedia:
Efficiency issues
Functional programming languages have
been perceived as less efficient in
their use of CPU and memory than
imperative languages such as C and
Pascal.[26] However, for programs that
perform intensive numerical
computations, functional languages
such as OCaml and Clean are similar in
speed to C. For
programs that handle large matrices
and multidimensional databases, array
functional languages (such as J and K)
were designed with speed optimization
in mind.
Purely functional languages have a
reputation for being slower than
imperative languages.
However, immutability of data can, in
many cases, lead to execution
efficiency in allowing the compiler to
make assumptions that are unsafe in an
imperative language, vastly increasing
opportunities for inlining.
Lazy evaluation may also speed up the
program, even asymptotically, whereas
it may slow it down at most by a
constant factor (however, it may
introduce memory leaks when used
improperly).
So, I am writing some sort of a statistics program (actually I am redesigning it to something more elegant) and I thought I should use a language that was created for that kind of stuff (dealing with huge data of stats, connections between them and some sort of genetic/neural programming).
To tell you the truth, I just want an excuse to dive into lisp/smalltalk (aren't smalltalk/lisp/clojure the same? - like python and ruby? -semantics-wise) but I also want a language to be easily understood by other people that are fond of the BASIC language (that's why I didn't choose LISP - yet :D).
I also checked Prolog and it seems a pretty cool language (easy to do relations between data and easier than Lisp) but I'd like to hear what you think.
Thx
Edit:
I always confuse common lisp with Smalltalk. Sorry for putting these two langs together. Also what I meant by "other people that are fond of the BASIC language" is that I don't prefer a language with semantics like lisp (for people with no CS background) and I find Prolog a little bit more intuitive (but that's my opinion after I just messed a little bit with both of them).
Is there any particular reason not to use R? It's sort of a build vs. buy (or in this case download) decision. If you're doing a statistical computation, R has many packages off the shelf. These include many libraries and interfaces for various types of data sources. There are also interface libraries for embedding R in other languages such as Python, so you can build a hybrid application with a GUI in Python (for example) and a core computation engine using R.
In this case, you could possibly reduce the effort needed for implementation and wind up with a more flexible application.
If you've got your heart set on learning another language, by all means, do it. There are several good free (some as in speech, some as in beer) implementations of Smalltalk, Prolog and LISP.
If you're putting a user interface on the system, Smalltalk might be the better option. If you want to create large rule sets as a part of your application, Prolog is designed for this sort of thing. Various people have written about the LISP ephiphany that influences the way you think about programming but I can't really vouch for this from experience - I've only really used AutoLISP for writing automation scripts on AutoCAD.
At the risk of offending some, I have a hard time reconciling "easily understood by other people that are fond of the BASIC language" with any of the languages you mentioned. That's not intended as a criticism, but as an observation that each of the languages you mention has a style and natural idiom that's quite different from that of BASIC.
Smalltalk - pure OO from the ground up, usually (e.g. Squeak) coupled with an integrated environment that is simultaneously the IDE and the runtime. IOW you enter the Smalltalk VM and work inside it rather than just writing a text that is "source code".
LISP - much closer to functional programming (although with imperative overtones); the prefix notation is the first barrier to most people who "like" other languages, but the concept and use of macros is a much more substantial one.
Clojure - The combination of LISP, OO, and JVM integration makes this one even less BASIC-like.
Python and Ruby - I lump these together (at the risk of further annoying fans of either ;-) because they are both OO language with distinct notations that will take an outsider a bit of learning curve. The use of indentation-only for control nesting in Python and the Perl-like use of special characters in Ruby are often points of the complaint by newcomers. Although both can be written in an imperative style, that would be considered non-standard by seasoned users.
Prolog - This is the most unlike BASIC of all languages mentioned. All of the other languages you mentioned can be (ab)used in a semi-procedural style, but that is essentially impossible in Prolog. It requires a thorough understanding of, and comfort with, recursion to do anything non-trivial.
Code written with a "native accent" in essentially all of these languages (but especially Prolog, IMHO) will make use of idioms and concepts that are outside the norm for conventional BASIC programming. Put another way, if you pick one of these and then write code "with a BASIC accent" you've pretty much wasted the benefits that the language can offer.
I believe that all of them are worth learning for the concepts they can teach (or at least reinforce, depending on your background). But the similarity to Language X (for a wide range of values of X) is not what you'll get.
I can answer you partially
(aren't Smalltalk/Lisp/Clojure the same? - like python and ruby? -semantics-wise)
No, it is not. Smalltalk is OO language with message pass instead method calls. Lisp is Lisp ;-) It means truly functional language with the powerful macro system, OO support which is never seen in other languages (in CL) and many more features. Closure is Lisp-like language without many Lisp features but good integration to JVM. It's not supporting tail call optimization for example. And python or ruby are classic imperative OO languages with some limited functional ability. Note word limited. For example, Guido doesn't like functional programming and removed some functional features in version 2.5 and 2.6.
If you familiar with imperative procedural programming as in Python and you want to change your paradigm you should make your decision carefully.
Prolog is a very different language. It can be very hard to grasp, mainly because it relies heavily on recursion to do very basic tasks. If you are really willing then give it a go. It can be very powerful because it allows to expess relationships and solve complicated problems simply, typical examples are Towers of Hanoi or quicksort. It will change the way you think, which can be difficult if you are used to imperative languages.
If you're interested in Prolog then there's a free version of Visual Prolog available and the commercial version is reasonably priced.
It's a strong type offshoot of Prolog so isn't your classic implementation of the language, but has a respectable history - Borland marketed the DOS ancestor of it as Turbo-Prolog back in the late '80s.
It's also Windows only, but can be used to create standard Windows DLLs so you can link your code into a 'normal' windows programming language. I've never used the package in anger myself, but I did a couple of Prolog courses at Uni so have downloaded it from time to time to play with and look for possible uses and it looks solid enough. Might be just the set of cogs you're looking for.